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Our 2018 plans for research

Thu, 04/19/2018 - 09:58

This is the second of three posts that form our annual review and plan for the following year. The first post reviewed our progress in 2017. The following post will cover GiveWell’s progress and plans as an organization. We aim to release our metrics on our influence on donations in 2017 by the end of June 2018.

Summary

Our primary research goals for 2018 are to:

  1. Explore areas that may be more cost-effective than our current recommendations but don’t fit neatly into our current criteria by investigating (i) interventions aimed at influencing policy in low- and middle-income countries and (ii) opportunities to influence major aid agencies.
  2. Find new top charities that meet our current criteria by (i) completing intervention reports for at least two interventions we think are likely to result in GiveWell top charities by the end of 2019, (ii) considering renewal of GiveWell Incubation Grants to current grantee organizations that may become top charities in the future and making new Incubation Grants, and (iii) developing and maintaining high-quality relationships with charities, funders, and influencers in the global health and development community.
  3. Improve our internal processes to support the above goals. We plan to continue to delegate significant parts of our top charity update process to non-management staff and to improve our year-end process for making recommendations.
  4. Continue following our top charities and address priority questions. We are devoting fewer resources than we have in the past to top charity updates. We plan to continue gathering up-to-date information to allow us to make high-quality allocation decisions for giving season, and to answer a small number of high-priority questions.

Our secondary goals (which we hope to achieve, but are lower priority than the goals above) are to:

  1. Improve the quality of our decisions and transparency about our decision-making process.
  2. Hire more flexible research capacity to increase our output.
  3. Complete reviews of two new potential top charities.

We discuss each of these goals in greater depth below.

Goal 1: Explore areas that may be more cost-effective than our current recommendations

We’ve added five new top charities in the last two years. We now believe that our current top charities have more room for more funding than we are able to fill. This increases the relative value of identifying giving opportunities that are substantially more cost-effective than our current top charities (because identifying similarly cost-effective opportunities will crowd out marginal funding for our current top charities), even if we believe we have a lower chance of success of identifying these opportunities.

We’re therefore prioritizing investigating the areas we believe have the highest chance of containing opportunities that are substantially more cost-effective than our current top charities.

The primary staff working on this are James Snowden (Research Consultant) and Josh Rosenberg (Senior Research Analyst).

Sub-goal 1.1: Assess interventions to influence policy in low- and middle-income countries

Our current top charities all implement direct-delivery interventions (although we believe that some leverage substantial domestic government funding). We think there’s a reasonable, intuitive case that philanthropists may, in some cases, have a greater impact by influencing government policy because (i) governments have access to regulatory interventions that are unavailable to philanthropists and (ii) there may be opportunities to help improve the allocation of large pools of funds. We’ve started work investigating advocacy for tobacco control (notes 1, 2, 3), lead paint regulation (1, 2, 3), and J-PAL’s Government Partnership Initiative (1, 2). More about why we’re prioritizing this area here.

What does success look like? We publish at least five reports on interventions to influence policy in low- and middle-income countries and prioritize one to three for deeper assessment.

Sub-goal 1.2: Improve our understanding of aid agencies

We believe there may be opportunities for GiveWell (or potential GiveWell grantees) to help improve the allocation of spending by aid agencies. We want to improve our understanding of what aid agencies spend their funds on, whether there are opportunities to improve this allocation, and whether GiveWell (or potential grantees) would be in a good position to assist.

What does success look like? As this project is at an early stage, we don’t yet have specific metrics to assess success.

Goal 2: Find new top charities that meet our current criteria

One of our most important long-term goals is to identify all charities that should be top charities under our current criteria. We are uncertain whether we will be able to identify organizations outside of our current scope of work that we believe are substantially better giving opportunities than our current top charities (Goal 1) and we want to ensure we’re recommending the best giving opportunities, even if we believe they’re similarly cost-effective to our current top charities.

The primary staff working on this are Caitlin McGugan (Senior Fellow), Andrew Martin (Research Analyst), Josh Rosenberg (Senior Research Analyst), Stephan Guyenet (Research Consultant), Sophie Monahan (Research Analyst), and Chelsea Tabart (Research Analyst).

Sub-goal 2.1: Produce two intervention reports

Intervention assessments are key to our research process. We generally only consider organizations that are implementing one of our priority programs—so designated upon our completion of an assessment of the intervention—for top charity status (an exception is if an organization has done rigorous evaluation of its own program, though in practice we have found this to be very rare). Last year, we completed two full intervention reports (as opposed to “interim” reports, which are less time-intensive). As we’re allocating a larger proportion of our capacity to Goal 1 than we did last year, we aim to maintain this level of output at two full intervention reports this year.

What does success look like? We complete and publish two full intervention reports on potential new priority programs.

Sub-goal 2.2: Complete grant renewal assessments and new reviews as part of GiveWell Incubation Grants

There are a number of GiveWell Incubation Grantees that we hope will become top charities in the future. We want to ensure we’re making good decisions about the renewals of their grants and to continue to support organizations in developing monitoring and evaluation to the point where they can be considered for top charity status.

In the past, we’ve made GiveWell Incubation Grants to promising opportunities that didn’t fit within our research priorities at the time. We want to remain open to investigating opportunities we’re not yet aware of.

What does success look like? Complete assessments for grant renewals for Results for Development, Charity Science: Health, and a new grant for Evidence Action’s work on iron and folic acid supplementation. Prioritize at least two new Incubation Grants and complete a thorough investigation of each.

Sub-goal 2.3: Develop and maintain high-quality relationships with charities, funders, and influencers in the global health and development community

We expect good relationships with relevant organizations to help us (i) increase the number and diversity of good-fit charities that express interest in applying for our recommendation, (ii) identify new interventions we should consider as potential GiveWell priority programs, and (iii) clearly communicate our approach to potential top charities, enabling them to determine whether they would be a good fit for our process.

While we feel our relationships with well-regarded global health and development implementers and funders have improved, we continue to feel limited in our ability to understand whether there are funding gaps for evidence-backed, highly cost-effective work within large international NGOs and multilateral aid organizations such as the Global Fund to Fight AIDS, Tuberculosis and Malaria.

What does success look like? We have at least one call or meeting with at least 60 different charities that we have not recommended or made an Incubation Grant to (last year, we had 42) and at least 100 such calls or meetings in total. We have at least five multi-program organizations with budgets of more than $50 million annually express interest in being considered for our top charity recommendation for a specific, promising program, if we invite them to apply. We prioritize research work beyond an initial, brief evidence assessment on at least five interventions that we became aware of through professional networks.

Goal 3: Continue to improve our internal processes

We believe there’s room for improvement in a number of research processes to support the above goals, as well as our work following our current top charities. We don’t expect the general public to see clear evidence of progress on these goals, as they largely relate to our internal operations.

The primary staff working on this are Elie Hassenfeld (Executive Director), Josh Rosenberg (Senior Research Analyst), and Natalie Crispin (Senior Research Analyst).

Sub-goal 3.1: Decrease the amount of time senior staff spend on top charity updates this year

In the past, much of the work on top charity updates has been the responsibility of Natalie Crispin (Senior Research Analyst). We plan to move a higher proportion of this work to other research staff to minimize the extent to which our institutional knowledge is dependent on any one individual.

What does success look like? Natalie spends less than 30 percent of her time on top charity updates, and, more subjectively, we believe at the end of 2018 that it would not cause significant disruption to further reduce Natalie’s time on this work (i.e., to 15 percent) in 2019.

Sub-goal 3.2: Improve our process for publishing our year-end recommendations

In 2017, we started finalizing our charity recommendations for giving season later than was optimal. This meant much of the work had to be completed in a short amount of time, and there was insufficient time to solicit feedback and criticism from our top charities. While this was partly a consequence of adding two new top charities, we want to be more disciplined this year about when we start preparation for our giving season recommendations.

What does success look like? With exceptions for cases where we need to wait (i.e., final room for more funding estimates and cost-per-treatment estimates for existing top charities, information related to new top charities, or information that isn’t available until after July 31 and is crucial to our recommendations), finalize underlying research directly relevant to our 2018 recommendations by July 31; finalize all research and pages by November 1 (two-plus weeks before our publication deadline) to allow for (a) charity feedback and (b) internal debate.

Goal 4: Continue following our top charities and address priority questions

We are devoting fewer resources than we have in the past to top charity updates. We plan to continue gathering up-to-date information to allow us to make high-quality allocation decisions for giving season and to answer a small number of high-priority questions:

  • For each top charity, we plan to review spending over the last year and new monitoring and evaluation reports; update our estimate of their cost per deliverable (e.g., deworming treatment, preventative malaria treatment, or loan provided); and complete an analysis of their room for more funding.
  • For Helen Keller International (HKI), we plan to explore three major outstanding questions:
    1. What is HKI’s impact on coverage rates in vitamin A supplementation campaigns? To date, we have only supported HKI’s work to fund campaigns that are unlikely to occur without funding from HKI, and we would like to understand whether we should expand this support to other campaigns that HKI works on.
    2. What other interventions are delivered alongside vitamin A and how does that impact the cost-effectiveness of HKI’s work?
    3. What would it take to gather more data on current levels of vitamin A deficiency in locations where HKI works or may work in the future?
  • We want to increase our confidence in the costs incurred by other actors for net distributions that are supported by the Against Malaria Foundation, one of our current top charities.
  • We plan to speak with each of our standout charities for an update on their work.

The primary staff working on this are Natalie Crispin (Senior Research Analyst), Isabel Arjmand (Research Analyst), Andrew Martin (Research Analyst), Chelsea Tabart (Research Analyst), and Nicole Zok (Research Analyst).

What does success look like? By the end of November 2018, we complete updated reviews of each of our current top charities that include the information listed above. We also publish conversation notes from discussions with each current standout charity.

Goal 5 (Secondary): Improve the quality of our decisions and transparency about our decision-making process

We would like to improve the process by which we set our allocations during giving season. We don’t know yet exactly what this will involve, but we intend to do some initial work to determine ways we can improve the quality of our decisions and transparency about them.

Goal 6 (Secondary): Hire more flexible research capacity to increase our output

We believe our research team is currently capacity constrained. We would like to hire more flexible research generalists at all levels of seniority. We don’t expect to spend more time on this goal than we already are, but we would be excited about hiring the right candidates. If you’re interested in working for GiveWell, you can apply through our jobs page.

Goal 7 (Secondary): Complete reviews of at least two new top charities

We are prioritizing top charity reviews less highly this year than we have in previous years because we currently expect to identify significantly larger funding gaps than we will be able to fill. However, we have a shortlist of potential candidates for top charity status, and if we have the capacity, would like to complete evaluations of one or two of these organizations.

What does success look like? Complete evaluations for one or two new potential top charities.

The post Our 2018 plans for research appeared first on The GiveWell Blog.

Review of our research in 2017

Wed, 04/18/2018 - 13:13

This is the first of three posts that form our annual review and plan for the following year. This post reviews and evaluates last year’s progress on our work of finding and recommending evidence-based, thoroughly-vetted charities that serve the global poor. The following two posts will cover (i) our plans for GiveWell’s research in 2018 and (ii) GiveWell’s progress and plans as an organization. We aim to release our metrics on our influence on donations in 2017 by the end of June 2018.

Summary

We believe that 2017 was a successful year for GiveWell’s research. We met our five primary goals for the year, as articulated in our plan post from the beginning of the year:

Our primary research goals for 2017 are to:

  1. Speed up our output of new intervention assessments, by hiring a Senior Fellow and by improving our process for reviewing interventions at a shallow level.
  2. Increase the number of promising charities that apply for our recommendation. Alternatively, we may learn why we have relatively few strong applicants and decide whether to change our process as a result. Research Analyst Chelsea Tabart will spend most of her time on this project.
  3. Through GiveWell Incubation Grants, fund projects that may lead to more top charity contenders in the future and consider grantees No Lean Season and Zusha! as potential 2017 top charities.
  4. Further improve the robustness and usability of our cost-effectiveness model.
  5. Improve our process for following the progress of current top charities to reduce staff time, while maintaining quality. We also have some specific goals (discussed below) with respect to answering open questions about current top charities.

We achieved our five primary goals for the year:

  1. Our intervention-related output was greater than in any past year, although we still see room for improvement in the pace with which we complete and publish this work (more). We hired a Senior Fellow and published nine full or interim intervention reports in 2017, compared to four in 2016.
  2. We increased the number of promising charities that applied for our recommendation (more).
  3. We added two new top charities: Evidence Action’s No Lean Season (the first top charity to start as a GiveWell Incubation Grant recipient) and Helen Keller International’s vitamin A supplementation program (which joined our list as a result of our charity outreach work). We continued to follow our current Incubation Grant recipients and made several new Incubation Grants to grow the pipeline of new top charities (more).
  4. We made substantial improvements to our cost-effectiveness analysis (more).
  5. We reduced the amount of staff time spent on following our current top charities. We also completed 17 of the 19 activities outlined in last year’s plan (more).

We discuss progress on each of our primary goals below. For each high-level goal, we include (i) the subgoals we set in our last annual review, (ii) an evaluation of whether we met those subgoals, and (iii) a summary of key activities completed last year.

Goal 1: Speed up intervention assessments

In early 2017, we wrote:

In recent years, we have completed few intervention reports, which has limited our ability to consider new potential top charities. We plan to increase the rate at which we form views on interventions this year by:

  • Hiring a Senior Fellow (or possibly more than one). We expect a Senior Fellow to have a Ph.D. in economics, public health, or statistics or equivalent experience and to focus on in-depth evidence reviews and cost-effectiveness assessments of interventions that appear promising after a shallower investigation. In addition, Open Philanthropy Project Senior Advisor David Roodman may spend some more time on intervention related work.
  • Doing low-intensity research on a large number of promising interventions. We generally start with a two to four hour “quick intervention assessment,” and then prioritize interventions for a 20-30 hour “interim intervention report” (example). We don’t yet have a good sense of how many of these of these we will complete this year, because we’re unsure both about how much capacity we will have for this work and about how many promising interventions there will be at each step in the process.
  • Continuing to improve our systems for ensuring that we become aware of promising interventions and new relevant research as it becomes available. We expect to learn about additional interventions by tracking new research, particularly randomized controlled trials, in global health and development and by talking to select organizations about programs they run that they think we should look into.

How did we do? Achieved our goal.

Due to our uncertainty about the capacity we could devote to intervention assessments, we did not have an explicit target for how many reports we expected to complete. In 2017, we published seven interim intervention reports, two full intervention reports, and completed ~30 quick evidence assessments (defined below). Our research output for 2017 was higher than 2016, when we published one full intervention report, three interim intervention reports, and completed 30 quick evidence assessments.

What did we do?

Goal 2: Increase the pipeline of promising charities applying for our recommendation

In early 2017, we wrote:

We would like to better understand whether we have failed to get the word out about the potential value we offer or communicate well about our process and charities’ likelihood of success, or, alternatively, whether charities are making well-informed decisions about their fit with our criteria. (More on why we think more charities should consider applying for a GiveWell recommendation in this post.)

This year, we have designated GiveWell Research Analyst Chelsea Tabart as charity liaison. Her role is to increase and improve our pipeline of top charity contenders by answering charities’ questions about our process and which program(s) they should apply with, encouraging promising organizations to apply, and, through these conversations, understanding what the barriers are to more charities applying.

We aim by the end of the year to have a stronger pipeline of charities applying, have confidence that we are not missing strong contenders, or understand how we should adjust our process in the future.

How did we do? Achieved our goal.

More charities entered our top charity review process in 2017, although it’s unclear whether this was due to our charity liaison activities. Five charities formally applied in 2017, compared to two in 2016, and four in 2015. One of those charities, Helen Keller International’s vitamin A supplementation program, became a top charity.

While we feel our relationships with well-regarded global health and development implementers and funders have improved, we continue to feel limited in our ability to understand whether there are funding gaps for evidence-backed, highly cost-effective work within large international NGOs and multilateral aid organizations such as the Global Fund to Fight AIDS, Tuberculosis and Malaria.

What did we do?

  • We had at least one conversation with 42 organizations to introduce them to GiveWell’s work in 2017, compared to 16 in 2016.
  • Where organizations running multiple programs expressed interest in applying for our recommendation, we had several calls with them to help determine whether they should apply and which of their programs would be the most promising fit for a top charity evaluation. We had not offered this proactive support to organizations in the past.
  • We hosted two charity-focused events: (i) a conference call for charities with GiveWell senior staff to present an update on our work as it relates to charities and to give them a chance to ask questions directly of our senior team and (ii) a networking event for our recommended organizations in London.
  • We attended seven conferences on global health and development issues to broaden our network and perspective in subject-matter areas that GiveWell has not historically worked on.
Goal 3: Maintain Incubation Grants

In early 2017, we wrote:

We made significant progress on Incubation Grants in 2016 and plan in 2017 to largely continue with ongoing engagements, while being open to new grantmaking opportunities that are brought to our attention.

Among early-to-mid stage grants, we plan to spend the most time on working with IDinsight and New Incentives (where our feedback is needed to move the projects forward), and a smaller amount of time on Results for Development and Charity Science: Health (where we are only following along with ongoing projects).

Another major priority will be following up on two later-stage grantees, No Lean Season and Zusha!, groups that are contenders for a top charity recommendation in 2017. For No Lean Season, a program run by Evidence Action, our main outstanding questions are whether the program will have room for more funding in 2018 and whether monitoring will be high quality as the program scales. We have similar questions about Zusha! and in addition are awaiting randomized controlled trial results that are expected later this year.

How did we do? Exceeded goal.

As expected, our work last year focused on following up on current grantees. No Lean Season, one of our later-stage grantees, graduated to top charity status and we made one grant to a new grantee, the Centre for Pesticide Suicide Prevention. We also made a number of grants to improve our understanding of the evidence base for our priority programs and deepened our partnership with IDinsight.

What did we do?

Goal 4: Improve our cost-effectiveness analysis

In early 2017, we wrote:

We plan to continue making improvements to our cost-effectiveness model and the data it draws on (separate from adding new interventions to the model, which is part of the intervention report work discussed above). Projects we are currently prioritizing include:

  • Making it more straightforward to see how personal values are incorporated into the model and what the implications of those values are.
  • Revisiting the prevalence and intensity adjustment that we use to compare the average per-person impact of deworming in places that our top charities work to the locations where the studies that found long-term impact of deworming were conducted. More in this post.
  • Improving the insecticide-treated nets model by revisiting how it incorporates effects on adult mortality and adjustments for regions with different malaria burdens and changes in malaria burden over time.

How did we do? Achieved goal.

We made substantial progress on improving our cost-effectiveness analysis in 2017.

What did we do?

  • Moved to a system of making more frequent updates to our cost-effectiveness analysis. This has made it easier to identify which specific factors are driving changes in the estimated cost-effectiveness of our top charities.
  • Revisited how we think about leverage and funging (how donating to our top charities influences how other funders spend their money) and updated our cost-effectiveness analysis accordingly.
  • Published a report on how other global actors approach the difficult moral tradeoffs we face.
  • Prior to announcing our 2017 recommendations, we performed a sensitivity check on our cost-effectiveness analysis to identify how sensitive our final outputs were to different uncertain inputs. This has helped us identify which inputs we should prioritize additional research on, and we believe it has made our communication more transparent, particularly around our personal values.
  • Revisited and updated our prevalence and intensity adjustments for deworming.
  • Deprioritized improving how our insecticide-treated net model incorporates effects on adult mortality. A limited number of conversations with malaria experts made us less confident that there was informative research on the question that would improve the accuracy of our models.
  • Deprioritized making adjustments for subnational regions with different malaria burdens because it would take substantial time to deeply understand the assumptions informing the subnational models we have seen. We believe this remains an important weakness of our model and that it limits our ability to make high-quality decisions about prioritization among different regional funding gaps.
Goal 5: Improve our process for following top charities

In early 2017, we wrote:

“In 2017, we plan to have a single staff member do most of this work and expect it to take a half to two-thirds of a full-time job. Three other staff will spend a small portion of their time, totaling approximately the equivalent of one full-time job, on this work.”

How did we do? Achieved goal.

We estimate that it took about 40 percent of the staff member’s time who focused on this work plus a small portion of four other staff members’ time, totaling at most and likely somewhat less than the equivalent of a full-time job (roughly half the time we dedicated to top charity updates in 2016).

We believe we maintained or increased the quality of the top charity updates, as we completed or made major progress on all but two of the activities and questions outlined in last year’s plan.

What did we do?

The table below summarizes our progress on each of the activities and open questions outlined in last year’s plan.

Charity Goals and open questions from 2017 plan Did we meet our goal? What did we do? Evidence Action’s Deworm the World Initiative “We have now followed these groups for several years and do not have major outstanding questions about them. We plan to ask for updates on financial information, monitoring results, and room for more funding and have regular phone calls with them to learn about operational changes that might lead us to ask additional questions.” Yes We had regular phone calls, received up-to-date financial information, updated room for more funding, and reviewed new monitoring information from Nigeria, Vietnam, Kenya, and Ethiopia (see rows 11-20 and an overview of what we learned). GiveDirectly “We have now followed these groups for several years and do not have major outstanding questions about them. We plan to ask for updates on financial information, monitoring results, and room for more funding and have regular phone calls with them to learn about operational changes that might lead us to ask additional questions.” Yes We had regular phone calls, received up-to-date financial information, updated room for more funding, and reviewed new monitoring information from Kenya (1, 2). (Overview of what we learned.) Schistosomiasis Control Initiative “We have now followed these groups for several years and do not have major outstanding questions about them. We plan to ask for updates on financial information, monitoring results, and room for more funding and have regular phone calls with them to learn about operational changes that might lead us to ask additional questions.” Yes We had regular phone calls, received up-to-date financial information, updated room for more funding, and reviewed new monitoring information from 2016 programs in a number of countries. (Monitoring information, overview of what we learned.) Against Malaria Foundation (AMF) “Will AMF’s monitoring processes be high quality?” Yes We commissioned IDinsight, an organization with which we are partnering as part of our Incubation Grants program, to observe post-distribution surveys in Malawi and Ghana and report their findings. “Going forward, AMF aims to fund larger distributions and commit funding further ahead of when a distribution is scheduled to occur than it has, for the most part, done in the past. Will this increase the extent to which AMF funds displace funds from other sources, or will there continue to be evidence that AMF’s funds are largely adding to the total number of nets distributed?” Partial We learned relatively little about the displacement/fungibility question because AMF signed relatively few new agreements to fund long-lasting insecticide-treated net distributions in 2017. There was an update to how AMF will be tracking displacement, described in the second paragraph here. “In order to estimate AMF’s room for more funding, we will seek out information on the location and size of funding gaps for mass net distribution campaigns from AMF, the African Leaders Malaria Alliance, and possibly other funders of nets. As we have in the past, we will use this information in conjunction with conversations with AMF about non-funding bottlenecks to its ability to fill various gaps.” Yes We got updates on AMF’s room for more funding, as summarized in this post. The END Fund’s deworming program “We have not yet seen monitoring on par with that from our other top charities from the END Fund. We expect results from coverage surveys from END Fund programs this year. Will these surveys be high quality and demonstrate that the END Fund is funding successful programs?” Yes We saw some monitoring from END Fund programs; previously our recommendation of the END Fund was based on specific monitoring plans that we found credible (more here). “We have not yet tried to compare the cost-effectiveness of the END Fund to our other top charities in our cost-effectiveness model. We will be seeking additional information from the END Fund about cost per treatment and baseline infection rates” Yes We significantly improved our understanding of the END Fund’s cost per treatment and the baseline prevalence in areas where the END Fund works. We completed a cost-effectiveness analysis, though we continue to have lower confidence in our estimates than we do for the deworming organizations that we have recommended for several years. “Questions around room for more funding: the extent to which funding due to GiveWell’s recommendation increases the amount that the END Fund spends on deworming versus other programs, actual and projected revenue from other sources, and what deworming grantmaking opportunities the END Fund expects to have.” Yes We estimated the extent to which funding due to GiveWell’s recommendation increases the amount that the END Fund spends on deworming versus other programs, discussed here. “We visited the END Fund’s programs in Rwanda and Idjwi island, DRC in January 2017 and will publish notes and photos from our visit shortly.” Yes We posted notes and photos from our site visit here. Malaria Consortium’s seasonal malaria chemoprevention program “Further research on the evidence of effectiveness, cost-effectiveness, and potential downsides of seasonal malaria chemoprevention (SMC) (due to time constraints we have not yet completed a full intervention report, though we felt sufficiently confident in the intervention to recommend Malaria Consortium).” Yes We reviewed each of the RCTs included in the Cochrane review for seasonal malaria chemoprevention, and possible negative/offsetting impacts. We updated our interim intervention report to a full intervention report and added new information to our cost-effectiveness analysis. Our key conclusions did not change substantially and SMC remains a priority program. “Getting a better understanding of the methodology Malaria Consortium uses for estimating coverage rates.” Yes We spoke with Malaria Consortium to understand how they measure coverage and updated our cost-effectiveness analysis to account for different levels of coverage in the Malaria Consortium program relative to the headline results of the RCTs in the Cochrane review (conversation notes here). “Completing a more in-depth room for more funding analysis for the program for 2018 than we did for 2017.” Yes We completed a significantly more in-depth room for more funding analysis than we had previously (more here). “We may visit a Malaria Consortium seasonal malaria chemoprevention program in summer 2017.” No We did not conduct a site visit. Sightsavers’ deworming program “We expect to make limited progress this year because the first deworming mass drug administration funded with GiveWell-influenced funds is not expected to take place until September at the earliest and monitoring results aren’t expected until early 2018. Because Sightsavers has done fairly little deworming in the past year, we don’t expect to be able to learn much from its ongoing programs.” Exceeded In 2017, as expected, we learned relatively little about the performance of Sightsavers’ deworming programs, because programs funded with GiveWell-directed funds were at early stages. We did not expect to receive any monitoring results from programs funded with GiveWell-directed funds; however, Sightsavers shared a coverage survey from Guinea with us earlier than expected. The survey found middling coverage results. “Getting more information from Sightsavers about baseline prevalence and intensity of worm infections in the areas it is working, to inform our cost-effectiveness analysis.” Yes We significantly improved our understanding of Sightsavers’ cost per treatment and the baseline prevalence in areas where Sightsavers works (which is used in our cost-effectiveness analysis). “Using Sightsavers’ budget for the projects and planned treatment numbers to improve our estimate of the cost per treatment – another input into our cost-effectiveness analysis.” Yes We significantly improved our understanding of Sightsavers’ cost per treatment and the baseline prevalence in areas where Sightsavers works (which is used in our cost-effectiveness analysis). “Completing a room for more funding analysis for 2018.” Yes We completed a room for more funding analysis (more here). Standout charities “We plan to have at least one phone call with each of these groups to discuss whether anything has changed that might lead us to reopen consideration of the organization as a potential top charity” Yes We spoke with each standout charity. Conversation notes here: Development Media International, Food Fortification Initiative, Global Alliance for Improved Nutrition’s Universal Salt Iodizational program, Iodine Global Network, Living Goods, and Project Healthy Children.

The post Review of our research in 2017 appeared first on The GiveWell Blog.

Allocation of discretionary funds from Q4 2017

Fri, 04/06/2018 - 12:02

In the fourth quarter of 2017, we received $5.6 million in funding for making grants at our discretion. In this post we discuss:

  • The decision to allocate the $5.6 million to the Schistosomiasis Control Initiative (SCI).
  • Our recommendation that donors give to GiveWell for granting to top charities at our discretion so that we can direct the funding to the top charity or charities with the most pressing funding need. For donors who prefer to give directly to our top charities, we continue to recommend giving 70 percent of your donation to AMF and 30 percent to SCI to maximize your impact.

We noted in November that we would use funds received for making grants at our discretion to fill the next highest priority funding gaps among our top charities. We also noted that our best guess at the time was that we would give 70 percent to the Against Malaria Foundation (AMF) and 30 percent to SCI.

Based on information received since November, described below, we allocated the $5.6 million to SCI, rather than dividing these funds between AMF and SCI, as previously expected. GiveWell’s Executive Director, Elie Hassenfeld, the fund advisor on the Effective Altruism Fund for Global Health and Development, also recommended that the fund grant out the $1.5 million that it held to SCI.

Update on AMF

AMF has been somewhat slower to make commitments to fund distributions of insecticide-treated nets than we expected and our best guess is that its currently available funding will be sufficient to fund all distributions that it is likely to commit to before our next major round of funding allocations in November. Notwithstanding that fact, we continue to believe that AMF has room for more funding. Additional funds would reduce the risk that AMF’s progress will be slowed if it is able to sign several major agreements in the next few months, which, while somewhat unlikely in our estimation, remains a possibility.

We wrote in November 2017:

Progress at signing new agreements was slow in 2017, leaving AMF with a large amount of funds on hand. We attribute this to the fact that countries spent much of 2017 applying for Global Fund funding and decisions about how much funding would be allocated to LLIN distributions for 2018-2020 and what the funding gaps would be for LLINs were being finalized in many countries as of October 2017. AMF noted that it did not commit to funding distributions earlier in part because GiveWell had asked AMF not to make funding commitments until the size of funding gaps were known.

Our expectation had been that the last couple months of 2017 and first months of 2018 would be a period in which AMF would commit a significant portion of its available funding to help fill these gaps because we expected countries to have more visibility into their funding gaps following finalization of Global Fund commitments around October 2017. This has not been the case. AMF recently told us that most of the countries that it was in discussions with did not have visibility into their funding gaps until December 2017, and in some cases it has taken longer than that. In making the decision regarding the fourth quarter discretionary funds, we relied on a document from AMF detailing its signed and potential agreements as of early February. The document noted that AMF had committed to one new distribution since October, in Ghana in 2018. This distribution will cost about $8 million. (We have since learned that AMF has also committed to additional distributions in Papua New Guinea in 2019 and 2020, costing $5.2 million and signed in November 2017, and in Malawi in 2018, costing $10.1 million and signed in mid February.)

AMF’s pipeline of potential future distributions includes both repeat distributions with partners and in countries it has worked with in the past and distributions with new potential partners. AMF has decided to move somewhat slowly with both types of partners. In the case of repeat partners, for several distributions, AMF is waiting to verify that the partner is able to deliver all requested data from distributions that took place in 2017 (and the monitoring that follows each distribution) before agreeing to fund the next round of nets to be delivered in 2020. These decisions seem very reasonable to us, but do result in a short-term decrease in the amount of funding we expect AMF to be able to absorb. When it is ready to do so, AMF could potentially commit up to $50 million to distributions in this category. For the largest potential new partnership that AMF is considering, there are some concerns about in-country capacity and AMF expects to to commit to a smaller-scale distribution (with an estimated cost of $5 million) with the partner and assess the results of that distribution before committing to a larger-scale distribution. AMF is also considering two additional opportunities to commit $5 to $7 million each to distributions with new partners. It could potentially commit tens of millions of dollars to one or more of these countries in future rounds if the initial engagements go well. AMF is also in several early stage conversations about potential distributions with new partners.

According to the document that we relied on for this decision, AMF held $64 million in uncommitted funds, of which $15 million was set aside for “agreement imminent” distributions, leaving $49 million “available to allocate.” Accounting for the additional agreements for Papua New Guinea and Malawi noted above, we estimate that AMF had $49 million in uncommitted funds and $45 million available to allocate as of late February.

The combination of somewhat slower progress in signing distributions than expected and our updated understanding of AMF’s pipeline led us to conclude that AMF continues to have room for more funding, but that SCI’s funding needs were more urgent. Our best guess was that the $5.6 million from GiveWell discretionary funds and $1.5 million from the Effective Altruism Fund would have a greater impact if allocated to SCI.

Update on SCI

In November, we recommended that donors give 30 percent to SCI because SCI had additional room for more funding to sustain its work in its current countries of operation and would need to scale down without additional funding. SCI recently confirmed to us that it would need to cut budgets if it did not receive additional funds before setting its annual budget for April 2018 to March 2019 in March 2018. With AMF having a less urgent funding need than previously expected, we concluded that the best use of the fourth quarter discretionary funds would be to allocate them to SCI.

It is also the case that in the last few months of 2017 SCI received less funding than we projected, both from donors influenced by GiveWell’s research and other donors.

We believe that SCI will continue to have room for more funding after the two grants totaling about $7 million. Recently, SCI sent us an early version of a budget for its 2018-19 budget year. It includes funding requests from each country program, estimates of country program requests in cases where the country has not yet submitted a request, and estimates of SCI spending on central costs and research costs. We estimate that, assuming the same budget in each of the next three years, SCI’s funding gap for that period, after receiving the grants discussed above, is about $9 million. SCI could likely absorb funding beyond that level, as the budget does not include opportunities it has to expand to additional countries. It also assumes that SCI’s other major funders will continue their support at the same level, and some of this funding may be in doubt. We note that about 13 percent of treatments that would be delivered at this scale would be for adults (discussion of this here).

Other possibilities that we decided against

Helen Keller International (HKI) for stopgap funding in one additional country

In December, Good Ventures, on GiveWell’s recommendation, provided HKI with funding for vitamin A supplementation (VAS) programs in Burkina Faso, Mali, and Guinea. Since then, HKI has learned about an unanticipated funding gap for VAS in another country. As a result, a planned VAS distribution in September may not reach national scale and/or may not include deworming (as is common for VAS campaigns). We are in ongoing conversations with HKI about either HKI allocating some of the Good Ventures funding to this country, or GiveWell providing additional funding to cover the gap. We plan to consider this funding opportunity when allocating discretionary funds from the first quarter of 2018. We expect to hold more than enough in discretionary funds (received in the first quarter of 2018) to fill the potential gap and HKI has told us that more information about the gap will be available in time for that decision. (We grant out funds from the previous quarter about two months after the end of that quarter, after we have fully checked the accuracy of our data and the size of grants).

Evidence Action’s Deworm the World for Nigeria

The grant that Good Ventures made to Evidence Action for Deworm the World in December 2017, based on our recommendation, did not include sufficient funds to fund expansion of Deworm the World’s work in Nigeria. Deworm the World sought funding for this work and we prioritized other charities’ funding gaps ahead of this work because we modeled the cost-effectiveness of this work as being lower. We noted in November, “its planned work in Nigeria is around three times as cost-effective as cash transfers (though this estimate is based on low-quality information).” We continue to think that AMF and SCI’s marginal uses of funding are likely more cost-effective than Deworm the World’s potential work in Nigeria, but this conclusion is highly dependent on a model that incorporates many highly uncertain values.

Malaria Consortium for seasonal malaria chemoprevention (SMC)

Our recommendation of Malaria Consortium has resulted in about $30 million in funding for its SMC program since November; however, we believe that there will still be a large funding gap for the program over the next three years. We decided against providing additional funding to Malaria Consortium at this time because of worries about increasing our already very large bet on a program that’s relatively new to us. We are not opposed to increasing this funding level in the future but on balance believe that granting additional funds to SCI is a stronger option at current levels. We’d also note that we’d expect additional funding at this time to go to funding SMC in 2019 and beyond (given the time needed to order drugs and plan programs for the 2018 SMC season) and there is some uncertainty as to the size of the funding gap for SMC in 2019. The program is in a scale-up phase globally and other major funders may increase their contributions to SMC starting in 2019.

What is our recommendation to donors?

We continue to recommend that donors give to GiveWell for granting to top charities at our discretion so that we can direct the funding to the top charity or charities with the most pressing funding need. For donors who prefer to give directly to our top charities, we are continuing to recommend giving 70 percent of your donation to AMF and 30 percent to SCI to maximize your impact.

As part of the process we went through to decide where to allocate these funds, we also discussed whether we should update our recommendation for donors who prefer to give directly to our top charities. We ultimately decided that because updating that recommended allocation is a difficult and time-consuming process because of the additional research and internal discussions involved and because, relatively speaking, few dollars follow this recommendation outside of giving season, we plan to update that allocation only once each year (in November) unless we believe our previously recommended allocation is clearly suboptimal.

In this case, we believe that the $7 million in grants to SCI roughly brings the situation back in line with where it was in November, with AMF and SCI having the next most impactful funding gaps and it being difficult to distinguish on the margin between the quality of AMF and SCI’s funding gaps. SCI has better modeled cost-effectiveness, while AMF appears to be better on several qualitative factors, including monitoring of program performance.

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GiveWell’s money moved and web traffic in 2016

Fri, 03/30/2018 - 10:00

In September 2017, we posted an interim update on GiveWell’s 2016 money moved and web traffic. This post summarizes the key takeaways from our full 2016 money moved and web traffic metrics report. Note that some of the numbers, including the total headline money moved, have changed since our interim report. Since then, we decided to exclude some donations from our headline money moved figure (details in the full report), and we corrected some minor errors.

This report was highly delayed (as discussed in the interim update). We expect to publish our report on GiveWell’s 2017 money moved and web traffic much more quickly; our current expectation is that we will publish that report by the end of June.

GiveWell is dedicated to finding outstanding giving opportunities and publishing the full details of our analysis. In addition to evaluations of other charities, we publish substantial evaluation of our own work. This post lays out highlights from our 2016 metrics report, which reviews what we know about how our research impacted donors. Please note:

  • We report on “metrics years” that run from February through January; for example, our 2016 data cover February 1, 2016 through January 31, 2017.
  • We differentiate between our traditional charity recommendations and our work on the Open Philanthropy Project, which became a separate organization in 2017 and whose work we exclude from this report.
  • More context on the relationship between Good Ventures and GiveWell can be found here.

Summary of influence: In 2016, GiveWell influenced charitable giving in several ways. The following table summarizes our understanding of this influence.

Headline money moved: In 2016, we tracked $88.6 million in money moved to our recommended charities. Our money moved only includes donations that we are confident were influenced by our recommendations.

Money moved by charity: Our seven top charities received the majority of our money moved. Our six standout charities received a total of $2.9 million.

Money moved by size of donor: In 2016, the number of donors and amount donated increased across each donor size category, with the notable exception of donations from donors giving $1,000,000 or more. In 2016, 93% of our money moved (excluding Good Ventures) came from 19% of our donors, who gave $1,000 or more.

Donor retention: The total number of donors who gave to our recommended charities or to GiveWell unrestricted increased about 16% year-over-year to 17,834 in 2016. This included 12,461 donors who gave for the first time. Among all donors who gave in the previous year, about 35% gave again in 2016, down from about 40% who gave again in 2015.

Our retention was stronger among donors who gave larger amounts or who first gave to our recommendations prior to 2014. Of larger donors (those who gave $10,000 or more in either of the last two years), about 77% who gave in 2015 gave again in 2016.

GiveWell’s expenses: GiveWell’s total operating expenses in 2016 were $5.5 million. Our expenses increased from about $3.4 million in 2015 as the size of our staff grew and average seniority level rose. We estimate that about one-third of our total expenses ($2.0 million) supported our traditional top charity work and about two-thirds supported the Open Philanthropy Project. In 2015, we estimated that expenses for our traditional charity work were about $1.1 million.

Donations supporting GiveWell’s operations: GiveWell raised $5.6 million in unrestricted funding (which we use to support our operations) in 2016, compared to $5.1 million in 2015. Our major institutional supporters and the five largest individual donors contributed about 70% of GiveWell’s operational funding in 2016. This is driven in large part by the fact that Good Ventures funded two-thirds of the costs of the Open Philanthropy project, in addition to funding 20% of GiveWell’s other costs.

Web traffic: The number of unique visitors to our website was down very slightly (by 1%) in 2016 compared to 2015 (when excluding visitors driven by AdWords, Google’s online advertising product).

For more detail, see our full metrics report (PDF).

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Considering policy advocacy organizations: Why GiveWell made a grant to the Centre for Pesticide Suicide Prevention

Thu, 03/22/2018 - 12:00

In August 2017, GiveWell recommended a grant of $1.3 million to the Centre for Pesticide Suicide Prevention (CPSP). This grant was made as part of GiveWell’s Incubation Grants program to seed the development of potential future GiveWell top charities and to grow the pipeline of organizations we can consider for a recommendation. CPSP implements a different type of program from work GiveWell has funded in the past. Namely, CPSP identifies the pesticides which are most commonly used in suicides and advocates for governments to ban the most lethal pesticides.

Because CPSP’s goal is to encourage governments to enact bans, its work falls into the broader category of policy advocacy, an area we are newly focused on. We plan to investigate or are in the process of investigating several other policy causes, including tobacco control, lead paint regulation, and measures to improve road traffic safety.

Summary

This post will discuss:

  • GiveWell’s interest in researching policy advocacy interventions as possible priority programs. (More)
  • Why CPSP is promising as a policy advocacy organization and Incubation Grant recipient. (More)
  • Our plans for following CPSP’s work going forward. (More)

Policy advocacy work

One of the key criteria we use to evaluate potential top charities is their cost-effectiveness—how much good each dollar donated to that charity can accomplish. In recent years, we’ve identified several charities that we estimate to be around 4 to 10 times as cost-effective as GiveDirectly, which we use as a benchmark for cost-effectiveness. Our top charities are extremely cost-effective, but we wonder whether we might be able to find opportunities that are significantly more cost-effective than the charities we currently recommend.

Our current top charities largely focus on direct implementation of health and poverty alleviation interventions. One of our best guesses for where we might find significantly more cost-effective charities is in the area of policy advocacy, or programs that aim to influence government policy. Our intuition is that spending a relatively small amount of money on advocacy could lead to policy changes resulting in long-run benefits for many people, and thus could be among the most cost-effective ways to help people. As a result, researching policy advocacy interventions is one of our biggest priorities for the year ahead.

Policy advocacy work may have the following advantages:

  • Leverage: A relatively small amount of spending on advocacy may influence larger amounts of government funding;
  • Sustainability: A policy may be in place for years after its adoption; and
  • Feasibility: Some effective interventions can only be effectively implemented by governments, such as increasing taxes on tobacco to reduce consumption.

Policy advocacy also poses serious challenges for GiveWell when we consider it as a potential priority area:

  • Evidence of effectiveness will likely be lower quality than what we’ve seen from our top charities, e.g. it may involve analyzing trends over time (where confounding factors may complicate analysis) rather than randomized controlled trials or quasi-experimental evidence;
  • Causal attribution will be challenging in that multiple players are likely to be involved in any policy change and policymakers are likely to be influenced by a variety of factors;
  • There may be a substantial chance of failure to pass the desired legislation; and
  • Regulation may have undesirable secondary effects.

Overall, evaluating policy advocacy requires a different approach to assessing evidence and probability of success than our top charities work has in the past.

Incubation Grant to the Centre for Pesticide Suicide Prevention

CPSP began work in 2016 and aims to reduce deaths due to deliberate ingestion of lethal pesticides. With this Incubation Grant, which is intended to cover two years of expenses, CPSP expects to collect data on which pesticides are most often used in suicide attempts and which are most lethal, and then to use this data to advocate to the governments of India and Nepal to implement bans of certain lethal pesticides.

Research suggests that worldwide, approximately 14% to 20% of suicides involved the deliberate ingestion of pesticides. This method of suicide may be particularly common in agricultural populations. The case we see for this grant relies largely on data from Sri Lanka, where bans on the pesticides that were most lethal and most commonly used in suicide coincided with a substantial decrease in the overall suicide rate; we find the case that the decline in suicides was primarily caused by the pesticide bans reasonably compelling. CPSP’s director, Michael Eddleston, was involved in advocating for some of those bans. Read more here.

GiveWell learned of CPSP’s work through James Snowden, who joined GiveWell as a Research Consultant in early 2017. We decided to recommend support to CPSP based on the evidence that pesticide regulation may reduce overall suicide rates, our impression that an advocacy organization could effect changes in regulations, our view that Michael Eddleston and Leah Utyasheva (the co-founders) are well-positioned to do this type of work, and our expectation that we would be able to evaluate CPSP’s impact on pesticide regulation in Nepal and India over the next few years. We thus think CPSP is a plausible future GiveWell top charity and a good fit for an Incubation Grant.

While deciding whether to make this grant, GiveWell staff discussed how to think about the impact of preventing a suicide. Thinking about this question depends on limited empirical information, and staff did not come to an internal consensus. Our best guess at this point is that CPSP generally prevents suicide by people who are making impulsive decisions.

We see several risks to the success of this grant:

  • Banning lethal pesticides may be ineffective as a means of preventing suicide, in India and Nepal or more broadly. The case for this area of policy advocacy relies largely on the observational studies from Sri Lanka mentioned above, supported by Sri Lankan medical records suggesting the decline is partially explained by a shift to less lethal pesticides in suicide attempts.
  • CPSP may not be able to translate its research into policy change. This risk of failure to achieve legislative change characterizes policy advocacy work in general, to some extent, and requires us to make a type of prediction that is not needed when evaluating a charity directly implementing a program.
  • Banning pesticides could lead to offsetting effects in agricultural production. The limited evidence we have seen on this question suggests that past pesticide bans have not led to notable decreases in agricultural production, but we still believe this is a risk.
  • CPSP is a new organization, so it does not have a track record of successfully conducting this type of research and achieving policy change.

To quantify the risks above, GiveWell Executive Director Elie Hassenfeld and James Snowden each recorded predictions about the outcomes of this grant at the time the grant was made. Briefly (more predictions here), Elie and James predict with 33% and 55% probability, respectively, that Nepal will pass legislation banning at least one of the three pesticides most commonly used in suicide by July 1, 2020, and with 15% and 35% probability, respectively, that at least one state in India will do so.

Going forward

We plan to continue having regular conversations with CPSP, and a more substantial check-in one year after the grant was made. At that point, we intend to assess whether CPSP has been meeting the milestones it expected to meet and decide whether to provide a third year of funding. If this grant is successful, we hope we may be able to evaluate CPSP as a potential top charity.

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March 2018 open thread

Tue, 03/13/2018 - 16:27

Our goal with hosting quarterly open threads is to give blog readers an opportunity to publicly raise comments or questions about GiveWell or related topics (in the comments section below). As always, you’re also welcome to email us at info@givewell.org or to request a call with GiveWell staff if you have feedback or questions you’d prefer to discuss privately. We’ll try to respond promptly to questions or comments.

You can view our December 2017 open thread here.

The post March 2018 open thread appeared first on The GiveWell Blog.

Revisiting leverage

Tue, 02/13/2018 - 11:05

Many charities aim to influence how others (other donors, governments, or the private sector) allocate their funds. We call this influence on others “leverage.” Expenditure on a program can also crowd out funding that would otherwise have come from other sources. We call this “funging” (from “fungibility”).

In GiveWell’s early years, we didn’t account for leverage in our cost-effectiveness analysis; we counted all costs of an intervention equally, no matter who paid for them.1For example, see row 3 of our 2013 cost-effectiveness analysis for Against Malaria Foundation. jQuery("#footnote_plugin_tooltip_1").tooltip({ tip: "#footnote_plugin_tooltip_text_1", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); For example, for the Schistosomiasis Control Initiative (SCI), a charity that treats intestinal parasites (deworming), we counted both drug and delivery costs, even when the drugs were donated. We did this because we felt it was the simplest approach, least prone to significant error or manipulation.

Over the last few years, our approach has evolved, and we made some adjustments for leverage and funging to our cost-effectiveness analyses where we felt they were clearly warranted.

In our top charities update at the end of 2017, we made a major change to how we dealt with the question of leverage by incorporating explicit, formal leverage estimates for every charity we recommend.

This change made our cost-effectiveness estimates of deworming charities (which typically leverage substantial government funding) look more cost-effective than our previous method. For example, our new method makes SCI look 1.2x more cost-effective than in the previous cost-effectiveness update. More details are in the table at the end of this post.

We also think the change makes our reasoning more transparent and more consistent across organizations.

In this post, we:

  • Describe how our treatment of leverage and funging has evolved.
  • Highlight two major limitations of our current approach.
  • Present how much difference leverage and funging make to our cost-effectiveness estimates.

Details follow.

How our thinking has evolved

We last wrote about our approach to leverage and funging in a 2011 blog post. In short, we didn’t explicitly account for leverage in our cost-effectiveness analysis, counting costs to all entities equally. We concluded:

When we do cost-effectiveness estimates (e.g., “cost per life saved”) we consider all expenses from all sources, not just funding provided by GiveWell donors. For SCI, we count both drug and delivery costs, even when drugs are donated. (Generally, we try to count all donated goods and services at market value, i.e., the price the donor could have sold them for instead of donating them.) For [the Against Malaria Foundation (AMF)], we count net costs and distribution costs, even though AMF pays only for the former. In the case of VillageReach, we even count government costs of delivering vaccines, even though VillageReach works exclusively to improve the efficiency of the delivery system.

We consider this approach the simplest approach to dealing with the issues discussed here, and given our limited understanding of how “leverage” works, we believe that this approach minimizes the error in our estimates that might come from misreading the “leverage” situation. As our understanding of “leverage” improves, we may approach our cost-effectiveness estimates differently.

Since 2011, our thinking changed. Over time, we started applying some adjustments to our cost-effectiveness model to account for leverage and funging when it seemed important to our bottom line and fairly clear that some adjustment was warranted:

  • We applied discounts to costs incurred by certain entities. For example, we applied a 50% discount to the value of teacher time spent distributing deworming tablets, and excluded the costs to pharmaceutical companies donating these tablets.2See our May 2017 cost-effectiveness analysis. jQuery("#footnote_plugin_tooltip_2").tooltip({ tip: "#footnote_plugin_tooltip_text_2", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); Our rationale was that without our top charities, these resources would likely otherwise been used less productively.
  • We applied ‘alternative funders adjustments’ to account for the possibility that we were crowding out other funders. For example, some of the distributions that AMF considered funding, but didn’t ultimately fund, were picked up by other funders (more).

This helped us explicitly think through considerations relevant to our top charities. But by the end of 2016, our model had a handful of ad hoc adjustments that were difficult to identify, understand, and vet. For example, the discounts we applied to costs incurred by certain entities were ‘baked in’ to our estimates of cost per treatment, rather than explicit on the main spreadsheet of our cost-effectiveness analysis.

Changes to how we incorporate leverage and funging into our cost-effectiveness analysis

We revisited the way we thought about leverage and funging in preparation for our 2017 top charities decision. We wanted to make sure our adjustments were transparent and consistent across all charities.

We now explicitly make quantitative judgments about (i) the probability that our charities are causing governments and multilateral aid agencies to spend more or less on a program than they otherwise would have and (ii) the value of what those funds would otherwise have been spent on.3Our current best guess of a reasonable benchmark for the counterfactual value of government funds is ~75% as cost-effective as GiveDirectly (discussed later in the post). We view this is a very rough guess. jQuery("#footnote_plugin_tooltip_3").tooltip({ tip: "#footnote_plugin_tooltip_text_3", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

Here’s an exercise that some GiveWell staff have found helpful for getting a more intuitive feel for different ways of treating leverage.

Suppose a charity pays $5,000 to purchase magic pills. This would cause (with 100% certainty) the government to spend another $5,000 distributing those pills. The pill distribution saves 1,000 lives in total. If the government didn’t fund the pill distribution, it would have spent $5,000 on something that would have saved 250 lives.

How should a philanthropist think about the cost-effectiveness of this charity?

  1. One option is to include all costs to all actors on the cost side of the cost-effectiveness ratio. Total costs are $10,000 to save 1,000 lives and cost-effectiveness is $10 / life saved. This was GiveWell’s approach in 2011.
  2. Another option is to discount government costs by 50%, because the government would otherwise have spent the funds on something 50% as effective. So total costs are $5,000 + (50% x $5,000) = $7,500. 1,000 lives are saved and cost-effectiveness is $7.50 / life saved. This was GiveWell’s approach from 2014 through 2016.
  3. A third option is to include only the costs to the charity on the ‘cost’ side. The charity causes the magic pill distribution to happen, saving 1,000 lives. But it also causes the government to spend $5,000, which otherwise would have been used to save 250 lives. So the total costs are $5,000, and 1,000 – 250 = 750 lives are saved. Cost-effectiveness is $6.66 / life saved. This is GiveWell’s approach now.4In order to isolate the effect that leverage/funging has, we first calculate the impact of the program using the first method (including all costs equally), then apply a “leverage/funging” adjustment to transform the answer to the third method. jQuery("#footnote_plugin_tooltip_4").tooltip({ tip: "#footnote_plugin_tooltip_text_4", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

We believe the third way of treating leverage best reflects the true counterfactual impact of a charity’s activities. It also makes charities that are leveraging other funders look substantially more cost-effective than we previously thought.

Limitations of our approach

There are two important limitations to the way we account for leverage and funging.

First, these estimates rely on more guesswork than most of our cost-effectiveness analysis, reflecting a fundamental tradeoff we face in deciding which considerations to explicitly quantify. Quantification forces us to think through not just whether a particular consideration matters, but how much it matters relative to other factors, and to be explicit about that. On the other hand, incorporating very uncertain factors into our analysis can reduce its reliability, give a false impression of certainty, and make it difficult for others to engage with our work. In this case, we thought the benefits of explicit quantification outweighed the costs.

Two examples of assumptions going into our leverage and funging adjustments that we’re highly uncertain about:

  1. Our best guess is that the average counterfactual use of domestic government spending that could be leveraged by our top charities is ~75% as cost-effective as GiveDirectly. We think using this figure is a useful heuristic, which roughly accords with our intuitions (and ensures we’re being consistent between charities), but we don’t feel confident that we have a good sense of what governments would counterfactually spend their funds on, or how valuable those activities might be.
  2. We estimate there is a ~70% chance that, without Malaria Consortium funding, the marginal seasonal malaria chemoprevention (SMC) program would go unfunded, but only a ~40% chance that, without Against Malaria Foundation funding, the marginal bednet distribution would go unfunded. Estimating these probabilities is challenging, but taking our best guess forces us to evaluate how much weight to place on the qualitative consideration that there are more alternative funders for bednet distribution than SMC.

Second, we don’t explicitly model the long-term financial sustainability of a program. One worldview we find plausible for the role of effective philanthropy is in demonstrating the effectiveness of novel projects that, in the long run, are taken up by governments. This is not captured within our current model, which only looks at the effects of leverage and funging in the short term. Due to the difficulty of explicitly modelling this consideration, we take it into account qualitatively.5For example, we allocated more discretionary funding than we would have on the basis of cost-effectiveness alone to No Lean Season in 2017 due to our view that it was demonstrating the effectiveness of a novel program, which may have long-run funding implications. jQuery("#footnote_plugin_tooltip_5").tooltip({ tip: "#footnote_plugin_tooltip_text_5", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

 

How much of a difference do leverage and funging make?

In the table below, we present how our new method of accounting for leverage and funging compares to (i) counting all costs equally and (ii) our previous method of accounting for leverage and funging.

Adjustments range between a modest penalty for AMF (because we expect AMF crowds out some funds from other sources) to a large boost to SCI (because the cost to pharmaceutical companies of manufacturing donated drugs comprises a substantial proportion of cost per treatment in SCI distributions, and we expect that without SCI, these resources would have been put to less valuable uses).

Note: 1.2x implies the adjustment makes the charity look 20% more cost-effective; 0.8x implies the adjustment makes the charity look 20% less cost-effective. All charities listed are GiveWell top charities as of November 2017.

Charity Versus counting all costs equally6Calculations here. “N/A” refers to charities for which we had not completed a cost-effectiveness analysis before October 2017. jQuery("#footnote_plugin_tooltip_6").tooltip({ tip: "#footnote_plugin_tooltip_text_6", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); Versus our 2014-16 methodology Commentary Against Malaria Foundation 0.8x 1.1x Government costs represent a small proportion of funding for AMF programs. Our analysis of distributions that AMF considered, but did not fund, suggests that some of these distributions are covered by alternative funders, who would otherwise have supported less valuable programs. Schistosomiasis Control Initiative 2x 1.2x We estimate ~60% of the costs of SCI-supported deworming programs are incurred by either governments or pharmaceutical companies. We expect that without SCI, most of these resources would have been used on less valuable programs. Evidence Action’s Deworm the World Initiative 1.4x 1.1x We estimate ~40% of the costs of Deworm the World-supported deworming programs are incurred by either governments or pharmaceutical companies. We expect that without Deworm the World, most of these resources would have been used on less valuable programs. Sightsavers’ deworming program 1.6x 1.3x We estimate ~50% of the costs of deworming in Sightsavers supported programs are from governments or donated drugs from pharmaceutical companies. We expect that without Sightsavers, most of these resources would have been used on less valuable programs. END Fund’s deworming program 1.3x N/A We estimate ~40% of the costs of END Fund-supported deworming programs are incurred by either governments or pharmaceutical companies. We expect that without the END Fund, most of these resources would have been used on less valuable programs. Helen Keller International (HKI)’s vitamin A supplementation (VAS) program 1.1x N/A We estimate ~25% of the costs of HKI-supported VAS programs are covered by governments. We expect that without HKI, most of these resources would have been used on less valuable programs. GiveDirectly 1x 1x Due to the scalability of GiveDirectly’s program, we believe it is unlikely that GiveDirectly crowds out funding from other sources. GiveDirectly does not leverage funds from other sources. Malaria Consortium’s seasonal malaria chemoprevention program .98x 1.04x Government costs represent a small proportion of funding for Malaria Consortium programs. We believe it is possible but unlikely that Malaria Consortium crowds out additional government funding. Evidence Action’s No Lean Season 1x N/A No Lean Season is a novel program, and we think it’s unlikely to be crowding out funding from other sources. No Lean Season does not leverage substantial funding from other sources.

Notes   [ + ]

1. ↑ For example, see row 3 of our 2013 cost-effectiveness analysis for Against Malaria Foundation. 2. ↑ See our May 2017 cost-effectiveness analysis. 3. ↑ Our current best guess of a reasonable benchmark for the counterfactual value of government funds is ~75% as cost-effective as GiveDirectly (discussed later in the post). We view this is a very rough guess. 4. ↑ In order to isolate the effect that leverage/funging has, we first calculate the impact of the program using the first method (including all costs equally), then apply a “leverage/funging” adjustment to transform the answer to the third method. 5. ↑ For example, we allocated more discretionary funding than we would have on the basis of cost-effectiveness alone to No Lean Season in 2017 due to our view that it was demonstrating the effectiveness of a novel program, which may have long-run funding implications. 6. ↑ Calculations here. “N/A” refers to charities for which we had not completed a cost-effectiveness analysis before October 2017. function footnote_expand_reference_container() { jQuery("#footnote_references_container").show(); jQuery("#footnote_reference_container_collapse_button").text("-"); } function footnote_collapse_reference_container() { jQuery("#footnote_references_container").hide(); jQuery("#footnote_reference_container_collapse_button").text("+"); } function footnote_expand_collapse_reference_container() { if (jQuery("#footnote_references_container").is(":hidden")) { footnote_expand_reference_container(); } else { footnote_collapse_reference_container(); } } function footnote_moveToAnchor(p_str_TargetID) { footnote_expand_reference_container(); var l_obj_Target = jQuery("#" + p_str_TargetID); if(l_obj_Target.length) { jQuery('html, body').animate({ scrollTop: l_obj_Target.offset().top - window.innerHeight/2 }, 1000); } }

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GiveWell is hiring!

Thu, 01/25/2018 - 14:09

We’re actively hiring for roles across GiveWell.

Operations

We’re hiring a Director of Operations. The job posting is here.

The Director of Operations is responsible for many domains and manages a team of eight people. A successful candidate will excel at prioritizing the most impactful work, shepherding improvements to completion, and managing the team.

This job is perfect for someone who wants to:

  • be part of the leadership team at an organization that’s dedicated to making the world a better place.
  • work with colleagues who are passionate about the problems they’re trying to solve.
  • have significant personal ownership and responsibility.

We’re looking for someone based in the San Francisco Bay Area, where GiveWell’s office is located. This job has flexible hours and can partly be done remotely.

Outreach

We’re hiring a Head of Growth. The job posting is here.

The Head of Growth will be responsible for leading our efforts to increase the amount of money GiveWell’s recommended charities receive as a result of our recommendation. The Head of Growth will set a strategy to maximize our money moved by identifying, implementing, and testing a variety of growth strategies and will build a team to support these objectives.

We’re looking for a Head of Growth who is excited for the challenge of starting and building our Growth team and aligned with our commitment to honesty and transparency about our, and our recommended organizations’, shortcomings and strengths.

Research

We’re looking for talented people to add to our research team. Some of our most successful analysts are people who followed our work closely prior to joining GiveWell, so if you read our blog, please consider applying!

We’re hiring for three positions:

Research Analysts and Senior Research Analysts are responsible for all of our research work: reviewing potential top charities and following up with current recommended charities, reviewing the evidence for charitable interventions, building cost-effectiveness models, and evaluating potential Incubation Grants.

Our Summer Research Analyst position is for rising college seniors or graduate students with one year left in their program, and offers the opportunity to work on a variety of research tasks at GiveWell over two to three months.

Research Analysts and Senior Research Analysts do not need to be based in the San Francisco Bay Area. Summer Research Analysts do need to be in the San Francisco Bay Area.

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Revisiting the evidence on malaria eradication in the Americas

Fri, 12/29/2017 - 09:14
Summary
  • Two of GiveWell’s top charities fight malaria in sub-Saharan Africa.
  • GiveWell’s valuations of these charities place some weight on research by Hoyt Bleakley on the impacts of malaria eradication efforts in the American South in the 1920s and in Brazil, Colombia, and Mexico in the 1950s.
  • I reviewed the Bleakley study and mostly support its key findings: the campaigns to eradicate malaria from Brazil, Colombia, and Mexico, and perhaps the American South as well, were followed by accelerated income gains for people whose childhood exposure to the disease was reduced. The timing of these events is compatible with the theory that rolling back malaria increased prosperity. Full write-up here.
Introduction

I blogged three weeks ago about having reviewed and reanalyzed Hoyt Bleakley’s study of the effort in the 1910s to rid the American South of hookworm disease (not malaria). That study, published in 2007, seems to show that the children who benefited from the campaign attended school more and went on to earn more as adults.

For GiveWell, Bleakley’s 2010 study is to malaria parasites as his 2007 study is to intestinal worms. Like the 2007 paper, the 2010 one looks back at large-scale, 20th-century eradication campaigns in order to estimate impacts on schooling and adult income. It too produces encouraging results. And it has influenced GiveWell’s recommendations of certain charities—the Against Malaria Foundation and Malaria Consortium’s seasonal malaria chemoprevention program.

Because GiveWell had already invested in replicating and reanalyzing Bleakley (2007), and because the two papers overlap in data and method, I decided to do the same for Bleakley (2010). And here the parallel between the two papers breaks down: having run the evidence through my analytical sieve, my confidence that eradicating malaria boosted income is substantially higher than my confidence that eradicating hookworm did. I’m a bit less sure that it did so in the United States than in Brazil, Colombia, and Mexico; but the Latin American experience is probably more relevant for the places in which our recommended charities work.

This post will walk through the results. For details, see the new working paper. Because my malaria reanalysis shares so much with the hookworm one, I have written this post as if you read the last one. If you haven’t, please do that now.

How the malaria analysis differs from the hookworm one

Having just emphasized the commonality between Bleakley’s hookworm and malaria eradication studies—and my reanalyses thereof—in order to orient you, I should explain how the two differ:

  • The hookworm study is set exclusively in the American South, while the malaria study looks at efforts in four countries. In the United States in the 1920s, no doubt inspired by the previous decade’s success against hookworm, the Rockefeller Foundation and the U.S. Public Health Service promoted a large-scale program to drain swamps and spray larvicides, which cut malaria mortality in the South by 60%. Then in the 1950s, with the discovery of DDT, the World Health Organization led a worldwide campaign against the disease. Partly because of data availability, Bleakley (2010) studies the consequences in Brazil, Colombia, and Mexico.1Bleakley (2010) also chose these countries because they had malarial and non-malarial regions, allowing comparisons. See Bleakley (2010), note 6. For sample maps see this. jQuery("#footnote_plugin_tooltip_1").tooltip({ tip: "#footnote_plugin_tooltip_text_1", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });
  • Where the hookworm study groups data two ways—first by place of residence to study short-term effects, then by place of birth to study long-term effects—the malaria study does only the latter.
  • I pre-registered my analysis plan for the malaria study with the Open Science Framework and hewed to it. While I did not allow the plan to bind my actions, it serves to disclose which analytical tactics I settled on before I touched the data and could know what results they would produce.2Actually we registered a plan for the hookworm study too, but the malaria plan was better informed—and better followed—precisely because it came on the heels of the similar hookworm reanalysis. For brevity, I skipped this theme in my blog post. I did write about it in the hookworm working paper. jQuery("#footnote_plugin_tooltip_2").tooltip({ tip: "#footnote_plugin_tooltip_text_2", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });
  • The Bleakley malaria paper appeared in a journal published by the American Economic Association (AEA), which requires its authors to post data and computer code on the AEA website. This aided replication and reanalysis. Unfortunately, as appears to be the norm among AEA journals, the Bleakley (2010) data and code only reproduce the paper’s tables, not the graphs that in this case I see as central.
  • For Brazil, Colombia, and Mexico, I mostly relied on that publicly posted data for the crucial information on which regions within a country had the most malaria, rather than trying to construct those variables from old maps and books in Spanish and Portuguese. I also relied on the public data for geographic control variables. I think it can be valuable to go back to primary sources, but for the time being at least, this step looked too time-consuming. I did update and expand the Latin outcome data, on such things as literacy and income, because it is already conveniently digitized in IPUMS International. And I reconstructed all the U.S. data from primary sources, simply by copying what we assembled for the hookworm reanalysis.
Results

In showing you what I found, I’ll follow nearly the same narrative as in my previous post’s section on the “long-term impact on earnings.” To start, here is a key graph from the Bleakley (2010) paper—or really four graphs. In each country’s graph, as with the hookworm graphs, each dot shows the association between historical disease burden in a state (or municipio) and the average income in adulthood of people born there in a given year. In all but Colombia, the leftmost dots line up with the negative range on the vertical axis, meaning that, initially, coming from a historically malarial area stunted one’s income. For example, some of the early U.S. dots are around –0.1 on the vertical axis, which means that being native to swampy Mississippi instead of arid Wyoming cut one’s adult earnings by about 10%.3For cross-country comparability, Bleakley (2010) normalizes the malaria mortality and ecology indexes so that the 5th- and 95th-percentile geographic units—Wyoming and Mississippi in the U.S. case—score 0 and 1. Income proxies are taken in logs. jQuery("#footnote_plugin_tooltip_3").tooltip({ tip: "#footnote_plugin_tooltip_text_3", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); The dots later rise, suggesting that the liability of coming from malarial areas faded, and even reversed. In Colombia, the dots start around zero but also then rise.

As in the hookworm study, here, Bleakley (2010) superimposes on the dots the step-like contour representing how malaria eradication is expected to play out in the data. The steps reach their full height when the campaigns are taken to have started—1920 in the United States and 1957 in the Latin nations. All babies born after these points were alike in that they grew up fully in the post–eradication campaign world. The step contours begin their rises 18 years earlier, when the first babies were born who would benefit from eradication at least a bit by their 18th birthdays.4These graphs incorporate all of Bleakley’s control variables. In my hookworm post, I began both results sections with “basic” graphs that did not include all the controls, imitating Bleakley (2007). In contrast, all the Bleakley (2010) graphs incorporate full controls. So I do the same. jQuery("#footnote_plugin_tooltip_4").tooltip({ tip: "#footnote_plugin_tooltip_text_4", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

Next is my closest replication of the key Bleakley (2010) graphs. These use Bleakley’s data, as posted, but not Bleakley’s computer code, since that was not posted:

The next version adds the latest rounds of census data from the Latin nations and the newer, larger samples from old census rounds for the United States. It also redefines childhood as lasting 21 instead of 18 years, because I discovered that the Bleakley (2010) code uses 18 but the text uses 21. That budges the first dashed lines back by three years:

I avoided superimposing step contours on these data points because I worried that it would trick the brain into thinking that the contours fit the data better than they do. But whether the step contour fits the plots above is exactly what you should ask yourself now. Does it seem as if the dots rise, or rise more, between each pair of vertical, dashed lines? I could see the answer being “yes” for all but Mexico. And that could be a fingerprint of malaria eradication.

I ask that question more formally in the next quartet, fitting line segments to successive ranges of the data. The dots in the four graphs are the same as above, but I’ve taken away the grey confidence intervals for readability. The p values in the lower-left of each pane speak to whether any upward or downward bends at the allowed kink points are statistically significant, i.e., hard to ascribe to chance alone. Where the p values are low—and they mostly are, even in Mexico—they favor the Bleakley (2010) reading that rolling back malaria raised incomes.

In Brazil, Colombia, and Mexico, this statistical test is fairly confident that red lines bend upward at the first kinks (p = 0.00 for Brazil and Colombia and 0.07 for Mexico). That is: in high-malaria areas, relative to low-malaria areas, as the first babies were born who could benefit in childhood from eradication, future incomes rose. The test is less confident for the United States, where the first allowed kink, in 1899, gets a high-ish p value of 0.39. However, the U.S. trend clearly bends upward—just earlier than predicted by the Bleakley (2010) theory. That might mean that the Bleakley (2010) theory is slightly wrong: maybe when it came to impacts on future earnings, malaria exposure continued to matter into one’s twenties, at least in the United States 100 years ago. Then, people born in the South even a bit before 1899 (the date of the first U.S. kink point) would have benefited from the eventual campaign against malaria; and that first kink should be moved to the left, where it would match the data better and produce a lower p value. Or perhaps that high p value of 0.39 signifies that the Bleakley (2010) model is completely wrong for the United States, and that forces other than malaria eradication drove the South’s catch-up on income.

Now, in addition to the four measures of income studied above–one for each country—the Bleakley (2010) paper looks at eight other outcomes. Six are literacy and years of schooling completed, tracked separately in Brazil, Colombia, and Mexico. In addition, there is, for Brazil, earned income—as distinct from total income (“earned” meaning earned through work). And there is, for the United States, Duncan’s Socioeconomic Index (SEI), which blends the occupational income score, explained in my last post, with information about a person’s education level. Your Duncan’s SEI is highest if you hold what is typically a high-paying job (as with the occupational income score) and you have a lot of education.

The first public version of the Bleakley study makes graphs for the additional eight outcomes too. But the final, journal-published version drops them, perhaps to save space. Since for me, the graphs are so central, I generated my own graphs for the other eight outcomes:

These figures hand us a mixed bag. In the United States, the trend on Duncan’s index appears to bend as predicted at the first allowed kink (p = 0.04) but not the second. Seemingly, relative income gains continued in the South well after malaria eradication could cause them. In Brazil, while relative progress on earned income slows when expected (second kink, p = 0.04), it does not appear to accelerate when expected (first kink), perhaps owing to small samples in the early years. In none of the Latin countries does relative progress on adult literacy or years of schooling slow with much statistical significance at the expected time (second kink points in bottom six graphs). The trend bends in all six at the first kink point, and with statistical significance—but the wrong way in Mexico.

In fact, the mixed bag partly corroborates Bleakley (2010), which also questions whether rolling back malaria increased schooling. The new results depart from Bleakley (2010) in also questioning the benefit for literacy. And they cast some doubt on the income impact in the United States. In both the U.S. plots—in the upper-left of the last two sets of graphs above—it’s clear that the income gap between the South and the rest narrowed over many decades. It’s less clear that it did so with a rhythm attributable to the malaria eradication effort of the 1920s.

Conclusion

For me, this reanalysis triggers a modest update to my understanding of the impacts of malaria prevention. With regard to adult income in Latin America, and perhaps the United States, the Bleakley (2010) theory withstands reexamination. It holds up less well for literacy, but this is not very surprising given that Bleakley (2010) also did not find clear impacts on schooling.

I wouldn’t say that my confirmation proves that malaria eradication campaigns in the Americas boosted income in the way that a large-scale randomized study might. But then neither, if you read him closely, does Bleakley. Rather, the evidence “indicates” impact. The theory that malaria eradication in the Americas increased earnings fits pretty well to the data we have. And that is probably about as much certainty as we can expect from this historical analysis.

Much of the data and code for this study are here (2 GB). Because of IPUMS licensing limitations, the download leaves out the census data for Brazil, Colombia, and Mexico. The included “read me” file explains how to obtain this data. The full write-up is here.

Notes   [ + ]

1. ↑ Bleakley (2010) also chose these countries because they had malarial and non-malarial regions, allowing comparisons. See Bleakley (2010), note 6. For sample maps see this. 2. ↑ Actually we registered a plan for the hookworm study too, but the malaria plan was better informed—and better followed—precisely because it came on the heels of the similar hookworm reanalysis. For brevity, I skipped this theme in my blog post. I did write about it in the hookworm working paper. 3. ↑ For cross-country comparability, Bleakley (2010) normalizes the malaria mortality and ecology indexes so that the 5th- and 95th-percentile geographic units—Wyoming and Mississippi in the U.S. case—score 0 and 1. Income proxies are taken in logs. 4. ↑ These graphs incorporate all of Bleakley’s control variables. In my hookworm post, I began both results sections with “basic” graphs that did not include all the controls, imitating Bleakley (2007). In contrast, all the Bleakley (2010) graphs incorporate full controls. So I do the same. function footnote_expand_reference_container() { jQuery("#footnote_references_container").show(); jQuery("#footnote_reference_container_collapse_button").text("-"); } function footnote_collapse_reference_container() { jQuery("#footnote_references_container").hide(); jQuery("#footnote_reference_container_collapse_button").text("+"); } function footnote_expand_collapse_reference_container() { if (jQuery("#footnote_references_container").is(":hidden")) { footnote_expand_reference_container(); } else { footnote_collapse_reference_container(); } } function footnote_moveToAnchor(p_str_TargetID) { footnote_expand_reference_container(); var l_obj_Target = jQuery("#" + p_str_TargetID); if(l_obj_Target.length) { jQuery('html, body').animate({ scrollTop: l_obj_Target.offset().top - window.innerHeight/2 }, 1000); } }

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Key questions about Helen Keller International’s vitamin A supplementation program

Thu, 12/28/2017 - 11:46

One of our two new top charities this year is Helen Keller International (HKI)’s vitamin A supplementation program. We named HKI’s vitamin A supplementation program a top charity this year because:

  • There is strong evidence from many randomized controlled trials of vitamin A supplementation that the program leads to substantial reductions in child deaths.
  • HKI-supported vitamin A supplementation programs are inexpensive (we estimate around $0.75 in total costs per supplement delivered) and highly cost-effective at preventing child deaths in countries where HKI plans to work using GiveWell-directed funds.
  • HKI is transparent—it has shared significant, detailed information about its programs with us, including the results and methodology of monitoring surveys HKI conducted to determine whether its vitamin A supplementation programs reach a large proportion of targeted children.
  • HKI has a funding gap—we believe it is highly likely that its vitamin A supplementation programs will be constrained by funding next year.

HKI’s vitamin A supplementation program is an exceptional giving opportunity, but as with the case for donating to any of our other top charities, not a “sure thing.”

I’m the Research Analyst who has led our work on HKI this year. In this post, I discuss some key questions about the impact of Helen Keller International’s vitamin A supplementation program and what we’ve learned so far. I also discuss GiveWell’s plans for learning more about these issues in the future.

In short:

  • Is vitamin A deficiency still a major concern? Our best guess is that vitamin A deficiency is considerably less common today where HKI works than it was among children who participated in past trials of vitamin A supplementation, but not so rare that vitamin A supplementation would not be cost-effective. We are quite uncertain about our estimate of the prevalence of vitamin A deficiency where HKI works because little high-quality, up-to-date data on vitamin A deficiency is available. We plan to consider funding new surveys of vitamin A deficiency to improve our understanding of the effectiveness of HKI’s programs.
  • Have improvements in health conditions over time reduced the need for vitamin A supplementation? Child mortality rates remain quite high in areas where HKI plans to use GiveWell-directed funding for vitamin A supplementation programs. We think it’s unlikely that health conditions in these countries have improved enough for vitamin A supplementation to no longer be effective.
  • How strong is HKI’s track record of supporting fixed-point vitamin A supplement distributions? HKI expects to primarily support fixed-point vitamin A supplement distributions (rather than door-to-door campaigns) going forward. Results from monitoring surveys have found that, on average, HKI’s fixed-point programs have not reached as high a proportion of targeted populations as its door-to-door programs, but these monitoring surveys may not have been fully representative of HKI’s programs overall. Our best guess is that future fixed-point programs will achieve moderate to high coverage.
Is vitamin A deficiency still a major concern?

Vitamin A deficiency, a condition resulting from chronic low vitamin A intake, can cause loss of vision and increased severity of infections. If vitamin A deficiency is less common today than it was among participants in trials of vitamin A supplementation, today’s programs may prevent fewer deaths than the evidence from the trials suggests.

We estimate that the prevalence of vitamin A deficiency was high (around 60%) in the populations studied in trials included in the Cochrane Collaboration review of vitamin A supplementation programs for preschool-aged children, Imdad et al. 2017.1See the “Imdad 2017 – VAD prevalence estimates” sheet here for details. jQuery("#footnote_plugin_tooltip_1").tooltip({ tip: "#footnote_plugin_tooltip_text_1", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

The map below, from Our World in Data, presents the World Health Organization (WHO)’s most recent estimates of the prevalence of vitamin A deficiency among preschool-aged children by country, covering the period from 1995 to 2005. WHO categorizes prevalences of vitamin A deficiency among preschool-aged children of 20% or above as a severe public health problem.2WHO Global prevalence of vitamin A deficiency in populations at risk 2009, Pg 8, Table 5. jQuery("#footnote_plugin_tooltip_2").tooltip({ tip: "#footnote_plugin_tooltip_text_2", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

Since WHO’s most recent estimates are now considerably out-of-date, we decided to investigate a variety of additional sources in order to create best-guess estimates of rates of vitamin A deficiency today in countries in sub-Saharan Africa where HKI works.

We learned that there is very little useful, up-to-date data on vitamin A deficiency in countries in sub-Saharan Africa. In many countries, the most recent surveys of vitamin A deficiency were completed ten or more years ago. Many governments have also recently mandated the fortification of vegetable oil or other foods with vitamin A, but little information is available on whether foods are actually adequately fortified in practice.3See this spreadsheet for the information we collected on the most recent vitamin A deficiency surveys and on vitamin A fortification programs in countries where HKI has supported vitamin A supplementation programs. jQuery("#footnote_plugin_tooltip_3").tooltip({ tip: "#footnote_plugin_tooltip_text_3", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

Taking the limited available data into account, our best guess is that prevalence of vitamin A deficiency in countries where HKI works today is likely to be considerably lower than the prevalence of vitamin A deficiency among children who participated in vitamin A supplementation trials—closer to 20% prevalence than 60% prevalence.

We find that HKI’s vitamin A supplementation programs still appear highly cost-effective, even when taking our estimate of the change in the prevalence of vitamin A deficiency over time into account (see our most recent cost-effectiveness analysis for full details). But we remain quite uncertain about our estimate of the prevalence of vitamin A deficiency in countries where HKI works—new information could cause us to update our views on HKI’s cost-effectiveness considerably.

Next year, we’ll continue to follow research relevant to estimating vitamin A deficiency rates where HKI works. We also plan to consider funding new vitamin A deficiency surveys ourselves through a GiveWell Incubation Grant.

Have improvements in health conditions over time reduced the need for vitamin A supplementation?

In a blog post last year, we wrote that vitamin A supplementation has a mixed evidence base. There is strong evidence from many randomized controlled trials conducted in the 1980s and 1990s that the program reduces child mortality, but a more recent trial in northern India with more participants than all the other trials combined (the Deworming and Enhanced Vitamin A trial, or DEVTA) did not find a statistically significant effect.

There have been broad declines in child mortality rates over the past few decades. Participants in the control group in the DEVTA trial had a mortality rate of 5.3 deaths per 1,000 child-years, lower than the mortality rates in the control groups in earlier trials that found statistically significant results (ranging from 10.6 to 126 deaths per 1,000 child-years). One potential explanation for the difference between the results of the DEVTA trial and earlier trials is that the some types of deaths prevented by vitamin A supplementation in previously studied populations had already been prevented through other means (e.g., increased access to immunizations and medical care) in the DEVTA population.

We looked into child mortality rates in countries in sub-Saharan Africa where HKI plans to use GiveWell-directed funding in the near future—Guinea, Burkina Faso, and Mali—as well as other countries where HKI has recently worked. Mortality rates among preschool-aged children in Guinea, Burkina Faso and Mali remain quite high—around 13 deaths per 1,000 child-years, within the range of mortality rates among control groups in vitamin A trials that found statistically significant results.4The control group mortality rate in the DEVTA trial was 5.3 per 1,000 child-years. See this spreadsheet for child mortality rates in Burkina Faso, Guinea, and Mali (13 deaths per 1,000 child-years is the simple average of “Average of GBD and UN IGME data” child mortality rates for the three countries), and see here for more information on control group mortality rates in other vitamin A supplementation trials. jQuery("#footnote_plugin_tooltip_4").tooltip({ tip: "#footnote_plugin_tooltip_text_4", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); Based on these high child mortality rates, we don’t believe it’s very likely that overall health conditions have improved enough in these countries for vitamin A supplementation to no longer be effective at preventing deaths.

It is also possible that changes in causes of child deaths between the 1980s and 1990s and today could mean that vitamin A supplementation is now less effective than it was in the past. Different vitamin A experts have different views on whether vitamin A primarily prevents deaths due to a few specific causes (we’ve seen diarrhea and measles most frequently pointed to) or whether it reduces deaths due to a wider range of conditions by, perhaps, strengthening the immune system against infection. In our view, the research on this is inconclusive. According to the data we’ve seen, infectious disease overall and diarrhea in particular cause a similar proportion of total deaths among young children today as they did in the 1980s and 1990s; measles causes a substantially lower proportion of total deaths today than it did in the past.5See the final bullet point in this section of our review of HKI for more on this topic. jQuery("#footnote_plugin_tooltip_5").tooltip({ tip: "#footnote_plugin_tooltip_text_5", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); We’ve added an adjustment to our cost-effectiveness analysis to account for changes in the composition of causes of child mortality since the vitamin A trials were implemented—HKI’s work still appears highly cost-effective following this adjustment.

We may conduct additional research next year to learn about child mortality rates in places where HKI works at a more granular (e.g., regional or sub-regional) level. We may also conduct additional research on the impact of changes in cause-specific mortality rates on the effectiveness of vitamin A supplementation.

How strong is HKI’s track record of supporting fixed-point vitamin A supplement distributions?

In many past HKI-supported campaigns, healthcare workers have traveled door-to-door to administer vitamin A supplements to preschool-aged children. Funding was already available from other sources for sending teams of healthcare workers door-to-door to administer polio vaccinations, and adding vitamin A supplementation to these campaigns was relatively simple and cheap.

In fixed-point distributions, caregivers are expected to bring their children to a central location to receive vitamin A supplements. Due to recent progress in polio elimination, many door-to-door programs have recently been scaled-down or eliminated, so HKI expects to primarily be supporting fixed-point distributions going forward.

It may be more challenging to reach a large proportion of a targeted population with fixed-point distributions. HKI’s recent monitoring surveys have found that, on average, its door-to-door distributions have achieved higher coverage rates (around 90%) than its fixed-point distributions (around 60%). The average of around 60% for fixed-point programs reflects surveys finding high coverage in a few campaigns in the Democratic Republic of the Congo and Mozambique, and relatively low coverage in campaigns in Nigeria, Tanzania, and Kenya.

A complication for assessing HKI’s track record is that HKI often chose to conduct coverage surveys in areas where it expected coverage to be particularly low, so we would guess that these results are not fully representative of HKI’s work on fixed-point distributions.

Based on the available information, our best guess is that HKI-supported fixed-point vitamin A supplementation distributions next year will achieve moderate to high coverage.6To be more precise about what I mean: in Guinea (the program I am most familiar with, following our site visit in October), I’m 70% confident that coverage surveys representative of the distribution as a whole will indicate that the first vitamin A supplement distribution in 2018 reached at least 55% of targeted children across the country. jQuery("#footnote_plugin_tooltip_6").tooltip({ tip: "#footnote_plugin_tooltip_text_6", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); HKI has told us that it will conduct representative monitoring surveys (not only in areas where it expects coverage to be low) following its vitamin A supplement distributions supported with GiveWell-directed funding next year—we expect that these surveys will provide data useful for assessing how successful the programs were overall.

Notes   [ + ]

1. ↑ See the “Imdad 2017 – VAD prevalence estimates” sheet here for details. 2. ↑ WHO Global prevalence of vitamin A deficiency in populations at risk 2009, Pg 8, Table 5. 3. ↑ See this spreadsheet for the information we collected on the most recent vitamin A deficiency surveys and on vitamin A fortification programs in countries where HKI has supported vitamin A supplementation programs. 4. ↑ The control group mortality rate in the DEVTA trial was 5.3 per 1,000 child-years. See this spreadsheet for child mortality rates in Burkina Faso, Guinea, and Mali (13 deaths per 1,000 child-years is the simple average of “Average of GBD and UN IGME data” child mortality rates for the three countries), and see here for more information on control group mortality rates in other vitamin A supplementation trials. 5. ↑ See the final bullet point in this section of our review of HKI for more on this topic. 6. ↑ To be more precise about what I mean: in Guinea (the program I am most familiar with, following our site visit in October), I’m 70% confident that coverage surveys representative of the distribution as a whole will indicate that the first vitamin A supplement distribution in 2018 reached at least 55% of targeted children across the country. function footnote_expand_reference_container() { jQuery("#footnote_references_container").show(); jQuery("#footnote_reference_container_collapse_button").text("-"); } function footnote_collapse_reference_container() { jQuery("#footnote_references_container").hide(); jQuery("#footnote_reference_container_collapse_button").text("+"); } function footnote_expand_collapse_reference_container() { if (jQuery("#footnote_references_container").is(":hidden")) { footnote_expand_reference_container(); } else { footnote_collapse_reference_container(); } } function footnote_moveToAnchor(p_str_TargetID) { footnote_expand_reference_container(); var l_obj_Target = jQuery("#" + p_str_TargetID); if(l_obj_Target.length) { jQuery('html, body').animate({ scrollTop: l_obj_Target.offset().top - window.innerHeight/2 }, 1000); } }

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How uncertain is our cost-effectiveness analysis?

Fri, 12/22/2017 - 15:22

When our cost-effectiveness analysis finds robust and meaningful differences between charities, it plays a large role in our recommendations (more on the role it plays in this post).

But while our cost-effectiveness analysis represent our best guess, it’s also subject to substantial uncertainty; some of its results are a function of highly debatable, difficult-to-estimate inputs.

Sometimes these inputs are largely subjective, such as the moral weight we assign to charities achieving different good outcomes (e.g. improving health vs increasing income). But even objective inputs are uncertain; a key input for anti-malaria interventions is malaria mortality, but the Institute for Health Metrics and Evaluation estimates 1.6 times more people died in Africa from malaria in 2016 (641,000) than the World Health Organization does (407,000; pg. 41).1Differences in their methodology have been discussed, with older figures, in a 2012 blog post by the Center for Global Development. jQuery("#footnote_plugin_tooltip_1").tooltip({ tip: "#footnote_plugin_tooltip_text_1", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

Before we finalized the recommendations we released in November, we determined how sensitive our results were to some of our most uncertain parameters.

In brief:

  • Comparisons between charities achieving different types of good outcome are most sensitive to the relative value we assign to those outcomes (more on how and why we and other policymakers assign these weights in this post).
  • Our deworming models are very uncertain, due to the complexity of the evidence base. They are also sensitive to the choice of discount rate: how we value good done today vs. good done in the future.
  • Our malaria models (seasonal malaria chemoprevention and long-lasting insecticide-treated nets) are less uncertain than our deworming models, but are particularly sensitive to our estimate of the long term effects of malaria on income.

In this post, we discuss:

  • The sensitivity of our analysis to moral weights (more) and other parameters (more).
  • How this uncertainty influences our recommendations (more).
  • Why this sensitivity analysis doesn’t capture the full scope of our uncertainty and ways in which we could improve our assessment and presentation of uncertainty (more).

The tornado charts at the bottom of this post show the results of our full sensitivity analysis. For a brief explanation of how we conducted our sensitivity analysis see this footnote.2Each contributor to our cost-effectiveness analysis inputs their own values for particularly uncertain parameters in our cost-effectiveness analysis. We use the median of contributors’ final cost-effectiveness results for our headline cost-effectiveness figures. To simplify the sensitivity analysis, we used the median of contributors’ parameter inputs to form a central cost-effectiveness estimate for each charity. The results below therefore differ slightly from our headline cost-effectiveness figures. To determine how sensitive the model is to each parameter, we flexed each parameter between the highest and lowest contributors’ inputs, while holding all other parameters constant. For more details, see our sensitivity analysis spreadsheet. jQuery("#footnote_plugin_tooltip_2").tooltip({ tip: "#footnote_plugin_tooltip_text_2", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

Sensitivity to moral weights

Some of the inputs in our model rely on judgement calls, which reasonable, informed people might disagree on. For example, we assign quantitative weights to our relative valuations of different good outcomes. These inputs capture important considerations in our decision-making, but are often difficult to justify precisely.

We ask contributors to our cost-effectiveness analysis (mostly staff) to input how many people’s income would have to double for 1 year to be equally valuable to averting the death of a child under 5. Contributors’ values vary widely, between 8 and 100 (see Figure 1).3You can see each of our contributors’ inputs for moral weights, and other uncertain parameters, on the Moral weights and Parameters tabs of our cost-effectiveness analysis. This year, contributors were also asked to provide a brief justification for their inputs in the cell notes. jQuery("#footnote_plugin_tooltip_3").tooltip({ tip: "#footnote_plugin_tooltip_text_3", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

Differences in cost-effectiveness between charities which primarily prevent child deaths (Helen Keller International, Malaria Consortium, Against Malaria Foundation) and charities which primarily increase income (Deworm the World Initiative, Schistosomiasis Control Initiative, Sightsavers, No Lean Season, End Fund) are highly sensitive to different plausible moral weights (See Figure 2).

The orange points represent the median estimated cost-effectiveness of our charities (in terms of how many times more cost-effective than GiveDirectly we model them to be). The blue bars represents the range of cost-effectiveness for different valuations of preventing the death of an under-5 child between 8x and 100x as good as doubling consumption for one person for one year (holding all other parameters in the model constant). Deworming sensitivities

Our deworming models are very uncertain, due to the complexity of the evidence base, and the long time horizons over which we expect the potential benefits to be realized. Aside from our moral weights, our deworming charities are highly sensitive to three inputs:

  • Replicability adjustment. We make a “replicability adjustment” for deworming to account for the fact that the consumption increase in a major study we rely upon may not hold up if it were replicated. If you’re skeptical that such a large income increase would occur, given the limited evidence for short-term health benefits and generally unexpected nature of the findings, you may think that the effect the study measured wasn’t real, wasn’t driven by deworming, or relied on an atypical characteristic shared by the study population but not likely to found among recipients of the intervention today. This adjustment is not well-grounded in data. (For more discussion see our deworming intervention report and blog posts here, here, here and here).4You can read more about how contributors settled on the values they used for this parameter in the cell notes in row 16 of the Parameters sheet of our November 2017 cost-effectiveness model. jQuery("#footnote_plugin_tooltip_4").tooltip({ tip: "#footnote_plugin_tooltip_text_4", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });
  • Adjustment for years of treatment in Baird et al. vs. years of treatment in charities’ programs. Our charities aim to deworm children for up to 10 years, which is longer than the intervention studies in Baird et al. 2015 (where children in the treatment group received 4 years of deworming). There may be diminishing returns as the total years of treatment increase, although this is difficult to estimate.
  • Discount rate. The discount rate adjusts for benefits that occur at different points in time. For a number of reasons, individuals may believe it is preferable for income to rise now than at some point in the future.

Figure 3 shows how the cost-effectiveness of Deworm the World Initiative5The sensitivity of other deworming charities is largely dependent on the same parameters. Charts are presented in the Appendix jQuery("#footnote_plugin_tooltip_5").tooltip({ tip: "#footnote_plugin_tooltip_text_5", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); varies depending on different contributor inputs for different parameters (more on how to interpret these parameters here).

The orange line represents the median estimated cost-effectiveness of our charities (in terms of how many times more cost-effective than GiveDirectly we model them to be). The blue bars represents the range of cost-effectiveness for different inputs from our contributors for that parameter (holding all other parameters in the model constant). The figures in square brackets represent the range of contributor inputs for those parameters. Malaria sensitivities

Our malaria models are less uncertain than our deworming models, but are still sensitive to our estimate of the long term effects of malaria on income (see Figures 4 and 5).

Interpreting the evidence base for the effect of malaria prevention on long run income is complex, and contributors differ widely in their interpretation. We’re planning to do more research on this topic further but summarize our current understanding here.

What does this mean for our recommendations?

When we model large differences in cost-effectiveness, we generally follow those recommendations. When charities are closer on cost-effectiveness, we pay more attention to qualitative considerations, such as the quality of their monitoring and evaluation, and potential upside benefits which are difficult to quantify (e.g. scaling a novel program).

What counts as a meaningful difference in modelled cost-effectiveness depends on a number of factors, including:

  • Do the programs target the same outcomes? We place less weight on modelled differences between charities which have different good outcomes because our cost-effectiveness analysis is sensitive to different reasonable moral weights.
  • How similar are the programs? We’re more confident in our comparison between our deworming charities than we are between deworming charities and other charities targeting income such as GiveDirectly. This is because we expect the most likely errors in our deworming estimates (e.g. based on our interpretation of the evidence) for different charities to be correlated.
  • Are there important qualitative reasons to differentiate between the charities? We place less relative weight on cost-effectiveness analysis when there are important qualitative reasons to differentiate between charities.

For a more detailed explanation of how we made our recommendations this year, see our recent announcement of our top charities for giving season 2017.

What are the limitations of this sensitivity analysis?

This sensitivity analysis shouldn’t be taken as a full representation of our all things considered uncertainty:

  • The charts above show the sensitivity of the cost-effectiveness analysis to changing one input at a time (holding all other constant). The ranges don’t necessarily imply any particular credible interval, and are more useful for identifying which inputs are most uncertain than for reflecting our all things considered uncertainty around the cost-effectiveness of a particular charity.
  • We don’t ask multiple contributors to input their own values for all uncertain inputs (e.g. because we think the benefits of using the inputs of the contributors with most context outweigh the benefit of getting inputs from many contributors). These inputs have not been included in the sensitivity analysis.
  • Model uncertainty. Explicitly modelling all the considerations relevant to our charity would be infeasible. Even if all our inputs were fully accurate, we’d still retain some uncertainty about the true cost-effectiveness of our charities.

We’re considering a number of different options to improve our sensitivity analysis and communication of uncertainty in the future, such as expressing inputs as probability distributions or creating a Monte Carlo simulation. But we’re uncertain whether these would create sufficient decision-relevant information for our readers to justify the substantial time investment and additional complexity.

If you’d find such an analysis helpful, let us know in the comments.

Appendix

In this section, we present tornado charts for each of our top charities. You can see more detailed descriptions of how to interpret these parameters here, or in the cell notes of our cost-effectiveness analysis.

Notes   [ + ]

1. ↑ Differences in their methodology have been discussed, with older figures, in a 2012 blog post by the Center for Global Development. 2. ↑ Each contributor to our cost-effectiveness analysis inputs their own values for particularly uncertain parameters in our cost-effectiveness analysis. We use the median of contributors’ final cost-effectiveness results for our headline cost-effectiveness figures. To simplify the sensitivity analysis, we used the median of contributors’ parameter inputs to form a central cost-effectiveness estimate for each charity. The results below therefore differ slightly from our headline cost-effectiveness figures. To determine how sensitive the model is to each parameter, we flexed each parameter between the highest and lowest contributors’ inputs, while holding all other parameters constant. For more details, see our sensitivity analysis spreadsheet. 3. ↑ You can see each of our contributors’ inputs for moral weights, and other uncertain parameters, on the Moral weights and Parameters tabs of our cost-effectiveness analysis. This year, contributors were also asked to provide a brief justification for their inputs in the cell notes. 4. ↑ You can read more about how contributors settled on the values they used for this parameter in the cell notes in row 16 of the Parameters sheet of our November 2017 cost-effectiveness model. 5. ↑ The sensitivity of other deworming charities is largely dependent on the same parameters. Charts are presented in the Appendix function footnote_expand_reference_container() { jQuery("#footnote_references_container").show(); jQuery("#footnote_reference_container_collapse_button").text("-"); } function footnote_collapse_reference_container() { jQuery("#footnote_references_container").hide(); jQuery("#footnote_reference_container_collapse_button").text("+"); } function footnote_expand_collapse_reference_container() { if (jQuery("#footnote_references_container").is(":hidden")) { footnote_expand_reference_container(); } else { footnote_collapse_reference_container(); } } function footnote_moveToAnchor(p_str_TargetID) { footnote_expand_reference_container(); var l_obj_Target = jQuery("#" + p_str_TargetID); if(l_obj_Target.length) { jQuery('html, body').animate({ scrollTop: l_obj_Target.offset().top - window.innerHeight/2 }, 1000); } }

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Update on our work on outreach

Tue, 12/19/2017 - 11:33

GiveWell’s impact is a function of the quality of our research and the amount of money we direct to our recommended charities (our “money moved”). Historically, we’ve focused mostly on research because we felt that the quality of our recommendations was a greater constraint to our impact than our money moved.

This has changed. Outreach is now a major organizational priority. The goal of this work is to increase the amount of money we direct to our top-recommended charities.

In April 2014 I wrote about our work on outreach to explain why we hadn’t prioritized it: in brief, our growth had largely been driven by inbound interest in GiveWell, and proactive outreach efforts (beyond building relationships with existing donors) hadn’t yielded results that were worth the cost.

What changed?

  • We believe that the amount of money we move is now a greater constraint to our impact than additional improvements in the quality of our research. Over the last two years, we’ve added five new top charities (three of which implement programs that weren’t previously represented on our top charities list), and we expect that our top charities, collectively, will have more than $200 million in unfilled funding gaps once they’ve received the funding that we expect to direct to them. (This calculation excludes GiveDirectly, which we believe could absorb and distribute hundreds of millions of dollars.) At the same time, the quality of our research and our capacity for research is higher than it’s ever been, so the returns to adding staff there (in terms of the pace at which we identify significantly better giving opportunities) are now lower.
  • Increased capacity for outreach. In our 2014 post, we wrote that one of our key constraints was that senior staff (which at the time meant primarily GiveWell Co-Founder Holden Karnofsky and me) were necessary for most outreach-related work. This has changed. We now have capacity to take on outreach work as other staff have been hired and trained on this type of work.
  • Better information on the impact of GiveWell’s outreach. We now have better information about the returns to outreach because:
    1. We’ve collected better data (via an improved donations processing system and outreach efforts) about where donors find out about us. Because of our ability to track donors, we know that a single appearance on NPR or major podcasts tends to drive $50,000+ in annual donations.
    2. More time passing has demonstrated that the lifetime value of the donations of a first time donor is higher than we expected. In several cases, we’ve seen major donors (i.e., those giving $10,000-$100,000) increase their annual giving by a factor of 10 or more.

We’re in the early stages of figuring out how we can proactively invest time and money in outreach to significantly increase our money moved. For now, we’ve taken some opportunities that we think will have positive returns; these are the three that we’ve invested the most time and money in to date:

  • Podcast advertising. We’ve been advertising on podcasts that we believe our target audience listens to, based on interviews with current donors and GiveWell staff. In February and March, we ran a small experiment with a few ads on FiveThirtyEight’s Politics podcast and Vox’s The Weeds.1We’ve also been running ads on Julia Galef’s Rationally Speaking podcast since then. Because it’s much smaller and more targeted, we’ve excluded it from this analysis. Measured returns to advertising on Rationally Speaking have been significantly better than the more mainstream podcasts discussed in this post. jQuery("#footnote_plugin_tooltip_1").tooltip({ tip: "#footnote_plugin_tooltip_text_1", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

    In total, we spent approximately $20,000 on ads for this initial experiment. We ask donors who give via our website to tell us where they learned about GiveWell when they donate. GiveWell received approximately $8,000 in donations between February 1 and November 20 from donors who reported that they had learned about us via these podcasts.

    The donations we received were from first-time donors; to assess the impact of our advertising, we need to estimate the lifetime value of acquiring a new donor. In work we’ve done to assess our retention rate, we’ve seen that (a) approximately 20-25% of the donors who make a first-time donation of less than $1,000 give again in the subsequent year but (b) because many first-time donors increase the size of their donation over time, collectively, the donors who recur give more than 100% of the value of what they give in their first year.

    At higher donation levels ($1,000-$100,000), we measure 40-45% retention among donors, which leads to retention of approximately two-thirds of dollars given.2I say “measure” retention because we’ve learned that many donors give subsequent donations directly to our top charities and don’t report those donations to us. We’ve tried to follow up with lapsed donors and with charities to track these donors down. jQuery("#footnote_plugin_tooltip_2").tooltip({ tip: "#footnote_plugin_tooltip_text_2", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

    We therefore estimated the net present value of expected future donations (over the next five years) from these podcasts ads as somewhere between approximately $20,000 (assuming two-thirds dollar retention for the first two years and 100% dollar retention subsequently) and $45,000 (assuming 100% dollar retention).3We only projected donations over five years. This is fairly arbitrary because we don’t have long-term enough data to know whether or not this is a reasonable assumption. We capped it to prevent our assessment being driven by speculation about how much money would be donated many years in the future. jQuery("#footnote_plugin_tooltip_3").tooltip({ tip: "#footnote_plugin_tooltip_text_3", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

    A few additional facts are worth keeping in mind about the above figures:

    • We ran this experiment in February and March; most donors give at the end of the calendar year. We consistently see donors who find out about GiveWell during the course of the year, but donate in December. Other things equal, we expect that our advertising would have had greater measured returns in December than earlier in the year.
    • We are only able to track donors who (a) fill out our donation form telling us where they learned about us and (b) give directly through our website rather than to our top charities. Less than 50% of donors who give via credit card (and a smaller percentage of donors who give via check) tell us where they learned about GiveWell. Also, roughly speaking, approximately 50% of the donors and dollars we influence come through GiveWell rather than going to our top charities.4I took this rough estimate from footnote 26, on page 15, of GiveWell’s 2015 metrics report. jQuery("#footnote_plugin_tooltip_4").tooltip({ tip: "#footnote_plugin_tooltip_text_4", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });
    • It’s certainly possible that donors who learn about us via podcast would be more likely to give through our website than an average donor, more likely to report on how they found us (since their source is clear), or less likely to be retained. My best guess is that donors who learn about us via podcast ads behave similarly to our other donors, but I won’t be surprised if they don’t.

    With all that in mind, I believe that the impact of our podcast advertising is higher than what we directly measured.

    The results we saw from February to November this year were promising enough that we decided to increase the size of our experiment by spending approximately $100,000 on podcast ads. We’re currently running ads on FiveThirtyEight’s Politics podcast and Ezra Klein’s podcast and The Weeds at Vox.

  • Earned media outreach. Mentions of GiveWell in the media have historically been a strong driver of growth. We aimed to increase mentions of GiveWell in high-quality, high-profile media where we’ve had the most past success as measured by dollars donated (i.e., media like The New York Times, NPR, The Wall Street Journal, and Financial Times). We retained a PR firm that came strongly recommended; we also increased 1-to-1 outreach by GiveWell staff to members of the media who have covered GiveWell in the past. It’s very hard to attribute the impact of the additional effort we’ve invested—overall, our effort has been fairly limited, and it’s hard to easily draw the causal lines between our work and the stories that appear—but my guess is that our increased efforts have led to more coverage of GiveWell and our top charities this giving season than in the recent past.
  • Website improvements. Companies that sell products online invest significant effort into optimizing their websites and checkout pages to maximize their revenues. We retained a marketing consultant, Will Wong of Mission Street, and we’ve been A/B testing different donation pages and plan to test other pages on our website such as our homepage or top charities page to see whether we can increase our conversion rate (i.e., the percentage of visitors to our website who give to one of our top charities). For context, our current conversion rate is 1%. Our understanding is that a standard conversion rate for e-commerce companies is 2%, and that international nonprofits have a similar conversion rate.5See Pg 51 of the study downloadable here. jQuery("#footnote_plugin_tooltip_5").tooltip({ tip: "#footnote_plugin_tooltip_text_5", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); An increase in our conversion rate to the industry average would lead to a significant increase in the amount of money we direct to our top charities.

Notes   [ + ]

1. ↑ We’ve also been running ads on Julia Galef’s Rationally Speaking podcast since then. Because it’s much smaller and more targeted, we’ve excluded it from this analysis. Measured returns to advertising on Rationally Speaking have been significantly better than the more mainstream podcasts discussed in this post. 2. ↑ I say “measure” retention because we’ve learned that many donors give subsequent donations directly to our top charities and don’t report those donations to us. We’ve tried to follow up with lapsed donors and with charities to track these donors down. 3. ↑ We only projected donations over five years. This is fairly arbitrary because we don’t have long-term enough data to know whether or not this is a reasonable assumption. We capped it to prevent our assessment being driven by speculation about how much money would be donated many years in the future. 4. ↑ I took this rough estimate from footnote 26, on page 15, of GiveWell’s 2015 metrics report. 5. ↑ See Pg 51 of the study downloadable here. function footnote_expand_reference_container() { jQuery("#footnote_references_container").show(); jQuery("#footnote_reference_container_collapse_button").text("-"); } function footnote_collapse_reference_container() { jQuery("#footnote_references_container").hide(); jQuery("#footnote_reference_container_collapse_button").text("+"); } function footnote_expand_collapse_reference_container() { if (jQuery("#footnote_references_container").is(":hidden")) { footnote_expand_reference_container(); } else { footnote_collapse_reference_container(); } } function footnote_moveToAnchor(p_str_TargetID) { footnote_expand_reference_container(); var l_obj_Target = jQuery("#" + p_str_TargetID); if(l_obj_Target.length) { jQuery('html, body').animate({ scrollTop: l_obj_Target.offset().top - window.innerHeight/2 }, 1000); } }

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Maximizing the impact of your donation: saving on fees means more money for great charities

Fri, 12/15/2017 - 14:09

We recently discussed how you can give to reduce the administrative burden on charities. This post will focus on how you can save money on fees and give tax-efficiently so that more of your charitable budget can go directly to the organizations you want to support. This is an updated version of a post we originally ran in 2012; some content is the same, other content has been added or updated.

  1. Don’t wait until the last minute. Many donors wait until the very end of the calendar year to give. If you’re hoping to make a donation by that deadline, we strongly advise against this. Here’s why:
    • Some methods of donating require some planning and preparation, such as giving appreciated stock.
    • Checks are tax-deductible according to the postmarked date on the envelope—you can’t write a check in 2018, backdate it to 2017, and claim a deduction. So, please head to the post office before the new year if you’re looking to get a tax deduction this year.
    • Leaving little time between making your donation and the deadline means you’ll have limited time to react if something unexpected happens, such as your credit card charge being declined.

    We recommend building in a cushion of a week or two if you’re aiming to donate by a particular deadline. The earlier you can give, the less likely you’ll have any issues. For end-of-year giving, we recommend a target date of December 24 or earlier.

  2. Try to get a tax benefit. Details vary by country and personal situation, but a tax deduction can allow you to give much more to charity at the same cost to yourself. (That said, as discussed later in the post, we believe it is more important to give to the most effective possible charity than to get the maximum tax benefit.) Below, we discuss our understanding of donation methods for tax-advantaged giving, although please note that none of this information should be construed as legal or tax advice.

    Donors in the United States may make tax-deductible gifts to any of our nine top charities by giving to GiveWell. There are also a large number of tax-deductible options for giving to our top charities in other countries; please see the table here for more information.

    Donors in certain U.S. states and income brackets who are interested in maximizing their tax deduction may also consider “donation bunching,” or making two donations in one year rather than one donation in each of two years to take advantage of the standard deduction in one year and maximize the size of their itemized charitable deduction in a subsequent year. Considerations related to donation bunching are discussed in this post by former GiveWell intern Ben Kuhn.

  3. Avoid the large transaction fees and delays associated with large online donations. When donating via credit card, you will almost always be charged standard credit card processing fees. Making a large donation via credit card may also trigger your card’s fraud protection (though a call to the credit card company can generally resolve the situation quickly).

    We discussed some of the tradeoffs between the ease of donating via certain platforms and the fees for donors and the administrative costs to charities for processing them in a previous post. In short, we do not advise making donations via credit card if you’re planning to give $1,000 or more.

  4. Give appreciated stock and cryptocurrency. In the U.S., if you give stock or cryptocurrency (such as Bitcoin) to a charity, neither you nor the charity will have to pay taxes on capital gains (as you would if you sold the stock yourself). If you have stock or cryptocurrency that you acquired for $1,000 (and has a cost basis of $1,000) but is now worth $2,000, you can give the stock to charity, take a deduction for $2,000, and not have to pay capital gains tax on the $1,000 of appreciation. This can result in significant savings.

    Due to the administrative cost associated with processing donations of stock, we ask that donors donate stock directly to GiveWell only if the value of the stock at the time of transfer is estimated at approximately $1,000 or more. More information on giving appreciated stock to GiveWell, either through E*Trade or GiveWell’s Vanguard donor-advised fund, is available here. You can also use Betterment to donate appreciated stock to GiveWell. If you’re interested in making a Bitcoin donation to GiveWell, please email us at donations@givewell.org to receive instructions on how to give.

  5. Look into donor-advised funds to make the process smoother and more consistent year-to-year. Donor-advised funds allow donors to make a charitable donation (and get a tax deduction) now, while deciding which charity they’d like to support later. The donation goes into a fund that is “advised” by the donor, and the donor may later recommend a grant from the fund to the charity of his/her choice.

    We see a couple of advantages to this setup. One advantage is that you can separate your “decision date” (the date on which you decide which charity you’d like to support) from your “transaction date.” That means that if you aren’t ready to decide which charity to support yet, you can still get started on the process of transferring funds and getting a tax deduction for the appropriate year. Another advantage is that if you change the charity you support from year to year, you’re still working with the same partner when it comes to transactions, so the process for e.g. donating stock will not change from year to year. Donor-advised funds are often set up to easily accept donated stock or non-traditional assets, whereas charities may or may not be.

    Many large investment companies—Vanguard, Fidelity, Schwab—offer donor-advised funds. They generally charge relatively modest management fees. We also maintain our own donor-advised fund for donors interested in supporting our recommended charities; the minimum size for a donation is $5,000. The GiveWell donor-advised fund is likely most helpful for donors interested in giving certain types of securities, such as Vanguard mutual funds, that are not accepted by E*Trade.

  6. Find out if your company offers donation matching. Many companies offer to match employees’ gifts up to a certain amount. We recommend checking with your employer if you’re unsure whether they offer this option. Some employers have a limited list of charities to which they will match donations; consider asking your employer whether they would add the charity of your choosing if it isn’t already on the list.
  7. Consider the political environment. If you believe that your likelihood of taking charitable deductions is higher in 2017 than it will be in 2018, consider increasing your giving this year.
  8. Choose your charity wisely. Saving money on taxes and transaction fees can be significant, in some cases approaching or exceeding a 50 percent increase in the amount you’re able to give. However, we believe that your choice of charity is a much larger factor in how much good your giving accomplishes.

    Our charity recommendations make it possible to support outstanding, thoroughly vetted organizations—which we’ve investigated by reviewing academic evidence, interviewing staff, analyzing internal documents, conducting site visits, assessing funding needs, and more—without needing to do your own research. We publicly publish the full details of our process and analysis, so you can spot-check whatever part of our work and reasoning you’d like to.

Final notes

If you support our recommended charities (on the basis of our recommendation) but you don’t give through our website, please fill out this form to let us know about your gift; doing so helps GiveWell track our impact.

We believe that even when dealing with a relatively complicated gift (for example, a gift of stock), it’s possible to give quite quickly and with only minor hassle. The much more difficult challenge is choosing a charity, and we’ve tried to make that easy as well. We hope you’ll give this season, even if you’re just starting to think about it now.

If you’d like more advice about how to donate, please don’t hesitate to contact us. We’re happy to talk.

The post Maximizing the impact of your donation: saving on fees means more money for great charities appeared first on The GiveWell Blog.

December 2017 open thread

Fri, 12/15/2017 - 11:18

Our goal with hosting quarterly open threads is to give blog readers an opportunity to publicly raise comments or questions about GiveWell or related topics (in the comments section below). As always, you’re also welcome to email us at info@givewell.org or to request a call with GiveWell staff if you have feedback or questions you’d prefer to discuss privately. We’ll try to respond promptly to questions or comments.

You can view our September 2017 open thread here.

The post December 2017 open thread appeared first on The GiveWell Blog.

Give efficiently and reduce the work for charities

Wed, 12/13/2017 - 11:42

GiveWell’s research aims to help donors by recommending charities we believe can put donations to use efficiently to save or improve lives. Our research focuses on maximizing the good donors can accomplish with their gifts by identifying where to donate effectively.

This is the first of two posts discussing another important aspect of giving effectively: how you donate. The second post will discuss how to maximize your gift (via tax deductions, employer matches, and other strategies) and to ensure the greatest percentage of your donation reaches the charity, rather than being taken up by fees. This post will discuss how to reduce the administrative burdens on charities by choosing your donation method wisely.

How you choose to donate—whether you write a check, fill out a PayPal form, or enter your credit card online—can make a huge difference for the charities that receive your gift. You can save charities time and administrative headaches by being strategic about your method of donation. Our advice follows.

  1. Give predictably. We’re often asked whether it’s better to give a recurring monthly donation or to give once every year. We don’t think one is inherently better than the other. We do think it’s important that you communicate with charities about your plans; this enables them to budget for your donation.
  2. Consider the fees and processing costs of your donation method. Some donation methods require more administrative work for charities to process than others. For example, check donations require multiple manual steps (such as mail retrieval, scanning, data entry, and composing a receipt), whereas online donations can be recorded and thanked automatically. The table below summarizes administrative burden and fees for donations made to GiveWell via the following methods:
    Processing burden Fees GiveWell recommends for what size gift? Online credit card form Low 2.15% (3.20% for AMEX) + $0.28 on each transaction. GiveWell pays the fee. Under $1,000 Check High None for domestic checks. Currency conversion and vetting fees may apply for international checks. GiveWell pays these fees. Over $1,000 Wire transfer Medium Variable. Donor pays the fee. Over $1,000 Appreciated securities High Variable. For E*Trade and Vanguard, GiveWell pays the fee. Over $1,000

    The fees associated with each method also matter. Online credit card donations generally have the highest fees, but the lowest processing time for GiveWell. Checks, on the other hand, have no fees but the highest processing time.

    As a result, we recommend that donors giving under $1,000 make a donation via our online credit card form. For donors giving over $1,000, the calculus changes – we recommend giving via a check. Note that due to the high processing time required for each check we receive, we would advise donors giving via check to make an annual gift, rather than dividing their gift into monthly check payments.

  3. Tell charities where you heard about them and why you chose to support their work. Knowing how donors who use our research or support our operations found GiveWell and why they chose to make a donation is extremely helpful for improving our outreach and research product. We recommend giving charities this basic information. Supporters of GiveWell and our recommended charities can do this by filling out this survey.
  4. Keep in touch! Charities love hearing from their supporters. Ask them questions about their work, let them know if your giving plans change, and offer them feedback on how to improve.

A separate post will discuss how you can save money on fees and give tax-efficiently so that more of your charitable budget can go directly to the organizations you want to support.

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Staff members’ personal donations for giving season 2017

Mon, 12/11/2017 - 08:25

For this post, GiveWell staff members and contributors wrote up the thinking behind their personal donations for the year. We made similar posts in previous years (2013, 2014, 2015, 2016). Staff and contributors are listed in order of their start dates at GiveWell.

You can click the below links to jump to an entry:

Elie Hassenfeld

This year, I’m planning to donate to GiveWell for granting to top charities at its discretion.

GiveWell is currently producing the highest-quality research it ever has, which has led to more thoroughly researched, higher-quality recommendations that have been compared to more potential alternatives than ever before. Personally, I only spent about a third of my time on top-charities-related research in 2017, so I’m thrilled by the quality of the research the GiveWell research team produced this year.

In making this decision I also talked to Lewis Bollard (about animal welfare) and Nick Beckstead (about effective altruism movement building and long-term future giving opportunities) but ultimately felt that the funding gaps that GiveWell’s top charities face were more pressing given the Open Philanthropy Project’s support of their respective portfolios.

Natalie Crispin

I continue to believe that GiveWell top charities are the best option for impact-focused giving for individuals and I plan to give my annual gift this year to GiveWell for granting at its discretion to top charities. I am grateful for all the work, thoughtfulness, and hours of debate that my colleagues put into the recommendations, and I believe that the recommendations are as strong as they’ve ever been. I am excited to support the most effective charities I know of.

Josh Rosenberg

This year I’m planning to give:

  • 80% to GiveWell to grant to top charities at its discretion. I believe that GiveWell’s top charities are among the most effective ways to help people. I know how intensely our team has scrutinized these giving opportunities and am excited to give based on our research.
  • 10% to the long-term future EA Fund. I would like to see future generations thrive. This podcast provides a good summary of some arguments for the moral importance of helping future generations. Based on my experience following the Open Philanthropy Project, I believe that donations to this fund will be put to good use.
  • 10% to charities focused on farm animal welfare. I believe that the welfare of farm animals is a particularly important and neglected problem. I expect to choose a farm animal welfare charity to give to based on Animal Charity Evaluators’ recommendations. I look forward to using its research and would be excited to see similar charity evaluation organizations exist in other domains (e.g., policy-related giving).

I chose to diversify a portion of my giving because I want to signal my interest in a variety of important cause areas that I believe people should be considering and I want to continue to engage with the strongest giving opportunities in other domains to help myself reflect on which donations seem to be most effective. I focused most of my giving on global health and development since GiveWell’s top charities have the most pressing funding gaps I am aware of. If I knew of a strong case for a particular giving opportunity in another cause area, I would be open to changing my allocation in the future.

I also considered giving to the global development EA Fund. I think that this fund would be a good option for donors who (a) are open to higher-risk, higher-reward giving opportunities in global development, and (b) have a high degree of trust in GiveWell (Elie is the manager of the fund). The description of the fund notes that GiveWell’s Incubation Grants (GIG) program has not been hampered by insufficient funding to date. However, I think it may be useful to know if there is a large pool of donors who would like to see more GIG-type giving on the margin; giving to this fund would be a good way to show support for GIG. I ultimately chose not to donate to this fund because a substantial portion of my job is to work on GIG, and I would rather leave it to external observers to assess whether they think it deserves further support. (I see GiveWell’s top charities differently because we’ve thoroughly publicly justified the case for giving to these charities.)

Sophie Monahan

I believe that all of GiveWell’s recommended charities are excellent giving opportunities. I believe that donating to GiveWell for granting to recommended charities is an excellent option (allowing valuable flexibility) for donors whose values align well with GiveWell’s. (On values: more, more, more.)

This year, I am giving to No Lean Season for the following reasons:

  • I place greater value on reducing near-term poverty for adults and children of all ages relative to preventing deaths of very young children, compared to GiveWell as a whole. I also value certainty in the near-term impact of programs relatively more. According to my values, No Lean Season and GiveDirectly are undervalued by GiveWell. Therefore I believe that their funding gaps are a higher priority for people with values like mine.
  • I am giving to No Lean Season despite the fact that this year, GiveWell recommended sufficient funding to No Lean Season to fill its highest priority funding gap (to implement its program in Bangladesh in the next three years), citing reasons other than pure considerations of cost-effectiveness,1“While No Lean Season’s cost-effectiveness is at the lower end of our top charities (~5x cash transfers), we see additional reasons to prioritize this gap. We believe No Lean Season is the top charity where there is the strongest case to be made for “upside”; our cost-effectiveness analysis may not capture the potential impact of scaling a new program that could lead to greater visibility and funding for a novel type of program.” GiveWell blog: Our top charities for giving season 2017 jQuery("#footnote_plugin_tooltip_1").tooltip({ tip: "#footnote_plugin_tooltip_text_1", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); which may not repeat in future years. Therefore, I believe that marginal donations to No Lean Season are likely to increase No Lean Season’s multiyear funding.
  • I am also moved by reasons of sentiment—I led GiveWell’s evaluation of No Lean Season and was very impressed—and to promote the visibility of this new top charity.

Catherine Hollander

I plan to give 90% of my donation to the Against Malaria Foundation (AMF) and 10% to No Lean Season. I trust GiveWell’s review process and its recommendation of AMF as having one of the highest-value funding gaps to fill.

Like Sophie, I plan to support No Lean Season to increase the visibility of a new charity on the list, and because it was the charity review I engaged with most deeply and personally in my time at GiveWell—I traveled with Sophie and Christian to Bangladesh to visit No Lean Season and review its work in September. I plan to limit my donation to No Lean Season to 10% of my total gift because I do not believe its need for funding is as pressing as that of AMF.

Andrew Martin

This year, I’m planning to donate to GiveWell for granting to top charities at its discretion.

I think the case remains as strong as ever that donating to GiveWell’s top charities is an exceptional opportunity for donors who want to maximize their impact. Even after accounting for Good Ventures’ $75 million in grants based on GiveWell’s recommendations this year, we believe that our top charities still have a large amount of room for more funding and that additional donations will accomplish a lot of good.

I’ve decided to donate to GiveWell for granting to top charities at its discretion—rather than donating directly to individual top charities—because I believe it’s valuable for GiveWell to have the flexibility to provide funding to whichever top charities have the most pressing funding needs.

Chelsea Tabart

I plan to donate to GiveWell for granting to top charities at its discretion this year. Another year of exposure to the thoughtful, rigorous work of my colleagues has increased my belief in GiveWell’s research process, and I’m excited that my giving can be a small part of the exceptional work our top charities do.

Christian Smith

I’m planning to direct all of my year-end donations to GiveWell for granting to top charities at its discretion. Several of our charities have large, high-priority funding gaps, and I’m excited to be supporting work that I expect to have a large positive impact.

I think there are reasonable worldviews and ethical positions that would make thoughtful giving in other cause areas (e.g. basic research, animal welfare, or improving the far future) appear much more cost-effective than thoughtful giving to organizations involved in global health and development. I considered directing some of my donations towards these cause areas, but ultimately had a preference for supporting causes in global health and development. I feel fine about this decision, but I may have approached my giving differently if I was not working for GiveWell.

Isabel Arjmand

The allocation of my charitable giving this year will be quite similar to what I did last year, though with a slightly higher proportion going to GiveWell’s top charities. As a general note, I’m inclined to diversify my giving between (1) organizations that are promising from a utilitarian point of view (like GiveWell’s top charities) and (2) those that appeal to different moral considerations.

I’m excited to give 75% of my donation to GiveWell for granting to recommended charities at its discretion. My understanding of GiveWell’s research is much deeper than it was at this point last year (when I was a fairly new staff member), and I remain very enthusiastic about the quality of GiveWell’s recommendations. Especially as someone whose moral values are very close to the median values in our cost-effectiveness analyses, I think giving for granting at GiveWell’s discretion is my best option for impact-focused giving. I considered giving directly to Malaria Consortium’s seasonal malaria chemoprevention program, as I think that it may have the highest-impact remaining funding gap of our top charities, but ultimately the flexibility of giving to GiveWell’s discretionary fund and my trust in GiveWell’s judgment lead me to prefer that option.

Additionally, I plan to give 5% of my donation to GiveDirectly, a GiveWell-recommended organization that I also supported last year. I’m supporting GiveDirectly because I think it’s an exceptionally strong, innovative organization with high potential for ‘upside,’ including the potential to serve as a model for other organizations. I’m thinking of the rationale for this portion of my giving as somewhere in between what I describe in the previous paragraph and what I describe below.

Like last year, I’m thinking of the remainder of my charitable contribution (in this case, 20%) as serving a different, less impact-focused purpose. My goals with this portion of my giving are to promote more justice-focused causes, further my own civic engagement, and signal support for work I’d like to see more of. I’d be surprised if any of the organizations below were as cost-effective as GiveWell’s top charities; I also haven’t vetted them with an intensity that comes anywhere close to the rigor of GiveWell evaluations. Of the four organizations among which I plan to divide this donation, the first two are organizations I supported last year, and the remaining two are new to my list.

  • Causa Justa :: Just Cause: As I wrote last year, I see supporting Causa Justa :: Just Cause—a Bay Area-based grassroots organization supporting housing rights, immigrant rights, and racial justice—as a means of supporting the community in which I live.
  • Planned Parenthood: Reproductive justice and access to healthcare continue to be important to me. Particularly given the absence of a GiveWell-recommended organization providing these services abroad (which I’d guess may be more cost-effective), I’m happy to donate to a U.S.-based organization that I’m personally familiar with and have confidence in.
  • ProPublica: I’m donating to ProPublica in support of its high-quality independent journalism, which I think is critical to a well-functioning civic society.
  • Earthjustice: I decided this year to support an organization working on climate change and environmental justice, and after researching the space briefly, I found Earthjustice—which focuses on environmental protection via legal advocacy—most compelling.

James Snowden (Research Consultant)

This year, I donated monthly through the Effective Altruism Global Health and Development Fund, so I’ve already made the majority of my personal annual donations this year. At the end of year, I set my priorities for the next year, and adjust my automatic monthly donations accordingly.

In practice, donating to the Global Health and Development Fund is similar to donating to GiveWell for granting to top charities at its discretion, as Elie is the fund manager. My primary reason for donating to Effective Altruism Funds rather than directly to GiveWell is that I want to signal support for a project I think is valuable.

I plan to continue giving 80% of my donations to the Global Health and Development fund, but now donate 10% each to the Animal Welfare fund and Long-term Future fund. I think animal welfare and improving the long-term future are extremely important (more so than I did last year). I don’t feel I have enough context to independently evaluate organizations in this area so want to outsource my decisions to Lewis Bollard (for animal welfare), and Nick Beckstead (for global catastrophic risks). I’m uncertain whether, given Good Ventures’ support for animal welfare and the relatively small number of funding opportunities, there’s substantial room for more funding in that area. But I think the ‘worst case scenario’ is that I funge with Good Ventures, which I’d still think was a reasonably good outcome.

I also considered:

  • Donating to the Centre for Pesticide Suicide Prevention. I was the primary researcher working on this GiveWell Incubation Grant and believe it’s a potentially very cost-effective (though risky) giving opportunity. I decided not to donate because the Incubation Grant is intended to fully cover their costs for two years.
  • Donating to Malaria Consortium’s Seasonal Malaria Chemoprevention (SMC) program. Having spent more time looking into SMC this year, I believe it’s a more cost-effective giving opportunity than Against Malaria Foundation (our recommendation to donors this year is 70% Against Malaria Foundation and 30% Schistosomiasis Control Initiative). I decided not to donate to the SMC program this year because (i) we recommended Good Ventures grant $27.9m to Malaria Consortium this year (vs $2.5m for AMF), and I don’t have a strong view that SMC would be more cost-effective on the margin after this grant (ii) I think allowing GiveWell to regrant at its discretion allows for more flexibility (iii) I place more weight in GiveWell’s aggregate view than the inside view of any individual researcher (including myself!)—although I think there’s value in thinking about this independently to identify if GiveWell is making decisions I disagree with.
  • Continuing to donate only to the Global Health and Development fund. I think there’s a strong argument for just donating to the opportunity you think is best in expectation, rather than diversifying. I decided to diversify a fairly small amount because (i) it more accurately signals that I care about those areas (ii) it motivates me to learn more about those areas than I otherwise would have (although I don’t expect this to be a major priority for me).
  • Donating a larger proportion to the Animal Welfare and Far Future funds. Given my relatively greater knowledge in global health and development, I don’t yet feel comfortable giving a greater proportion to areas I know less about.

Aside from my personal giving, I advise a small foundation on their grantmaking. We haven’t yet decided where to give this year, and this will partly depend on the priorities of others involved in the decision.

Notes   [ + ]

1. ↑ “While No Lean Season’s cost-effectiveness is at the lower end of our top charities (~5x cash transfers), we see additional reasons to prioritize this gap. We believe No Lean Season is the top charity where there is the strongest case to be made for “upside”; our cost-effectiveness analysis may not capture the potential impact of scaling a new program that could lead to greater visibility and funding for a novel type of program.” GiveWell blog: Our top charities for giving season 2017 function footnote_expand_reference_container() { jQuery("#footnote_references_container").show(); jQuery("#footnote_reference_container_collapse_button").text("-"); } function footnote_collapse_reference_container() { jQuery("#footnote_references_container").hide(); jQuery("#footnote_reference_container_collapse_button").text("+"); } function footnote_expand_collapse_reference_container() { if (jQuery("#footnote_references_container").is(":hidden")) { footnote_expand_reference_container(); } else { footnote_collapse_reference_container(); } } function footnote_moveToAnchor(p_str_TargetID) { footnote_expand_reference_container(); var l_obj_Target = jQuery("#" + p_str_TargetID); if(l_obj_Target.length) { jQuery('html, body').animate({ scrollTop: l_obj_Target.offset().top - window.innerHeight/2 }, 1000); } }

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Questioning the evidence on hookworm eradication in the American South

Thu, 12/07/2017 - 09:40
Summary
  • Four of GiveWell’s top charities support deworming—the mass distribution of medicines to children in poor countries to rid their bodies of schistosomiasis, hookworm, and parasites.
  • GiveWell’s recommendation relies primarily on research from western Kenya finding that deworming in childhood boosted income in adulthood. GiveWell has also placed weight on a study by Hoyt Bleakley of the hookworm eradication effort in the American South 100 years ago.
  • I reviewed the Bleakley study and reach a different conclusion than he did: the deworming campaign in the American South did not coincide with breaks in long-term trends that would invite eradication as the explanation.
  • GiveWell research staff took the conclusions of this post into account when updating their recommendations for the 2017 giving season. GiveWell continues to recommend deworming charities.
  • I also reviewed a separate Bleakley study of the impacts of malaria eradication in the United States, Brazil, Colombia, and Mexico. My reading there is more supporting. I’m finalizing the write-ups now and will share them soon.
Introduction

After the latest refresh, GiveWell’s list of top charities includes four that support deworming—the mass distribution of medicines to children to rid their guts of certain parasites. Several dozen randomized studies measure the short-term effects of deworming programs (within a year or so) on everything from body weight to being in school.1The 2016 Campbell review finds 52 short-term studies with follow-up duration under five years. Most last one to two years. jQuery("#footnote_plugin_tooltip_1").tooltip({ tip: "#footnote_plugin_tooltip_text_1", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); If intestinal worms were often fatal, then short-term gains against them might be measured in lives saved, which could on its own make a decisive case for deworming. But the symptoms are normally subtler. On the other hand, some research finds that the aftereffects last into adulthood. This is why the long-term effects of deworming dominate GiveWell’s estimates of the cost-effectiveness of charities that support it.

Unfortunately, only a handful of experimental studies assess deworming’s impacts over the long haul, and most of those are based on a single experiment in Kenya. For summaries, see this 2016 post, in the section entitled “The research on the long-term impacts of deworming.” This paucity of experimental evidence has led GiveWell to place weight on a non-experimental, historical study of deworming. Hoyt Bleakley‘s 2007 paper tracks the impacts of the campaign to eradicate hookworm from the American South a century ago.

As part of an ongoing effort to scrutinize the evidence on the long-term impacts of deworming (this, this), GiveWell worked over the past year to revisit the Bleakley study. With huge assists from Christian Smith, Zachary Tausanovitch, and Claire Wang, I have formed a fresh and critical assessment of the evidence. The hookworm eradication effort in the American South did not coincide with breaks in long-term trends that would invite eradication as the explanation. For example, after the eradication campaign, outcomes such as school attendance indeed rose faster for children in historically worm-endemic areas, which could be taken as a sign of success. But that trend began decades before eradication. The full write-up is in this new working paper.

As John D. Rockefeller, arguably the richest human in history, entered philanthropy just over a century ago, he was persuaded to back large-scale, scientifically informed public health campaigns—not unlike Bill Gates in our era. In 1910, he gave $1 million to create the Rockefeller Sanitary Commission for the Eradication of Hookworm Disease. Across eleven southern states from North Carolina to Texas, the RSC soon launched what today would be called the War on Worms. Drugs were dispensed to treat infected children. Doctors, teachers, and the public were educated about the importance of sanitation, especially the use of proper privies.

From a researcher’s point of view, the suddenness and success of the campaign, and its broad geographic sweep, offer hope for credible impact assessment. If, for example, school attendance rates jumped just as infection rates plunged, that could be a compelling sign of the knock-on effects of mass deworming of children. The Bleakley (2007) study recognizes and exploits this opportunity for impact assessment. Paralleling the modern research out of Kenya, the study finds that after the RSC campaign, children in formerly worm-afflicted areas went to school more (a short-term development) and earned more as adults (a long-term effect).

In this post, I’ll explain how the GiveWell reanalysis of the Bleakley (2007) hookworm research differs from Bleakley’s original. Then I will show you some graphs that tell most of the analytical story.

I have also reviewed the related Bleakley (2010) study of the impacts of malaria eradication in the United States, Brazil, Colombia, and Mexico. There, my conclusion is more positive. I hope to release and blog that review in the next few weeks.

What we did

The reanalysis of the Bleakley (2007) hookworm study included the following steps:

  • Returning to primary sources to reconstruct the data set. The data and computer code for the study are not publicly available. In correspondence starting a year ago, Hoyt Bleakley stated that they are effectively inaccessible now. Re-gathering the data was a major undertaking because Bleakley culled nearly 50 variables from obscure, century-old books and articles. Some, such as the student-teacher ratio in each county of the eleven southern states, were found in state government reports that varied in completeness and reporting conventions. Christian Smith, Claire Wang, and, especially, Zachary Tausanovitch, poured many hours into this effort.
  • Expanding the census data sets. Bleakley (2007) tracks outcomes such as school attendance, literacy, and income using U.S. census data. These come to us not from old books, but from the IPUMS online database. Until recently, all the IPUMS data sets were samples from a given year’s census records, taking, for example, one household from every fifth page of the enumeration. (Here’s a sample page from 1920 with my great-grandparents and family in rows 3–6.) When carrying out this research in 2003–05, Bleakley appears to have used the biggest sets then available, such as the 1-in-250 sample from the 1910 census and the 1-in-100 sample from 1920. No data were then to be had from 1930. The GiveWell reanalysis takes advantage of the newer, bigger samples, including preliminary 100% samples for 1910–40. In aggregate, the new data set is about 100 times larger than that in Bleakley (2007).
  • Copying choices from one Bleakley (2007) table or figure to another. For example, one table in the paper estimates impacts on school enrollment, school attendance, and literacy. A corresponding figure, discussed soon, only depicts impacts on attendance. In the new paper, I rerun the figure for all three outcomes.
  • Imposing an arguably tougher standard for proof of impact. I concur with Bleakley that after the eradication campaign swept through the South in 1911–14, prospects improved disproportionately for children born in areas historically prone to hookworm. This catch-up, or convergence, surfaces in the data whether comparing counties within the South (low-lying counties tended to have more hookworm than mountainous ones), or comparing southern states to other states. But that observation alone leaves me unconvinced that ridding children’s bellies of hookworm was the cause. What if the trend began well before eradication or continued well after? I therefore focus on this question: Did convergence temporarily accelerate in tandem with eradication? The Bleakley (2007) tables and figures do not approach this question so aggressively.

We shared drafts of the paper and this post with Hoyt Bleakley. This did not yield any additional insight into why our analysis differs from the original.

The short-term impact on schooling

The figure below, adapted from one edition of the Bleakley study, illustrates the finding that I just mentioned, that after eradication, school attendance surged among kids living where hookworm had been common.2Versions of Bleakley (2007) appeared in the Quarterly Journal of Economics, a World Bank report, and the site of the National Center for Biotechnology Information. They are nearly the same. jQuery("#footnote_plugin_tooltip_2").tooltip({ tip: "#footnote_plugin_tooltip_text_2", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); I will convey the gist of the figure first, then explain it more precisely. You can see that the central red line stays essentially flat from 1870 to 1910. Then it jumps to about zero between 1910 and 1920, census years bracketing the Rockefeller campaign. Thereafter, the red line mostly again holds steady. The one-time jump looks like a fingerprint of eradication.

What does the red line mean exactly? For each census round with available data between 1870 and 1950, Bleakley (2007) computes the association within Southern counties between the school attendance rate of 8–16-year-olds and the hookworm infection rate as measured at the start of eradication, circa 1910.3The regressions for each census year control for the interactions of sex and race on the one hand and age on the other. They do not include the other Bleakley (2007) controls. Samples are restricted to eleven Southern states. The unit of observation is the State Economic Area, which is an aggregation of several counties. jQuery("#footnote_plugin_tooltip_3").tooltip({ tip: "#footnote_plugin_tooltip_text_3", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] }); That the red line starts around –0.1 in 1870 means that on average, if a county’s child hookworm infection rate was 10 percentage points higher when measured around 1910, its school attendance rate in the 1870 census was 1 percentage point lower. More plainly, counties with more worms in kids had fewer kids in school. But between the 1910 and 1920 censuses, that bad-news association abruptly faded. As of 1920, a child in a historically high-hookworm county was no less likely to be in school. The black, dashed lines show confidence intervals for these census-by-census estimates—probably 95% confidence, but I cannot tell for sure.

Here is the best replication of that graph using the reconstructed data and code. I have drawn it differently to emphasize that we only have data from certain decennial censuses, and to depict the gradations of confidence within the 95% confidence intervals.4The 1890 census records were destroyed in a fire. 1930 records had not been digitized at the time Bleakley did this work. jQuery("#footnote_plugin_tooltip_4").tooltip({ tip: "#footnote_plugin_tooltip_text_4", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

I discern a resemblance between the original graph and the reconstruction. In both, school enrollment rises especially quickly between 1910 and 1920 and then declines slightly. But there is a difference too, and it is more than cosmetic. Now it appears that children in hookworm-infested areas gained substantially on school attendance not just between 1910 and 1920 but between 1880 and 1900 as well—and maybe throughout 1880–1910. For lack of access to Bleakley’s data and code, I cannot explain the discrepancy between this reconstruction and the original. There could be an error in the new or the old, or some subtle difference in data or method.

The new graph’s ambiguous mix of confirmation and contradiction forces a question that is at once conceptual and practical. How do we systematically judge whether the signal of hookworm eradication is present amidst the noise of other influences? To what degree does the new graph confirm or contradict the old?

I think there is no one best way to answer that question. One approach that I took is depicted with the red lines in the reconstructed graph above, and in the p values in the bottom-left corner. I drew the red lines to connect the dots that surround the eradication campaign. I wanted to quantify how much the red contour bends upward in 1910 and downward in 1920—as in Bleakley’s graph—and with what statistical significance. That is: Suppose the education gains took place at a constant pace between 1900 and 1940 with no acceleration around the campaign in the early 1910s. (I would have substituted 1930 for 1940 were 1930 data available in this graph.) What is the chance that we would see as much bending in the red line as we do? The computer says that for the upward kink at 1910, the answer is 0.37, which is not very low. On the other hand, the deceleration around 1920 is quite hard to ascribe to pure chance, at p = 0.03. Still, the new graph casts doubt on the proposition that the campaign brought a big break with the past.

Having settled on an analytical approach, the next step was to add all the census data that has been digitized since Bleakley did his work. This brings an obvious change (see below; now that 1930 data are included, I extend the third red line only that far). Now it looks far more as though the high-hookworm parts of the South began closing the schooling gap with low-hookworm parts around 1880, some 30 years before the hookworm campaign:

In a final test, I recomputed the graph while incorporating all the Bleakley (2007) control variables. Hookworm eradication was hardly a clean experiment, in the sense that the geographic reach of the disease was not random going in. The South had it more than the rest of the country; within the South, the coastal plains had it most. If the beneficiaries of eradication differed systematically from the rest before eradication, they could continue to differ after for reasons having little to do with hookworm prevention, creating a false appearance of impact. Striving to statistically remove such initial differences, Bleakley (2007) introduces into some of the regressions an aggressive set of controls. They relate to education, health, agriculture, and race. The paper includes these controls in some of the schooling regressions reported in a table, but does not bring them to the schooling graph shown above. It turns out that doing so (in our expanded-data graph) removes most signs of any long-term gains:

The lack of upward trend here does not mean that the historically hookworm-burdened parts of the South did not after all close a schooling gap between 1880 and 1920. It does suggest that the closure was correlated with, and therefore potentially caused by, the non-hookworm factors that Bleakley sometimes controls for.5Consistent with this graph, while the Bleakley (2007) full-controls regressions continue to put a statistically significant coefficient on the treatment proxy, the reconstructions do not. This is one of the few cases where the original results are not recognizable in the reconstruction. See Table 6, panel B, of the new paper. jQuery("#footnote_plugin_tooltip_5").tooltip({ tip: "#footnote_plugin_tooltip_text_5", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });

In sum, I do not see robust evidence that schooling and literacy improved at an historically anomalous rate circa 1910, in a way naturally attributable to hookworm eradication.

The long-term impact on earnings

What the first half of the Bleakley (2007) study does for short-term impacts on schooling, the second does for long-term impacts on earnings. Here too, the conclusion is encouraging. “Long-term follow-up,” writes Bleakley, “indicates a substantial income gain as a result of the reduction in hookworm infection.” This finding resonates strongly with the GiveWell cost-effectiveness analysis, which makes a key assumption about how much deworming children boosts future income. The number we use for that impact comes from modern, experimental research in Kenya; yet Bleakley’s inference from American history had boosted our confidence in the Kenya number. (That said, GiveWell has discounted the Kenya number by 80–90% out of fear that it won’t replicate to other settings.6See the “Replicability adjustment for deworming” row of the “Parameters” tab of the cost-effectiveness analysis spreadsheet. jQuery("#footnote_plugin_tooltip_6").tooltip({ tip: "#footnote_plugin_tooltip_text_6", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });)

The Bleakley (2007) graph I will focus on draws together data from censuses as ancient as 1870 and modern as 1990. One problem with measuring impacts on income over this span is that not until 1940 did Census takers begin asking people how much money they made. For this reason, the IPUMS census database provides proxies for income that reach back farther. One is the occupational income score (OIS), which is, approximately speaking, the average income in 1950 associated with a person’s census-reported profession. Thus, if lawyers averaged $10,000 in income in 1950, then any self-described lawyer between 1870 and 1990 is taken to earn that much. The OIS is expressed in hundreds of dollars of 1950, and is an example of an index of “occupational standing.”

Before scrutinizing the evidence of long-term impacts on occupational standing, I need to describe a twist that Bleakley (2007) introduces in moving from short- to long-term. As one tries to follow people over longer periods of time, the analytical tack that Bleakley took for schooling starts to break down. For it looks at how the people in given places fared over time. The problem is that sometimes people move—across the state or across the country. And in this analytical set-up, the researcher does not follow them. If deworming gave children in coastal Georgia more agency in life—better health, more education—perhaps they exercised that agency by moving to Atlanta. If we only looked at the incomes of the people who stayed behind, we would miss the full story.

To minimize this attrition from migration, in studying long-term impacts, Bleakley (2007) groups census records not by place of residence at the time of census, but by place of birth. Then, if a person was born in Georgia in 1915, showed up in the census in 1940 as a bricklayer in Atlanta, in 1950 as a general contractor in Lexington, and in 1960 as the manager of a construction company in Phoenix, all three census records would be associated with Georgia in 1915. After organizing the data this way, Bleakley (2007) could study whether children born in certain areas after eradication went on to earn more than those born in the same places before eradication.

Reorganizing the data this way generates two ripple effects. First, while census takers record place of residence with extreme precision, they only record place of birth by state. We cannot differentiate people by whether they were born in hookworm-prone areas within, say, Mississippi. We can only differentiate by whether they were native to a historically high-hookworm state such as Mississippi or a low-hookworm one such as Michigan. Thus, while the short-term analysis compares counties within 11 southern states, the long-term analysis compares states across the continental U.S.

The second ripple effect is that the data come to us at higher temporal resolution: by birth year, not census decade. In response, Bleakley (2007) hypothesizes that how much hookworm depressed adult earnings depended on the percentage of one’s childhood spent where it was endemic. If we take eradication to have occurred in 1910 and assume with Bleakley (2007) that childhood lasts 19 years, then babies born in or before 1891 would have reached adulthood before eradication, too soon to benefit. Babies born in endemic areas in 1892 would have been helped for one year (between their 18th and 19th birthdays); in 1893 for two; and so on. Those born in 1910 or later stood to reap the full 19 years of benefit. Bleakley (2007) therefore hypothesizes that the impact of eradication follows a sort of diagonal step shape with respect to birth year. The step starts rising in 1891 and stops in 1910. Bleakley depicted that contour with dashed lines in this figure:

As you can see, Bleakley (2007) fit this contour to data, to see how well it could explain historical patterns. These dots are derived much as in the earlier Bleakley (2007) figure. For example, the leftmost dot is for the year 1825, and has a vertical coordinate of about –2. That means that among people born in 1825, being native to a state whose hookworm infection rate circa 1910 was 10 percentage points (0.1) higher corresponded to having an Occupational Income Score 0.20 lower. That means $20/year less income throughout adulthood, in the dollars of 1950. The graph shows that this association was generally negative in the mid-19th century and generally positive after 1910: formerly, coming from a hookworm zone depressed lifetime earnings. And the graph suggests that the transition followed the step pattern expected if the cause was hookworm eradication.

Below is my best reproduction of that graph. As before, I have plotted both the dots and their 95% confidence intervals. I have avoided superimposing the step-like contour the way Bleakley (2007) does because I worry that it tricks the eye into believing that the contour fits the data better than it really does. But I have marked the years when the contour kinks, 1891 and 1910:

Here is the same graph when using the 100-times-bigger census data sets now available7In addition to adding data, this version mimics the rest of the Bleakley (2007) analysis in adding blacks and in fitting directly to census microdata rather than aggregates, in order to include controls for race, sex, and their interaction. jQuery("#footnote_plugin_tooltip_7").tooltip({ tip: "#footnote_plugin_tooltip_text_7", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });:

And here is the graph when I copy Bleakley (2010) in incorporating all the controls for cross-state differences in health and health policy, education policy, and other traits8As I noted, when looking at short-term impacts on education, Bleakley (2007) does not plot a graph while incorporating all controls. But now, when looking at long-term impacts on occupational standing, Bleakley (2007) does also include such a graph. See the bottom right of this figure. jQuery("#footnote_plugin_tooltip_8").tooltip({ tip: "#footnote_plugin_tooltip_text_8", tipClass: "footnote_tooltip", effect: "fade", fadeOutSpeed: 100, predelay: 400, position: "top right", relative: true, offset: [10, 10] });:

Does it look to you like the upward trends in these last two graphs accelerated around 1891 and decelerated around 1910, as predicted by the Bleakley (2007) theory? To me, I have to say, not much. The climbs look steady and longer-term.

Since “not much” is muddy, I moved once again to formalize my interpretation. In analogy with my earlier graphs for schooling, I fit lines to the data points in the 19 years between 1891 and 1910, as well as to the 19 years on either side. Then I checked whether any bending in 1891 and 1910 is statistically significant. The final two graphs fit lines to the dots in the previous two. The dots in these next graphs are the same as in the previous two. It doesn’t look that way because I erased the grey confidence bars in order to expand the vertical scales.

In the both graphs the trend looks quite straight over the three generations surrounding the eradication campaign. The p values, shown in the bottom-right of each plot, are high.

Conclusion

Reanalyzing the Bleakley (2007) study left me unconvinced that the children who benefited from hookworm eradication went to school more or earned more as adults. Conceivably, if I had access to the original data and code, the confrontation with the reconstructed versions would expose errors in the GiveWell version that would alter my view. But this seems unlikely. The new census data sets are much bigger than the old, which improves precision. And most of the differences probably do not arise from clear-cut errors on either side, but from minor differences in implementation, such as taking education spending from a different edition of an annual government report. If the conclusions swing on such modest and debatable discrepancies, then they are not robust and reliable.

Finally, even if the two versions of the data matched exactly, I might still disagree on interpretation, since I use tests, illustrated above, that focus more exclusively on whether the time trends contain the temporal fingerprint of hookworm eradication. For me, that fingerprint is characterized not merely by once-high-hookworm areas catching up with low-hookworm ones, but catch-up that accelerates and decelerates at times that fit the timing of the eradication campaign.

The data and code for this study are here (1.6 GB). The full write-up is here.

 

Notes   [ + ]

1. ↑ The 2016 Campbell review finds 52 short-term studies with follow-up duration under five years. Most last one to two years. 2. ↑ Versions of Bleakley (2007) appeared in the Quarterly Journal of Economics, a World Bank report, and the site of the National Center for Biotechnology Information. They are nearly the same. 3. ↑ The regressions for each census year control for the interactions of sex and race on the one hand and age on the other. They do not include the other Bleakley (2007) controls. Samples are restricted to eleven Southern states. The unit of observation is the State Economic Area, which is an aggregation of several counties. 4. ↑ The 1890 census records were destroyed in a fire. 1930 records had not been digitized at the time Bleakley did this work. 5. ↑ Consistent with this graph, while the Bleakley (2007) full-controls regressions continue to put a statistically significant coefficient on the treatment proxy, the reconstructions do not. This is one of the few cases where the original results are not recognizable in the reconstruction. See Table 6, panel B, of the new paper. 6. ↑ See the “Replicability adjustment for deworming” row of the “Parameters” tab of the cost-effectiveness analysis spreadsheet. 7. ↑ In addition to adding data, this version mimics the rest of the Bleakley (2007) analysis in adding blacks and in fitting directly to census microdata rather than aggregates, in order to include controls for race, sex, and their interaction. 8. ↑ As I noted, when looking at short-term impacts on education, Bleakley (2007) does not plot a graph while incorporating all controls. But now, when looking at long-term impacts on occupational standing, Bleakley (2007) does also include such a graph. See the bottom right of this figure. function footnote_expand_reference_container() { jQuery("#footnote_references_container").show(); jQuery("#footnote_reference_container_collapse_button").text("-"); } function footnote_collapse_reference_container() { jQuery("#footnote_references_container").hide(); jQuery("#footnote_reference_container_collapse_button").text("+"); } function footnote_expand_collapse_reference_container() { if (jQuery("#footnote_references_container").is(":hidden")) { footnote_expand_reference_container(); } else { footnote_collapse_reference_container(); } } function footnote_moveToAnchor(p_str_TargetID) { footnote_expand_reference_container(); var l_obj_Target = jQuery("#" + p_str_TargetID); if(l_obj_Target.length) { jQuery('html, body').animate({ scrollTop: l_obj_Target.offset().top - window.innerHeight/2 }, 1000); } }

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Want to talk to someone at GiveWell about your giving decision?

Tue, 12/05/2017 - 10:12

If you’re thinking about where to give to charity this year and it would be helpful to speak with a member of GiveWell’s staff about your decision, please let us know. We’re happy to answer questions sent to info@givewell.org or to schedule a call via the form here.

We know we publish a lot of information, and we’re glad to provide a brief overview of our headline recommendations. We can also answer questions about our process for finding top charities, the strengths and weaknesses of our top charities, or how your personal values might point you toward one organization we recommend over another. Conversations like these also help us understand how people use our research and what questions they have.

Due to limited staff capacity, it’s possible we won’t be able to speak with everyone who requests a call, although based on past experience we hope to be able to connect with anyone who gets in touch.

We look forward to hearing from you!

The post Want to talk to someone at GiveWell about your giving decision? appeared first on The GiveWell Blog.

Our top charities for giving season 2017

Mon, 11/27/2017 - 14:33

This year, we added two new top charities, Evidence Action’s No Lean Season program and Helen Keller International’s vitamin A supplementation program, and retained our seven top charities from 2016. We also added Evidence Action’s Dispensers for Safe Water program to our list of standout charities.

We recommend that donors give to GiveWell for granting to top charities at our discretion so that we can direct the funding to the top charity or charities with the most pressing funding need. For donors who prefer to give directly to our top charities, we recommend giving 70 percent of your donation to the Against Malaria Foundation (AMF) and 30 percent to the Schistosomiasis Control Initiative (SCI) to maximize your impact. We expect Good Ventures, a foundation with which we work closely, to provide significant support to each top charity; our recommendation to give to AMF and SCI is based on how much good we believe additional donations can do.

Our top charities and recommendations for donors, in brief

Top charities

We now have nine top charities. They are:

Standout charities

We also provide a list of standout charities. We believe they are implementing programs that are evidence-backed and may be extremely cost-effective. However, we do not feel as confident in the impact of these organizations as we do in our top charities.

Conference call to discuss recommendations

We are planning to hold a conference call at 1:30pm ET/10:30am PT on Thursday, November 30 to discuss our charity recommendations and answer your questions.

If you’d like to join the call, please register using this online form. If you can’t make this date, but would be interested in joining another call at a later date, please indicate this on the registration form.

Additional details and explanation

Below, we provide:

  • An explanation of changes to our recommended charity list and of major changes to our review process in the past year that are not specific to any one organization. More
  • A discussion of our approach to determining how much funding charities can use effectively (“room for more funding”) and our ranking of charities’ funding gaps. More
  • Reasoning behind how we have ranked charities’ funding gaps. More
  • Details about each of our new top charities, including an overview of what we know about their work and our understanding of their funding needs. More
  • Details about each of the top charities we are continuing to recommend, including an overview of their work, major changes over the past year, and our understanding of their funding needs. More
  • A brief overview of each of our standout charities. More
  • The process we followed that led to these recommendations. More
  • An update on giving to support GiveWell’s operations versus giving to our top charities. More
Major changes in the last 12 months

Major changes to our recommended charities list and review process over the past year include:

  • Overall, we believe our top charities are able to absorb more funding than they could in previous years. This is a result both of recent additions to the top charities list with large funding gaps (particularly Malaria Consortium) as well as expansion by top charities that have been on the list for a longer time (particularly Deworm the World and AMF).

    We expect overall “room for more funding” to continue to expand as we gain more confidence in recently-added top charities and continue to add new top charities, particularly through GiveWell Incubation Grants, our program to grow the pipeline of potential future top charities and improve our understanding of our current top charities.

  • We added two new programs to our list of top charities: vitamin A supplementation (VAS) and seasonal migration subsidies. We have not previously recommended charities that work on these programs.

    We had considered VAS a priority program for a number of years but had not found an organization that was able to answer our key questions. While we have some remaining questions, we can now make a strong case for supporting HKI’s work on VAS.

    We initially supported No Lean Season through GiveWell’s Incubation Grants program. No Lean Season is the first organization we have added to our top charity list through our Incubation Grants program.

  • Last year, the charities we recommended on the margin were estimated to be about three times as cost-effective as unconditional cash transfers, the program implemented by top charity GiveDirectly. This year, we believe that the charities we are recommending on the margin are about six times as cost-effective as cash transfers. For the most part, this change was due to (a) a series of small adjustments to our cost-effectiveness model and (b) changes in which individuals contribute to the model and the values entered into the model by these and other contributors.

    We now feel fairly confident that there will be large amounts of room for more funding in this range. As more time has passed without identifying opportunities that are considerably more cost-effective than this, we have become more pessimistic about finding such opportunities. Our current best guess is that, if they exist, they will be in the area of policy advocacy in developing countries, on issues like lead regulation and tobacco taxation. We intend to do further research in those areas.

  • We made a significant change to our cost-effectiveness analysis to more formally incorporate adjustments for the way in which our top charities’ funding affects funding from other sources by (a) attracting more resources to the programs they work on (e.g., governments contributing staff time to support implementation of the programs) or (b) displacing resources that would have otherwise supported the programs. We will be writing more about this in a future post.

  • We continued to analyze the complex evidence base for deworming (treating intestinal parasites), the program implemented by four out of our nine top charities.

    At the end of 2016, David Roodman, a Senior Advisor to GiveWell, conducted a detailed review of the core evidence underlying our deworming recommendation (blog posts here and here).

    This year, we saw new follow-up results on the main study that leads us to recommend deworming, which continued to show similar long-term impacts of deworming on adult earnings as were estimated previously.

    Further investigation and updates based on new data led us to believe that two deworming studies (Croke 2014 and Bleakley 2007) no longer provide substantial support for the theory that deworming has long-term impacts. We plan to write more about this in the future. All together, this work led us to the same conclusion about deworming: that it is a reasonable bet to take based on its strong cost-effectiveness (which incorporates our uncertainty about the impact).

Room for more funding analysis

Types of funding gaps

In the last two years, we used a framework of “capacity funding” and “execution levels” to compare funding gaps (unfilled funding needs) across charities. This framework was intended to capture whether funding would enable a charity to expand or grow in important ways and how likely it was, in our estimation, that each top charity would be constrained by funding in the next year.

We developed this approach in response to a situation where we expected to direct more funding to several of our top charities than they would be able to use (commit or spend) in that year. We used capacity funding to describe opportunities to increase the amount of funding a charity might be able to absorb in the future (by, say, investing in expanding to a new location) and execution levels to describe the likelihood, down to the 5 percent level, that a charity would be able to make use of additional funding before encountering non-funding bottlenecks to their work.

This year, because we have added new top charities and most of our other top charities have more room for more funding than in previous years, we expect that the funding we will direct to each organization will not reach the level where they will encounter significant non-funding bottlenecks. As a result, we have moved away from describing capacity funding and execution levels.

Ranking funding gaps

The first million dollars to a charity can have a very different impact from the 20th million dollars. Accordingly, we have created a ranking of individual funding gaps that accounts for our best guess of the impact of additional funds at each level.

The below table lays out our ranking of funding gaps, up to $75.7 million in total funding. We expect Good Ventures to give $75 million to GiveWell’s top charities this year, so this table is our recommendation to Good Ventures, plus the allocation of funding that GiveWell holds to allocate at its discretion (currently $0.7 million). We then discuss our recommendation for all other donors.

The Open Philanthropy Project, which was incubated at GiveWell but is now a separate organization, plans to write more soon about the reasons for Good Ventures increasing its support of GiveWell top charities from $50 million last year to $75 million this year. In short, the amount was based on discussions about how to allocate funding across time and across cause areas. It was not set based on the total size of top charities’ funding gaps or the projection of what others would give.

Charity Description Amount (millions) All top charities Incentive grants: $2.5 million per charity 22.5 All standout charities Standout grants: $100,000 per charity 0.7 Deworm the World Funding gaps in India and Kenya over the next three years (including central costs) 3.0 Helen Keller International Funding gaps over three years in Burkina Faso, Mali, and Guinea—countries that have missed recent vitamin A campaigns due to lack of funding 4.7 No Lean Season Full funding gap over three years for implementing the program in Bangladesh 9.0 Deworm the World Three years of funding for a new program in Pakistan and reserves to protect against funding shortfalls in India 10.4 Malaria Consortium Part of the funding gap for SMC in Burkina Faso, Nigeria, and Chad over the next three years 25.4

In total, we are recommending that Good Ventures make the following grants:

  • Malaria Consortium’s seasonal malaria chemoprevention program: $27.9 million
  • Evidence Action’s Deworm the World Initiative: $15.2 million. We are also recommending that GiveWell’s Board of Directors grant the $0.7 million in discretionary funds that we currently hold from the third quarter (from donors who selected to give to “Grants to recommended charities at GiveWell’s discretion” on our donation form) to Deworm the World, bringing the total to $15.9 million.
  • Evidence Action’s No Lean Season program: $11.5 million
  • Helen Keller International’s vitamin A supplementation program: $7.2 million
  • Schistosomiasis Control Initiative: $2.5 million
  • Against Malaria Foundation: $2.5 million
  • Sightsavers’ deworming program: $2.5 million
  • END Fund’s deworming program: $2.5 million
  • GiveDirectly: $2.5 million

Our recommendation to donors

For donors who are interested in directing funding to whichever recommended charity or charities GiveWell believes has the most pressing funding need at the time the funds are granted, we recommend giving to “Grants to recommended charities at GiveWell’s discretion.” These grants will respond to the greatest funding need we see; they may not match the recommended allocation outlined below.

For donors (other than Good Ventures) who are interested in donating directly to our top charities, we recommend splitting your donation as follows:

  • 70 percent to the Against Malaria Foundation
  • 30 percent to the Schistosomiasis Control Initiative
Why these recommendations?

Our recommendations to donors, including Good Ventures, are based on:

  1. Overall cost-effectiveness of the charity. Our cost-effectiveness model is a key input into our decision-making process, and large differences in modeled cost-effectiveness impact our recommendations. We try not to put significant weight on relatively small differences in cost-effectiveness according to the model because many inputs are highly uncertain.

    Our model this year found relatively small differences between many top charities, with Deworm the World at ~12 times as cost-effective as cash transfers, four top charities in the ~6-10x cash transfers range, and three top charities in the ~3-5x cash transfers range. We consider differences between charities implementing the same intervention or interventions that have similar inputs and output in the model more meaningful (e.g., malaria nets and seasonal malaria chemoprevention) than differences between charities implementing quite different interventions.

    We have completed a sensitivity analysis of our cost-effectiveness analysis to get a better sense for which parameters are most sensitive. We are more hesitant to consider differences in the cost-effectiveness as meaningful when they rely on very sensitive inputs.

  2. Cost-effectiveness of particular funding opportunities. Charities’ work can vary significantly in cost-effectiveness across locations due to different costs, disease burdens, uptake in the targeted population, or probability that other funders would step in in GiveWell’s absence. While not a part of our formal cost-effectiveness model, we ran supplementary analyses of cost-effectiveness for some locations for which our top charities were seeking additional funding and considered the output as part of our prioritization of funding gaps.
  3. Qualitative factors not captured in our cost-effectiveness model. The main factors we focused on were:
    • Proportion of the global funding need for the program that is filled. We expect that funders will generally (but imperfectly) select the areas where cost-effectiveness is higher first, leaving the areas with higher costs, lower disease burden, lower cultural acceptance of the program, etc. for last. We believe we have captured some of the consequences of this in our cost-effectiveness analysis. For example, we use national level disease burden estimates for the countries in which each charity has worked and/or plans to work; charities working in higher burden countries are therefore modelled as more cost-effective. But we do not use sub-national estimates to distinguish the highest priority regions within a country; if charities are filling the lowest priority funding gaps within a county, they will likely be less cost-effective than our model suggests. This was an important consideration in comparing AMF and Malaria Consortium. We estimate that ~80 percent of the global funding need for nets (the program AMF implements) has been filled, and ~35 percent of the global funding need for seasonal malaria chemoprevention (the program Malaria Consortium implements).
    • Our level of knowledge about the organization. We have recommended AMF, Deworm the World, SCI, and GiveDirectly for many years. We know less about Malaria Consortium and No Lean Season and the least about HKI. We seek to be somewhat conservative about recommending large amounts of funding to organizations where there is a relatively high chance that additional research could lead us to believe the program was less cost-effective than we previously thought.
    • Ease of communication with the organization. It is important to us that we are able to learn over time about the charities we recommend, to enable us to improve our decisions. The ability to communicate effectively with an organization is a key factor in our ability to learn from the organization’s experiences.
    • Ongoing monitoring and likelihood of detecting future problems. Evaluating an organization’s monitoring processes and results is an important part of our charity reviews and for the most part is not captured in our cost-effectiveness analysis. As with ease of communication, we have more confidence in recommending funds to an organization if we believe that we will learn about how successful its work has been.

Summary of key considerations for top charities

The table below summarizes the key considerations for our nine top charities. More detail is provided below, as well as in the charity reviews.

Estimated cost-effectiveness (relative to cash transfers) Our level of knowledge about the organization Primary benefits of the intervention Ease of communication Ongoing monitoring and likelihood of detecting future problems Room for more funding, after expected funding from Good Ventures and donors who give independently of our recommendation Other major considerations AMF ~6x High Deaths averted and possible increased income in adulthood Strong Strong High: could absorb tens of millions of dollars High proportion (~80%) of global gap for program is filled Malaria Consortium (SMC program) ~7x Moderate Under-5 deaths averted and possible increased income in adulthood Strong Strong High: could absorb tens of millions of dollars Relatively low proportion (~35%) of global gap for program is filled Helen Keller International (VAS program) ~9x Moderate Under-5 deaths averted Strong Moderate High: could absorb tens of millions of dollars Learning benefits Deworm the World ~12x High Possible increased income in adulthood Strong Strong Moderate: could absorb millions of dollars END Fund (deworming program) ~4x Moderate Possible increased income in adulthood Moderate Moderate Moderate: could absorb millions of dollars SCI ~10x High Possible increased income in adulthood Moderate Moderate High: could absorb tens of millions of dollars Sightsavers (deworming program) ~5x Moderate Possible increased income in adulthood Moderate Moderate Moderate: could absorb millions of dollars No Lean Season ~5x Moderate Immediate increase in consumption Strong Moderate Low: further funding would be used for different types of activities Potential upside GiveDirectly Baseline High Immediate increase in consumption and assets Strong Strong Very high: could absorb over 100 million dollars

Reasons for this funding gap ranking

Prioritization of funding that we have recommended to Good Ventures (we recommend Good Ventures fill the highest-priority funding needs first, to ensure these are funded):

  1. We start by recommending that each top charity receive $2.5 million as an “incentive grant.” These grants are intended to be a major contribution to the charity’s work in recognition of the fact that they have met GiveWell’s criteria and have dedicated significant time to working with us to help us follow their progress and plans each year. We don’t want our top charity funding process to be winner-takes-all because we believe that charities would be less likely to want to participate in that case.

  2. After incentive grants, we believe the next most valuable funding to provide is for Deworm the World’s work in Kenya and India over the next three years. Deworm the World’s work in Kenya and India is the most cost-effective opportunity we have found. We estimate that its work in Kenya is ~20x as cost-effective as cash transfers and in India is ~30x+ as cost-effective as cash transfers.
  3. We rank providing funding to our two new top charities, Helen Keller International (HKI)’s VAS program and No Lean Season, next.

    We estimate that HKI could use $7.2 million over three years to support VAS campaigns in countries with high child mortality rates that have recently missed campaigns due to lack of funds. HKI’s cost-effectiveness is at the high end of the range for top charities (~9x cash transfers). We believe HKI could absorb more than $7.2 million in additional funding for VAS effectively but that this $7.2 million gap is likely more cost-effective than HKI’s average cost-effectiveness. Also, because HKI is a new top charity of ours, we expect this first part of its gap to have significant learning benefits for us: by giving this money, we’ll be better positioned to follow HKI’s work and review its monitoring, which we believe will make it more likely that we have a more accurate estimate of its impact in future years.

    We decided to recommend funding all of No Lean Season’s funding gap in Bangladesh for the next three years. While No Lean Season’s cost-effectiveness is at the lower end of our top charities (~5x cash transfers), we see additional reasons to prioritize this gap. We believe No Lean Season is the top charity where there is the strongest case to be made for “upside”; our cost-effectiveness analysis may not capture the potential impact of scaling a new program that could lead to greater visibility and funding for a novel type of program.

  4. We think the next highest priority funding to provide is $10.4 million to Deworm the World. This funding would support a new program in Pakistan and provide reserve funding for programs supported with restricted funds. We estimate that the program in Pakistan will be roughly ~7x as cost-effective as cash transfers, though this estimate is very sensitive to estimates of worm burdens in the locations where Deworm the World plans to work.

    The reserve funding is intended to make it unlikely that the India program, which we believe is very highly cost-effective, will be interrupted—Deworm the World relies on restricted funding for this program and there is some chance that this funding will not be available in the future. It may use this GiveWell-directed funding for other opportunities if it is not needed to backstop restricted funding in India; we expect that it will have unfunded opportunities remaining in the next few years, particularly in Nigeria.

  5. The last funding gap on our list of recommendations for Good Ventures is $23.6 million to Malaria Consortium for its work on SMC. When choosing which gap to recommend for the remainder of Good Ventures’ $75 million, we focused on the remaining funding needs for Malaria Consortium’s SMC program, AMF, and SCI, which we believe to have the next highest-value gaps. Our cost-effectiveness model indicates that SCI is the most cost-effective of these three organizations (~10x cash transfers, compared with ~6-7x cash transfers for AMF and Malaria Consortium), but when the difference in modelled cost-effectiveness between two charities is relatively small, we also put significant weight on qualitative factors. We believe that AMF and Malaria Consortium are stronger on some qualitative factors, particularly the likelihood that we will be able to learn about the programs’ performance through the monitoring they conduct. Between AMF and Malaria Consortium, we have prioritized Malaria Consortium’s funding gap primarily due to the qualitative considerations discussed above around the proportion of the global funding need that is filled. After following Malaria Consortium for a second year, we believe that Malaria Consortium and AMF are comparable on other major qualitative factors, such as quality of ongoing monitoring and likelihood of detecting future problems.

    The total amount we are recommending for Malaria Consortium’s SMC program represents a rough compromise between providing a high level of funding to a program that we prefer to the next funding gap on the list and not wanting to make too large of a bet on an organization that we have less experience with than some other top charities.

Prioritization for non-Good Ventures donors:

  1. Our current recommendation for donors is to give to GiveWell for making grants to top charities at our discretion. Our goal is for SCI to receive $9 million, in addition to the $2.5 million incentive grant that we are recommending to Good Ventures, and AMF to receive the remainder of expected GiveWell-directed funding because AMF and SCI represent the next highest-value funding opportunities we see. Giving us funding to grant at our discretion allows GiveWell to better target this allocation, and to adapt if we learn new information about pressing, high-value funding needs at our top charities.
  2. For donors who prefer to give directly to charities, we recommend giving 70 percent to AMF and 30 percent to SCI. These percentages are our best guess of what will achieve our target allocation given our projections of total donations driven by our recommendations.

    This allocation comes from a belief that, at these margins, it is difficult to distinguish between the quality of AMF and SCI’s funding gaps. SCI has better modeled cost-effectiveness, while AMF appears to be better on several qualitative factors, including monitoring of program performance. We have roughly targeted a two-to-one ratio between the two.

Details on new top charities

Helen Keller International (HKI) for work on vitamin A supplementation

Our full review of HKI’s work on vitamin A supplementation is here.

Overview

HKI (http://www.hki.org/) is a large organization with multiple programs focused on reducing malnutrition and averting blindness and poor vision. Our review focuses on HKI’s work on vitamin A supplementation (VAS) and our recommendation is specific to its VAS program. HKI provides technical assistance, engages in advocacy, and contributes funding to government-run VAS programs.

There is strong evidence from many randomized controlled trials (RCTs) conducted in the 1980s and 1990s that VAS can substantially reduce child mortality, but weaker evidence on how effective VAS is in the places HKI would work with additional funding in the next few years. In particular, there is little available information on current rates of vitamin A deficiency in areas where HKI works. We have adjusted our cost-effectiveness analysis for our best guess of how much less effective VAS is today (~25 percent as effective as in the trials in the 1980s and 1990s); the intervention remains cost-effective with that adjustment.

We feel that the monitoring data that we have seen from HKI’s programs gives us limited information on HKI’s past performance, but demonstrates the types of data HKI is able to collect on program performance. We have requested that HKI collect this monitoring data of all programs funded with GiveWell-directed funds.

Overall, we have not yet investigated HKI at the same level of depth as some of our other top charities, which we have recommended for several years. We have reviewed documents from HKI, had a number of conversations with their staff, and spent three days meeting with HKI and observing a VAS campaign in Guinea. We have remaining questions about HKI’s work that we will seek more information on in the future, but overall we believe this program is, like our other top charities, an excellent giving opportunity.

Funding gap

We believe that HKI’s VAS work is highly likely to be constrained by funding next year. HKI has provided details of VAS programs that it could support with additional funding of up to about $41.4 million in 2018-2020. HKI appears to have limited prospects for funding these programs from other sources.

Our understanding is that with additional funds, HKI would cause additional rounds of VAS to occur in some countries, while in other countries, HKI primarily aims to increase coverage rates in rounds of VAS that would take place regardless of its involvement. We have asked HKI to prioritize use of GiveWell-directed funding in countries where it expects to cause additional rounds of VAS to occur. HKI’s funding gap for countries that have recently missed VAS campaigns due to lack of funds is $7.2 million.

HKI’s VAS work was supported by the Canadian government in the past. That funding ended in 2016 and has not been renewed. Over the past year, several VAS campaigns have been skipped in countries HKI previously supported.

Evidence Action’s No Lean Season program

Our full review of No Lean Season is here.

Overview

No Lean Season (https://www.evidenceaction.org/beta-no-lean-season/) provides no-interest loans to poor rural households during the season of income and food insecurity (‘lean season’) between planting and the major rice harvest in rural northern Bangladesh. Loans are conditional on a household member stating their intention to migrate to urban or other rural locations to seek short-term employment.

Several randomized controlled trials (RCTs) of subsidies to increase migration provide moderately strong evidence that such an intervention increases household income and consumption during the lean season. An additional RCT is ongoing. We estimate that No Lean Season is roughly five times as cost-effective as cash transfers (see our cost-effectiveness analysis).

Evidence Action has shared some details of its plans for monitoring No Lean Season in the future, but, as many of these plans have not been fully implemented, we have seen limited results. Therefore, there is some uncertainty as to whether No Lean Season will produce the data required to give us confidence that loans are appropriately targeted and reach their intended recipients in full; that recipients are not pressured into accepting loans; and that participants successfully migrate, find work, and are not exposed to major physical and other risks while migrating.

Funding gap

We expect No Lean Season to have opportunities to spend $11.5 million more than we expect it to receive over the next three years to implement and monitor the program in Bangladesh. We expect it to have a further $3.9 million in opportunities to expand to other countries and do further research, in Bangladesh and other locations. Evidence Action is seeking funding beyond this level to allow it to build reserves for No Lean Season.

Details on top charities we are continuing to recommend

Against Malaria Foundation (AMF)

Our full review of AMF is here.

Background

AMF (againstmalaria.com) provides funding for long-lasting insecticide-treated net (LLIN) distributions for protection against malaria in developing countries. AMF has conducted post-distribution surveys of all completed distributions to determine whether LLINs have reached their intended destinations and how long they remain in good condition. AMF’s post-distribution surveys have generally found positive results (with some exceptions); we believe they have some methodological limitations.

We estimate that AMF’s program is roughly six times as cost-effective as cash transfers (see our cost-effectiveness analysis). This estimate seeks to incorporate many highly uncertain inputs, such as the effect of mosquito resistance to the insecticides used in nets on how effective they are at protecting against malaria, how differences in malaria burden affect the impact of nets, and how to discount for displacing funding from other funders, among many others.

Important changes in the last 12 months

Prior to this year, we had seen results from AMF’s “post-distribution check ups” (PDCUs) from two countries, Malawi and the Democratic Republic of the Congo, and had significant uncertainties about the methodology used in each location. We have now also seen results from Ghana. We have more confidence in our understanding of AMF’s PDCUs than we did previously, though this work is ongoing. In particular, we commissioned IDinsight, an organization with which we are partnering as part of our Incubation Grants program, to observe post-distribution surveys in Malawi and Ghana and report their findings (see links). Further discussion of the strengths and weaknesses of PDCUs here.

In 2017, AMF signed relatively few new agreements to fund LLIN distributions and, as a result, has a balance of $58 million in uncommitted funds, or $35 million if distributions where AMF believes agreements are imminent are counted as committed. Our understanding is that many of AMF’s conversations with countries could not progress until decisions were made about how much Global Fund funding each country would allocate to LLIN distributions (as opposed to other malaria control efforts). This decision-making process extended into late 2017. Global Fund funding is allocated on three-year cycles and we do not expect this to continue to be a bottleneck for AMF in 2018.

Funding gap

We believe that AMF is very likely to be constrained by lack of funding. There is high uncertainty in the maximum amount of funding that AMF could use productively, though we expect the maximum to be much greater than what AMF is likely to receive. To fund all of the distributions that it is currently in detailed discussions about, AMF would need $50 million more than we project it will receive. The total funding gap for LLINs for 2018-2020 appears to be hundreds of millions of dollars.

With additional funding, AMF’s top priorities would be to fund a portion of the next round of distributions, in 2018-2020, in each of the countries in which it has recently funded distributions.

END Fund (for work on deworming)

Our full review of the END Fund’s work on deworming is here.

Background

The END Fund (end.org) manages grants, provides technical assistance, and raises funding for controlling and eliminating neglected tropical diseases (NTDs). We have focused our review on its support for deworming.

Slightly more than half of the treatments the END Fund has supported have been deworming treatments, while the rest have been for other NTDs. The END Fund has funded SCI, Deworm the World, and Sightsavers. We see the END Fund’s value-add as a GiveWell top charity as identifying and providing assistance to programs run by organizations other than those we separately recommend, and our review of the END Fund has excluded results from charities on our top charity list.

We have seen limited monitoring results on the number of children reached in END Fund-supported programs. In 2016, the END Fund began requiring that surveys be conducted to determine whether its programs have reached a large proportion of children targeted; we have seen coverage surveys for (a non-random sample of) 35 percent of its 2016 deworming grant portfolio. These studies leave us with some remaining questions about the program’s impact.

Important changes in the last 12 months

We significantly improved our understanding of the END Fund’s cost per treatment and the baseline prevalence in areas that the END Fund works (which is used in our cost-effectiveness analysis), though we continue to have lower confidence in our estimates than we do for the deworming organizations that we have recommended for several years. We also saw some monitoring from END Fund programs; previously our recommendation of the END Fund was based on specific monitoring plans that we found credible.

Funding gap

We believe the END Fund could substantially increase its deworming grantmaking with additional funds. We roughly estimate that there is gap of $18 million between the amount of funding the END Fund will have available for grants for deworming and the amount of funding it would need to make all of the potential grants it has identified. Sources of major uncertainty in this estimate include whether the END Fund will encounter non-funding bottlenecks in some of its identified and early-stage opportunities, the amount of funding it will receive from other sources, the proportion of funding it will allocate to deworming, and costs other than grants.

Evidence Action’s Deworm the World Initiative

Our full review of Deworm the World is here.

Background

Evidence Action’s Deworm the World (evidenceaction.org/#deworm-the-world) advocates for, supports, and evaluates deworming programs. Its main countries of operation are India, Kenya, and Nigeria, and it is considering expanding to Pakistan.

Deworm the World retains or hires monitors who visit schools during and following deworming campaigns. We believe its monitoring is the strongest we have seen from any organization working on deworming. Monitors have generally found high coverage rates and good performance on other measures of quality.

As noted above, we believe that Deworm the World overall is the most cost-effective charity we have found. We estimate that it is ~12 times as cost-effective as cash transfers, but note that, due to differences in worm burdens and costs across countries, there is significant variation in cost-effectiveness across the countries in which it works. We estimate that its work to date in India has been more than 30 times as cost-effective as cash transfers, while its planned work in Nigeria is around three times as cost-effective as cash transfers (though this estimate is based on low-quality information).

Important changes in the last 12 months

We estimate that Deworm the World could absorb considerably more funding this year than we estimated last year, due to opportunities it has identified to expand its geographic reach. (More in the next section.)

The quality of the monitoring that we have seen from Deworm the World has remained high. To date, we have seen limited monitoring from Nigeria, which is a new addition to Deworm the World’s portfolio and is expected to become a major portion of its work in the future. This is of minor concern given the strong monitoring track record elsewhere and how new the program is in Nigeria.

Funding gap

We believe that Deworm the World is very likely to be constrained by funding. We expect Deworm the World to have opportunities to spend $18.9 million more than we expect it to receive over the next three years. Funding beyond this level would allow Deworm the World to build its reserves and take advantage of unanticipated opportunities.

With additional funding, Deworm the World would sustain its current work in Kenya and India, and would seek to expand its work in Nigeria and India to additional states and support the government in Pakistan to initiate a deworming program.

GiveDirectly

Our full review of GiveDirectly is here.

Background

GiveDirectly (givedirectly.org) transfers cash to households in developing countries via mobile phone-linked payment services. It targets extremely low-income households. The proportion of total expenses that GiveDirectly has delivered directly to recipients is approximately 82 percent overall. We believe that this approach faces an unusually low burden of proof, and that the available evidence supports the idea that unconditional cash transfers significantly help people.

We believe GiveDirectly to be an exceptionally strong and effective organization, even more so than our other top charities. It has invested heavily in self-evaluation from the start, scaled up quickly, and communicated with us clearly. We believe that GiveDirectly has been effective at delivering cash to low-income households. GiveDirectly has one major randomized controlled trial (RCT) of its impact and took the unusual step of making the details of this study public before data was collected. It continues to experiment heavily, with the aim of improving how its own cash transfer programs are run as well as those of governments. It has recently started work on a universal basic income trial and has started partnering with major funders on evaluations of cash transfers in new geographies with the aim of influencing the broader international aid sector to use its funding more cost-effectively.

We believe cash transfers are less cost-effective than the programs our other top charities work on, but have the most direct and robust case for impact. We use cash transfers as a “baseline” in our cost-effectiveness analyses and only recommend other programs that are robustly more cost-effective than cash.

Important changes in the last 12 months

We had previously expressed reservations about GiveDirectly’s targeting strategy: that by excluding the least poor households in each village, the program might lead to negative reactions by non-recipients, increase costs per household reached, and exclude households that were still quite poor. In 2017, GiveDirectly largely switched to a “saturation” approach of making transfers to all households in selected villages. It will continue to use a targeted approach in Rwanda, where government regulations require such an approach, but the saturation approach will be used in Kenya and Uganda.

In 2016, GiveDirectly built up its operations in Uganda and Kenya with the anticipation of revenue growth in 2017. Revenue growth has been slower than expected and GiveDirectly had to lay off some staff as a result.

GiveDirectly launched its universal basic income project this month.

In 2015, Good Ventures made a grant of $25 million to GiveDirectly on GiveWell’s recommendation. GiveDirectly’s goals for the grant were to expand its ability to raise funds from donors not influenced by GiveWell’s recommendation and to collaborate with large aid institutions or governments to address their questions about cash transfers. We expect to write more about the performance of the grant in the future, but, in short, our impression is that fundraising has progressed slower than expected and collaborative projects have progressed more quickly than expected.

Funding gap

We believe that GiveDirectly is highly likely to be constrained by funding next year. It expects to use additional funding primarily for standard cash transfers and for additional collaborative projects. For collaborative projects, GiveDirectly’s potential partners require it to contribute funding, which the partner matches (at a one-to-one ratio, minimum). These projects would largely be in countries GiveDirectly has not worked in before and many are at an early stage of discussion. We estimate that GiveDirectly could use more than $200 million in additional funding in 2018-2019.

Malaria Consortium (for work on seasonal malaria chemoprevention)

Our full review of Malaria Consortium’s seasonal malaria chemoprevention program is here.

Background

Malaria Consortium (malariaconsortium.org) works on preventing, controlling, and treating malaria and other communicable diseases in Africa and Asia. Our review has focused exclusively on its seasonal malaria chemoprevention (SMC) programs, which distribute preventive anti-malarial drugs to children 3-months to 59-months old in order to prevent illness and death from malaria.

There is strong evidence that SMC substantially reduces cases of malaria. The randomized controlled trials on SMC that we considered showed a decrease in cases of clinical malaria but were not adequately statistically powered to find an impact on mortality.

Malaria Consortium and its partners have conducted studies in all of the countries where it has worked to determine whether its programs have reached a large proportion of children targeted. These studies have generally found positive results, though past surveys have been conducted after four rounds of SMC (SMC is given in a maximum of four treatment courses at monthly intervals) and may be subject to error due to the inaccurate recall or recordkeeping. Starting in 2017, Malaria Consortium is conducting coverage surveys after each round of SMC, to reduce recall error.

Important changes in the last 12 months

We have increased our confidence in Malaria Consortium’s monitoring, though we have not yet seen all of the research that Malaria Consortium expected to share in 2017 (in particular, tracking of malaria cases and deaths over time in areas where Malaria Consortium works). Coverage survey results from 2016 were generally positive, with a couple of outliers. The change from conducting coverage surveys after four treatment cycles to conducting them after each cycle will increase our confidence in the results.

Last year, we had only a rough estimate of how much additional funding Malaria Consortium could use productively. We have significantly improved our understanding of its room for more funding this year.

Funding gap

We believe that Malaria Consortium could productively use more funding than it expects to receive to scale up its SMC activities. It appears that there is a large remaining global need for additional funding for SMC programs and that Malaria Consortium is well-positioned to fill these gaps, if it has sufficient funding to do so.

Malaria Consortium estimates that it could spend $28-30 million per year on SMC in each of the next three years and that this level of funding would largely fill the global funding gap for SMC, with the exception of Nigeria, where the scale of the gap would be beyond Malaria Consortium’s operational capacity in the short term.

It appears to have limited prospects for major funding from other sources. The major grant for Malaria Consortium’s work on SMC previously, from Unitaid, is ending and Malaria Consortium told us that it will not be renewed.

Schistosomiasis Control Initiative (SCI)

Our full review of SCI is here.

Background

SCI (imperial.ac.uk/schisto) works with governments in sub-Saharan Africa to create or scale up deworming programs. SCI’s role has primarily been to identify partner countries, provide funding to governments for government-implemented programs, provide advisory support, and conduct research on the process and outcomes of the programs.

SCI has conducted studies to determine whether its programs have reached a large proportion of children targeted. These studies cover (a non-random sample of) about 40 percent of treatments SCI reports having delivered over the past few years. The studies have generally found moderately positive results, but leave us with some remaining questions about the program’s impact.

As noted above, we believe that SCI is less cost-effective than Deworm the World and more cost-effective than Sightsavers and the END Fund. Given the uncertainty in our cost-effectiveness model, we are hesitant to say that SCI is more cost-effective than AMF and Malaria Consortium, though taken literally, SCI is 1.5 times as cost-effective as AMF and Malaria Consortium (~10x cash transfers vs. ~6-7x cash transfers).

Important changes in the last 12 months

We continued to follow SCI’s progress in 2017 and there have not been many major changes to its work. As in the past, SCI shared monitoring of deworming coverage levels for a portion of its programs with us; there continue to be several SCI-supported countries for which we have not seen monitoring results. In the past, we have noted that we had low confidence in the accuracy of the financial information that SCI provided and that SCI made significant improvements to its financial systems in 2016; our remaining concerns about SCI’s financial management and reporting are fairly minor.

In 2017, SCI allocated nearly all available funding to programs in its 2017-2018 budget year. This was a large increase in spending over the previous budget year ($9.6 million in 2016-2017 compared with $22.5 million in 2017-2018), driven in large part by a large increase in GiveWell-directed funding ($3.7 million in 2015 compared with $16.6 million in 2016). We believe this decision was due in part to a miscommunication with GiveWell—in a conversation with SCI in early 2017, we recommended that they treat the funds like a multi-year grant because of the risk of large fluctuations in GiveWell-directed funding, but we did not emphasize this point. SCI told us that it plans to allocate future funding over multiple years, noting that its funding allocation decisions in 2016-2017 were due to the desire to avoid allowing drugs to expire as well as a misunderstanding with GiveWell about how the funding was intended to be used.

Funding gap

We estimate that SCI could productively use about $30 million more than it expects to receive to deliver treatments to school-aged children over the next three years. It could use almost three times this amount if it were to follow World Health Organization guidelines, which include treating many adults; we are not recommending funding to treat adults because we haven’t seen sufficient evidence on the impact of treating adults.

The primary use of this funding, and SCI’s top priority, would be to sustain and expand work in current countries of operation. A smaller portion would be used to expand to up to four additional countries.

Sightsavers (for work on deworming)

Our full review of Sightsavers is here.

Background

Sightsavers (sightsavers.org) is a large organization with multiple program areas that focuses on preventing avoidable blindness and supporting people with impaired vision. Our review focuses on Sightsavers’ work to prevent and treat neglected tropical diseases (NTDs) and – more specifically – advocating for, funding, and monitoring deworming programs. Deworming is a fairly new addition to Sightsavers’ portfolio; in 2011, it began delivering some deworming treatments through NTD programs that had been originally set up to treat other infections.

Sightsavers has shared surveys for some of its past NTD programs that measure whether these programs have reached a large proportion of children targeted. These studies have generally found moderately positive results, but leave us with some remaining questions about the program’s impact. We have seen very limited results from Sightsavers’ deworming programs specifically. For GiveWell-supported programs, Sightsavers has told us it will conduct coverage surveys for each round of deworming; we have reviewed one of those surveys to date.

Important changes in the last 12 months

In 2017, as expected, we learned relatively little about the performance of Sightsavers’ deworming programs, because programs funded with GiveWell-directed funds were at early stages. We did not expect to receive any monitoring results from programs funded with GiveWell-directed funds; however, Sightsavers shared a coverage survey from Guinea with us earlier than expected. The survey found middling coverage results.

We significantly improved our understanding of Sightsavers’ cost per treatment and the baseline prevalence in areas where Sightsavers works (which is used in our cost-effectiveness analysis), though we continue to have lower confidence in our estimates than we do for the deworming organizations that we have recommended for several years.

Funding gap

We believe that Sightsavers’ deworming work is likely to be constrained by funding next year. Sightsavers has provided details of deworming programs that it could fund with additional funding of up to about $6.4 million in 2018 and 2019. Sightsavers appears to have limited prospects for funding these programs from other sources. We believe it is likely that Sightsavers could absorb funding beyond this amount to extend programs to 2020 and/or seek out additional opportunities to fund deworming programs.

Of the $6.4 million, $2.8 million would be used to add deworming to existing NTD programs and $3.7 million would be used to fund NTD programs that would treat several NTDs in addition to schistosomiasis and STH. We will request that Sightsavers prioritize the first set of opportunities, because we believe they will likely be more cost-effective.

Standout charities

In addition to our top charities, we recognize standout charities—organizations that support programs that may be extremely cost-effective and are evidence-backed but for which we have less confidence in their impact than we do for our top charities. We have reviewed their work and feel these groups stand out from the vast majority of organizations we have considered in terms of the evidence base for the program they support, their transparency, and their potential cost-effectiveness. These organizations offer additional giving options for donors who feel highly aligned with their work.

We’ve added one organization to the list this year: Evidence Action’s Dispensers for Safe Water.

We don’t follow standout organizations as closely as we do our top charities. We generally have one or two calls per year with representatives from each group and publish notes on our conversations. We provide brief updates on these charities below.

New addition to the standout list:

  • Evidence Action’s Dispensers for Safe Water. The Dispensers for Safe Water program provides chlorine dispensers for decontamination of drinking water to prevent diarrhea and associated deaths of young children. We believe that there is strong evidence that chlorination is biochemically effective at inactivating most diarrhea-causing microorganisms, but weaker evidence on the causal relationship between water chlorination programs and reductions in under-5 diarrhea and death. Our rough cost-effectiveness analysis of Dispensers for Safe Water suggests that the program is in a similar range of cost-effectiveness as unconditional cash transfer programs. Our review of Dispensers for Safe Water is here.

Organizations that have conducted randomized controlled trials of their programs:

  • Development Media International (DMI). DMI produces radio and television programming in developing countries that encourages people to adopt improved health practices. It conducted a randomized controlled trial (RCT) of its child survival media campaign in Burkina Faso and has been highly transparent, including sharing preliminary results with us. The results of its RCT were mixed, with a household survey not finding an effect on mortality (it was powered to detect a reduction of 15 percent or more) and data from health facilities finding an increase in facility visits. (The results have not yet been published.) We believe there is a possibility that DMI’s work is highly cost-effective, but we see no solid evidence that this is the case. DMI is conducting an RCT of its family planning radio campaign in Burkina Faso and it is planning work on early child development in Burkina Faso and child survival in Mozambique. It is our understanding that DMI will be constrained by funding in the next year. Our full review of DMI is here and notes from our most recent conversation with DMI are here.
  • Living Goods. Living Goods recruits, trains, and manages a network of community health promoters who sell health and household goods door-to-door in Uganda and Kenya and provide basic health counseling. They sell products such as treatments for malaria and diarrhea, fortified foods, water filters, bednets, clean cookstoves, and solar lights. Living Goods completed a RCT of its program and measured a 27 percent reduction in child mortality. Our best guess is that Living Goods’ program is less cost-effective than our top charities, with the possible exception of GiveDirectly. It is conducting a second RCT of its program and results are expected in 2020. Living Goods recently expanded the number of family planning products it offers and is interested in expanding to a third country. Living Goods is scaling up its program and could scale up more quickly with additional funding. Our review of Living Goods is here and notes from our most recent conversation with Living Goods are here.

Organizations working on micronutrient fortification:

We believe that food fortification with certain micronutrients can be a highly effective intervention. For each of these organizations, we believe they may be making a significant difference in the reach and/or quality of micronutrient fortification programs but we have not yet been able to establish clear evidence of their impact. The limited analysis we have done suggests that these programs are likely not significantly more cost-effective than our top charities—if they were, we might put more time into this research or recommend a charity based on less evidence.

  • Food Fortification Initiative (FFI). FFI works to reduce micronutrient deficiencies (especially folic acid and iron deficiencies) by doing advocacy and providing assistance to countries as they design and implement flour and rice fortification programs. We have not yet completed a full evidence review of iron and folic acid fortification, but our initial research suggests it may be competitively cost-effective with our other priority programs. Because FFI typically provides support alongside a number of other actors and its activities vary widely among countries, it is difficult to assess the impact of its work. FFI’s recent work includes advocating for legislation to mandate that rice imported to West Africa is fortified with vitamins and minerals. Our full review is here and notes from our most recent conversation are here.
  • Global Alliance for Improved Nutrition (GAIN) – Universal Salt Iodization (USI) program. GAIN’s USI program supports national salt iodization programs. We have spent the most time attempting to understand GAIN’s impact in Ethiopia. Overall, we would guess that GAIN’s activities played a role in the increase in access to iodized salt in Ethiopia, but we do not yet have confidence about the extent of GAIN’s impact. GAIN has focused its recent USI work on Tanzania, Mozambique, Ethiopia, and Kenya, which it targeted based on relatively low levels of coverage of iodized salt and strong relationships with stakeholders. It is our understanding that GAIN’s USI work will be constrained by funding in the next year. Our review of GAIN is here and notes from our most recent conversation are here.
  • Iodine Global Network (IGN). Like GAIN-USI, IGN supports (via advocacy and technical assistance rather than implementation) salt iodization. IGN is small, and GiveWell-directed funding has made up a large part of its funding in recent years. It expects to have data from before and after its recent work in Madagascar, Lebanon, and possibly Israel by the end of 2018; this data may provide additional evidence of IGN’s impact. It is our understanding that IGN will be constrained by funding in the next year. Our review of IGN is here and notes from our most recent conversation here.
  • Project Healthy Children (PHC)/Sanku. PHC/Sanku aims to reduce micronutrient deficiencies by providing assistance to small countries as they design and implement food fortification programs and by enabling fortification among small-scale millers. PHC is scaling up its Sanku project, which equips small millers with a machine that enables them to fortify their flour with micronutrients; we have not done as much formal analysis of Sanku as of PHC’s core work on advocacy and technical assistance to countries to implement fortification. PHC/Sanku expects to be constrained by funding in the future. Our review of PHC/Sanku is here and notes from our more recent conversation are here.
Our research process in 2017

We plan to detail the work we completed this year in a future post as part of our annual review process. A major focus of 2017 was improving our recommendations in future years, in particular through our work on GiveWell Incubation Grants and prioritizing promising programs for further investigation.

Below, we highlight the key research that led to our current charity recommendations. This page describes our overall process.

  • Following existing top charities. We followed the progress and plans of each of our 2016 top charities. We had several conversations by phone with each organization, met in person at least once with each top charity (including a three-day visit to Rwanda and the Democratic Republic of the Congo with the END Fund), and reviewed documents they shared with us.
  • Identifying new top charities.
    • No Lean Season. We had recommended a series of Incubation Grants to No Lean Season beginning in 2014 and have followed its progress since then. This year, due to the scale at which No Lean Season was operating and the track record it had established, we decided that the No Lean Season program was at a stage of development where we could evaluate it as a potential top charity. In addition to extensive communications with No Lean Season staff over the phone and reviewing documents they shared with us, GiveWell staff spent five days visiting the program in Bangladesh.
    • Helen Keller International’s vitamin A supplementation program. Earlier this year, Research Analyst Chelsea Tabart began reaching out to organizations that might be a fit for our criteria, but with which we had limited or no previous contact with. As a result of that process, we reconnected with Helen Keller International (which we first considered as a potential top charity in 2007) and began to consider its vitamin A supplementation program as a potential top charity. In addition to extensive communications with HKI staff over the phone and reviewing documents they shared with us, GiveWell staff spent three days meeting with HKI staff in Guinea and observing a vitamin A supplementation program.
  • Completing intervention reports on obstetric fistula surgery and measles vaccination campaigns; completing interim intervention reports on SMS reminders for vaccination, Sayana® Press (an injectable contraceptive), oral rehydration solution, and antiretroviral therapy for HIV/AIDS; and expanding our interim intervention report on seasonal malaria chemoprevention to a full intervention report.
  • Staying up to date on the research for malaria nets, cash transfers, and deworming. We did not find major new research on cash transfers, nets, or deworming that affected our recommendation of GiveDirectly, AMF, or the organizations we recommend for their work on deworming. David Roodman published an in-depth review (parts 1 and 2) of the deworming studies that form the primary basis of our views on the impact of deworming (though much of this work was completed in 2016 and informed our top charity recommendations last year).
  • Making extensive updates to our cost-effectiveness model and publishing several updates to the model over the course of the year. We instituted a process to track and report publicly on updates to the model to reduce the possibility of errors and make our process more transparent. This year, staff members have also provided substantially more detail in our cost-effectiveness file about why they have chosen particular inputs.
Giving to GiveWell vs. top charities

GiveWell is currently in a stable financial position. We project that our revenue and our expenses will be approximately equal in the future. However, this projection forecasts some growth in the level of operating support we receive.

In the long term, we seek to have a model where donors who find our research useful contribute to the costs of creating it, while holding us accountable to providing high-quality, easy-to-use recommendations. We retain our “excess assets policy” to ensure that if we fundraise for our own operations beyond a certain level, we will grant the excess to our recommended charities.

We cap the amount of operating support we ask Good Ventures to provide to GiveWell at 20 percent, for reasons described here. We thus ask that donors who use GiveWell’s research consider the following:

  • If you have supported GiveWell’s operations in the past, we ask that you maintain your support. Having a strong base of consistent support allows us to make valuable hires when opportunities arise and to minimize staff time spent on fundraising for our operating expenses.
  • If you have not supported GiveWell’s operations in the past, we ask that you designate 10 percent of your donation to help fund GiveWell’s operations. This can be done by selecting the option to “Add 10% to help fund GiveWell’s operations” on our credit card donation form or letting us know how you would like to designate your funding when giving another way.

We’re happy to answer questions in the comments below. Please also feel free to reach out directly with any questions.

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How GiveWell and mainstream policymakers compare the “good” achieved by different programs

Tue, 11/07/2017 - 12:44

In a previous blog post, we described how we use cost-effectiveness analyses when deciding which charities to recommend to donors.

Today, we published a report that discusses how GiveWell and other actors, such as governments and global health organizations, approach one of the most subjective and uncertain inputs into cost-effectiveness analyses: how to morally value different good outcomes.

For example, GiveDirectly, one of GiveWell’s seven top charities, increases recipients’ consumption, while the primary benefit we see from our top charity the Against Malaria Foundation is that it averts the deaths of young children. How can one make a direct comparison between the amount of “good” achieved by each of these charities?

GiveWell does this by assigning quantitative “moral weights” to different outcomes in our cost-effectiveness analyses. As a check on how sensitive our recommendations are to our moral assumptions, we investigated how others typically answer these questions in their cost-effectiveness analyses.

For a full discussion of the findings from our investigation, see our detailed report.

The summary of the report is:

We focus on the following questions:

  • Why does GiveWell explicitly include moral weights in our cost-effectiveness analyses, and how do we decide on moral weights?
  • Is there a “standard” approach to moral weights in cost-effectiveness analyses? How do other actors, such as governments and the World Health Organization, make these judgments?
  • How much would GiveWell’s cost-effectiveness analyses change if we took a “standard” approach to moral weights?

In brief:

  • We include moral weights in our cost-effectiveness analyses because they are an important part of any giving decision and we think it is valuable to be transparent about them. The moral weights that drive our cost-effectiveness estimates are based on our staff’s personal values.
  • Governments and other prominent actors often use “value of a statistical life” estimates to compare the value of improving health relative to raising incomes. These estimates often imply that a year of healthy life is roughly 2-3x as valuable as a year of doubling someone’s income. However, there is little relevant research to inform such estimates in low- and middle-income country (LMIC) contexts; we understand that how income is valued relative to health may shift when a population is much poorer.
  • There does not seem to be a standard approach for comparing the value of life at different ages; the most commonly used framework that we have seen (the disability-adjusted life year framework) explicitly does not provide judgments on this topic. Nevertheless, most other analyses that we have seen assume that averting death during childhood is about 1-2x more valuable than averting death during adulthood.
  • Our initial analysis suggests that using relatively “standard” moral weight assumptions (i.e., the assumptions in the previous two bullet points) instead of our staff’s moral weights would not change our overall view of the relative cost-effectiveness of our current top charities. It may affect how we view some interventions in the future, particularly those that disproportionately focus on averting deaths for young children or adults. We plan to include explicit comparisons between staff moral weights and relatively “standard” moral weights in our analyses going forward.

For more detail, see the full report here.

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