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Published: December 2014

Summary

What do they do? GiveDirectly (www.givedirectly.org) transfers cash to households in developing countries via mobile phone-linked payment services. It targets extremely low-income households (more).

Does it work? 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. It appears that GiveDirectly has been effective at delivering cash to low-income households. GiveDirectly has one major randomized controlled trial of its impact, and took the unusual step of making the details of this study public before data was collected (more).

What do you get for your dollar? The proportion of total expenses that GiveDirectly delivers directly to recipients is approximately 87% (more).

Is there room for more funding? We believe that GiveDirectly has significant room for more funding and could effectively absorb up to an additional $25-30 million (beyond what it already expects to receive) in the next year (more).

GiveDirectly is recommended because of its:

  • Focus on a program with a low burden of proof and a strong track record (more).
  • Strong (and evolving) process for ensuring that cash is well-targeted and consistently reaches its intended targets (more).
  • Documented success in transferring a high portion of funds raised directly to recipients (more).
  • Standout transparency and commitment to self-evaluation (more).
  • Room for more funding - we believe that GiveDirectly can use substantial additional funding productively (more).

Major unresolved issues include:

  • While GiveDirectly has one major RCT of its activities in Kenya, there is still limited evidence on the humanitarian impact of the type of transfers (large, one-time transfers) that GiveDirectly provides, particularly the long-term impact of such transfers. GiveDirectly has one ongoing RCT that includes a long-term follow up component and will hopefully shed light on the question of humanitarian impacts.
  • GiveDirectly has been rolling out a new technology platform for its cash transfer campaigns. GiveDirectly expects the technology platform will improve efficiency and save staff time. At this point, it is too early for us to tell whether efficiency gains will be realized and what issues may arise.
  • In 2014, GiveDirectly spent time networking with potential government and NGO partners. This time involved taking meetings and providing advice that was closer to advocacy work than the implementation work that GiveDirectly has been focused on to date. While these potential partnerships are at an early stage, they could develop into projects that take a significant amount of GiveDirectly's executive-level staff time and/or partially determine GiveDirectly's implementation agenda. We have yet to see how this may change GiveDirectly's model or impact.

Our full review, below, discusses our full assessment of GiveDirectly, including what we see as its strengths and weaknesses as well as issues we have yet to resolve. This review was initially written in 2012 and has since been updated. All content on GiveDirectly is available here.

Table of Contents

Our review process

To date, our review process has consisted of

  • Conversations with GiveDirectly staff: Paul Niehaus (Director and President), Piali Mukhopadhyay (COO, International), Joy Sun (COO, Domestic), Carolina Toth (Manager, People & Partnerships), and Stuart Skeates (Uganda Field Director).
  • Conversations with GiveDirectly board members: Rohit Wanchoo (Director), Michael Faye (Director), and Jeremy Shapiro (former Director).
  • Reviewing documents GiveDirectly sent in response to our queries.
  • In November 2012, we visited GiveDirectly's operations in Kenya, where we met with beneficiaries of its work and spoke with its local field staff.
  • In October 2014, we visited GiveDirectly's operations in Uganda, where we met with beneficiaries of its work, spoke with local field staff, and observed a cash out day.

All content on GiveDirectly, including updates, blog posts and conversation notes, is available here.

What do they do?

GiveDirectly transfers cash to poor households in developing countries via mobile phone-linked payment services.1 It is currently active in Kenya and Uganda.2

Its standard model involves grants of $1,000 (USD) per household over approximately one year,3 after which recipients become ineligible.4 GiveDirectly aims to help the poorest households, targeting those that are in "acute poverty."5 Recipient households are currently identified by (a) selecting poor villages based on poverty data, and (b) determining eligibility based on building materials of homes (more). It aims to deliver approximately 90 cents directly to recipients of every $1 in campaign expenses.6

Below, we

  • Discuss the structure of GiveDirectly's transfers
  • Report the status of GiveDirectly's transfer campaigns
  • Summarize GiveDirectly's expenses to date
  • Discuss GiveDirectly's process for identifying recipient households and delivering cash transfers
  • Describe GiveDirectly's staff structure

Grant structure

GiveDirectly's standard model involves grants of $1,000 (USD) over approximately one year,7 after which recipients become ineligible.8 This is a very different approach from the approach we've seen in government cash transfer programs. One way of putting the difference (which has been reflected in GiveDirectly's communications with us) is that government programs aim for "income transfers" (small supplements to income over many years), whereas GiveDirectly aims for "wealth transfers" (large, one-off transfers that hopefully give people more flexibility to make large purchases and investments).

Note that household size varies substantially in the data we've reviewed (from the first round of Siaya transfers): while the mean household size is ~4.7 and the median size is 4, 16% of households have 1 or 2 people, ~20% have 6 or more, and the maximum household size is 16.9 We estimate that the average family receives $288 per capita from GiveDirectly, which is 121% of baseline annual consumption per capita.10

Frequency and sizing of transfers

In Kenya, GiveDirectly's standard transfer schedule involves a small initial transfer of about $50 (USD), followed by two larger transfers of about $475 (USD). These transfers are sent over a period of approximately 8 months.11

In Uganda, GiveDirectly's transfer schedule involves 10 monthly transfers of about $100 (USD) each.12 GiveDirectly told us that the transfer schedule in Uganda was designed to be more manageable for the mobile money providers than two lump-sums, and also that it would provide more frequent opportunities to evaluate the performance of the mobile money providers.13

GiveDirectly has an ongoing study of behavioral interventions that will allow some recipients the ability to choose when they receive their transfers.

Status of transfer campaigns

As of September 2014, GiveDirectly has provided partial or full cash transfers to more than 10,000 households in western Kenya and eastern Uganda, and is continuing to transfer funds to additional households in both places.14

GiveDirectly's work to-date can be grouped into 9 campaigns:

  • Rarieda: This campaign includes cash transfers to the treatment groups of a randomized controlled trial (RCT) of the effects of unconditional cash transfers (more); once RCT data collection was complete, GiveDirectly provided "top-up" transfers to all participants who previously received less than $1,000. First transfers were sent in June 2011.
  • Siaya: This campaign is in Kenya. First transfers were sent in July 2012.
  • Nike: This campaign includes transfers to young women in Siaya district as part of a RCT funded by the Nike Foundation. First transfers were sent in September 2012.
  • Google: This campaign is in Kenya, funded by a Google Global Impact Award. First transfers were sent in January 2013.
  • Kenya 2M: This campaign is in Kenya. First transfers were sent in October 2013.
  • Uganda pilot: This is GiveDirectly's first campaign in Uganda. It was funded by the Google Global Impact Award. First transfers were sent in June 2013.
  • Kenya 1.2M: This campaign is in Kenya. First transfers were sent in January 2014.
  • Kenya rolling enrollment: This campaign is in Kenya. First transfers were sent in May 2014. Starting with this campaign, enrollment in Kenya no longer happens within discreet campaigns but on an ongoing ("rolling") basis.
  • Uganda 2M: This campaign is in Uganda. First transfers were sent in September 2014.

Details of each of these transfer campaigns is provided in this table:15

Campaign Households enrolled (#) Transfer funds sent (as a % of total committed) Status
Rarieda 538 100.0% Completed
Siaya 199 100.0% Completed
Nike 77 100.0% Completed
Google 861 98.7% Ongoing
Kenya 2M 2055 95.7% Ongoing
Uganda pilot 960 99.1% Ongoing
Kenya 1.2M 1200 56.2% Ongoing
Kenya rolling enrollment 7116 17.5% Ongoing
Uganda 2M 2000 5.7% Ongoing

Expenses to date

Based on the financial information that GiveDirectly provided, we calculate that it has spent a total of $17.3 million through the end of October 2014.16 This amount includes:

  • Campaign costs (incurred + future): Direct grants to households, plus all associated costs of sending transfers. Incurred campaign costs account for transfers already sent; future campaign costs include transfers that have been committed but not yet sent to enrolled recipients, as well as the associated costs of sending those transfers (e.g., future wages for staff).17
  • Set up costs (incurred): costs of setting up in Kenya and Uganda, and of international expansion (e.g., management, infrastructure, equipment, legal and compliance).18
  • Marketing costs (incurred): costs of GiveDirectly's outreach and fundraising work (e.g., staff time spent on fundraising, mailing materials, software tools), as well as some domestic office expenses (e.g., New York City office rent).19

Costs not included in GiveDirectly's total spending are the value of its President's time (~40 hours/week), which was unpaid before FY 2014;20 research costs of the independently-run studies of GiveDirectly's program; and the roughly $2 million that GiveDirectly has set aside as reserves to cover staff salaries in the event that GiveDirectly has a funding shortfall.21 The total spending figures also do not include set up and marketing costs from September and October 2014. This is due to a slight mismatch in the time period reported for campaign versus set up and marketing costs.

GiveDirectly has stated that marginal donations from the public are used to support transfer campaigns, while set-up and outreach costs are funded separately, by designated gifts from large donors.22

Of GiveDirectly's total incurred costs through October 2014, $6.4 million (or 80.4%) was transferred directly to recipients.23 When including projected future costs for current campaigns, the ratio of direct grants to total spending rises to 86.7%.24

GiveDirectly calculates its "efficiency ratio" by the amount transferred directly to recipients out of total campaign costs. GiveDirectly excludes set-up and marketing costs from total spending in this calculation,25 though it recently started amortizing fixed costs of campaigns across campaigns and including those within total campaign costs.26 Under this condition, GiveDirectly's efficiency ratio for incurred costs in all campaigns is 86.6%, and including future costs for ongoing campaigns the ratio rises to 89.7%.27

Below we break down GiveDirectly's total spending through October 2014.28

Cost category Incurred Future Total Cost (incurred + future) % of incurred costs % of total costs
Direct Grants To Households $6,381,367 $8,609,217 $14,990,584 80.4% 86.7%
Enrollment Costs $234,698 $45,577 $280,275 3.0% 1.6%
Transfer Costs $202,947 $271,697 $474,644 2.6% 2.7%
Follow-up Costs $45,591 $99,666 $145,257 0.6% 0.8%
Core operations $451,804 $283,560 $735,365 5.7% 4.3%
Core Operations - general $48,602 $38,282 $86,884 0.6% 0.5%
Set up $199,962 - $199,962 2.5% 1.2%
Marketing $372,016 - $372,016 4.7% 2.2%
Total $7,936,987 $9,348,000 $17,284,987 100.0% 100.0%


GiveDirectly's process

The steps of GiveDirectly's process are as follows:

  1. Selection of a country. GiveDirectly told us that it chose to work in Kenya due to the robustness of M-Pesa as a mobile banking platform and the large population of people meeting its criteria who have access to mobile technology.29 In choosing a second country in which to work, GiveDirectly said that it considered whether there was a mobile money provider accessible to the very poor, how costly it would be to operate in the country, how politically stable the country is, and how common corruption is in government affairs. The ease of moving staff between Kenya and Uganda was also a factor, as GiveDirectly's current COO (International) oversees the work in both places.30
  2. Selection of a region. GiveDirectly told us that it initially chose to work in western Kenya and eastern Uganda based on poverty statistics.31 We have reviewed the poverty data for Uganda; we have not reviewed poverty data across districts for Kenya.
  3. Selection of districts or counties. For Kenya, GiveDirectly told us that its executive staff32 uses data on poverty, population density, security, and presence of poverty-focused NGOs (with the goal of avoiding overlapping with these) to select counties;33 we have reviewed poverty data for divisions within Siaya district, but not the data used to select other counties in Kenya.34 For Uganda, GiveDirectly told us that it chose a county to target initially based on poverty statistics, logistical factors and security considerations;35 we have reviewed the poverty data for Uganda.
  4. Selection of villages. GiveDirectly states that it selects villages based on poverty level and location.36 GiveDirectly shared the full details of its village selection process for an early campaign in Kenya, including data for each village and the method for weighting the different factors used to select villages in that campaign.37 We have not reviewed recent data used to select villages in Kenya. For the pilot campaign in Uganda, GiveDirectly relied on publicly available poverty data, which we have reviewed, as well as data that it received from local officials, which we have not reviewed. GiveDirectly also sent field staff to test cell phone reception and measure proximity to market centers, and used these as inputs into its village selection (optimizing for good reception and longer distances from market centers). GiveDirectly also considered population size in the villages, so that it could enroll all eligible households in each village and not exceed the budget for this campaign, which was funded by part of the Google Global Impact Award.38 For recent campaigns in Kenya and Uganda, GiveDirectly has used various methods to estimate poverty levels through census data and the proportion of thatch-roof to iron-roof households.39 For details on how GiveDirectly has targeted villages historically, see this footnote.40
  5. Obtaining permission from local officials. Before beginning to work in a given area, GiveDirectly obtains permission from local officials. This process can involve officials from the national to the village level and generally requires a series of conversations to get all the relevant stakeholders on board.41 GiveDirectly signs written agreements with or obtains approval letters from local officials to formalize permissions.42
  6. Enrollment process.
    1. Census: GiveDirectly has field staff visit the village to create a census of all households. In conducting the census, field staff collect data about each household (e.g., GPS coordinates, roof materials, household name) and note if the household is eligible for transfers43 (the criterion for eligibility in a standard campaign is that the roof is made of thatch44). The census process was different in GiveDirectly's early campaigns.45
    2. Registration: GiveDirectly has a separate set of field staff visit households marked as eligible in the census and register them. In Kenya, registration involves giving the household member a SIM card (if they do not already have an M-PESA account), which is used to transfer funds through the M-PESA system,46 and collecting other data that can be checked against the initial data from the census.47 Recipients are given the option of purchasing a cell phone from GiveDirectly at the time of registration, the cost of which is removed from the recipient's transfer.48 In Uganda, a similar registration process exists. Additionally, GiveDirectly helps recipients in Uganda obtain national ID cards and arranges for mobile money agents to visit villages to register recipients in the mobile money system.49

      A registered household is formally enrolled only after all phases of enrollment have been completed and the household has obtained a mobile money account (if necessary).50 Registration was different in early transfer campaigns.51

    3. Back check: GiveDirectly sends a separate team of field staff to revisit every registered household and collect data about that household that can be compared to data collected during census and registration.52 GiveDirectly field staff also ask households if they were asked to pay a bribe to register.53
    4. Audits: GiveDirectly sends field staff to revisit a portion of the registered households for audits. In Kenya, the field staff who do audits are from the follow up team.54 In Uganda, the field staff who have done audits in past campaigns were from earlier enrollment teams.55 GiveDirectly determines which households to audit based on the extent of the discrepancies between data collected at different phases in enrollment.56 GiveDirectly field staff resolve discrepancies during audits to determine whether households are eligible or ineligible. Households found to be eligible through this process are then considered formally enrolled, in addition to the households considered eligible after backcheck and not selected for audit.57

      The procedure for deciding which households to audit and determining eligibility was different in prior campaigns.58

    GiveDirectly aims to enroll all eligible households. If eligible members of the household are not home during a phase of enrollment, GiveDirectly staff revisit the household several times until they can be found.59

    We have reviewed (and made public) data collected during each step of the enrollment process, with deletions to preserve anonymity.60 We have not yet reviewed enrollment data for the Kenya rolling enrollment campaign or the Uganda 2M campaign.

  7. Village meeting. A village meeting is held "to answer questions anyone may have about the program, clarify that [GiveDirectly is not] affiliated with a political party, etc."61 Village meetings were first implemented in the Google campaign.62
  8. Sending transfers to recipients. GiveDirectly sends transfers to recipients via mobile money providers. In Kenya, transfers are sent in an initial installment of approximately $50, then two larger installments of approximately $475. In Uganda, transfers are sent in ten installments of approximately $100 each.63 See above for more on grant structure.
  9. Holding "cash out" days [Uganda only]: In Uganda, the mobile money agent network is less robust, so GiveDirectly coordinates cash out days for recipients to withdraw funds after each of the ten monthly installments.64 Cash out days are overseen by the Uganda Field Director, who coordinates with mobile money agents to travel to the village and set up stations for recipients to withdraw cash. In each village, there are two recipients nominated by the community to assist the Uganda Field Director in monitoring cash out day activities. GiveDirectly's call center staff also conduct phone surveys with a randomly selected 10% of recipients in the village to ask if there are any issues at the payday. We have not reviewed the logs of these calls. GiveDirectly changed its cash out day procedure in response to a case of staff fraud in Uganda.65
  10. Conducting follow up calls. GiveDirectly field staff make multiple phone calls to recipients as transfers are being sent. There are short verification calls to confirm that the transfer was received and ask if the recipient experienced any problems.66 There are also 2 longer surveys administered after larger amounts of the transfers have been sent.67 In the longer surveys, GiveDirectly staff ask recipients a number of questions including whether they received the transfers or had any trouble withdrawing funds, how they spent the funds, and whether there were any problems in their community relating to the transfers.68

    The schedule of follow up calls has varied somewhat by campaign.69 We have reviewed and made public data from these calls for ongoing transfer campaigns in Kenya.70

    In addition to these calls, GiveDirectly maintains a phone "hotline" for recipients to call if they have any questions about the transfers or issues in obtaining funds.71 We have reviewed the records of calls made to GiveDirectly's Kenya hotline from May 2012 – September 2014.72 Recipients can also report issues to GiveDirectly field staff when they are in the village; GiveDirectly created a formal mechanism for recording these reports.73

Key differences in some past campaigns were (a) the lack of a "census" (instead, GiveDirectly asked village officials to take them to eligible households, and thus conducted two in-person checks of each house rather than three); and (b) the lack of a village meeting.

In October 2014, we spoke with GiveDirectly field staff about the challenges they face in carrying out the enrollment process.74

Partnerships

In 2014, GiveDirectly’s President and COO (International) spent time networking and developing potential partnerships with government officials and international aid agencies.75 The projects that GiveDirectly is considering partnering on involve varying degrees of responsibility for implementing cash transfers on behalf of another agency. For a full list of GiveDirectly’s potential partnership projects that we know of, see this footnote.76

One of the projects that GiveDirectly is pursuing is implementing a cash transfer program in Rwanda in partnership with the United States Agency for International Development (USAID).77 GiveDirectly has been invited to apply to implement cash transfers in Rwanda and conduct a RCT comparing the impacts of cash transfers to other types of aid in USAID's Rwanda portfolio. This application is outstanding. If approved, GiveDirectly would likely begin working in Rwanda in spring 2015 and would establish field staff there to carry out the program. Funding for this work, as well as for the research costs of the RCT, would be provided through the USAID grant, if awarded.78

We have not yet attempted to assess the value of the potential partnership projects, but can imagine cases where they might be very high leverage (e.g., enabling another organization to "benchmark" its current programming against cash) and also cases that may have limited value (e.g., implementing a program that would have been implemented effectively without GiveDirectly’s involvement). We expect partnerships to take up some higher-level staff time but not involve a significant amount of GiveDirectly’s funding over the next year.

Staff structure

GiveDirectly delivered its first cash transfers in 2011.79 Starting in January 2011 it had one full-time staff member.80 In early 2013 it hired a second full-time staff member to serve as COO (Domestic).81 GiveDirectly has since expanded its staff significantly. It's current organizational structure in East Africa includes:82

  • Chief Operating Officer (COO): Oversight and quality control of the entire operation. The COO oversees the Field Directors.
  • Field Directors (FDs): This role was created in mid-2013. FDs are in charge of overseeing field operations, as well as approving transfer schedules and rosters. FDs oversee Senior Field Officers.
  • Senior Field Officers (SFOs): This role was created in mid-2013. SFOs manage the logistics of transfer rounds and oversee Field Officers, as well as conduct high-level analysis of field operations and work on technology integration.83
  • Project Associate (PA): This role was created in 2014 and currently only exists in Kenya. The PA supervises SFOs, focusing on quality control, management and training of FOs.84
  • Field Officers (FOs): FOs implement the steps required on the ground to enroll and follow up with households. They have the most face-to-face interaction with recipients and are all hired within the country of the transfers. There is a separate group of FOs for each of the first three pre-transfer stages: census, registration, and backchecks. FOs are also hired to conduct audits and follow-up surveys with recipients post-transfers.85

Does it work?

This section discusses the following questions:

  • Generally speaking, are unconditional cash transfers a promising approach to helping people? We believe that this approach faces an unusually low burden of proof and that the available evidence is consistent with the idea that unconditional cash transfers help people.
  • Are the people meeting GiveDirectly's criteria low-income? The evidence we have suggests that they are.
  • Is GiveDirectly effectively targeting people who meet its criteria? We believe GiveDirectly's enrollment process is a relatively effective way of targeting people who meet its criteria.
  • Does GiveDirectly have an effective process for getting cash to recipients? GiveDirectly's process seems to have been relatively successful so far, with one notable exception.
  • How do recipients spend their cash, and how does this spending impact their lives? We present a variety of evidence, including findings from a randomized controlled trial of GiveDirectly's work.
  • Do the cash transfers cause problems and complications that offset their positive impact? GiveDirectly has taken some measures to address this question, and we believe that the evidence so far suggests that while the cash transfers do raise some problems, these problems are relatively minor in the scheme of things.
  • Are the size and structure of the cash transfers well-thought-through and appropriate? We find GiveDirectly's approach to be defensible, but hope to see more experimentation with different approaches in the future.

Generally speaking, are unconditional cash transfers a promising approach to helping people?

We discuss this question more extensively at our report on cash transfers. In brief:

  • The evidence most relevant to GiveDirectly comes from an RCT of a GiveDirectly campaign (available here). We discuss the findings of this RCT in our cash intervention report.
  • Cash transfers are among the best-studied development interventions, though questions remain. These studies generally show substantial increases in short-term consumption, especially food, and little evidence of negative impacts (e.g., increases in alcohol or tobacco consumption). It is important to note that most of these studies are of income transfers; there is more limited evidence for programs with wealth transfer models like GiveDirectly's. This is a potential cause for concern and one of the reasons that we are particularly interested in GiveDirectly experimenting with and evaluating different approaches.
  • There is also some evidence that recipients are able to invest cash transfers at high rates of return (e.g., ~20% per year), leading to long-term increases in consumption.
  • We feel that this intervention faces an unusually low burden of proof, given that poverty reduction is an outcome by definition, though donors' intuitive reactions to it may vary widely.

Are the people meeting GiveDirectly's criteria low-income?

GiveDirectly has collected data on poverty levels of the people receiving cash transfers as part of its studies (these people were selected using the process detailed above). GiveDirectly has shared the full survey form used to interview participants,86 as well as its own summary of the data collected as of March 2012:87

Well over half of adults skip meals, less than half of household members eat until they are content, people commonly go to sleep hungry and a paltry 18% report having enough food for tomorrow in their household. Those living in eligible homes are even worse-off than the average household, consuming less and holding fewer assets. Overall, mean and median daily per capita consumption among eligible households are $0.65 and $0.55 at nominal rates, and 74% are below the Kenyan poverty line, indicating a very poor population.

GiveDirectly also provided charts that show a clear difference in the consumption, expenditures, and assets of households in mud and thatch homes compared to those in cement homes, but fairly small differences between those living in mud and thatch homes and those living in mud and iron roof homes.88

The RCT that Innovations for Poverty Action conducted of GiveDirectly's transfers in Rarieda provides end-line data on food consumption among control group recipients.89 This data shows that "20% [sic90] of the control group reports that not all household members usually eat until they are content, 23% of respondents report sleeping hungry in the last week, and only 36% report having enough food in the house for the next day."91 Other results related to food consumption are measured as well which are, in our view, consistent with the notion that recipients are extremely poor.

GiveDirectly has received feedback from field staff and recipients that using housing materials as the targeting criteria systematically misses some households that are viewed within communities as comparably poor to those in thatch-roof houses.92 GiveDirectly is considering modifying its targeting criteria to capture more of these households.93

Anecdotal evidence from GiveWell's site visit to Kenya

In November 2012, GiveWell staff visited Kenya to view GiveDirectly's program in the field. See our notes and photographs from the site visit. We visited 5 locations (3 in Siaya and 2 in Rarieda) where GiveDirectly had transferred funds or was in the process of enrolling recipients to receive funds. We visited approximately 15 households across the 5 locations (including 2 non-recipient households with metal roofs and cement walls and floors that did not qualify for GiveDirectly's program). For details on how homes we visited were selected, see this footnote.94

We would characterize the ~15 households we visited (as well as other households we saw while walking but did not speak with directly) as extremely poor. We summarize characteristics of these households as follows:

  • Most homes are made up of three rooms.
  • The main room is a sitting area. In the homes we visited, this room varied in size from approximately 10'x12' to 12'x20'. This room has 3 doors: one to the outside; one to what appeared to be a storage room; one to a bedroom. The husband and wife sleep in the bedroom and the children sleep in the storage room or in the kitchen.
  • The kitchen is often a separate structure, most often thatched-roof (even for homes that have tin roofs). Some households have no kitchen structure and cook outside. Others have a small kitchen in place of a storage room.
  • There are no doors in between rooms in the house, just hung curtains.
  • The living room has many chairs and couches for sitting. They often almost fully cover the wall area (aside from doors). There are also coffee tables in the middle of the room. Poorer homes had less furniture; one home we saw had a single chair and a single broken table.
  • People have wall hangings for decoration. The most common hanging we saw was old calendars (e.g., from 2003) that have pictures and can be used for decoration.
  • Most houses had 1-2 kerosene lamps that provide light since they don't have electricity. One home (a non-recipient we visited) had two electric lights, which were powered with a solar panel.
  • People we spoke with reported walking 5-20 minutes daily to obtain drinking water, which one recipient reported doing 1-2x per day.
  • Most households owned a bicycle.
  • Some households have radios (both of the non-recipients we saw had radios; one had a TV). Of the others, 3/14 had radios. These were most often powered with what looks like a car battery .
  • Most people owned one cell phone pre-GiveDirectly.
  • Households tend to own some livestock. Most commonly, we saw 1-2 cows and 4-5 chickens each. They reported selling the milk or saving it for personal use, and many mentioned being able to sell their cows in the future to pay for their kids to attend secondary school.

Note that among the households we visited, many had already received part or all of their transfer from GiveDirectly, so these characterizations are based on a selection of households that include some newly-built or renovated structures in addition to older structures. Given that some of the recipients we met used transfers to build larger houses or buy livestock, our observations would likely over-estimate the assets of each household pre-transfer.

In addition, the homes we saw from afar in villages we visited and homes we passed while driving in the area appeared to be at a similar level of extreme poverty.

Is GiveDirectly effectively targeting people who meet its criteria?

GiveDirectly's process for identifying and enrolling households is described above. It involves multiple unannounced visits by different staff to each recipient home in order to confirm that recipients meet the criteria. (That is, if someone were to temporarily occupy a mud and thatch home in order to be enrolled, they would be unlikely to be sure of being present for future re-checks.) We have examined data collected by GiveDirectly from its enrollment process (registration, backchecks, remote checks and audits) for most transfer campaigns.95

If the information collected about a household at different stages of enrollment is inconsistent, GiveDirectly staff revisit the household for an audit.96 GiveDirectly tracks the percentage of households found to be ineligible at registration, backcheck, and audit in its monthly operations reports.97 We believe this process to be generally effective at identifying and enrolling households that meet its criteria.

Does GiveDirectly have an effective process for getting cash to recipients?

Mobile money providers

GiveDirectly transfers funds to recipients through mobile money providers. In Kenya, the mobile money provider, M-PESA, allows users to receive, send, deposit, and withdraw funds on their mobile phones. When withdrawing funds, recipients must present ID along with their mobile phone number and a user-specified M-PESA PIN number to the M-PESA agent.98 Users enter the amount they want to withdraw on their own phone, and after each transaction, they can see their remaining balance,99 reducing the ability of agents to defraud clients of funds.

In Uganda, GiveDirectly worked with two different mobile money providers in its pilot campaign (745 recipients were assigned to EZEE Money, 215 recipients to the MTN).100 GiveDirectly said that after assessing the relative performance of these two providers, it chose to work exclusively with MTN in the next campaign.101 MTN also has the advantage of having a more robust agent network than EZEE Money, so MTN recipients are somewhat less dependent on cash out days.102 MTN has similar security measures as M-PESA: a user must present ID to an agent before making withdrawals, provide their phone or SIM card, and enter their PIN number. Confirmation messages are also sent after withdrawals.103

Despite these mobile money security measures, Lydia Tala, a Senior Field Officer who has been responsible for making post-transfer phone calls to recipients in Kenya, reports that one of the most common client complaints is the belief that M-PESA agents are overcharging or stealing funds. Ms. Tala believes that these reports are incorrect and that approximately 10% of recipients are not fully aware of how to use M-PESA, so they may withdraw funds without checking their balance, ultimately being surprised when they have drawn down their account.104 GiveDirectly told us that it recognizes this issue and maintains a hotline to provide recipients with assistance in navigating the M-PESA system.105 In Uganda, some recipients have experienced delays in accessing their funds due to MTN not activating them immediately.106 Another issue that GiveDirectly has noted is that recipients who have not previously had a mobile phone or mobile money account are often less familiar with how to use them and how to keep their account information secure. GiveDirectly field staff explained that they will provide training to recipients in how to use their phones and accounts, and reminders are also given at cash out days.107

In Kenya, recipients withdraw cash from mobile money agents located in or near their villages.108 In Uganda, the agent network is less robust, so GiveDirectly coordinates cash out days for recipients to withdraw funds after each of the ten monthly installments.109

After the transfers are sent, GiveDirectly also administers follow up surveys that ask recipients if they have collected their funds and if they had any trouble doing so.110 The percentages of recipients who report issues withdrawing funds is consistently low (above for details. Follow up surveys also ask recipients what size of transfer they received. These amounts generally appear to vary slightly among cohorts of recipients. For example, in a survey for ongoing campaigns in Kenya, recipients reported receiving various amounts between 37,000 KES – 40,000 KES.111 Other than the mobile phone purchase deduction, we do not know the causes of this variance.

Staff fraud

The most significant issue that GiveDirectly has had in making sure that cash gets to recipients is the case of staff fraud in the Uganda pilot campaign. We discuss this case more below.

How do recipients spend their cash, and how does this spending impact their lives?

Findings from the RCT

Effects of receiving cash transfers
72% of treatment group households in the evaluation received just $287; the rest received $1,085.112 In the sections below, we use the outcomes from the larger transfer group unless otherwise specified, because GiveDirectly typically gives transfers of similar size.113 For every outcome, the larger transfer led to more spending compared to the smaller transfer with a few exceptions, where we have noted the outcome for the smaller transfer group in the text, and for tobacco and alcohol and indices of health and education, where the effects were not statistically different from zero. Though we report transfer sizes in exchange-rate adjusted terms, we report the outcomes in purchasing power parity (PPP) adjusted U.S. dollars.114

How GiveDirectly transfers were spent
Researchers collected data by surveying members of the treatment and control groups about their recent spending. All data that follows comes from participant self-reports. GiveDirectly recipients increased the value of their non-land assets and their monthly consumption.115 Their spending is broken down in more detail below.

  • Total non-land assets.116 Receipt of large transfers increased households’ non-land assets by an average of $463 (95% CI: $378 to $549).117 The largest categories of asset increases were livestock ($131, 95% CI: $79 to $183), durable goods ($100, 95% CI: $71 to $129; primarily furniture), and savings ($18, 95% CI: $9 to $27).118 Households receiving transfers (small or large) were 23 percentage points (95% CI: 17% to 29%) more likely to have an iron roof than the control households.119 Though Haushofer and Shapiro 2013 doesn't report the change in likelihood for recipients of large transfers alone, recipients of large transfers were 23 percentage points (95% CI: 13% to 33%) more likely to have iron roofs at end-line than recipients of small transfers.120 Haushofer and Shapiro 2013 estimated that iron roofs cost about $564 USD PPP based on a survey of one respondent in each of 20 villages.121 GiveDirectly ran a survey that sampled a respondent from each of 20 villages and found that iron roofs cost $418 USD PPP on average.122 We do not know what explains this discrepancy.
  • Business expenses. Households receiving large transfers spent about $13 per month (95% CI: $1 to $25) more than control households on business expenses, which were primarily made up of non-durable expenses on non-agricultural businesses.123 Recipients of small transfers also spent about $13 more per month (95% CI: $4 to $22).124
  • Health expenditures Recipients of large transfers spent about $3 (95% CI: -$1 to $6) per month more than control households on health expenditures.125 Recipients of small transfers also spent about $3 (95% CI: $1 to $5) more.126 This spending was also included within the estimate of spending on consumption, below.
  • Education expenditures. Haushofer and Shapiro 2013 reports that treatment households receiving large transfers spent $1.89 (95% CI: $0.20 to $3.58) more than the control households on education expenditures and treatment households receiving small transfers spent $0.79 (95% CI: -$0.31 to $1.89) more.127 We're not sure of the time period over which this estimate is calculated. Haushofer and Shapiro 2013 also reports that treatment households receiving large transfers spent $16.26 (95% CI: -$6.50 to $39.02) more than control households on education expenditures in the past month and treatment households receiving small transfers spent $19.41 (95% CI: -$12.22 to $44.74) more.128 We're not sure if the difference between the two estimates is due to the difference in the samples used to calculate them (they have different sample sizes) or the different time periods over which they might be calculated or some other explanation.129 Education expenditures were also included within the estimate of spending on consumption, below.
  • Consumption. Treatment households consumed about $51 more per month (95% CI: $32 to $70) than control households.130 About half of this additional consumption was on food.131 This additional consumption also included increased spending on social expenditures and various other expenditures.132
  • Alcohol and tobacco. Treatment households did not increase their spending on alcohol or on tobacco.133

Impacts of GiveDirectly transfers on recipients

  • Food security. At baseline, food security was low among participants.134 Program participants reported a 0.37 standard deviation (95% CI: 0.17 to 0.57) increase in a food security index over controls.135
  • Health and education. The study did not detect an effect on indices of health and educational outcomes.136
  • Revenue and profits. Receipt of large transfers lead to a $15 per month (95% CI: -$1 to $32) increase in total revenues and receipt of small transfers lead to a $17 (95% CI: $4 to $30) increase but neither resulted in a detectable increase in profits.137 We emphasize that these are very short-run effects and we do not know whether participants’ business investments might lead to profits in the longer run.

Researchers also considered more subjective measures of impact on recipients' quality of life:

  • Psychological well-being. Treatment improved an index of psychological wellbeing by 0.45 standard deviations (95% CI: 0.25 to 0.65).138 There was no observable effect on cortisol for the treatment group as a whole although cortisol, an indicator of stress, was slightly lower in the large transfer group than the small transfer group, a difference that was statistically significant at the 10% level when controls were included in the model.139
  • Female empowerment. Control households in treatment villages measure 0.23 standard deviations (95% CI: 0.05 to 0.41) higher on an index of female empowerment than control households in control villages.140 This suggests that cash transfers to a village unexpectedly empowered females in both recipient and non-recipient households. The researchers propose potential mechanisms for this effect, but are explicit that these measured results are surprising and warrant further investigation.141 Note that we report this result for the sake of comprehensiveness but would guess that it is more likely to be random than real.

Data from follow-up surveys

GiveDirectly provided us with data from responses recipients gave to surveys conducted by GiveDirectly staff concerning how recipients used their cash transfers. This data was collected at different points in the transfer cycle of each campaign.142 We summarize the data from recent campaigns in Kenya and Uganda below.143

Number of recipients who reported spending, by category

Kenya Uganda
Category # of respondents who reported spending in category % of respondents who reported spending in category # of respondents who reported spending in category % of respondents who reported spending in category
Food 1205 59.0% 618 31.0%
Clothing 274 13.4% - -
Household items 634 31.0% 426144 21.3%
Building 1595 78.1% 1075 53.9%
Land 72 3.5% 147 7.4%
Livestock 453 22.2% 496 24.8%
Farm business 189 9.3% 116 5.8%
Non-farm business 243 11.9% 48 2.4%
School 687 33.6% 424 21.2%
Medical 132 6.5% 186 9.3%
Water 2 0.1% 0 0.0%
Debt 84 4.1% 68 3.4%
Savings 415 20.3% 176 8.8%
Life event 127 6.2% 5 0.3%
Family 165 8.1% 17 0.9%
Church 22 1.1% 14 0.7%
Transport 138 6.8% - -
Alcohol - - 1 0.1%
Other 94 4.6% 57 2.9%
Total respondents 2043 1996

Amount of reported funds spent, by category

Kenya Uganda
Category Amount of funds reported to be spent in category (KES) % of total funds reported to be spent in category Amount of funds reported to be spent in category (UGX) % of total funds reported to be spent in category
Food 4,794,402 5.7% 20,667,800 4.4%
Clothing 614,522 0.7% - -
Household items 3,760,451 4.5% 28,061,120145 5.9%
Building 46,449,810 55.1% 194,449,559 41.2%
Land 2,214,850 2.6% 19,603,000 4.1%
Livestock 6,438,295 7.6% 66,344,250 14.0%
Farm business 1,047,850 1.2% 10,536,000 2.2%
Non-farm business 3,971,973 4.7% 8,414,000 1.8%
School 5,639,148 6.7% 49,246,000 10.4%
Medical 652,657 0.8% 13,434,010 2.8%
Water 2,200 0.0% 0,000 0.0%
Debt 466,230 0.6% 6,444,000 1.4%
Savings 4,107,516 4.9% 19,258,500 4.1%
Life event 2,066,035 2.4% 750,000 0.2%
Family 750,880 0.9% 866,000 0.2%
Church 63,750 0.1% 141,000 0.0%
Transport 393,375 0.5% - -
Alcohol - - 5,000 0.0%
Other 909,025 1.1% 6,190,000 1.3%
Total 84,342,969 100.0% 472,471,359 100.0%

Anecdotal evidence from our site visit

In our site visit to GiveDirectly recipients in Kenya, we asked about the value of items commonly purchased with transfer funds.146 Recipients reported that their thatched-roofs frequently leak when it rains and require replacement every 3-4 months at a cost of 1,000 Kenyan shillings ($11.68 based on the exchange rate as of November 15, 2012147) as well as time/labor. One recipient also reported that when it rains, she moves her family and their belongings into other structures to stay dry. Recipients reported buying livestock as an investment/savings device, hoping that they could (a) use the milk from the cow or goat for additional income and (b) sell the cow or goat and any offspring in the future if/when they needed additional funds (for e.g., secondary school fees for their children which are approximately 15,000 Kenyan shillings per year148 ($175.13 based on the exchange rate as of November 15, 2012149)).

Do the cash transfers cause problems and complications that offset their positive impact?

  • Does distribution to some community members and not others result in jealousy, conflict, or related issues?

    The RCT that Innovations for Poverty Action conducted of GiveDirectly's transfers in Rarieda found no significant effects of transfers on the rate of crime in treatment villages150 or on instances of physical, sexual, or emotional violence in treatment households as compared to control households in treatment villages.151

    GiveDirectly surveys recipients (post-transfer) on the following questions:152

    • Have you heard complaints about GD in your community? What complaints are you hearing? Who is upset/complaining? Who are they upset with?
    • Has there been any shouting or angry arguments among people in your village about these transfers? If yes, describe.
    • Has there been any violence, theft, or other crime in your village related to these transfers? If yes, describe.

    GiveDirectly has sent us results from follow-up surveys conducted in multiple transfer campaigns. Below, we summarize the survey data from recent campaigns in Kenya and the pilot campaign in Uganda for some of the questions included in these surveys.153 For a full list of follow-up survey questions, see GiveDirectly, Kenya verification template, August 5, 2013.154 Percentages reported in this table represent the number of recipients who are marked as having responded "yes" (that they had the issue) out of those for whom a response is recorded in the data.

    Kenya Uganda
    Issue # of reports/# of respondents % reports of total respondents # of reports/# of respondents % reports of total respondents
    Trouble collecting 68/6395 1.1% 39/1950 2.0%
    Complaints 1120/14463 7.7% 139/1949 7.1%
    Theft155 265/6373 4.2% 8/1950 0.4%
    Bribes156 34/14458 0.2% 52/7795 0.7%
    Shouting 265/14459 1.8% 65/1949 3.3%
    Crime 138/14457 1.0% 21/1949 1.1%
    Household argument 62/14461 0.4% 31/1948 1.6%

    Note that GiveDirectly surveys only cash recipients, not non-recipients, and all data is self-reported.

    We have found very limited information about jealousy and conflict related to other cash transfer programs, but one study that found small levels of hostility towards recipients of an unconditional wealth transfer in Uganda is discussed in our cash transfer intervention report.

    We have also reviewed the records of calls made to GiveDirectly's hotline from May 2012 – September 2014, which provide anecdotal evidence of tension and conflict caused by the cash transfers, according to recipient reports, including marital disputes and Village Elders requesting funds from recipients.157 In the most recent follow up tracker,158 the most common type of adverse event recorded is household conflict, followed by theft. The number of issues reported for recent campaigns are equal to about 6% of the total households in the campaigns (though it is possible that single households account for more than one issue recorded).159

  • Do the cash transfers lead to more frequent or more serious criminal activity?

    The RCT that Innovations for Poverty Action conducted of GiveDirectly's transfers in Rarieda found no significant effects of transfers on the rate of crime in treatment villages.160 However, we do not know if the cash transfers cause more serious crimes (in terms of damages), but it seems plausible given that they create an influx of resources into villages. GiveDirectly notes that crime could become a more serious problem as its program becomes larger and more well-known.161

    Examples of attempted and/or successful criminal activity relating to GiveDirectly cash transfers include:

    • People stealing cash and cell phones from recipient households162
    • People contacting recipients and posing as GiveDirectly staff to defraud recipients of funds163
    • Mobile money agents defrauding recipients of funds164

    To mitigate the risk of small-scale crime, GiveDirectly emphasizes ways that recipients can keep their mobile money accounts and phones secure.165 It does not communicate with recipients via text message and tells recipients of this policy in order to protect against mass attempts at fraud,166 and it follows up with recipients who report crimes to try to resolve the issues.167

    Case of staff fraud: In mid-2014, GiveDirectly experienced one case of large-scale crime, when 2 of its field staff colluded with mobile money agents to defraud recipients of funds. The staff and mobile money agents were able to steal a total of $20,500 in the form of $20 deductions from 85% of recipients and $100 deductions from 15% of recipients.168 GiveDirectly found out about the fraud through follow-up calls to recipients, which were accelerated after a separate issue had been reported to GiveDirectly's hotline.169 GiveDirectly has taken multiple measures to address the vulnerabilities exposed by this case of fraud.170 We consider fraud to be an ongoing risk to the success of GiveDirectly's programs, but feel that the risk is mitigated by these measures as well as GiveDirectly's monitoring.

    As GiveDirectly scales, we would expect greater awareness of its program and more attention to be paid by people outside of the villages in which it works. This could increase the risk of large-scale crime. The cash out days that GiveDirectly administers in Uganda seem to be particularly easy targets for large-scale theft, as there is a substantial amount of cash in one location and no formal security. We are not aware of security measures that GiveDirectly has taken to mitigate the risk of large-scale crime beyond its response to the staff fraud. In addition to harming recipients, crime would likely cause delays for GiveDirectly's work.

  • Do grants distort incentives and decisionmaking? We have not seen information on the question of whether individuals who live in the areas served by GiveDirectly change their behavior in order to increase their chances of receiving transfers - for example, by spending more time at home to increase their chances of being at home when GiveDirectly staff visit, or by choosing to live in poorer quality housing in hopes of receiving transfers. The one-off nature of transfers (recipients are not eligible for a second round of transfers)171 may help to mitigate these effects among past and current recipients, though there is information to suggest that some recipients believe transfers could be given again in the future.172 We also have seen some very limited evidence (mostly pointing to no distortion) in the broader literature on cash transfers.

    Another way in which grants may distort decisionmaking is if they are promised and not delivered in time (causing people to make plans that cannot be executed). We do not have data directly addressing this issue, but GiveDirectly did provide statistics on the speed with which transfers were received for Rarieda and Siaya.173 In Rarieda, while 67% (359 of 536) of recipients waited less than a month and 84% (448 of 536) waited 3 months or less, 6% (34 of 536) waited 6 months or more. In Siaya (a later group), 188 of 193 recipients waited less than a month, and the remaining 5 waited 2-3 months. GiveDirectly comments:174

    We were able to accelerate [the time it took for recipients to register for M-PESA] significantly for two reasons: (a) we gave clearer instructions, and (b) we let recipients designate which household member they wanted to receive the transfers, which gives them flexibility to choose someone who already has a National ID; in the Rarieda round we could not do this as we were randomizing recipient gender. I expect the Nike cohort will take longer to register as that project focuses on 18-19 year old women, many of whom will not yet have IDs.

    GiveDirectly told us that for Kenya, the key factor determining when a recipient receives funds is when he or she registers for M-PESA, and that recipients are told from the beginning that they will not receive transfers until they have registered.175 GiveDirectly's records of calls to its Kenya hotline demonstrate that some recipients have been delayed in registering for M-PESA or collecting transfers due to issues outside of their control (e.g., a recipient's SIM number was already registered to someone else's M-PESA account; another recipient reported that an agent mistakenly claimed that the recipient's account had expired). The hotline records also document the steps that GiveDirectly has taken to follow up on recipients' concerns; we have reviewed some of these cases and find the steps taken to resolve issues to be reasonable and appropriate.176

    In Uganda, the agent networks of GiveDirectly's two mobile money providers are not very robust, which means that recipients must either travel farther, on average, to reach an agent or must withdraw cash only on days when GiveDirectly has arranged for agents to visit the villages (which GiveDirectly announces in advance).177 These challenges and the lack of flexibility may hamper recipients' abilities to execute on plans for how and when to use funds. GiveDirectly told us that so far, the vast majority of recipients have been able to collect their transfers, with a few delays of up to a few hours on days when transfers are scheduled due to agents needing to replenish their cash stocks.178

  • Do grants distort local markets? It seems possible to us that a large infusion of cash into an area could alter economic opportunities for both recipients and non-recipients. Such effects could be positive (for example by spurring investment and job creation or by increasing the availability of retail goods) or negative (for example, by leading primarily to local inflation). The limited evidence addressing this issue in the RCT of GiveDirectly's program in Rarieda and the broader literature on cash transfers points to no distortion. There is an ongoing RCT of GiveDirectly's program that is testing for macroeconomic effects.
  • Do cash transfers lead to large increases in spending on alcohol and tobacco? The RCT of GiveDirectly's program in Rarieda did not find an increase in spending on alcohol or tobacco. As discussed in our intervention report on cash transfers, RCTs of other programs that report spending on alcohol or tobacco do not find large increases in spending on these goods.

We also spoke with recipients and non-recipients about potential problems during our site visit to GiveDirectly's operations in Kenya in November 2012. For more, see our site visit notes.

Are the size and structure of the cash transfers well-thought-through and appropriate?

GiveDirectly’s standard model involves grants of $1,000 (USD) to households over approximately one year,179 after which recipients become ineligible for future transfers.180 It gives the following rationale for the size of its transfers:181

GiveDirectly sends each recipient household $1,000, or $200 per person for an average household. These payments are spaced out in time to respect limits imposed by the M-PESA system and to give recipients time to plan for them, but should be thought of as wealth and not income transfers. GiveDirectly sized transfers at this level to ensure that they are fair, well-understood, and potentially transformative.
  • Fair. Transfers are calibrated to be large enough to enable eligible households to raise their incomes to the level of their least well off but ineligible neighbors. This calculation was made using baseline data from our ongoing impact evaluation and assuming a 25% annual rate of return. (Our estimate of the return on capital was triangulated using average micro-credit loan charges, academic studies on the returns to capital in developing countries and interviews with recipients.) Calculations based on equalizing net worth, as opposed to income streams, led us to a similar ballpark figure. [GiveDirectly further notes, "'fair' is a subjective concept and we are not arguing for a particular concept of 'fairness' per se but rather that we think many would consider it 'unfair' to transfer so much to eligible [households] that we re-order the wealth distribution. We do not make the claim that non-recipients or particular donors agree that any particular transfer policy is fair."]
  • Well-understood. Transfers are sized to be within the range of transfers issued by other well-studied cash transfer programs. Examples of transfer sizes from other well-known programs include
    • $406 per household per year for participants in Progressa / Opportunidades, and up to $4,059 in total over ten years.
    • $524 per household per year for participants in Bolsa Familia (Brazil) in 2011, and a maximum of $7,855 in total over five years.

    If anything we would lean towards transferring more than these programs do, since they serve people starting from a higher level of wealth.

  • Potentially transformative. Because cash transfers are flexible by design there are a number of relevant ways to think about what they could do for a recipient.
    • If invested at a 25% real rate of return, the transfer would allow the average recipient to permanently increase his/her [daily] consumption by $0.14 over a baseline level of $0.65, a 22% increase.
    • The transfer is enough to purchase
      • 5.5 years of secondary schooling (estimated returns on a year of education for rural Kenya are around 15%)
      • 5.2 years of basic food requirements for one adult.
      • 1.2 acres of land, which is 1.8 times average baseline landholdings among eligible households.
      • Tin roofs for 4 houses (estimated financial rate-of-return: 17%, not including health and comfort benefits.)

We have reservations about the above reasoning:

  • Regarding "fair." Pre-cash-transfer wealth/income differences between eligible and ineligible recipients may exist for a number of reasons; we don't believe it's warranted to assume that a "fair" world would see the two groups with the same wealth/income due to an equalizing transfer, and more to the point, we don't believe that the ineligible households are likely to see the situation as "fair." In addition, we are concerned that by aiming to equalize eligible and ineligible households, GiveDirectly takes on a substantial risk of its calculations being off in a way that leads to eligible households becoming systematically better off than ineligible households, which could distort incentives and lead to conflict.
  • Regarding "well-understood." GiveDirectly notes that its transfers are similar - in dollar terms - to those of government programs, but that they are likely much larger in "percentage of income" terms. We note that the cash transfer programs that have been studied to date seem to be in the range of 9-27% of recipients' annual consumption; by contrast, if GiveDirectly's clients average $0.65 in daily per capita consumption and receive an average of $288 per person over the course of a year (see above), this implies that people receive an average of 121% of their annual consumption in the year in which they receive the transfer.182 The quote above states that the lower level of initial income is an argument for making the cash transfer larger, but to us, it means that the risks of distorting incentives, causing conflict, etc. are likely to be greater than those of previously-studied programs, since the transfers are a substantially greater percentage of consumption. This issue is somewhat mitigated by the fact that GiveDirectly's transfers are designed as "wealth transfers" rather than as "income transfers": recipients receive funds over the course of a year and then become ineligible, whereas the government programs it alludes to have longer periods of eligibility. GiveDirectly has also told us that its decision to make larger transfers over a shorter period of time is based on recipients' reported preferences.183 But psychologically, the impact of GiveDirectly's transfers may be very different from those of government programs.

Perspectives of recipients and field staff

On our site visit to Uganda in 2014, we spoke with a small number of recipients and field staff about the size of transfers. We asked whether people felt it would be better for GiveDirectly to keep the transfer size the same or reduce the transfer size but provide transfers to more people.184 4 out of 4 recipients said that the transfer size should stay the same (or be increased).185 One GiveDirectly Field Officer also held this view, saying that $1000 is enough to help someone advance but is not so much that it would distort incentives to work. Two other field officers suggested that it would be better for GiveDirectly's transfers to reach more people in a village, even if it meant reducing the size of a standard transfer.186

Discussion of the merits of further research

GiveDirectly has considered experimenting with transfer size but does not view this as a high priority, in part because it feels that although further research on this question may improve GiveDirectly's program, it would be unlikely to influence other cash transfer programs. GiveDirectly is not concerned that people will run out of good uses of funds from $1000 transfers. The Rarieda RCT included both a $300 transfer treatment group and a $1000 transfer treatment group, but did not provide strong evidence on what the best transfer size would be, because of small sample sizes and the difficulty of assessing the relative value of different uses of funds.187

Does GiveDirectly's targeting strategy seem well-founded, and how is it received?

GiveDirectly targets households with thatch roofs and excludes households with iron roofs. In GiveDirectly's campaigns in Kenya, about 35-45% of households have been eligible based on these criteria, while in Uganda about 80% of households have been found to be eligible.188 GiveDirectly has experimented with more inclusive targeting and community-based targeting, and plans to consider slight modifications to its targeting criteria next year (more).

We have reservations about the approach of targeting people based on the materials their houses are made of:

  • As noted above, it is not clear to us that people in thatched-roof homes (eligible for transfers) are substantially and consistently poorer than people in iron-sheet-roofed homes with mud walls and floors (not eligible for transfers in a standard campaign). In community-based targeting pilots, GiveDirectly recipients identified households that did not meet GiveDirectly's standard targeting criteria but seemed comparably poor.189 GiveDirectly still feels that housing materials are an effective means of targeting the poorest of the poor, on average, though it is considering modifying its targeting criteria to catch some of the outlier cases.190
  • To the extent that there are differences in income or wealth between residents of thatched-roof homes and those who live in iron-sheet-roofed homes, it seems possible that these differences come down to fortune/luck (i.e., people in iron-sheet homes have been more fortunate and thus able to afford iron sheets), but we also think it may come down to differences in choices regarding financial management (i.e., people in iron-sheet homes may have demonstrated better financial management and planning, thus allowing them to acquire iron sheets). If the latter is the case, there is a potential risk that GiveDirectly is systematically targeting the people who are less likely to use additional money well. GiveDirectly comments: "The most informative data available on this point are the differential impacts we’re seeing within the set of eligible households – specifically, poorer families seeing bigger impacts on nutrition while richer households see bigger impacts on tangible investment."191
  • GiveDirectly's follow up tracker demonstrates that cash transfers can lead to tension between recipients and non-recipients.192 Though follow up surveys report low levels of tension and conflict, we would expect these to be underreported by recipients to GiveDirectly staff, a dynamic that GiveDirectly has seen play out in past cases.193 GiveDirectly conducted a small-scale study in Kenya to see whether more inclusive targeting criteria could reduce tension and conflict within villages. We find the results inconclusive (more). In addition, when we spoke with three field staff in Uganda, two of them suggested that it would be better for GiveDirectly's transfers to reach more people in a village, even if it meant reducing the size of a standard transfer. According to the Senior Field Officer, the current targeting model causes bragging and unrest in the communities, potentially motivating those who don't benefit to steal from those who do. He said it would be better for GiveDirectly to provide transfers to everyone in a village, even if some transfers were small.194

Does GiveDirectly divert skilled labor away from other areas?

As of October 2014, GiveDirectly had 39 total field staff members across Kenya and Uganda: 1 Project Associate, 6 Senior Field Officers, 30 Field Officers, and 2 other staff.195 GiveDirectly recruits FOs through referrals from peer organizations, postings at universities, and job advertisements. The application process involves an interview with the FD and a language competency exam. GiveDirectly reports that it receives approximately 6 times the number of resumes as openings for Field Officer positions.196 Regarding its field staff in Kenya, GiveDirectly explained that successful candidates generally have a college education197 and are paid approximately $12 per day, in addition to expenses for travel and lodging while working.198 GiveDirectly reported greater language heterogeneity in the areas in which it works in Uganda, which made it harder to hire qualified field staff who also had the necessary language skills.199 Based on GiveDirectly's current staffing situation, we do not see diversion of skilled labor as a serious concern.

Evaluation and experimentation


RCT of GiveDirectly's Rarieda campaign

Other evaluation and experimentation

Ongoing

  • Macroeconomic effects: Based on conversations with policymakers, GiveDirectly found that a key question relevant to government cash transfer programs is the impact they have on macroeconomic factors such as inflation and job creation. GiveDirectly is working with Professor Ted Miguel of the University of California, Berkeley, and Assistant Professor Johannes Haushofer of Princeton University, who will conduct an RCT on macroeconomic effects of GiveDirectly's program in Kenya. This study will include a long-term follow up component as well. GiveDirectly told us that the ideal sample size for this study, which is randomized at the village level, would require $15 million for cash transfers. Baseline data collection for the study began in August 2014. Paul Niehaus, GiveDirectly's President, is serving as a Principal Investigator on this study. In order to mitigate potential bias from his involvement with the research, GiveDirectly has applied a number safeguards, including preregistration of plans for measurement and analysis.201 We have not yet reviewed this preregistration, but plan to do so in the next year.
  • Behavioral interventions: GiveDirectly is conducting an RCT of two main behavioral interventions: (a) enabling recipients to decide when and how to receive their transfer payments; and (b) providing more information to recipients about spending options.202 The main outcome of interest in this study is the rate of return on spending.203 GiveDirectly is conducting the data collection for this study internally, and the analysis will be done by independent researchers.204 This study began in late October 2014.205 It is fully funded by an anonymous donor.206
  • Gender: GiveDirectly is planning to run a small pilot of informal contracts between spouses in the spring of 2015. External research partners will evaluate the impacts of the contracts on domestic violence and female empowerment. GiveDirectly has said that if the pilot is successful it will be expanded into a larger-scale project.207

Past

  • Small-scale RCT of cash transfers to young women: IPA conducted a RCT of GiveDirectly's Nike campaign, which provided transfers exclusively to young women ages 18-19. This campaign was funded by the Nike Foundation. GiveDirectly shared IPA's survey instrument with us prior to the study.208 We did not see an analysis plan prior to the study, as we did with the Rarieda RCT. GiveDirectly writes that "the pilot was designed at a small scale with the expectation that it would not produce statistically robust evidence, but would provide directional learnings to guide future investment and experimentation."209 The study is now complete, and GiveDirectly has shared its write-up, as well as a qualitative piece on the perspectives of the young women involved in the study, which was prepared for GiveDirectly by an independent researcher.210 We have not vetted either document.
  • Extended data collection by phone: IPA received a $30,200 grant to extend data collection in a sub-sample of participants from the Rarieda RCT using mobile phone-based data collection techniques. The grant is from USAID via the Policy Design and Evaluation Lab at UCSD. The goals of the project are to generate data on longer-term effects of cash transfers (up to 2 years after completion of the RCT) and how treatment effects unfold over time, as well as to study the potential for using mobile phones as cost-effective, easily adaptable tools for data gathering.211
  • Broadening eligibility with more inclusive targeting: GiveDirectly conducted a small-scale study in Kenya to see whether more inclusive targeting criteria could reduce tension and conflict within villages. In treatment villages, GiveDirectly applied a "saturation" model, which included households with iron roofs and mud walls as eligible. In total, about 85% of households in saturation villages received transfers. GiveDirectly collected its standard follow up survey data, which includes questions about tension and conflict, in the 19 treatment and 18 control villages. It also conducted focus groups in 3 treatment and 3 control villages to elicit opinions about targeting strategies.212 GiveDirectly found that the data on adverse events was inconclusive, and that when faced with the decision of how to allocate limited resources, focus groups preferred to prioritize thatched-roof households.213 We put limited weight on these results due to the small sample size of the study and would be interested in seeing further research on this question.
    • GiveDirectly also piloted "community-based targeting,"214 but is not planning to implement it more broadly.215

Future

GiveDirectly is considering many other ideas for future experimentation:

  • Providing cash transfers in an urban setting216
  • Providing cash transfers as humanitarian relief217
  • Facilitating the pooling of recipient funds for public goods projects218
  • Implementing a lifetime basic income guarantee219
  • Serving the role of payment provider at cash out days220
  • Using biometric authentication221

GiveDirectly's goals for experimentation include increasing the evidence base for cash, improving recipient returns and welfare, and developing capabilities necessary to implement larger-scale programs.222 GiveDirectly currently plans to use campaigns in Uganda as a "testing ground" for these experiments.223

What do you get for your dollar?

What percentage of GiveDirectly's expenses end up in the hands of recipients?

GiveDirectly aims to deliver a high proportion of campaign expenses directly to recipients: 90% in Kenya, and 87% in Uganda.224 GiveDirectly calculates its "efficiency ratio" by the amount transferred directly to recipients out of total campaign costs. GiveDirectly excludes set-up and marketing costs from total spending in this calculation,225 though it recently started amortizing fixed costs of campaigns across campaigns and including those within total campaign costs.226 Data from GiveDirectly's distributions imply that it has been hitting this target. When all costs are considered, including set-up and marketing, cash grants make up 86.7% of expenses (more).

Costs not included in GiveDirectly's total spending are the value of its President's time (~40 hours/week), which was unpaid before FY 2014;227 research costs of the independently-run studies of GiveDirectly's program; and the roughly $2 million that GiveDirectly has set aside as reserves to cover staff salaries in the event that GiveDirectly has a funding shortfall.228 The total spending figures also do not include set up and marketing costs from September and October 2014. This is due to a slight mismatch in the time period reported for campaign versus set up and marketing costs.

Does GiveDirectly offer a large amount of humanitarian impact per dollar?

We have not conducted a cost-effectiveness analysis that attempts to quantify the benefits of cash transfers in humanitarian terms. Instead, in comparing cash transfers to the interventions conducted by our other top charities, we have attempted to monetize some of the benefits of the latter, in particular the “developmental effects” of deworming and bednets. (In the case of the comparison with bednets, for instance, this means quantifying the estimated impact of bednets on later-in-life income of children through a comparison with the effects of deworming, and then subjectively comparing the cost per life saved with the value of that amount of money as a cash transfer.)

In practice, these calculations are highly sensitive to assumptions, especially regarding:

  • the investment returns to cash transfers;
  • how much confidence one places in the developmental impacts of deworming; and
  • the subjective assessment of the relative value of averting child mortality and improving incomes.

We guess that in purely programmatic terms, and given our values, bednet distributions are more cost-effective than deworming, which is more cost-effective than cash transfers. However, we think there are plausible values for these assumptions that would permit any ordering of these three programs.

We encourage readers who find formal cost-effectiveness analysis important to examine the details of our calculations and assumptions, and to try putting in their own. To the extent that we have intuitive preferences and biases, these could easily be creeping into the assumption- and judgment-call-laden work we’ve done in generating our cost-effectiveness figures, and we’re not entirely confident that the figures themselves are adding substantial information beyond the intuitions we have from examining the details of them.

Our 2014 cost-effectiveness spreadsheet is available here. See also, our 2012 discussion of the cost-effectiveness of cash transfers and other interventions.

Room for more funding

Projections for fiscal year 2015

In September 2014, GiveDirectly provided the following statement regarding its room for more funding in FY 2015:229

For 2015, we estimate our room for funding to be roughly $20 M with current resources, pace, and model, and $40 M at the optimal pace:

  • In Kenya, we are committing ~$1M/month and can create the same structure in Ug
  • If we buffer two months for holidays and set-up, that’s $10M/year in both countries
  • Teams are currently 5 FOs and can be increased to 10 with no other changes in structure. SFOs have previously shown the ability to manage teams of 10.
  • Teams of 10 would double our throughput to $40M/year

Note that the above statement refers only to GiveDirectly's room for more funding for transfer campaigns.

In October 2014, GiveDirectly sent us a scenario analysis of its room for more funding under different assumptions regarding government permissions and pace of enrollment, demonstrating how it would allocate Field Director time.230

GiveDirectly has successfully scaled up over time, increasing its rate of transfers about 4x every year.231 In FY 2014, GiveDirectly received $17.4 million232 spent $6.1 million, and incurred liabilities (future transfers and transfer costs for currently enrolled recipients) totaling $9.3 million.233

In recent months, GiveDirectly has been enrolling ~900 recipients per month in Kenya, equivalent to $900,000 in committed transfers.234 GiveDirectly intentionally paused its enrollment in Uganda for research-related reasons,235 but believes it could ramp up to a similar pace there within a couple months.236

GiveDirectly has received approximately $23.4 million since it was founded.237
Of this funding:

  • $16.7 million has been used for campaign costs238 representing transfers sent and committed to approximately 15,000 households as of October 2014.239
  • $572,000 has been spent on set-up and fundraising costs as of September 2014.240
  • Approximately $2 million was set aside for salary reserves.241
  • Approximately $1.8 million was designated for 2015 fundraising budget.242

GiveDirectly told us that it plans to use the remaining funds (approximately $2.3 million) for transfers to additional households in Kenya.243 At its current pace, GiveDirectly would complete this enrollment by the end of February 2015.244

GiveDirectly's past room for more funding statements have over-estimated the amount of funds it was actually able to use on campaigns in the given year, but it has nearly met or exceeded these targets shortly after the projected time periods.245 The lower end of GiveDirectly's FY 2015 room for more funding estimate seems very reasonable to us, given that it is based on the pace at which GiveDirectly is already operating in Kenya.246 GiveDirectly has told us that its median expectation of funding from donors other than GiveWell donors and Good Ventures is $10 million.247

Risks to room for more funding

GiveDirectly identified the following risks to its room for more funding:

  • Crime: Incidences of large-scale crime could cause delays and reduce GiveDirectly’s ability to transfer funds to recipients. The risk of crime seems likely to increase as GiveDirectly becomes better known in the regions in which it works. We discuss this risk more above. We consider this a moderate risk and plan to follow up on it over the coming year.
  • Government permissions: In order to expand into new areas, GiveDirectly must obtain permission from government officials at many levels. This process could be held up by an official who refused to grant permission, causing delays and possibly preventing GiveDirectly from expanding into an area indefinitely. GiveDirectly has attempted to mitigate this risk by networking with people with expertise in navigating such government relationships and could intervene if there were a problem.248 GiveDirectly feels that it now has a good understanding of the process for seeking government approvals and does not see this as a major risk.249 We do not consider this a limiting factor for FY 2015, as GiveDirectly has already obtained permissions for a cumulative capacity of about $30 million across Uganda and Kenya.250
  • Security: GiveDirectly notes that political violence and terrorism could hamper its ability to work in an area, and while these are risks in Kenya, they have not impacted Western Kenya (where GiveDirectly works) since 2008. GiveDirectly has attempted to mitigate this risk by working in multiple locations, so that it could shift its operations to Uganda if there were an issue.251 We know very little about security risks in Kenya and Uganda, but would guess based on GiveDirectly's assessment that it is a low risk.
  • Payment provider: Relying on one payment provider in each country introduces a risk that problems with the payment provider could cause delays. GiveDirectly feels that this risk is low, because if there were problems, it could switch to alternative providers.252 We would guess that this risk is low, as the mobile money providers that GiveDirectly uses are national networks, and GiveDirectly has identified alternatives.

Our bottom line

Based on our understanding of GiveDirectly's future plans, we believe GiveDirectly could absorb an additional $25-30 million beyond what it already expects to receive.

GiveDirectly estimates that it will hold approximately $3 million as of January 1, 2015 that could be targeted to additional transfers, and that it will receive $10 million from non-GiveWell-influenced sources over the next year. GiveDirectly has said it could receive and move up to approximately $40 million in a year. Though we do not believe that GiveDirectly will fully hit that target, we also see few risks to providing it with excess capital this year.

Unrestricted vs. restricted funds

We prefer that GiveDirectly spend funds in the way that it believes will maximize its potential and, accordingly, do not recommend that GiveWell donors restrict their donations in any way. On our "Donate" page, linked from here, we explain to donors that funds given via the link on this page will be treated as unrestricted donations (in which case GiveDirectly may use funds for all purposes, including experimenting with its model and process and organizational capacity building). Donations made directly via GiveDirectly’s website can be designated for Kenya, Uganda, either Kenya or Uganda, or as "flexible, including experiments."253

GiveDirectly as an organization

GiveDirectly is a relatively young organization. It was founded in 2008 when its founders were graduate students in economic development; Paul Niehaus, President and co-founder of GiveDirectly, is also an Assistant Professor of Economics at the University of California, San Diego.254 Professor Niehaus has been on sabbatical this year from his teaching position and working full time on GiveDirectly.255

We believe GiveDirectly to be an exceptionally strong and effective organization:

  • Self-evaluation: GiveDirectly has invested heavily in self-evaluation from the start, and furthermore, the study design of its Rarieda RCT was pre-registered for additional accountability and credibility. It continues to demonstrate a strong commitment to rigorous analysis of its work.
  • Track record: Although it is relatively young, we feel that GiveDirectly's first three years have gone well: GiveDirectly has successfully accomplished its goal of transferring cash to extremely low-income people at roughly a 90% ratio. We have also seen GiveDirectly refine its process over the years and take thoughtful measures in response to problems that arise, demonstrating a commitment to continuous improvement.
  • Communication: GiveDirectly has always communicated extremely clearly and directly with us and given thoughtful answers to our critical questions. Generally, GiveDirectly seems to come to conclusions that we find reasonable on key questions.
  • Transparency: GiveDirectly appears to value transparency as much as any organization we’ve encountered. We have not seen it hesitate to share information publicly (unless it had what we consider a good reason).

More on how we think about evaluating the leadership of organizations at our 2012 blog post.

Sources

Document Source
Conversation with Carolina Toth, Field Director, GiveDirectly, October 24, 2013 Unpublished
Conversation with Carolina Toth, GiveDirectly, November 20, 2014 Unpublished
Conversation with GiveDirectly field staff, October 20-21, 2014 Source
Conversation with GiveDirectly, April 8, 2014 Source
Conversation with GiveDirectly, December 7, 2013 Source
Conversation with GiveDirectly, July 24, 2014 Source
Conversation with GiveDirectly, July 7, 2014 Source
Conversation with GiveDirectly, July 7, 2014 (unpublished) Unpublished
Conversation with GiveDirectly, October 6, 2014 Source
Conversation with GiveDirectly, September 5, 2014 Source
Conversation with Paul Niehaus, November 14, 2014 Unpublished
Conversation with Paul Niehaus, President, and Joy Sun, COO, Domestic, GiveDirectly, August 27, 2013 Source
Conversation with Paul Niehaus, President, and Joy Sun, COO, Domestic, GiveDirectly, July 18, 2013 Source
Conversation with Paul Niehaus, President, and Joy Sun, COO, Domestic, GiveDirectly, July 18, 2013 [Unpublished] Unpublished
Conversation with Paul Niehaus, President, and Joy Sun, COO, Domestic, GiveDirectly, October 16, 2013 Unpublished
Conversation with Paul Niehaus, President, and Michael Faye, Director, GiveDirectly, November 19, 2013 Unpublished
Conversation with Paul Niehaus, President, and Michael Faye, Director, GiveDirectly, October 6, 2012 Source
Conversation with Paul Niehaus, President, and Rohit Wanchoo, Director, GiveDirectly, March 18, 2013 Unpublished
Conversation with Piali Mukhopadhyay, COO, International, GiveDirectly, October 22, 2013 Unpublished
Conversation with Piali Mukhopadhyay, GiveDirectly, October 20-21, 2014 Source
Conversation with Piali Mukhopadhyay, GiveDirectly, October 20-21, 2014 (unpublished) Unpublished
Conversation with Stuart Skeates, GiveDirectly, October 20-21, 2014 Source
Conversation with Stuart Skeates, GiveDirectly, October 20-21, 2014 (unpublished) Unpublished
Email from Carolina Toth, GiveDirectly, November 11, 2014 Unpublished
Email from Carolina Toth, GiveDirectly, November 14, 2014 Unpublished
Email from Carolina Toth, GiveDirectly, September 12, 2014 Unpublished
Email from Joy Sun, COO, Domestic, GiveDirectly, August 9, 2013 Unpublished
Email from Joy Sun, COO, Domestic, GiveDirectly, September 27, 2013 Unpublished
Email from Paul Niehaus, GiveDirectly, November 9, 2014 Unpublished
Email from Paul Niehaus, President, GiveDirectly, and Joy Sun, COO, Domestic, GiveDirectly, November 18, 2013 Unpublished
Email from Piali Mukhopadhyay, COO, International, GiveDirectly, November 25, 2013 Unpublished
Faizan Diwan, Innovations for Poverty Project Associate, conversation with GiveWell, November 8, 2012 Unpublished
GiveDirectly blog, Fighting fraud in Uganda Source (archive)
GiveDirectly FY 2011 Form 990 Source (archive)
GiveDirectly, 2013 Annual Report Source (archive)
GiveDirectly, 20140408 GD-GW update Source
GiveDirectly, 20140420 Uganda combined follow up data Source
GiveDirectly, 20140707 GW - GD quarterly update Source
GiveDirectly, 20140723 GW GD quarterly update Source
GiveDirectly, 20140904 GD – GW check in Source
GiveDirectly, 20140929 GW - GD annual update Source
GiveDirectly, 201410 Monthly Operations report Source
GiveDirectly, 20141010 Follow up tracker Source
GiveDirectly, 20141112 Kenya follow up data Source
GiveDirectly, Akumure, Uganda Enrollment database Source
GiveDirectly, Analysis plan for randomized controlled trial Source
GiveDirectly, Annotated budget projections (May 11, 2012) Source
GiveDirectly, Answers to questions from GiveWell, October 2013 Unpublished
GiveDirectly, Audit log Source
GiveDirectly, Back check instrument Source
GiveDirectly, Balance sheet Unpublished
GiveDirectly, Board spending breakdown Source
GiveDirectly, Budget summary, July 22, 2013 Unpublished
GiveDirectly, Campaign efficiency update for GW v2, October 24, 2013 Source
GiveDirectly, Capacity note Source
GiveDirectly, Cash transfer plan, November 7, 2013 Source
GiveDirectly, Chart of accounts Source
GiveDirectly, clarifications on GiveWell's draft review of GiveDirectly Source
GiveDirectly, Contextualizing transfer size Source
GiveDirectly, Disaggregated Google Follow-up Data (LS - long) Source
GiveDirectly, Disaggregated Nike Follow-up Data Source
GiveDirectly, Disaggregated Siaya Follow-up Data Source
GiveDirectly, Domestic organizational structure, November 7, 2013 Source
GiveDirectly, Enrollment speed of distributions Source
GiveDirectly, FAQs 2012 Source (archive)
GiveDirectly, FAQs 2013 Source (archive)
GiveDirectly, Final report Nike girls study Source
GiveDirectly, Financials 2013 Source (archive)
GiveDirectly, Financials 2014 Source (archive)
GiveDirectly, Follow-up tracker, July 2013 Source
GiveDirectly, FY 2012 Form 990 Source (archive)
GiveDirectly, GD – GiveWell update, October 16, 2013 Source
GiveDirectly, GD – GW update, July 17, 2013 Source
GiveDirectly, Give now Source
GiveDirectly, GiveWell clarifications (March 28, 2012) Source
GiveDirectly, Google Enrollment DB Source
GiveDirectly, Google transfer schedule Source
GiveDirectly, Google transfer schedule, December 2013 Source
GiveDirectly, Google transfer schedule, July 2013 Source
GiveDirectly, Google verification, September 21, 2013 Source
GiveDirectly, Government cash transfers follow-up Unpublished
GiveDirectly, GW Q&A, April 26, 2013 Source
GiveDirectly, GW scratch sheet Source
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GiveDirectly, How it works 2014 Source (archive)
GiveDirectly, Ideal budget overview, November 7, 2013 Source
GiveDirectly, Income and expense. Unpublished
GiveDirectly, Kanyamutamu, Uganda Enrollment database Source
GiveDirectly, Kawo, Uganda Enrollment database Source
GiveDirectly, Kenya 1.2M enrollment database Source
GiveDirectly, Kenya 2M census results, July 8, 2013 Source
GiveDirectly, Kenya 2M Enrollment database, September 23, 2013 Source
GiveDirectly, Kenya 2M transfer schedule, November 2013 Source
GiveDirectly, Kenya backcheck template, September 3, 2013 Source
GiveDirectly, Kenya census template, July 8, 2013 Source
GiveDirectly, Kenya hotline log, July 24, 2013 Unpublished
GiveDirectly, Kenya registration template, July 22, 2013 Source
GiveDirectly, Kenya verification template, August 5, 2013 Source
GiveDirectly, Kosile, Uganda Enrollment database Source
GiveDirectly, M-PESA transfer history Source
GiveDirectly, Name collection instrument Source
GiveDirectly, Nike Enrollment Database Source
GiveDirectly, Nike instrument Source
GiveDirectly, Nike transfer schedule, August 2013 Source
GiveDirectly, Nike transfer schedule, December 2013 Source
GiveDirectly, Nike verification (combined), May 18, 2013 Source
GiveDirectly, Nike verification (final), September 24, 2013 Source
GiveDirectly, Nike verification (short version), June 20, 2013 Source
GiveDirectly, Notes on verification data (November 17, 2011) Source
GiveDirectly, Notes to financial statements. Unpublished
GiveDirectly, Offering Memorandum (January 2012) Unpublished
GiveDirectly, Operating efficiency as of 31 August 2012 Source
GiveDirectly, Operational process overview Source
GiveDirectly, Overview of targeting process Source
GiveDirectly, Overview of update documents Source
GiveDirectly, Post-transfer audit Source
GiveDirectly, Rarieda Top-up Verification (short) Source
GiveDirectly, Rarieda transfer schedule, August 2013 Source
GiveDirectly, Rarieda verification (top ups), May 26, 2013 Source
GiveDirectly, Rarieda verification stats Source
GiveDirectly, RCT Enrollment DB Source
GiveDirectly, RCT mid-line results overview Unpublished
GiveDirectly, RCT midline variables Unpublished
GiveDirectly, Room for more funding summary Source
GiveDirectly, Sample scorecard Source
GiveDirectly, Saturation analysis Source
GiveDirectly, Set-up and domestic expenses, October 2, 2013 Source
GiveDirectly, Siaya enrollment database Source
GiveDirectly, Siaya poverty data by location Source
GiveDirectly, Siaya transfer schedule, June 2013 Source
GiveDirectly, Siaya verification stats Source
GiveDirectly, Siaya verification, June 15, 2013 Source
GiveDirectly, Siaya village index Source
GiveDirectly, Survey for randomized controlled trial Source
GiveDirectly, Team Source (archive)
GiveDirectly, Uganda backcheck template Source
GiveDirectly, Uganda census template Source
GiveDirectly, Uganda monthly forecast, November 18, 2013 Source
GiveDirectly, Uganda name collection template Source
GiveDirectly, Uganda targeting data, July 22, 2013 Source
GiveDirectly, Uganda transfer schedule Unpublished
GiveDirectly, Ugunja-GiveDirectly conditions Source
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GiveDirectly, Updated data (March 31, 2012) Source
GiveDirectly, Values Source (archive)
GiveDirectly, Verification data (November 17, 2011) Source
GiveDirectly, Verification template (November 7, 2011) Source
GiveDirectly, Verification template (October 1, 2012) Source
GiveDirectly, Village targeting regression Source
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GiveWell Site visit notes Source
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GiveWell visit to M-PESA agent, November 8, 2012 Source
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GiveWell, GiveDirectly financials 2014 update Source
GiveWell, GiveDirectly financials tables Source
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Haushofer and Shapiro 2013 Policy Brief Source (archive)
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Lydia Tala, GiveDirectly Field Assistant, conversation with GiveWell, November 7, 2012 Unpublished
Paul Niehaus and Jeremy Shapiro, GiveDirectly founders, phone conversation with GiveWell, October 6, 2012 Source
Paul Niehaus, GiveDirectly Founder, conversation with GiveWell, April 1, 2012 Unpublished
Paul Niehaus, GiveDirectly Founder, conversation with GiveWell, November 5, 2012 Unpublished
Paul Niehaus, GiveDirectly Founder, conversation with GiveWell, October 22 2012 Unpublished
Paul Niehaus, GiveDirectly Founder, email to GiveWell, April 23, 2012 Unpublished
Paul Niehaus, GiveDirectly Founder, email to GiveWell, November 20, 2012 Unpublished
Paul Niehaus, GiveDirectly Founder, email to GiveWell, November 24, 2012 Unpublished
Piali Mukhopadhyay, COO, International, GiveDirectly, conversation with GiveWell, November 7, 2012 Unpublished
Piali Mukhopadhyay, COO, International, GiveDirectly, conversation with GiveWell, November 8, 2012 Unpublished
Piali Mukhopadhyay, COO, International, GiveDirectly, email to GiveWell, January 25, 2012 Unpublished
Piali Mukhopadhyay, COO, International, GiveDirectly, email to GiveWell, November 23, 2012 Unpublished