GiveDirectly - 2013 Review

We have published a more recent review of this organization. See our most recent report on GiveDirectly.

GiveDirectly is one of our top-rated charities, and an organization that we feel offers donors an outstanding opportunity to accomplish good with their donations.

More information:

Published: November 2013


What do they do? GiveDirectly ( 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 two randomized controlled trials of its impact (one ongoing), and has taken the unusual step of making the details of these studies public before data is collected (more).

What do you get for your dollar? GiveDirectly aims to deliver about 90% of campaign expenses directly to recipients. Its current campaigns in Kenya hit this target (more).

Is there room for more funding? We believe that GiveDirectly has significant room for more funding and would like to see GiveDirectly receive at least $10 million over 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 intended targets (more), and 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 been accumulating more evidence on this question in addition to a recently released RCT studying 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 successfully scaled up its activities over the past year (including expanding into a second country) enabling it to transfer a few million dollars in 2013. It now hopes to scale up further. We are optimistic about its ability to do so, but note that there are substantial risks associated with scaling and whether GiveDirectly can continue to scale successfully is an open question.
  • The size, schedule, and targeting strategy of GiveDirectly's transfers have not been fully tested against possible alternatives. A major benefit we see in GiveDirectly is the opportunity it has to test different approaches to cash transfers and gather data relevant to answering questions about low-income households' preferences. We have yet to see GiveDirectly execute on this to the extent we hope it eventually will (more).
  • GiveDirectly is a relatively young organization and its leadership consists in part of directors who work part-time and unpaid; this may make the organization less likely to reach its maximum potential.

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 investigation process

To date, our investigation process has consisted of

  • Conversations with GiveDirectly staff: Paul Niehaus (Co-founder, President), Rohit Wanchoo (Co-founder, Director), Michael Faye (Co-founder, Director), and Jeremy Shapiro (Co-founder, former Director), Piali Mukhopadhyay (COO, International), Joy Sun (COO, Domestic), and Carolina Toth (Field 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 (including Lydia Tala, now serving as Senior Field Officer, and one of 8 staff members responsible for enrolling new recipients).

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 the developing world 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 though it continues to experiment with other grant size/duration approaches (more). 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; (b) determining eligibility based on pre-set criteria, such as building materials of homes and demographic criteria (more). It aims to deliver about 90 cents directly to recipients of every $1.00 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 one year.11

In Uganda, GiveDirectly's planned 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 indicated that it may be interested in experimenting with the frequency and sizing of transfers, possibly by giving recipients the ability to choose their transfer schedules.14

Status of transfer campaigns

As of October 2013, it has provided partial or full cash transfers to more than 4000 households in western Kenya and eastern Uganda, and is continuing to transfer funds to additional households in both places.15

GiveDirectly's work to-date can be grouped into 6 campaigns:

  • Rarieda: this campaign includes cash transfers to the treatment groups of a randomized controlled trial (RCT) of the effects of unconditional cash transfers; now that RCT data collection is complete, GiveDirectly is providing "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 includes villages in GiveDirectly's informal study of different targeting strategies (more); first transfers were sent in October 2013.
  • Uganda: this campaign includes GiveDirectly's transfers to households in Uganda, funded by the Google Global Impact Award; first transfers were sent in June 2013 as part of the initial pilot.

Details of each of these transfer campaigns is provided in this table:16

Cohort Number of recipients Timeline for sending transfers Size of transfers17 Current status
Rarieda, group A18 34819 June 2011 - April 2014 $300 + $700 Recipients who had been in the $300 treatment group for the RCT later received "top ups" of $700 sent in two installments, after the RCT data collection was complete; 98.8% of total funds were transferred by July 201320
Rarieda, group B21 13722 June 2011 - April 2014 $1,000 95% of total funds were transferred by July 2013
Rarieda, control group 50523 Not yet planned24 $100025 No transfers have been sent as of October 201326
Siaya27 199 July 2012-May 2013 (with one recipient outstanding, to receive completed transfer by December 2013) $1,000 99.5% of total funds were transferred by May 2013
Nike, group A28 40 September 2012 - September 2013 $500 100.0% of total funds were transferred by November 2013
Nike, group B29 37 September 2012 - April 2014 $1,000 98.6% of total funds were transferred by November 2013
Google30 86131 January 2013 - August 2014 $1,000 95.3% of total funds were transferred by November 2013
Kenya 2M32 2022 October 2013 - July 2014 $1,000 7.7% of total funds were transferred by October 2013
Uganda33 96034 June 2013 - September 2014 $1,000 19.9% of total funds were transferred as of October 2013

We have also tracked the total amounts that GiveDirectly has transferred to recipients or plans to transfer in each month for each campaign.35

Expenses to date

Based on the financial information that GiveDirectly provided, we calculate that in total it has incurred costs of $3,101,810 through the end of FY 2013 (August 31, 2013). This amount includes all spending on transfer campaigns and liabilities (future transfers committed to enrolled recipients and future wages for staff), as well as the costs of initially setting up in each country and of outreach/fundraising efforts.36 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.37 The costs that are not included in GiveDirectly's total spending are the value of its unpaid President's time (about 40 hours/week),38 and time spent by other board members (about 45 hours/week).39

Of GiveDirectly's total spending through FY 2013, $2,663,269 (or 85.9%) was transferred directly to recipients.40 Including projected future costs for current campaigns, the ratio of direct grants to total spending rises to 87.1%.41

GiveDirectly calculates its "efficiency ratio" by the amount transferred directly to recipients out of total spending on transfer campaigns. GiveDirectly explains that it excludes set-up and outreach costs from total spending in this calculation because they are one-time costs (e.g., NGO registration) that can be reused indefinitely, as opposed to marginal costs.42 Under this condition, GiveDirectly's efficiency ratio in Kenya is 89.7% based on incurred costs and 90.6% including projected future costs for ongoing campaigns;43 in Uganda, GiveDirectly's efficiency ratio is 92.5% based on incurred costs and 87.6% including projected future costs.44

Below we break down GiveDirectly's total spending through the end of FY 2013 (August 31, 2013).

Cost Category Incurred Future Total Cost (incurred + future) % of Incurred Costs % of Total Costs
Direct Grants To Households45 $2,663,269 $2,001,412 $4,664,681 85.9% 87.1%
Enrollment Costs46 $84,943 $11,766 $96,709 2.7% 1.8%
Transfer Costs47 $67,920 $62,044 $129,963 2.2% 2.4%
Follow-up Costs48 $8,774 $39,153 $47,927 0.3% 0.9%
Core Operations Costs49 $117,787 $102,574 $220,361 3.8% 4.1%
Core Operations - General Costs50 $2,319 $34,687 $37,006 0.1% 0.7%
Set-up Costs51 $103,101 Do not have estimates $103,101 3.3% 1.9%
Outreach Costs52 $53,698 Do not have estimates $53,698 1.7% 1.0%
Total $3,101,810 $2,251,637 $5,353,447 100.0% 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.53 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 will be overseeing the work in both places.54
  2. Selection of a region. GiveDirectly told us that it initially chose to work in western Kenya and eastern Uganda based on poverty statistics.55 We have reviewed the poverty data for Uganda; we have not reviewed poverty data across districts for Kenya.
  3. Selection of counties. For Kenya, GiveDirectly told us that its executive staff56 uses data on poverty, population density, security, and presence of poverty-focused NGOs (with the goal of avoiding overlapping with these) to select counties;57 we have reviewed poverty data for divisions within Siaya district but have not reviewed other data used to select counties in Kenya.58 For Uganda, GiveDirectly told us that it chose a county to target initially based on poverty statistics, logistical factors and security considerations;59 we have reviewed the poverty data for Uganda.
  4. Selection of villages. GiveDirectly states that it uses a predictive model of income to select villages.60 GiveDirectly has shared the full details of its village selection process used in Kenya, including data for each village and the method for weighting the different factors used to select villages;61 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 yet 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.62 For details on how GiveDirectly has targeted villages historically, see this footnote.63
  5. Obtaining permission from local officials. Throughout the process of planning and implementing a campaign, GiveDirectly meets with local officials to obtain permission to conduct the campaign.64
  6. Selection of households. GiveDirectly has field staff visit the village to create a census of all households (this step was different in earlier campaigns).65 In conducting the census, field staff collect data such as GPS coordinates and note which households are eligible for transfers66 (the criterion for eligibility in a standard campaign is that the home is made of mud and thatch).67 We have reviewed the census data collected for eligible recipients from all campaigns for which GiveDirectly conducted a census,68 as well as full census data for the Kenya 2M campaign.69
  7. Enrollment and eligibility checks. GiveDirectly has a separate set of field staff visit households marked as eligible in the census and enroll them. In Kenya, enrollment 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,70 and collecting other data including GPS coordinates which can be checked against the initial data set (with discrepancies being flagged for audit).71 Recipients are given the option of purchasing a cell phone from GiveDirectly at the time of enrollment, the cost of which is removed from the recipient's transfer.72 In Uganda, a similar enrollment process was carried out, and in addition, GiveDirectly helped recipients obtain ID cards and arranged for mobile money agents to visit villages to register recipients in the mobile money system.73 Enrollment was different in early transfer campaigns.74

    We have reviewed (and made public) data collected during enrollment, with deletions to preserve anonymity.75 GiveDirectly has told us that in the above enrollment and eligibility checks and the further checks and audits described below, it errs on the side of excluding rather than including a recipient if there is reason to believe that the potential recipient does not meet GiveDirectly's eligibility criteria.76

  8. Further checks and audits. GiveDirectly performs a series of checks and audits to confirm eligibility:
    1. GiveDirectly staff "check that the data collected in enrollment and the village census match, that GPS coordinates show an eligible house, that we have a valid photograph showing recipients in front of an eligible house, etc."77 Discrepancies are flagged for audit.78 We have reviewed (and made public) data from these checks, with deletions to preserve anonymity.79 Note that in enrollment rounds completed before November 2012, GiveDirectly did not use all of these steps as "hard checks." Recipients were still visited by two independent field teams who verified eligibility, but potential recipients could remain eligible even if they failed one of these steps.80
    2. GiveDirectly retains a third set of staff to conduct "back-checks," re-verifying eligibility and asking whether households were asked to pay a bribe to enroll.81 Discrepancies are flagged for follow-up phone calls or audits.82 We have reviewed (and made public) data from these checks, with deletions to preserve anonymity.83 GiveDirectly aims to identify all households and does not disqualify a household merely because a potential recipient is not home.84
    3. GiveDirectly "audits 15% of recipients including any who were flagged in any of the checks and including some of the work done by each field worker."85 We have reviewed (and made public) data from these checks, with deletions to preserve anonymity.86
  9. Communications with recipients and other village members
    1. A village meeting is held (first implemented in the Google campaign87 ) "to answer questions anyone may have about the program, clarify that [GiveDirectly is not] affiliated with a political party, etc." 88
    2. GiveDirectly staff make multiple phone calls to recipients. Before a transfer is sent, staff "call recipients to check that they know what they’re doing and ask if they had any problems / had to pay anyone to enroll."89 This includes verifying that their SIM card number matches the number they provided during enrollment.90 Staff make another call soon after GiveDirectly transfers an initial, small installment of funds (approximately 5-10% of the total transfer) to recipients.91 This is different from early transfer campaigns.92
    3. GiveDirectly staff call or visit recipients again 1-2 weeks after each main installment of the transfer is sent to conduct follow-up surveys that confirm the transfer was received, ask how recipients spent their funds, and ask again whether they experienced any problems.93 In Kenya, recipients are called twice for full follow-up surveys (once after each lump sum). In Uganda, GiveDirectly plans to conduct these follow-up surveys 3 times over the course of the ten monthly transfers, and is experimenting with conducting them in-person rather than over the phone,94 with shorter calls on off months to confirm that the transfer was received and ask if the recipient experienced any problems.95 We have reviewed and made public data from these calls for ongoing transfer campaigns in Kenya.96
    4. GiveDirectly maintains a phone "hotline" for recipients to call if they have any questions about the transfers or issues in obtaining funds.97 We have reviewed the records of calls made to GiveDirectly's Kenya hotline from May 2012 – October 2013.98

Key differences in some past distributions 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); (b) the lack of a village meeting.

In early transfer campaigns, GiveDirectly used a somewhat informal "preponderance of evidence" approach to determining eligibility: while it has conducted all the checks above, it has been open to declaring people eligible despite, e.g., the lack of a photo or GPS match.99 We discuss the details of how the "preponderance of evidence approach" was implemented below. In more recent transfer campaigns, GiveDirectly has more strictly adhered to eligibility checks. If any given check raises a potential issue, the household is flagged for audit.100 We have reviewed data from these checks and audits for all of GiveDirectly's ongoing campaigns.101

GiveDirectly implemented further changes to its process in its most recent campaign in Kenya (referred to in this review as Kenya 2M). Process changes included:102

  • Created Senior Field Officer layer of management to improve quality control
  • Used Google Earth to generate data on villages that is used for village selection
  • Signed memorandums of understanding (MOUs) with local officials to increase buy-in and formalize relationship
  • Created a formal mechanism to capture complaints from community at enrollment stage103
  • Reduced the time spent on and the cost of photo/satellite image back check by using crowd-sourced labor
  • Automated staff timecards and outsourced payroll deductions processing

GiveDirectly said that it plans to implement similar changes in Uganda in future campaigns.104

Staff structure

GiveDirectly delivered its first cash transfers in 2011 (see table above). Starting in January 2011 it had one full-time staff member;105 in early 2013 it hired a second full-time staff member to serve as COO, Domestic;106 and by May 2013 it had added one full-time Field Director with plans to hire another.107

As of October 2013, GiveDirectly was still in the process of expanding its staff to build capacity for current and future transfer rounds. GiveDirectly plans to have the following field staff going forward:108

  • Chief Operating Officer (COO): Previously, the COO was directly managing transfers in the field; in the new organizational structure, her time will be spent on oversight and quality control of the entire operation. The COO oversees the Field Directors.

    Piali Mukhopadhyay is continuing on as COO.

  • Field Directors (FDs): This is a new role as of mid-2013. FDs will be in charge of conducting audits and back-checks of enrollment data, as well as approving transfer schedules and rosters. FDs oversee Senior Field Officers.

    As of October 2013, GiveDirectly has hired one FD and is in the process of hiring a second.

  • Senior Field Officers (SFOs): This is a new role as of mid-2013. SFOs manage the logistics of transfer rounds and oversee Field Officers, providing coaching and feedback to them. Previously, this work has fallen on the COO, who was acting essentially as a FD in Kenya.

    GiveDirectly plans to have 2-3 SFOs per team of 30 Field Officers. It has hired three so far, all of whom were promoted from Field Officers; going forward, GiveDirectly plans to continue to hire from within its staff of Field Officers for this position.

  • Field Officers (FOs): FOs implement the steps required on the ground to enroll households and follow up with them. 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 pre-transfer stages: initial census, enrollment, and back checks. FOs are also hired to conduct follow-up surveys with recipients post-transfers.109

    GiveDirectly has hired all of the requisite FOs for its current campaigns.

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.
  • Does GiveDirectly have a reasonable and effective process for selecting recipients and getting cash to them? We believe GiveDirectly's process is a reasonable way to identify low-income people, and it appears that the process has been relatively effective so far.
  • Are the people meeting GiveDirectly's criteria low-income? The evidence we have suggests that they are.
  • 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 amongst 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, though donors' intuitive reactions to it may vary widely.

Does GiveDirectly have a reasonable and effective process for selecting recipients and getting cash to them?

GiveDirectly's process is described above. We find it to be generally reasonable, in that

  • We would guess that most people living in mud and thatch homes are low-income, particularly in villages in sub-Saharan Africa that available data has identified as high-poverty. (Our site visit in late 2012 was consistent with this.110 )
  • The process involves multiple visits by different staff to each recipient home, as well as spot-checks and remote checks by higher-level staff, in order to confirm that recipients meet criteria. (The idea being that if someone tries to temporarily occupy a mud and thatch home in order to be enrolled, they are unlikely to be sure of being present for future re-checks.)
  • The process also involves some procedures for catching other issues, in particular the surveys administered periodically after transfer installments are sent.

We have examined data collected by GiveDirectly from its enrollment process, back-checks, remote checks and audits for all ongoing transfer campaigns.111 We have also examined the results of its post-cash-transfer phone surveys.112

As an example, the enrollment and back-check file for Siaya lists 226 individuals who began the enrollment process; 27 of them were ultimately deemed ineligible and transfers were made to 199 of them.

GiveDirectly's President told us that ineligibility in this campaign was determined by a "preponderance of the evidence."113 We have not seen documentation of GiveDirectly's process in reaching these conclusions. GiveDirectly told us that in most cases where a household was deemed ineligible, GiveDirectly came to believe during its back-check based on information from other villagers that the ineligible individuals either did not live in the village GiveDirectly was targeting or lived in metal-roof houses and had tried to game the system by pretending to live in thatch-roof houses.114 (GiveDirectly believes many of these ineligible households were introduced because GiveDirectly allowed the village elder to lead staffers to households, enabling the village elder to help his/her friends or family. For this reason, GiveDirectly aims to rely on a village member rather than the village elder as a guide, when possible,115 although this method still seems vulnerable to manipulation.) The file also shows that the 199 eligible households were checked and met GiveDirectly's eligibility criteria.116 GiveDirectly now strictly adheres to all eligibility checks; if any given check raises a potential issue, the household is flagged for audit.117

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,118 as well as its own summary of the data collected as of March 2012:119

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.120

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.121 This data shows that "20% [sic122 ] 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."123 Other results related to food consumption are measured as well which are, in our view, consistent with the notion that recipients are extremely poor.

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 that had metal roofs and cement walls and floors and did not qualify for GiveDirectly's program). For details on how homes we visited were selected, see this footnote.124

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 but just 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 say they use the milk from the cows for themselves and also sell it and many mentioned being able to sell their cows in the future when they need money for kids to go to 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.

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

Findings from the RCT

Effects of receiving cash transfers

It is difficult to interpret the size of the main treatment effects reported in the RCT of GiveDirectly's program in Rarieda, because embedded within the “main treatment” were two different transfer sizes ($287 and $1,085), which we would expect to have very different impacts and to be spent in very different ways. The mean transfer size was about $513, which is about half of the size of GiveDirectly’s standard transfer.125 We also note that we have reported transfer sizes in exchange-rate adjusted terms, but outcomes are reported in purchasing power parity (PPP) adjusted U.S. dollars.126

Except for where we explicitly state otherwise, all results mentioned in this intervention report are statistically significant at the 95% level.

How were GiveDirectly transfers 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.127 Their spending is broken down in more detail below.

  • Total non-land assets.128 Receipt of transfers increased households’ non-land assets by an average of $279.129 Households that received large transfers increased their total non-land assets by about $253 more than households that received small transfers.130 The largest categories of asset increases were livestock ($85), durable goods ($53; primarily furniture), and savings ($10).131 Transfers also increased the likelihood that a household had an iron roof by 23 percentage points.132 Recipients of large transfers were 23 percentage points more likely to have iron roofs at end-line than recipients of small transfers.133 The RCT estimated that iron roofs cost about $564 USD PPP and had a return on investment of between 7 and 14%, but the source of this data was unexplained.134
  • Business expenses. Treatment households spent about $13 per month more than control households on business expenses, which were primarily made up of non-durable expenses on non-agricultural businesses.135 There was no evidence that recipients of large transfers invested more in business expenses than recipients of small transfers.136
  • Health expenditures. Treatment households spent about $3 per month more than control households on health expenditures.137 There was no evidence that recipients of large transfers spent more on healthcare than recipients of small transfers.138 This spending was also included within the estimate of spending on consumption, below.
  • Education expenditures. The average treatment household with children spent about $19 more per month on education than the average control household with children although this estimate was imprecisely measured and not statistically different from zero.139 There was no evidence that households receiving large transfers spent more on education than households receiving small transfers.140 This spending was also included within the estimate of spending on consumption, below.
  • Consumption. Treatment households consumed about $36 more per month than control households.141 According to point estimates, recipients of large transfers spent about $20 per month more on consumption than recipients of small transfers but this difference was not statistically different from zero.142 Slightly more than half of this additional consumption was on food.143 This additional consumption also included increased spending on social expenditures and various other expenditures.144
  • Alcohol and tobacco. Treatment households did not increase their spending on alcohol or on tobacco.145

What were the overall effects of GiveDirectly?

  • Food security. At baseline, food security was low among participants.146 Program participants reported a 0.25 standard deviation increase in a food security index over controls.147 Some food security related variables improved more for recipients of large transfers, but the study did not have high enough power to determine whether there was an effect on the overall index.148
  • Health and education. The study did not detect an effect on indices of health and educational outcomes.149
  • Revenue and profits. Receipt of transfers lead to a $17 per month increase in total revenues but no detectable increase in profits.150 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. There is no evidence that large transfers had greater effects on revenue or profits.151

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

  • Psychological well-being. Treatment improved an index of psychological wellbeing by 0.20 standard deviations.152 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 .153 Recipients of large transfers measure 0.35 standard deviations higher on the well-being index than recipients of small transfers.154
  • Female empowerment. Control households in treatment villages measure 0.23 standard deviations higher on an index of female empowerment than control households in control villages.155 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.156 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 (e.g., Google data represents only the small initial transfer plus one lump sum, while Siaya data represents full transfers).157 We summarize the data below.

Percentage of recipients who reported spending in each category

Category Rarieda (top-ups only)158 Siaya159 Nike160 Google161
Food 52.4% 58.1% 100.0% 28.6%
Small household items (e.g., clothes, utensils) 32.0% 28.8% 96.4% 12.2%
Large household items (e.g., furniture, mattresses) 23.7% N/A 60.7% 2.7%
School 40.2% 32.3% 69.6% 15.0%
Farm business 22.8% 12.6% 71.4% 9.4%
Non-farm business 12.1% 23.2% 50.0% 6.0%
Debt 11.8% 4.0% 30.4% 1.4%
Buildings (labor and materials) 55.9% 89.4% 71.4% 76.8%
Land 2.1% 1.5% 7.1% 0.9%
Livestock 33.1% 47.5% 66.1% 18.6%
Medical 15.1% 12.1% 62.5% 5.5%
Savings 13.6% N/A 14.3% 1.9%
Major life events (e.g., dowry, funeral) 1.5% N/A 1.8% 0.3%
Other 1.2% 63.6% 3.6% 17.4%

Percentage of funds reported to be spent in each category

Category Rarieda (top-ups only)162 Siaya163 Nike164 Google165
Food 7.9% 4.0% 13.8% 2.2%
Small household items (e.g., clothes, utensils) 3.8% 1.6% 9.5% 1.3%
Large household items (e.g., furniture, mattresses) 6.9% N/A 8.2% 0.3%
School 7.5% 3.7% 9.3% 2.1%
Farm business 3.9% 1.3% 4.9% 1.5%
Non-farm business 5.9% 6.6% 4.5% 1.6%
Debt 1.1% 0.4% 1.1% 0.2%
Buildings (labor and materials) 37.5% 54.7% 33.0% 77.7%
Land 1.6% 0.7% 2.5% 1.0%
Livestock 17.5% 13.6% 8.3% 5.6%
Medical 1.4% 0.7% 2.1% 0.7%
Savings 3.9% N/A 2.3% 0.4%
Major life events (e.g., dowry, funeral) 0.6% N/A 0.3% 0.1%
Other 0.5% 12.6% 0.0% 5.3%

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.166 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, 2012167 ) 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 year168 ($175.13 based on the exchange rate as of November 15, 2012169 )).

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 villages170 or on instances of physical, sexual, or emotional violence in treatment households as compared to control households in treatment villages.171

    GiveDirectly surveys recipients (post-transfer) on the following questions:172

    • 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 sent us results from the follow-up surveys that have been conducted for four ongoing transfer campaigns. Below, we summarize the survey data for some of the questions included in these surveys. For a full list of follow-up survey questions, see GiveDirectly, Kenya verification template, August 5, 2013. 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.

    Question Rarieda (top-ups only)173 Siaya174 Nike175 Google176
    Did you have any trouble collecting this transfer? 1.7% 4.6% 0.0% 1.3%
    Do you have any regrets about how you used the transfer? 0.3% 2.1% 5.4% 0.4%
    Are you unhappy with the spending decisions someone else made? 0.3% 0.5% 0.0% 0.6%
    Have you heard complaints about GD in your community? 28.5% 63.6%177 21.8% 46.4%
    Has there been any shouting or angry arguments among people in your village about these transfers? 0.4% 5.7% 1.8% 2.0%
    Has there been any violence, theft, or other crime in your village related to these transfers? 0.7% 2.1% 1.8% 1.2%
    Did you and others in your household argue about what to do with the transfer? 0.6% 0.0% 0.0% 1.3%
    Has anyone told you that you need to pay them to collect your transfer? 0.0% 0.0% 3.6% 0.0%
    Have you felt threatened by any one since you were visited by Give Directly? 0.3% 2.6% 3.6% 0.1%
    Has the village elder approached you for any money since you were visited by Give Directly? 5.9% 3.1% 7.3% 0.3%
    Have you heard of any other recipients in your village being asked to pay money? 5.0% 8.8% 7.3% 0.1%
    Did anyone ask you for money to check your M-Pesa balance? 0.0% - 0.0% 0.1%
    Did the M-Pesa agent ask you for a bribe? 0.0% 1.0% 0.0% 0.3%

    Note that GiveDirectly surveys only cash recipients, not non-recipients.

    We have also reviewed the records of calls made to GiveDirectly's Kenya hotline from May 2012 – October 2013, which provide anecdotal evidence of tension and conflict caused by the cash transfers, according to recipient reports. Reported issues include marital disputes and pressure from village elders to give them some of the funds from the transfer. Of the 78 issues tracked from July – October 2013, 9 involved tension, conflict or theft.178

    In its Kenya 2M campaign, GiveDirectly is experimenting with providing transfers to most of the households in a village, as opposed to targeting only mud and thatch households (more). GiveDirectly is conducting its standard follow-up phone surveys and will use that data to understand the effects of different targeting strategies on tension and conflict in the village.179 As of October 2013, GiveDirectly reported that preliminary survey data from the Kenya 2M campaign did not show a substantial difference in tension and conflict between villages with different targeting strategies.180 We have not yet reviewed this data.

    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.

  • 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)181 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.182 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.183 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:184

    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.185 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 documents the steps that GiveDirectly has taken to follow up on recipients' concerns; we have reviewed these and find them to be reasonable and appropriate. 186

    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).187 These challenges and 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.188

  • 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. GiveDirectly's future evaluation plans (discussed below) may include a study that would provide information on the matter.
  • 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.

Do the funds GiveDirectly transfers fully reach recipients?

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 user-specified M-PESA pin code to the M-PESA agent.189 Users enter the amount they want to withdraw on their own phone, and after each transaction, they can see their remaining balance,190 minimizing the ability of agents to defraud clients of funds.

Nonetheless, Lydia Tala, the Senior Field Officer who was 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.191 GiveDirectly told us that it recognizes this issue and maintains a hotline to provide recipients with assistance in navigating the M-PESA system.192

The records of calls to GiveDirectly's Kenya hotline indicate that some recipients have had trouble using the M-PESA system, which has caused a delay in their receipt of funds. In some cases, recipients needed to travel to Kisumu, a nearby city, to get help from customer service at Safaricom (the company that owns M-PESA) before they were able to obtain their cash transfers.193

In Uganda, GiveDirectly is working with two different mobile money providers (745 recipients were assigned to the primary provider, 215 recipients to the secondary provider). The primary mobile money system sends recipients SMS notifications about their transactions, but recipients cannot check their balances or conduct transactions using only their phones; these actions require visiting a mobile money agent. GiveDirectly told us that this mobile money provider plans to build in more mobile functionality over time.194

GiveDirectly has told us that the network of mobile money agents is not as ubiquitous in Uganda as it is in Kenya, especially for the primary provider, so recipients in Uganda have to travel farther to reach an agent.195 In order to address this, GiveDirectly arranged to have agents from the primary provider visit villages to conduct transactions with recipients, rather than have recipients travel to agents.196 GiveDirectly told us that it hopes providing cash transfers will create enough demand for both mobile money services that they will deploy more agents to the areas in which the transfers are being sent, making it more convenient for recipients to cash out on any given day.197

One reason that GiveDirectly designed the transfer schedule in Uganda as monthly transfers instead of lump-sums was to make it more manageable for the mobile money provider.198 GiveDirectly told us that it has also given the mobile money provider advance notice before sending the funds so that agents could be prepared.199

GiveDirectly reports that overall, recipients in Uganda have not had a problem withdrawing funds, but that there have been a few delays of up to a few hours for recipients waiting to withdraw funds, due to agents needing to replenish their cash stock.200

Does GiveDirectly divert skilled labor away from other areas?

If it were to continue moving funds to recipients at the rate of $8 million per year, GiveDirectly has said that it would want a field staff for each country of about 30 Field Officers, two Senior Field Officers, and one Field Director.201

GiveDirectly recruits FOs by referrals from peer organizations, postings at universities, and running 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.202 Regarding its field staff in Kenya, GiveDirectly explained that successful candidates generally have a college education203 and are paid approximately $12 per day, in addition to expenses for travel and lodging while working.204 GiveDirectly reports that there is 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.205 Based on GiveDirectly's current staffing situation, we do not see diversion of skilled labor as a serious concern.

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,206 after which point recipients become ineligible.207 It gives the following rationale for the size of its transfers:208

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.

    Strong evidence that the cash transfers do not lead to conflict and jealousy would reduce the weight we put on this concern, though as discussed above, it currently appears that GiveDirectly's cash transfers do cause some tension.

  • 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.209 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.210 But psychologically, the impact of GiveDirectly's transfers may be very different from those of government programs.

Our reservations about GiveDirectly's targeting strategy

We have reservations about the approach of targeting people based on the materials their houses are made of. GiveDirectly stated that it also views this as an open question, which is why it is experimenting actively with other targeting methods (e.g., village saturation).211

  • As stated 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).
  • As discussed above, cash transfers may lead to tension between recipients and non-recipients; making transfers to all people living in a village might mitigate this issue. (GiveDirectly is experimenting with making transfers to most of the households in a village in its most recent campaign in Kenya212 ).
  • We think it's possible that the difference between people in thatched-roof homes and people in iron-sheet-roofed homes comes down to fortune/luck (i.e., that the latter people have been more fortunate and thus have been 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:213
    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.

    We expect to learn more about the different spending choices of recipients in households with thatch roofs versus metal roofs from GiveDirectly’s most recent campaign in Kenya (referred to in this review as Kenya 2M).

Evaluation and experimentation

Results of the RCT of GiveDirectly's Rarieda campaign

Innovations for Poverty Action conducted a randomized controlled trial (RCT) of GiveDirectly's program in which eligible households were selected by lottery to receive cash transfers. These transfers were made in Rarieda (more information above) in 2011-12. GiveDirectly publicly provided the plan for collecting and analyzing data to determine the impact of these transfers. The RCT has now been published; we discuss it in detail here.

Other experimentation and evaluation

Cash transfers to girls
GiveDirectly's Nike transfer campaign will also be evaluated in a randomized controlled trial. These transfers target young women aged 18-19 and are being funded by the Nike Foundation. GiveDirectly has shared the survey instrument it plans to use with us.214 GiveDirectly has not yet shared an analysis plan for the Nike study, as it did for the Rarieda RCT.

Extended data collection by phone
Innovations for Poverty Action 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.215

Targeting strategies
GiveDirectly is also conducting an informal study in which it randomized villages into one of three groups:

  1. A control group, in which no households will receive transfers
  2. A treatment group with standard targeting (only mud and thatch-roof households will receive transfers)
  3. A treatment group in which most households in the village will receive transfers (all households with mud walls and thatch or metal roofs will receive transfers, but households with cement walls and metal roofs will not)216

GiveDirectly plans to collect standard follow-up data via phone surveys and use this data to assess how the different targeting strategies affect levels of tension and conflict in the villages.217 GiveDirectly has stated that with adequate funding it would be interested in expanding the number of villages in this study and using it to assess the comparative impacts of transfers on local economies.218

Behavioral economics
GiveDirectly has stated that it is interested in experimenting with other aspects of its process:

  • Frequency, timing, and sizing of transfer installments219
  • Messaging to recipients220
  • Decision-making supports (e.g., providing information on how other recipients have spent funds, providing a "sounding board" for recipients who are planning how they will use funds).221 GiveDirectly has said that it plans to implement decision-making supports in a campaign beginning in January 2014.222

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 88% in Uganda.223 GiveDirectly explains that it excludes set-up and outreach costs from total spending in this "efficiency" calculation because they are one-time costs (e.g., NGO registration) that can be reused indefinitely, as opposed to marginal costs.224 Data from GiveDirectly's distributions imply that it has been hitting this target. When all costs are considered, including set-up and outreach, cash grants make up 87.1% of expenses (more).225

Excluded from GiveDirectly's total costs is the unpaid time spent by its President and Directors, which GiveDirectly estimates at 85 hours per week.226

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 intervention conducted by our two other top charities, we have attempted to monetize some of the benefits of the latter, in particular the “developmental effects” of deworming.

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 based on limited evidence; 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, deworming is more cost-effective than cash transfers. However, we think there are plausible values for these assumptions that would permit any ordering of the three charities.

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 2013 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 2014

In October 2013, GiveDirectly provided the following statement regarding its room for more funding in FY 2014:227

We have installed capacity to move additional $9.4M in FY14 and plan to expand further.

We have uncommitted capacity to move $10M under the management of two Field Directors in Kenya and Uganda

  • Each [Field Director] FD has capacity to move $8M/year to new recipients; $1M increase from last estimate driven by recent process and tech improvements
  • Kenya FD has 10 months of uncommitted capacity in FY14, or $6.6M
  • New Uganda FD is scheduled to begin in Jan and will have capacity of $3.3M through June (less 1 month training)
  • FD capacity projected to grow to $12M when new tech comes online

Note that the above statement refers only to GiveDirectly's room for more funding for transfer campaigns. GiveDirectly fundraises separately to cover costs of fixed investments, including the costs of outreach and technology improvements. Accordingly, GiveDirectly excluded fixed investments from the above projection.

In November 2013, GiveDirectly sent us documents outlining its ideal funding for calendar years 2014-2015 with a general breakdown of proposed uses of funds and potential staff expansion. In these documents, GiveDirectly suggests that it could productively use $14.6 million in 2014 and $26 million in 2015.228 For the purposes of updating our view in 2013, we focused primarily on GiveDirectly's room for more funding in 2014. We did not thoroughly review GiveDirectly's proposals for 2015. We do not know how GiveDirectly would adjust its proposed uses of funds if it were to receive less than its ideal amount of funding.

We have reasons to believe that GiveDirectly's estimate for its room for more funding in 2014 is reasonable:

  • GiveDirectly successfully expanded its staff capacity over the past year and expects to hire a second field director imminently (more).
  • GiveDirectly incurred costs and liabilities of $2 million over a 3-month period in 2013; it used this as the basis for estimating the pace at which one Field Director could move funds ($8 million/year).229
  • The total amounts that GiveDirectly has transferred to recipients each month has increased dramatically since its inception. In 2012, the average total amount transferred to recipients per month was $27,000, in the first ten months of 2013, the average total amount transferred per month was $148,000.230

However, there are also factors that could limit GiveDirectly's capacity in the coming year:

  • In Uganda, GiveDirectly has had to be more proactive in working with one of the mobile money providers to arrange registration and cash-out days, as the provider's agent network is currently very limited.231 If the provider does not continue to cooperate with GiveDirectly, this could cause unexpected delays in enrollment or the transferring and withdrawal of funds.
  • As of November 2013, GiveDirectly was finalizing new hire arrangements with a second Field Director who would start working in January 2014. When adding new staff, there is some uncertainty as to whether they will be successful in the role and how much training and management time will be required. Though GiveDirectly has expanded its staff this year, it is still a relatively young organization with minimal experience training new staff into the Field Director role. In addition, hiring itself can meet with unexpected delays. In July, GiveDirectly told us that it expected the second FD to be hired by October, and now that timeline has been pushed back to January.232
  • In October 2013, GiveDirectly told us that it was currently in conversation with 8 potential donors who were considering gifts of $1 - $5+ million, though GiveDirectly was not able to predict whether or when any of these donations might come through.233 Some of these potential donations would go to support projects in Kenya, for which GiveDirectly would likely re-assign its current staff, thereby taking up some of its future capacity and room for more funding. Other projects being considered for funding by potential donors would be located in countries that are new for GiveDirectly, so it would likely increase its staff capacity for these projects, and its projected room for more funding would remain largely the same.234 However, we do not have a well-grounded estimate of how much unrestricted funding GiveDirectly is likely to receive, and were it to receive more than we anticipate, this would reduce its room for more funding.

Our bottom line

It is our understanding that GiveDirectly expects to use the majority of funds it receives in 2014-2015 for cash transfers that are part of ongoing or future experiments/evaluations, though we do not yet know the specifics of these studies.235

Based on our understanding of GiveDirectly's future plans, we would like to see GiveDirectly receive at least $10 million over FY 2014 (September 1, 2013 - August 31, 2014) to maintain its rapid pace of growth (roughly 2x what it received the year before). GiveDirectly has said it could receive and move up to approximately $40 million during 2014 and 2015.

Given GiveDirectly's track record over the past year of successfully scaling its operations, we believe it would not be unreasonable for donors to provide sufficient funding for GiveDirectly to scale as quickly as it can. Nevertheless, we remain cautious about recommending that GiveDirectly receive funding that would represent a large multiple of what it has previously received.

For follow-up on our projection of GiveDirectly's room for more funding in 2013 and its actual use of funds, see this footnote.236

Unrestricted vs. restricted funds

GiveDirectly has stated to us that by default, it intends to use all donations from individual donors as restricted funds for cash transfers of the same model as is standard in each country (in terms of size, structure and targeting), aiming to spend about 90% of such donations directly on transfers. However, GiveDirectly has also stated that it is interested in providing cash transfers in ways that differ from standard protocols in order to continue experimenting and learning, as discussed above. In the past, GiveDirectly has funded these more experimental projects with grants from larger donors and unrestricted funds from GiveWell donors.

GiveDirectly told us that it is also aiming to build capacity to provide cash transfers at a much larger scale, so that it could act in the future as an implementing organization for government-funded cash transfer programs in developing countries. Towards this goal, GiveDirectly is seeking funding to expand its domestic team, in order to execute a strategy for entering institutional markets, and to improve its technological capabilities, in order to be able to serve these markets.237 GiveDirectly has thus far been seeking funding for its capacity building from larger donors, but it could potentially use unrestricted funds from GiveWell donors for this purpose as well. We have not assessed the likely impacts of GiveDirectly serving institutional markets and have not vetted its plans to build capacity for this work, so we do not have a view on how it compares to GiveDirectly independently delivering cash transfers.

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). Any donations made directly via GiveDirectly’s website will continue to be directed to transfers using its standard process.

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.238

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.
  • Track record: Although it is relatively young, we feel that GiveDirectly's first two years have gone well: GiveDirectly has successfully accomplished its goal of transferring cash to extremely low-income people at roughly a 90% ratio.
  • 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).

However, we continue to see potential room for improvement, particularly related to the fact that Paul Niehaus, the President, spends the majority of his (unpaid) hours fundraising for GiveDirectly. We think that there is substantial potential for GiveDirectly to experiment with different approaches to its intervention, and that more of the President's attention would be beneficial for this.

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


Document Source
Conversation with Carolina Toth, Field Director, GiveDirectly, October 24, 2013 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
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, 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, 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, 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, Financials Source (archive)
GiveDirectly, Follow-up tracker, July 2013 Source
GiveDirectly, FY 2012 Form 990 Source
GiveDirectly, GD – GiveWell update, October 16, 2013 Source
GiveDirectly, GD – GW update, July 17, 2013 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, GW Q&A, April 26, 2013 Source
GiveDirectly, How it works 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 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, 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, Update on process changes, August 28, 2013 Source
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
GiveWell Household size analysis Source
GiveWell Site visit notes Source
GiveWell visit to M-PESA agent, November 8, 2012 Source
GiveWell, Amounts transferred by month by GiveDirectly Source
GiveWell, GiveDirectly financials tables Source
GiveWell, KES exchange rates, monthly Source
GiveWell, Uganda payments Source
GiveWell, UGX exchange rates, monthly Source
Johannes Haushofer and Jeremy Shapiro, Policy Brief: Impacts of Unconditional Cash Transfers, October 24, 2013 Source (archive)
Johannes Haushofer and Jeremy Shapiro, Welfare Effects of Unconditional Cash Transfers: Pre-Analysis Plan, June 27, 2013 Source (archive)
Johannes Haushofer and Paul Niehaus, DIL Demonstration Proposal Source
Lydia Tala, GiveDirectly Field Assistant, conversation with GiveWell, November 6, 2012 Unpublished
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