GiveDirectly - January 2017 Version

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

Published: November 2016

Summary

What do they do? GiveDirectly (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 (RCT) 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 has delivered directly to recipients is approximately 82% overall (more).

Is there room for more funding? We believe that GiveDirectly is highly likely to be constrained by funding next year. We expect GiveDirectly to have $19.8 million to spend on its standard cash transfer campaigns in its 2017 budget year. We estimate that if it received an additional $46 million (allowing it to commit $65.8 million) its chances of being constrained by funding would be reduced to 50%. (more).

GiveDirectly is recommended because of its:

• Focus on a program with a low burden of proof and a strong track record (more).
• Strong 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 (more).
• Room for more funding. We believe that GiveDirectly can use substantial additional funding productively (more).

Major open questions include:

• While GiveDirectly has one major RCT of its activities in Kenya, there is still limited evidence on the impact of the type of transfers (large, one-time transfers; and, in the future, unconditional long-term income transfers) that GiveDirectly generally provides, particularly the long-term impact of such transfers. There are currently several ongoing experimental evaluations of GiveDirectly's programs, including a long-term RCT.
• GiveDirectly chooses who should receive cash on a household-by-household basis, as opposed to simply giving cash transfers to everyone in a village. We have doubts about the efficiency of this strategy, given the difficulties of finding criteria that effectively target the poorest households, the large amount of staff time that goes into vetting each household, and the possible offsetting impact of conflict and jealousy. GiveDirectly will soon test giving cash to every recipient in a village in its basic income guarantee program.
• We believe GiveDirectly's basic income guarantee program is likely less cost-effective than GiveDirectly's standard cash transfer campaigns. In 2016, GiveDirectly chose to fundraise extensively for the basic income study rather than for its standard cash transfers, leaving it with a large funding gap for standard cash transfer campaigns in 2017.

Our review process

To date, our review process has consisted of

• Conversations with GiveDirectly staff: Paul Niehaus (Director and President), Piali Mukhopadhyay (COO, International), Ian Bassin (COO, Domestic), Joy Sun (former COO, Domestic), Carolina Toth (Manager, Finance and Operations), and Stuart Skeates (former 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 2014, we retained a journalist to visit GiveDirectly in Kenya. We published his report on our blog.
• 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. We have also published a page with additional, detailed information on GiveDirectly to supplement some of the sections below.

What do they do?

Overview

GiveDirectly transfers cash to poor households in developing countries primarily via mobile phone-linked payment services. It has operated since 2009 and is currently active in Kenya, Uganda, and Rwanda (launched in October 2016).1 To date, GiveDirectly has primarily provided large, one-time transfers. It expects to soon start a basic income guarantee program, in which recipients will receive long-term (over two or twelve years in the initial study), ongoing cash transfers sufficient for basic needs (more).

GiveDirectly's work of providing cash transfers to poor households may also include:

• Experimentation: GiveDirectly runs or participates in studies on a) the impact of cash transfers and b) the costs and benefits of various program designs, with the goal of improving its own cash transfer program, improving other cash transfer programs, or encouraging the creation of new programs. (More)
• Partnership work: GiveDirectly pursues opportunities to partner with other organizations on cash transfer projects. Through these projects, GiveDirectly aims to encourage the evaluation of aid projects (often by using cash transfers as a standard of comparison) and ultimately influence funders to move resources from less effective aid programs to more effective ones. (More)

We discuss GiveDirectly's experimentation and partnership work to some extent below, but most of our review focuses on its direct impact, rather than the experimentation or policy impact its programs might have. We focus on direct impact because this is the main use of additional unrestricted donations, the ability to justify GiveDirectly's work based on its direct impact alone, and the difficulty of evaluating the impact of experimentation and partnership work.

In 2014, three members of GiveDirectly's board, including founders of the organization, started and are partial owners of a for-profit company, Segovia, which develops software that NGOs and developing-country governments can use to help implement their cash transfer programs. GiveDirectly pays for use of Segovia's software. We discuss the potential for conflicts of interest on our page with additional information about GiveDirectly.

Below, we discuss:

• The structure of GiveDirectly's transfers
• GiveDirectly's process for identifying recipient households and delivering cash transfers
• GiveDirectly's staff structure
• GiveDirectly's experimentation work
• GiveDirectly's work on partnerships

Standard cash transfer program

Grant size

GiveDirectly's standard model involves grants of approximately $1,000 (USD) delivered over several months in multiple payments. We estimate that the average family receives $288 per capita from GiveDirectly, which is 121% of baseline annual consumption per capita for recipients in Kenya. More on GiveDirectly's grant structure can be found on our page with additional information about GiveDirectly.

Process

GiveDirectly's typical process is as follows:

1. Local area selection: Select local region and then villages based largely on poverty rates.
2. Census: Conduct a census in each village to identify eligible households.
3. Registration: Send a separate team to register eligible households. This includes a) helping recipients set up a payment system to receive transfers (if they don't already have such a system in place), and b) collecting an additional round of data from the household that can be checked against the initial data from the census.
4. Back check: GiveDirectly sends a separate team of field staff to revisit every registered household to check for discrepancies in the data and evidence of staff misconduct. As of late 2016, GiveDirectly was experimenting with removing this step.
5. Audit: Some households are flagged for audit based on discrepancies collected in the previous steps and are revisited to determine whether they are eligible.
6. Transfers sent: GiveDirectly sends transfers to recipients via mobile money providers (and, in one campaign, via a bank) (more).
7. Follow up calls: GiveDirectly field staff make multiple phone calls and, for vulnerable recipients, in-person visits, to all recipients as transfers are being sent to ask various questions about recipients' experiences. In addition to the follow-up calls, GiveDirectly maintains a phone "hotline" for recipients to call if they have any questions about the transfers or issues in obtaining funds.

More detail on the above process can be found on our page with additional information about GiveDirectly.

We have reviewed (and made public) data collected during each step of the enrollment process for most of GiveDirectly's campaigns, with deletions to preserve anonymity.2

Staff structure

In its countries of operation, GiveDirectly's programs are overseen by a Chief Operating Officer International (COO-I), Country Directors (CDs) and Field Directors (FDs). Day-to-day operations are overseen by Field Managers and Associate Field Managers, who focus on quality control, management, training of Field Officers, logistics, and management of Field Officers. Field Officers (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 back checks. FOs are also hired to conduct audits and follow-up surveys with recipients post-transfers; some of the FOs hired for these roles may have previously worked on the census, registration, or back check phases.

More on GiveDirectly's staff structure can be found on our page with additional information about GiveDirectly.

Evaluation and experimentation

GiveDirectly's goals for experimentation include increasing the evidence base for cash transfers, improving recipient returns and welfare (both in GiveDirectly's program and others), and developing capabilities necessary to implement larger-scale programs or programs in new contexts.3 When choosing which evaluations to run, GiveDirectly also considers the potential impact on policymakers.4 GiveDirectly has told us that it has increased its experimentation to the point where it aims to enroll every recipient in a study or a campaign variation.5 See this spreadsheet for full list of GiveDirectly experimentation projects. Below we discuss a few selected projects that are of greatest interest to us.

RCT of GiveDirectly's Rarieda campaign

Innovations for Poverty Action (IPA) conducted a randomized controlled trial (RCT) of GiveDirectly's program in which eligible households were selected randomly to receive cash transfers.6 These transfers were made in Rarieda, Kenya in 2011-2012.7 GiveDirectly publicly provided the plan for collecting and analyzing data to determine the impact of these transfers. The RCT has been published; we discuss it in detail here.

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.8 GiveDirectly is working to conduct an RCT examining the macroeconomic effects of GiveDirectly's program in Kenya.9 Details of the study are in this footnote.10 Endline data collection was expected to be completed by the end of 2016; as of September 2016, midline data was still being analyzed.11

Basic income guarantee study

GiveDirectly is planning to begin a study of providing long-term, ongoing cash transfers sufficient for basic needs ("basic income guarantee") in 2017; it launched a pilot of the program in October 2016.12 The study is expected to include approximately 30,000 individuals and provide a basic income for either 2 or 12 years to every adult enrolled (more details in footnote).13 The income will likely be close to $0.75 per day.14 GiveDirectly may solicit input from recipients when determining the timing of the basic income transfers; GiveDirectly suspects most recipients will want to receive larger, more infrequent payments.15

GiveDirectly told us that recently policymakers, academics, and others have shown an increased interest in universal basic income experiments and GiveDirectly believes the project could have significant policy impact.16 We and GiveDirectly believe that the direct impact of the program (excluding any potential policy impact) is likely to be less cost-effective than GiveDirectly's standard campaign (more on our page with additional information about GiveDirectly).17

Partnership work

GiveDirectly has been exploring projects with a number of partners. The projects that GiveDirectly has partnered on or considered generally involve implementing cash transfers as part of a study funded by an institutional partner. GiveDirectly has also provided informal advice to those considering cash transfer programs. For a sample of smaller potential partnership projects that GiveDirectly has considered, see this footnote.18

In 2015 and 2016, GiveDirectly's President spent approximately 25% of his time on developing partnership projects.19

GiveDirectly has signed an agreement for one partnership project (in Rwanda; costing $4 million) and a memorandum of understanding (MOU) to consider additional projects (GiveDirectly and its partner may each spend up to $15 million). The projects will involve running studies to test other interventions against cash transfers (see our page with additional information on GiveDirectly for details).

Additionally, GiveDirectly has told us that it has made progress in conversations with several other institutional funders about potential projects.20 If all of the partnership projects GiveDirectly is discussing came through (which GiveDirectly believes is unlikely), GiveDirectly would need $23 to $30 million to support all of them.21

Although partnership projects are now taking up a significant portion of Dr. Niehaus' time, GiveDirectly does not believe this has negatively affected its core operations.22 Over the last year, GiveDirectly has hired two additional high-level staff to help with its partnership work: Ian Bassin and Jo Macrae.23

We discuss the question of whether GiveDirectly has a broader impact on the international aid sector through its experimentation and partnership work below.

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.
• How effective and well-founded are GiveDirectly's criteria? The evidence we have suggests that GiveDirectly targets low-income recipients. We have reservations about the approach of giving cash transfers to only those who meet GiveDirectly's criteria.
• 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, although we note that GiveDirectly has experienced difficulties recently with some people in certain geographic areas refusing to enroll in its program.
• Does GiveDirectly have an effective process for getting cash to recipients? GiveDirectly's process seems to have been 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.
• Are the size and structure of the cash transfers well-thought-through and appropriate? We find GiveDirectly's approach to be defensible, but we look forward to seeing the results of GiveDirectly's experimentation with different approaches in the future.
• Are there negative or other offsetting impacts? 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.
• Does GiveDirectly have a broader impact on the international aid sector? We have chosen not to look at this question in depth. We have not seen compelling evidence that GiveDirectly has significantly affected the behavior of funders or other organizations, although GiveDirectly has shared some qualitative evidence that we have not followed up on.

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

We discuss this question more extensively in 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 short-term poverty reduction is an outcome by definition, though donors' intuitive reactions to it may vary widely.

How effective and well-founded are GiveDirectly's eligibility criteria?

GiveDirectly currently uses two different sets of eligibility criteria for its standard campaigns:

• Assets and vulnerability status: This approach, which GiveDirectly is using in Kenya and Rwanda, uses an algorithm to determine eligibility; the algorithm uses a number of inputs related to household assets and the vulnerability of recipients.24 GiveDirectly developed this algorithm after testing a number of new potential criteria.25
• Housing materials: This is the approach that GiveDirectly is using in Uganda26 (and previously used in Kenya). Households are selected based on housing materials, enrolling households who live in a house made of organic materials (thatched roof, mud walls, and a mud floor) and excluding households with iron roofs, cement walls, or cement floors.27

As part of the first RCT of GiveDirectly's program, during which the housing materials selection criteria were used, researchers collected in-depth information on poverty levels of recipients and found that those selected were extremely poor on a number of measures, including that half of adults skip meals and average per capita daily consumption is $0.65 at nominal rates.28 In a later study, GiveDirectly found that recipients in Uganda had a slightly higher per capita daily consumption of $0.83.29

Concerns about GiveDirectly's targeting strategy

We believe that GiveDirectly is consistently targeting extremely poor households. On our page with additional information about GiveDirectly, we discuss a few concerns we have about GiveDirectly's targeting strategy. In short:

• How much poorer are those selected by GiveDirectly's criteria? It is not clear to us that, within the villages GiveDirectly works in, eligible households are substantially and consistently poorer than ineligible households.
• What do housing materials or assets indicate about financial management? There is a potential risk that GiveDirectly is systematically targeting the people who are less likely to use additional money well. GiveDirectly notes that the data it has collected suggests otherwise.
• Are the benefits of targeting the poorest worth the costs? We also wonder if attempting to target only the poorest members of a community (with any eligibility criteria) is worth the costs (in GiveDirectly staff time and potential for conflict in villages), given that we expect almost everyone in the communities that GiveDirectly works in to be quite 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 five locations (three in Siaya and two 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 five locations (including two 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.30 Note that when we visited, GiveDirectly was using thatched roofs and mud building materials as its criteria.

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 in this footnote.31

Note that among the households we visited, many had already received part or all of their transfer from GiveDirectly, so our observations 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 in short above and in more detail on our page with additional information about GiveDirectly. 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, back checks, remote checks and audits) for most transfer campaigns; we have only spot-checked the data GiveDirectly shared with us in 2015 and 2016.32

GiveDirectly tracks the percentage of households found to be ineligible at the back check and audit stages on its website; as of October 2016, it reported that 3% of initially registered participants in Kenya and 6% in Uganda were found to be ineligible by the end of GiveDirectly's enrollment process.33 We are not sure over what time period these figures are calculated.34

We believe GiveDirectly's current process to be generally effective at identifying households that meet its criteria. However, GiveDirectly has told us that in the future it plans to experiment with streamlining its enrollment process by excluding the back check step from its process.35 It is possible that this change will allow a greater number of recipients to game the system. However, given that we expect almost everyone in the communities that GiveDirectly works in to be quite poor, we do not believe this is cause for much concern.

In 2016, GiveDirectly encountered high refusal rates – i.e., households declining to participate – in the Homa Bay region in Kenya (more on our page with additional information about GiveDirectly).

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

Mobile money providers and distribution models

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 an M-PESA agent.36 Users enter the amount they want to withdraw on their own phone, and after each transaction, they can see their remaining balance, reducing the ability of agents to defraud clients of funds.37 GiveDirectly has told us that recipients are generally able to withdraw cash from mobile money agents located in or near their villages.38 Recipients must pay a small fee when they withdraw a portion of their transfer (around 1% for large withdrawals, and higher for small withdrawals).39

GiveDirectly works with a mobile money provider called MTN in Uganda.40 MTN has similar security measures to M-PESA: a user must present ID to an agent before making withdrawals, provide their phone or SIM card, and enter their PIN number. Users must pay a fee to withdraw, and confirmation messages are sent after withdrawals.41

In Uganda, the agent network is less robust; however, GiveDirectly has found that recipients are still able to withdraw cash from mobile money agents.42 GiveDirectly tracks the ability of recipients to withdraw cash in its follow-up surveys, in which it asks recipients if they have withdrawn their transfer, if they experienced any issues, and how long it took them to make the trip to withdraw.43

Additionally, the "coffee RCT" that GiveDirectly is running will be conducted in Uganda (more), and GiveDirectly intends to use data from this study as a more rigorous check on how easily recipients can withdraw their money in Uganda.44

Staff fraud

The most significant issue that GiveDirectly has had in making sure that cash gets to recipients is a case of staff fraud in its Uganda pilot campaign. In mid-2014, GiveDirectly experienced a case of large-scale crime, when two 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.45 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.46 GiveDirectly has taken multiple measures to address the vulnerabilities exposed by this case of fraud (see footnote for details).47 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 by GiveDirectly's monitoring. It shifted to a distributed cash out model in Uganda in late 2015, which may be somewhat more secure.48

As GiveDirectly scales, we would weakly expect greater awareness of its program and more attention to be paid to it by people outside of the villages in which it works.49 This could increase the risk of large-scale crime.50 GiveDirectly believes that additional security measures are unlikely to be particularly useful (details in footnote).51 In addition to harming recipients, crime would likely cause delays for GiveDirectly's work.

Other issues

Other possible issues with GiveDirectly's process for sending cash to recipients include:

• In Kenya, M-PESA agents could be overcharging or stealing some of recipients' funds.52 GiveDirectly recognizes that this is a common criticism from recipients who call into GiveDirectly's hotline, but believes it is likely that many recipients with this complaint are not fully aware of how to use their mobile money accounts.53 Results from GiveDirectly's follow-up surveys indicate that this problem is fairly rare.54
• In Uganda, some recipients have experienced delays in accessing their funds due to MTN not activating their accounts immediately.55
• Recipients who are unfamiliar with mobile phones or mobile money accounts may not know how to keep their information secure. Field Officers may provide assistance during back check visits.56 GiveDirectly checks the quality of its Field Officers' interactions with potential recipients by administering "quality audits" that test how well recipients understand GiveDirectly's program and ask how the Field Officer conducted himself or herself.57
• Some of the recipients that GiveDirectly serves are not able to fully understand how to use the mobile money payments system on their own, or do not have the mobility to go to agents or cash out days to withdraw their funds.58 For these recipients, GiveDirectly finds a trustee or helper who aids them with their cash transfers; GiveDirectly tries to ensure that this person is someone the recipient trusts.59

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

Findings from the RCT

In the RCT, researchers collected data by surveying members of the treatment and control groups about their recent spending. GiveDirectly recipients increased the value of their non-land assets and their monthly consumption and did not increase spending on alcohol or tobacco. The RCT also found increases in food security, revenue, psychological well-being, and female empowerment for recipients of cash transfers. There was no significant effect found on health and education outcomes, profits, or cortisol levels.

We write extensively about the results from GiveDirectly's RCT in our intervention report on cash transfers.

Data from follow-up surveys

For several of GiveDirectly's past campaigns, GiveDirectly staff surveyed recipients on how they used their cash transfers during the follow-up calls, but has since discontinued the practice due to the limitations of self-reported data.60 Recipients reported spending a large portion of their transfer on "building." The next largest expenditure categories were household items, livestock, and school. See our page with additional information about GiveDirectly for more detail.

GiveDirectly has also presented some limited data on spending in a single village on its website.61 This data indicates that the vast majority of recipients (over 75%) in the village used their transfer to buy an iron roof.62 The next three largest categories of spending were on other home improvements, livestock, and furniture.63

Anecdotal evidence from our site visit

In our site visit to Kenya, we asked recipients about the value of items commonly purchased with transfer funds.64 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, 201265 ) 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 year66 [$175.13 based on the exchange rate as of November 15, 201267 ]).

Will the results be different in other campaigns?

GiveDirectly's RCT was conducted in Rarieda, Kenya. GiveDirectly now primarily works in Homa Bay, Kenya and Uganda, and recently started a standard campaign in Rwanda (in October 2016).68 We guess that these contexts are similar enough that the impact of cash transfers on recipients will be roughly similar.

GiveDirectly has informed us that most potential recipients in Homa Bay County already have iron roofs.69 Additionally, Rwanda recently banned thatched roofs, so recipients are more likely to already have iron roofs there.70 To date, our estimate of investment returns from GiveDirectly's cash transfers has been based on the return to buying an iron roof (due to this being a particularly common purchase). The fact that iron roofs are already common in Homa Bay raises questions about how recipients will spend transfers and what returns on their investments they will get. GiveDirectly has noted that Homa Bay County is geographically very close to Rarieda and that the poverty rate in Homa Bay County is higher than it was in Rarieda, which could indicate that cash transfers will do more good in Homa Bay.71 We expect to learn more about the impact of cash transfers on recipients in Homa Bay from the results of the Aspirations study (more).

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

We discuss GiveDirectly's rationale for setting the grant size at $1,000 per households and our reservations about it on our page with additional information about GiveDirectly. In short, we find GiveDirectly's approach to be defensible, but we look forward to seeing the results of GiveDirectly's experimentation with different approaches in the future.

Are there negative or offsetting impacts?

Below, we discuss questions about the possible negative effects of cash transfers and GiveDirectly's operations. For more, see our site visit notes from our visit to GiveDirectly's operations Kenya in November 2012, during which we spoke with recipients and non-recipients about potential problems.

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 villages or on instances of physical, sexual, or emotional violence in treatment households as compared to control households in treatment villages.72

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.

GiveDirectly has two primary mechanisms for tracking and resolving conflicts: its follow-up surveys and its hotline. GiveDirectly's follow-up surveys include questions like the following:73

• Have you heard complaints about GiveDirectly 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.

Recipients can use GiveDirectly's hotline to report issues at any time. GiveDirectly has informed us that recently its hotline service was not effectively responding to everyone who called in; it is in the process of upgrading its hotline.74

Data from follow-up surveys

GiveDirectly has sent us results from follow-up surveys conducted in multiple transfer campaigns. In 2016, we asked for a sample of recent follow-up survey data. GiveDirectly sent us a database covering 3,329 follow-up calls from late July to mid-August 2016 across its campaigns in Kenya, Uganda, and Rwanda.75 This data indicated that reported issues were low: 7% of recipients reported some regrets about how they spent their transfer, 2% reported hearing complaints, and 1% reported thefts.76 Note that GiveDirectly surveys only cash recipients, not non-recipients, and all data is self-reported.

Data from Kenya and Uganda for 2013-2015 is on our page with additional information about GiveDirectly.

Data from hotline calls
We have reviewed records of calls made to GiveDirectly's hotline from May 2012 – August 2015, which provide anecdotal evidence of tension and conflict caused by the cash transfers, according to recipient reports, including marital disputes, fraud committed by helpers, trustees, or family members, and Village Elders requesting funds from recipients.77 In the most recent complete hotline call data that we have seen (from October 2014; in 2015 we asked for sample data only and in 2016 we did not ask for a sample), the most common type of adverse event recorded is household conflict, followed by theft.78 The number of issues reported was about 6% of the total households in the campaigns (though it is possible that single households account for more than one issue recorded).79

Do the cash transfers have negative effects on non-recipients?

There is suggestive evidence that cash transfer programs may have moderate negative short-term effects on the well-being and economic outcomes (e.g., consumption, assets, and business revenue) of non-recipient households living in the same areas as similar households that receive transfers.80 However, the evidence for these effects primarily comes from studies of a variant of GiveDirectly’s program that may differ from its core program in important ways. GiveDirectly notes that even though it has not identified significant evidence of negative effects on non-recipients, it now generally avoids conducting experiments that randomize at the individual level, to avoid situations in which one eligible household receives transfers while a similarly situated neighbor does not.81

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

The RCT of GiveDirectly's transfers in Rarieda found no significant effects of transfers on the rate of crime in treatment villages.82 It is possible that cash transfers cause more serious crimes (in terms of damages) even if they do not cause more crimes; this seems plausible given that cash transfers 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, but GiveDirectly does not expect to see significantly higher rates of crime in the near future.83

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

• People stealing cash and cell phones from recipient households84
• People contacting recipients and posing as GiveDirectly staff to defraud recipients of funds85
• Mobile money agents defrauding recipients of funds86
• GiveDirectly staff defrauding recipients of funds (we discuss one particularly large case of this above)

To mitigate the risk of small-scale crime, in its communications with recipients GiveDirectly emphasizes ways that recipients can keep their mobile money accounts and phones secure.87 It does not communicate with recipients via text message and tells recipients of this policy in order to protect against mass attempts at fraud, and it follows up with recipients who report crimes to try to resolve the issues.88

Do grants distort incentives and decision-making?

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.89 The one-off nature of transfers (recipients are not eligible for a second round of transfers) 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.90

Another way in which grants may distort decision making 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 provides some statistics on the speed with which transfers are received.91 It is possible that this will become more of an issue in the future, as GiveDirectly recently changed its model such that recipients cannot receive their next transfer until a GiveDirectly staff member has followed-up with them about their previous transfers, and it is possible this will increase delays.92

GiveDirectly told us that in its Kenya campaigns the key factor determining when a recipient receives funds is when he or she registers for M-PESA; recipients are told that they will not receive transfers until they have registered.93 In Kenya, for recipients receiving their first transfer in February 2016 (the last time we checked this), the average time for recipients between the census survey and their first payment was 67 days and 2.5% of recipients had transfers that had been delayed for over 3 months.94 GiveDirectly's records of calls to its Kenya hotline demonstrate that some recipients are 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).95

In Uganda, the agent networks of mobile money providers are not as robust, which means that recipients must travel farther, on average, to reach an agent.96 This may hamper recipients' ability to execute plans for how and when to use funds. In late 2015 (the last time we checked this), 81% of recipients in GiveDirectly's Uganda model variations campaign had received their transfers on time (within 15 weeks of enrollment) and 14% had experienced registration problems.97 In early 2016, GiveDirectly reported that transfers in Uganda were delayed due to elections, but did not state by how much.98

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 find no impact on spending on these goods.

Does GiveDirectly divert skilled labor away from other areas?

In February 2016, GiveDirectly had 94 total field staff members across Kenya, Uganda, and Rwanda: 4 Country Directors and Field Directors, 2 Data Managers and Operations Managers, 7 Administration and Finance staff, 10 Field Managers and Associate Field Managers, and 71 Field Officers.99

GiveDirectly recruits Field Officers through referrals from peer organizations, postings at universities, and job advertisements. The application process involves an interview with a Field Director and a language competency exam. GiveDirectly reports that it receives approximately six times the number of resumes as openings for Field Officer positions.100 Regarding its field staff in Kenya, GiveDirectly explained that successful candidates generally have a college education and are paid approximately $12 per day, in addition to expenses for travel and lodging while working.101 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.102

Because GiveDirectly continues to easily hire additional staff and its compensation seems roughly in line with market value, we do not see diversion of skilled labor as a serious concern.

Does GiveDirectly have a broader impact on the international aid sector?

One of the aims of GiveDirectly's partnership and evaluation work is to influence the broader international aid sector to use its funding more cost-effectively.103 We have not yet seen compelling evidence that GiveDirectly is causing significant shifts within the international aid sector, although GiveDirectly has noted that we might find conversations with some of its partners to be qualitatively persuasive.104 GiveDirectly has provided evidence that weakly suggests that the international aid sector is moving towards benchmarking programs against cash.105 However, it is difficult to understand what portion of that shift is attributable to GiveDirectly. Below, we describe the types of examples GiveDirectly has provided in support of its impact on the sector:106

• Anecdotally, GiveDirectly has heard that some large funders are asking themselves "Is this better than cash?" before making grants.107 Additionally, several large funders partnering with GiveDirectly (or in discussions for future partnerships) have told GiveDirectly that they are having internal policy conversations around the idea of benchmarking programs against cash, in large part due to GiveDirectly.108
• GiveDirectly believes there has been an increase in demand from policymakers for evidence that compares programs to cash.109
• GiveDirectly believes there has been an increase in the number of studies that include cash arms (and GiveDirectly was invited to implement the cash arms of several new evaluations).110
• Anecdotally, GiveDirectly has heard that several new cash transfer programs, new evaluations, and increased transparency practices were inspired by GiveDirectly.111 GiveDirectly believes that, by executing an excellent program, it may put competitive pressure on other implementers to also perform effectively.112
• GiveDirectly has provided informal advice to new cash programs and studies.113
• GiveDirectly has participated in several high-level panels and roundtables.114
• GiveDirectly is used as an example in trainings and university courses.

We have created a spreadsheet with the examples of GiveDirectly's potential impact on the international aid sector that we are aware of.

It is easier to evaluate GiveDirectly's role in causing unique projects to happen, as opposed to its impact on the broader sector. We believe that the Rwanda project, which caused large donors to give $4 million to a study that will benchmark an intervention against cash transfers, would not have occurred without GiveDirectly and the media attention that GiveDirectly has attracted.115

We would guess that a large portion of any sector impact attributable to GiveDirectly comes from the fact that GiveDirectly has functioned as a proof of concept for cash transfers. Because GiveDirectly has already shown that implementing cash transfers broadly is feasible, we are unsure whether or not additional growth would have a similar sector impact. It is possible that some activities, such as policy-relevant experimentation or partnership projects, could cause significant sector impact in the future; we have not looked in-depth at the impact of these activities (beyond the direct impact on recipients).116 We remain highly uncertain of our ability to determine how much these activities sway policymakers' or funders' decisions, even if we put substantial time and effort into the question.

GiveDirectly notes that its standard cash transfer campaigns could also contribute to sector impact by attracting additional attention which later leads to partnership projects or changes in funders' behavior.117 While this is plausible, we do not see any clear way to verify the suggested causal connection.

What do you get for your dollar?

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

Cash grants make up 82.3% of GiveDirectly's all-time incurred expenses.118 This figure includes fundraising costs that are expected to generate revenue in the future and excludes some of the costs of following up with recent recipients.119 We do not have a detailed breakdown of projected future campaign costs, so we are unsure if the ratio of direct grant to total spending will look similar in the future. We believe it's likely to be slightly lower: for spending since June 2015, transfers have been closer to 80% of GiveDirectly's total spending.120

GiveDirectly notes that it expects its efficiency to be higher in its Rwanda standard cash transfer campaign.122

A breakdown of GiveDirectly's spending through July 2016 is on our page with additional information about GiveDirectly.

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 and deworming are both 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 values. 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 full cost-effectiveness model is available here. See also, our 2012 discussion of the cost-effectiveness of cash transfers and other interventions.

Are there significant differences in cost-effectiveness between GiveDirectly's various types of programs?

On our page with additional information about GiveDirectly, we discuss how the cost-effectiveness of GiveDirectly's basic income guarantee program and beachmarking partnership projects may differ from that of its standard cash transfers.

Is there room for more funding?

We believe that GiveDirectly could effectively use more funding than it expects to receive and is very likely to be constrained by funding next year. We estimate that if it received an additional $46 million (allowing it to commit $65.8 million) its chances of being constrained by funding would be reduced to 50%.

In short, we calculate this from (more detail in the sections below):

• Total opportunities to spend funds productively: We believe that GiveDirectly could productively use between $66 million (50% chance of scaling to this level) and $144 million (5% chance of scaling to this level) for cash transfers in its 2017 budget year. This excludes consideration of what GiveDirectly could productively use on activities other than standard cash transfer campaigns (such as fundraising) because GiveDirectly has told us its other activities are fully funded. This estimate includes the costs of enrollment, transferring funds, and follow-up.
• Cash on hand: GiveDirectly holds approximately $66 million. It expects to spend or allocate all of this before February 2017.
• Expected additional funding: We estimate that GiveDirectly will raise $19.8 million in additional funding for its 2017 standard cash transfer campaigns.

Below, we also discuss:

• Past spending: In recent months, GiveDirectly has enrolled recipients at a rate corresponding to transferring $21 million per year.
• Additional considerations: GiveDirectly has a track record of success in scaling its operations quickly. Recently, it grew its capacity for cash transfers by a factor of almost two in a year. It is not clear whether it will be able to continue this trend. Over the last year, GiveDirectly has experienced a high rate of targeted households refusing to be enrolled in an area GiveDirectly was expanding into.

Details follow.

Available and expected funds

As of July 2016, GiveDirectly had $66 million on hand.123 By the end of GiveDirectly's current budget year (February 2017), GiveDirectly expects to have spent or allocated all of this funding, along with an additional $17.5 million that it expects to raise for its basic income study (collectively, $83.5 million):124

• $30 million will be allocated to the basic income guarantee project and granted out over the next 12 years.
• $14 million is allocated to partnership projects.
• $8.5 million is allocated to GiveDirectly's fundraising activities for the next three years.
• $2 million is set aside for salary reserves.
• $29 million will be committed to households for standard cash transfers by the end of February 2017.

Excluding GiveWell-influenced donors, we predict that GiveDirectly will raise $15.8 million in unrestricted funding through the first half of its 2017 budget year that it could use for its standard cash transfer campaigns in 2017.125 We expect that GiveDirectly will receive an additional $4 million from GiveWell-influenced donors who do not follow our recommendation exactly.126

Funding priorities

In the table below, we've briefly summarized the details of GiveDirectly's funding gaps; further detail follows the table. All figures in this section are inclusive of the costs of enrollment, transferring funds, and follow-up.127

Note that:128

• A standard cash transfer team consists of one "team lead" (a Field Director or Country Director) and a team of Field Managers, Associate Field Managers, and Field Officers. GiveDirectly expects that each team in 2017 will be able to transfer $12 million per year (up from a pace of $7 million per team per year in mid-2016 and $11 million per team per year that GiveDirectly expects to transfer by the end of 2016; more below). Half of a team in the table below represents that team working on standard cash transfer campaigns for half of the year.
• GiveDirectly has estimated its "throughput"—the amount of cash that GiveDirectly can commit to households within a given time frame—will be $33 million in 2016.

GiveDirectly's funding gaps for 2017129

Additional detail:130

• Operating below 2016 throughput: GiveDirectly expects to transfer $33 million in its 2016 budget year (3.1 fully trained teams) and to be on pace, if it raises enough funding, to transfer $48 million in 2017 (4 teams).131 We discussed several scenarios with GiveDirectly about what it would look like if it scaled down its operations below its 2016 level in 2017:
  • If GiveDirectly raises a total of $20 million for its standard cash transfer campaigns in 2017, it will have to downsize its staff for standard cash transfer campaigns by approximately 33%.132
  • At a total of $30 million, GiveDirectly would operate 2.5 full teams (likely one full team in Kenya, one full team in Uganda, and a half team in Rwanda).133 GiveDirectly told us that it would still need to downsize its staff.134 GiveDirectly estimates that it would take half a year to scale back up to its current pace after the losses in staff it would experience at the $30 million level.135
• Funding level at which GiveDirectly has a 50% chance of being constrained by funding: GiveDirectly is currently on pace (with no additional hiring) to have four full teams operating its standard cash transfer model in 2017 (details in footnote).136 However, it believes that it could easily scale to 5.5 teams (details in footnote) and, if it receives enough funding to do so, has a 70-80% chance of scaling to this level successfully.137 We guess that this probability is lower (about 50%), given that (a) GiveDirectly has other major priorities as well in 2017 (e.g., partnership projects and the large basic income study), and (b) that GiveDirectly does not yet have the ability to raise enough funds to maintain an operation of this size in the future, which might make it more hesitant to scale to that size in 2017—GiveDirectly has expressed concerns about the negative attention that might come with reducing its size.138
• Funding level at which GiveDirectly has a 20% and 5% chance of being constrained by funding: We asked GiveDirectly to estimate the point at which it believes it would only have a 5% chance of succeeding at scaling to that level in 2017. While this estimate is highly uncertain, GiveDirectly estimated that scaling to 16 additional full teams, 20 total, would have a low likelihood of success.139 We estimate that the 5% level is at 8 additional teams, 12 total. This estimate is very rough and relies on our intuitions. Assuming a linear relation between team size and chance of success, we estimate that GiveDirectly has a 20% chance of success at a scale of 10 teams.140

GiveWell's prioritization of GiveDirectly's funding gaps

We have tried to rank our top charities' funding gaps based on:

• Capacity relevance: how important the funding is for the charity's development and future success.
• Execution relevance: how likely it is that the charity's activities will be constrained if it does not receive the funding.

We believe that "capacity-relevant" gaps are the most important to fill, and "execution"-related gaps vary in importance. More explanation of this model is in this blog post.

We consider all of the funding gaps for GiveDirectly's current priorities to all be "execution" gaps.141 We assign execution level gaps a level (1, 2 or 3) that corresponds with how likely we believe it is that GiveDirectly would be constrained by funding (rather than other factors, such as an inability to grow staff capacity quickly enough) if it is unable to fill the funding gap. Level 1 is 50% chance of funding being the constraint, level 2 is 20% chance, and level 3 is 5% chance. These judgements are rough and largely based on intuitions formed from following GiveDirectly's scale up over several years (more in the next section).

Past enrollment rate

GiveDirectly's past rate of committing funds to recipients is lower than its projected rate for the remainder of 2016 and 2017. Its enrollment rate from March 2016 - July 2016 (the period of GiveDirectly's current budget year for which we have information) implies a transfer rate of about $21 million per year,142 or, assuming three full teams were in operation (two in Kenya and one in Uganda), about $7 million per team per year.143 Including the costs of delivering transfers, GiveDirectly has been transferring about $7.7 million per team per year.144

Note that GiveDirectly expected to transfer $29 million in the period August 2016 - February 2017; assuming that it has 4 teams during that time period, that would require a pace of $12.4 million per team per year, much faster than its pace in the first half of the year.145 When we asked GiveDirectly about this, it noted that it is on pace with its plan, which had included significantly more transfers in the second half of the year.146 If GiveDirectly manages this pace for the second half of 2016, then it should be able to transfer $12 million in cash transfers per team per year (which includes the costs of delivering transfers) in 2017.

In the past, GiveDirectly has successfully scaled up over time, recently increasing its rate of transfers by about a factor of 1.5 to 2 in a year,147 but it is unclear if it will be able to continue this trend. In the table below, we show how GiveDirectly's rate of commitments has increased recently.

Rate of funds committed148

In the past, with a lag of about four months, distributed transfers have generally kept pace with committed transfers.149

To scale up to any point beyond 4 full teams on standard cash transfer campaigns, GiveDirectly will need to hire additional team leads (Country Directors or Field Directors), and it takes GiveDirectly several months to hire a team lead.150 Historically, GiveDirectly has not expected hiring more junior staff to be a challenge.151

Risks to room for more funding

GiveDirectly believes it can grow extremely quickly. However, there are some risks that might impede its ability to grow as fast as it believes it can. The following are concerns identified by GiveWell or GiveDirectly:

• Refusals: As discussed on our page with additional information about GiveDirectly, GiveDirectly has experienced a high rate of people refusing to be enrolled in Kenya over the last year. GiveDirectly has told us that this has not slowed down its productivity because (a) the refusals only affect the activities of one team (the census team; though this doesn't take into account increased travel time as other teams have to travel further on average between each house) and (b) GiveDirectly is flexible enough that it can pivot to new areas when refusals are high and come back later if refusal rates seem like they will decrease (perhaps due to outreach efforts).152 However, it is possible that the high rates of refusals could create challenges for GiveDirectly in its relationship with the Kenyan government; GiveDirectly has been working to build relationships with the government to mitigate this possibility.153 High refusal rates could also force GiveDirectly to move to new areas sooner than it expected, which could cause challenges if GiveDirectly struggles to obtain permission from local leaders to work in new areas (see next bullet). Additionally, similar challenges in other locations in the future might also reduce GiveDirectly's ability to scale as quickly as it hopes to.
• 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 who could intervene if there were a problem.154 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.155 In fall 2016, GiveDirectly was beginning the process of assessing how many households remained for it to enroll in the areas it has historically worked in and considering which areas it should enter next.156 GiveDirectly told us that there were sufficient eligible households to enroll over the next year, even if GiveDirectly worked with 5.5 full teams (we did not ask about whether there were sufficient households for more teams than this).157
• Crime: Incidents of large-scale crime could cause delays and reduce GiveDirectly’s ability to transfer funds to recipients. The risk of crime could increase as GiveDirectly becomes better known in the regions in which it works. We discuss this risk more above. We consider this a low to moderate risk.
• 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 or Rwanda if there were an issue.158 We know very little about security risks in Kenya, Uganda and Rwanda, but would guess based on GiveDirectly's assessment that it presents a low risk. As GiveDirectly continues to expand to other countries (e.g., Rwanda), we think this risk will be reduced because GiveDirectly will have more areas to redirect its work if necessary.
• 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.159 We would guess that this risk is low, as the mobile money providers that GiveDirectly uses are national networks, and GiveDirectly has identified alternatives. However, we note that GiveDirectly once tried working with an alternative provider in Uganda (Centenary Bank) and had difficulties in the partnership.160
• Maintaining staff quality as the organization grows: GiveDirectly noted that it has hired a number of new staff over the last year to scale up and prepare for additional scale-up in the future.161 It is possible that GiveDirectly will face issues if the new staff members learn slowly or turn out to be poor fits for their positions.162 So far, GiveDirectly believes that its hiring processes have been successful and that new staff are taking on responsibility quickly and competently.163
• Supporting operations as the organization grows: As GiveDirectly has grown in size, it has needed to expand its internal operations to support its larger team and activities. For example, GiveDirectly now uses Segovia (which we discuss above and on our page with additional information about GiveDirectly) to manage many of its enrollment, transfer, and follow-up activities. In 2015, GiveDirectly intended to hire a fundraising team leader to build out its fundraising operations.164 However, it did not manage to find someone for this position until late 2016, possibly affecting the amount of funding GiveDirectly will have available for standard cash transfer campaigns in 2017.165 We are unsure if GiveDirectly's internal operations and fundraising will be able to grow quickly enough to support its current size and continued expansion.
• Political instability or regulation: GiveDirectly has noted that there is some risk of political instability in the countries it works in. Elections could change how the government works with GiveDirectly or regulates NGOs.166 In the worst case scenario, GiveDirectly might be forced to move its operations out of one of the countries it is operating in.167 However, because GiveDirectly now operates in three different countries, it believes that this would be doable.168

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. We plan to grant funds to GiveDirectly unrestricted (such that GiveDirectly may use funds for all purposes, including experimenting with its model and process and organizational capacity building).

GiveDirectly as an organization

GiveDirectly is a relatively young organization. It was founded in 2009 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.169 Professor Niehaus was on sabbatical from his teaching position and working full time on GiveDirectly in 2014-2015.170 He returned to his professorship in fall 2015.171

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 few years have gone well; GiveDirectly has successfully accomplished its goal of transferring cash to extremely low-income people at a fairly low expense 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

• 1
  • "GiveDirectly was founded by Paul Niehaus, Michael Faye, Rohit Wanchoo and Jeremy Shapiro [...] They created GiveDirectly as a private giving circle in 2009 and opened it to the public in 2011 after two years of operational testing." GiveDirectly, FAQs 2015
  • As of November 2016, GiveDirectly had provided partial or full cash transfers to approximately 52,000 households in western Kenya and eastern Uganda, and was continuing to transfer funds to additional households in both places. Ian Bassin, edits to GiveWell's review, November 10, 2016
  • "In October 2016, GiveDirectly will launch a $5-million-dollar retail campaign in Rwanda." GiveWell's non-verbatim summary of a conversation with Ian Bassin and Piali Mukhopadhyay, GiveDirectly, August 23, 2016, pg. 6.

• 2
  • GiveDirectly, Siaya enrollment database
  • GiveDirectly, Google enrollment database
  • GiveDirectly, Nike enrollment database
  • GiveDirectly, RCT Enrollment Database
  • GiveDirectly, Kenya 2M enrollment database, September 2013
  • GiveDirectly, Uganda pilot enrollment database - Kosile
  • GiveDirectly, Uganda pilot enrollment database - Kawo
  • GiveDirectly, Uganda pilot enrollment database - Kanyamutamu
  • GiveDirectly, Uganda pilot enrollment database - Akumure
  • GiveDirectly, Kenya 1.2M enrollment database
  • GiveDirectly, Kenya 2M census results, July 2013
  • GiveDirectly, Kenya, Uganda, and Rwanda enrollment database, 2016
  • GiveDirectly gave permission to publish the following databases on the condition that all personally identifying information was removed. Due to the size of the databases, we have not yet anonymized them and therefore have not published them. If you are interested in the content of these databases, please contact us at info@givewell.org.
    • GiveDirectly, Kenya rolling campaign enrollment database - Homa Bay
    • GiveDirectly, Kenya rolling campaign enrollment database - Siaya
    • GiveDirectly, Uganda 2M campaign enrollment database

• 3

  GiveDirectly, Update for GiveWell, July 2014, Pg 5.

• 4

  Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016

• 5

  Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015 Note that we are calling rigorous tests of interventions "studies" and GiveDirectly's less rigorous, internal testing of new variations on its model (e.g, using biometric scans for additional security) "campaign variations."

• 6
  • "We conducted a randomized controlled trial (RCT) of the unconditional cash transfer program implemented by the NGO GiveDirectly in western Kenya between 2011 and 2012, in which poor rural households received unconditional cash transfers through the mobile money system M-Pesa." Pg 1.
  • "In each chosen village, GD conducted a census, usually with the help of the village
    elder, which identified all households in the village that met this targeting criterion. Among the eligible households, treatment households were chosen randomly (details are described in Section 2). Households were aware that recipients would be chosen by lottery, but the actual selection was done privately by means of random number generation." Pg 4.
  • "We are grateful to the study participants for generously giving their time; to Marie Collins, Faizan Diwan, Conor Hughes, Chaning Jang, Bena Mwongeli, Joseph Njoroge, Kenneth Okumu, James Vancel, and Matthew White for excellent research assistance; to Innovations for Poverty Action for implementation." Pg 1.

  Haushofer and Shapiro 2013 Policy Brief

• 7

  GiveDirectly, Rarieda transfer schedule, August 2013

• 8

  "Based on conversations with policymakers, GiveDirectly has identified gaps in the evidence-base for cash transfers that currently limit policymakers’ ability to implement cash transfer programs or to do so effectively. GiveDirectly has spoken with policymakers in Kenya and Indonesia, as well as representatives of the UK’s Department for International Development (DFID). The leading question that came out of these conversations was about the macroeconomic impacts, or “general equilibrium effects,” of cash transfers when conducted at a national scale. This includes factors such as enterprise structure, prices, local public finance, and local government activities. This question is the primary motivation for GiveDirectly’s top research priority: a study of general equilibrium effects." Conversation with GiveDirectly, July 7, 2014, Pg 2.

• 9

  "Objective:

  • Understand macro-economics impacts of transfers at scale (in-flation, job creation, etc.)
  • Measure impacts over a long time horizon (e.g., [less than[sic]] 5 years)

  Status:

  • Started baseline, with long term follow up mechanisms in place
  • Not fully funded– facing a gap of ~8M

  Partners:

  • Edward Miguel, Berkeley
  • Johannes Haushofer, Princeton

  Potential impact:

  • Increase government use of CT programs
  • Increase support for our particular model in proving LT impact"

  GiveDirectly, Update for GiveWell, October 2014, Pg 13.

• 10
  • This study may include a long-term follow up component that will provide information on the impacts of cash transfers several years after the transfer: "This study will potentially include long-term follow up as well, to address a separate question raised by policymakers about the long-term impacts of cash transfers. Professor Miguel previously worked on a study of the impacts of deworming (Miguel and Kremer 2004) that involved follow-up over a period of ten years and obtained a high response rate, so he has experience in setting up effective systems for tracking study participants over time." Conversation with GiveDirectly, July 7, 2014, Pg 3
  • The study is randomized at the village level, will involve 325 villages, and is expected to survey approximately 3,900 households and 4,875 enterprises. GiveDirectly, GE study design, Pgs. 4-5. Update: "Currently in the midst of endline data collection. Plan is to finish endline data collection by the end of the year, and hope to survey over 9,000 households, 700 village elders, 80 assistant chiefs, 200 school head teachers and 3,000 enterprises." GiveDirectly, Update for GiveWell on experimentation, September 2016, Pg 3.
  • Baseline data collection for the study began in August 2014 and was still in progress as of September 2015. Baseline data collection was slightly slower than expected, which meant that GiveDirectly had to delay some transfers (so that researchers could complete the baseline survey before recipients had received cash).
    • GiveDirectly, GE research and measurement plan, Pg 6.
    • "The GE study in Siaya is an example of how research studies can affect GiveDirectly’s timeline. In that case, GiveDirectly moved more quickly than anticipated, and so had to delay the token transfers for some of its recipients to give the GE team enough time to conduct its baseline survey, which had to be completed before the token transfers were sent." GiveWell's non-verbatim summary of a conversation with Paul Niehaus and Carolina Toth, September 7, 2015, Pg 8.
  • Endline data collection was expected to be completed by the end of 2016, although this may be delayed since baseline data collection has taken longer than expected. GiveDirectly, GE research and measurement plan, Pg 6.
  • Midline data was scheduled to be collected from November 2014 to early 2016. GiveDirectly, GE research and measurement plan, Pg 6.
  • Paul Niehaus, GiveDirectly's President, is serving as one of the Principal Investigators on this study, along with Edward Miguel (UC Berkeley), Johannes Haushoffer (Princeton), and Michael Walker (UC Berkeley). GiveDirectly, GE study design, Pg 2, and Carolina Toth, email to GiveWell, November 10, 2015.
  • In order to mitigate potential bias from his involvement with the research, GiveDirectly has applied a number of safeguards, including preregistration of plans for measurement and analysis: "Paul Niehaus, GiveDirectly’s Co-Founder and President, will serve as a Principal Investigator on the general equilibrium effects study. To mitigate potential bias when GiveDirectly staff are involved in research on the impacts of its programs, GiveDirectly has decided on a few safeguards: the research team conducting the study will 1) preregister their plans for measurement and analysis 2) use a (non-GiveDirectly staff) third party for measurement, and 3) include academic PIs who are not involved in GiveDirectly and have a reputation for honesty." Conversation with GiveDirectly, July 7, 2014, Pgs 2-3.

• 11

  "Currently in the midst of endline data collection. Plan is to finish endline data collection by the end of the year, and hope to survey over 9,000 households, 700 village elders, 80 assistant chiefs, 200 school head teachers and 3,000 enterprises.

  Pre-analysis plan for the midline data has been filed, and are actively working on finalizing pre-analysis plans for the local leader survey data and the rest of the endline data. Analysis has begun on the midline data and is ongoing." GiveDirectly, Update for GiveWell on experimentation, September 2016, Pg 3.

• 12
  • "Goals for 2016…GiveDirectly hopes to launch a test of a program that would guarantee a basic income to participants over the course of several years." Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016, Pg 1.
  • "This study could use the same control-group villages as the GE study." Conversation with GiveDirectly, September 5, 2014, Pg 6.
  • "The organization that we founded, GiveDirectly, has decided to try to permanently end extreme poverty across dozens of villages and thousands of people in Kenya by guaranteeing them an ongoing income high enough to meet their basic needs—a universal basic income, or basic income guarantee." Michael Faye and Paul Niehaus, Slate article, April 14, 2016
  • Paul Niehaus and Ian Bassin, conversation with GiveWell, September 15, 2016
  • GiveDirectly, Blog post, September 22, 2016

• 13
  • As of September 2016, GiveDirectly had raised slightly more than $21 million. It would like to raise $30 million for the study. Paul Niehaus and Ian Bassin, conversation with GiveWell, September 15, 2016
  • Sample size
    • "To do so, we’re planning to provide at least 6,000 Kenyans with a basic income for 10 to 15 years." Michael Faye and Paul Niehaus, Slate article, April 14, 2016
    • Ian Bassin and Carolina Toth, email to GiveWell, June 14, 2016 - noted that the study was expected to include ~12,000 recipients.
    • The study will cover 342 villages (including control) GiveDirectly, Update for GiveWell on experimentation, September 2016, Pg 2.
    • Ian Bassin, edits to GiveWell's review, November 10, 2016
  • Eligibility criteria
    • GiveDirectly will attempt to enroll everyone in the village. GiveDirectly wants its study to be as helpful to policymakers as possible, and policymakers interested in basic income programs are especially interested in universal programs. Paul Niehaus and Ian Bassin, conversation with GiveWell, September 15, 2016
    • "Adult individuals, not households, are the relevant unit for GiveDirectly for all arms (i.e., each adult in a household has their own line)
      All full-time resident adults (>=18) will receive payments
      All individuals >=15 years old will begin to receive payments once they turn 18 for whatever remains of the payment period (e.g., 9 years for a 15 year old)
      Migration: Eligible recipients who migrate out of the village will continue to receive. Recipients that migrate into the village after enrollment has begun are not eligible to receive." GiveDirectly, Update for GiveWell on experimentation, September 2016, Pg 2.
  • Arms of the study
    • There will be four arms: control (100 villages), 12 years of basic income received monthly (41 villages), 2 years of basic income received monthly (95 villages), and 2 years of basic income received in "lump sums" like in GiveDirectly's standard model (106 villages). GiveDirectly, Update for GiveWell on experimentation, September 2016, Pg 2.
  • Paul Niehaus and Ian Bassin, conversation with GiveWell, September 15, 2016
  • "The overall scale of the project remains incredibly ambitious: if fully funded, it will deliver transfers to over 26,000 individuals, including 6,000 receiving the full 12-year basic income transfers. This breaks down into 40 villages in the first treatment arm and 80 each in the other two, with roughly 120 to 150 individuals per village. Given this scale, we have reasonably good odds of detecting impacts not only on individuals, but also on village-level markets." GiveDirectly, Blog post, September 22, 2016

• 14
  • "The group is still finalizing details, but the payment is expected to be about $0.70 to $1.10 per person per day." Dylan Matthews, Vox article, April 15, 2016
  • "Snaswa: What is the minimum amount of cash that a household/individual can receive as Basic Income in the pilot study?... Paul Niehaus: "we're finalizing, looking at around $0.75 nominal = $1.50 PPP" Paul Niehaus, AMA on Reddit, May 31, 2016
  • Ian Bassin and Carolina Toth, email to GiveWell, June 14, 2016
  • GiveDirectly, Update for GiveWell on experimentation, September 2016, Pg 2.

• 15

  Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016

• 16
  • Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016
  • Paul Niehaus and Ian Bassin, conversation with GiveWell, September 15, 2016

• 17

  "We think the direct impact of the UBI program will be about ~60% as effective as the lump sum program, but that the potential policy impact more than makes up for that difference" GiveDirectly, Update for GiveWell on experimentation, September 2016, Pg 2.

• 18

  Some of GiveDirectly's potential partnership projects (note that these projects are small compared to the projects GiveDirectly is currently interested in):

  • Uganda District: Request from an MP to discuss working in his district GiveDirectly, Check in with GiveWell, September 2014, Pg. 5. Update: "GD declined request to work in Uganda's [Redacted] district - no obvious opportunity for policy impact to offset relocation costs" GiveDirectly, Update for GiveWell, September 2015, Pg 6.
  • GiveDirectly has spoken with researchers in a multilateral-funded program to which the partners were considering adding unconditional cash transfers. Conversation with Piali Mukhopadhyay, GiveDirectly, October 20-21, 2014 (unpublished). Update: GiveDirectly declined to participate in this program despite high potential policy impact, because a) the program was located in an area GiveDirectly had never worked and GiveDirectly did not have enough time to run pilots of cash transfers before making its decision and b) GiveDirectly was worried that study results would not be rigorous due to low sample size for the cash transfer arm. Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015
  • Multilateral agency: GiveDirectly has also spoken with another agency, which is considering using cash transfers as a benchmark to assess the impacts of one of its nutrition programs. Conversation with Piali Mukhopadhyay, GiveDirectly, October 20-21, 2014 (unpublished). Update: "GD declined to pursue implementation of nutrition benchmarking study, but will provide advice." GiveDirectly, Update for GiveWell, September 2015, Pg 6.
  • Haiti evaluation: GiveDirectly is discussing experimental impact evaluation in Haiti to assess how cash performs relative to other reconstruction projects there. GiveDirectly, Update for GiveWell, September 2015, Pg 6.
  • Evaluation non-profit benchmarking initiative: GiveDirectly spoke with a representative at an evaluation non-profit about adding cash transfer arms to some of the non-profit's studies. A survey of 31 ongoing studies found that 6 have a cash arm currently and 20 would like to add one. GiveDirectly does not plan to be the implementing partner for these studies because there are often implementing partners that are already set up who could implement the cash transfers if they had enough funding. But GiveDirectly is spreading awareness of this opportunity through its network. Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015

• 19

  He was primarily focused on Rwanda (see below) and replicating the Rwanda model.

  • Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015
  • Carolina Toth, email to GiveWell, November 10, 2015

• 20

  "GiveDirectly is offering up to $15 million in matching funds on a first-come, first-served basis to fund these types of projects. GiveDirectly hopes that offering the matching funding will incentivize large funders to move quickly on partnership projects. If all of GiveDirectly’s partnership projects discussions came through, GiveDirectly would need to contribute $23-30 million. While GiveDirectly cannot fund all of the projects it is currently discussing, it would consider talking to partners about opportunities to fund any projects approved by these potential funders that are beyond GiveDirectly's funding limit.

  One of the large funders is unlikely to begin providing funding until early 2017. This funder and GiveDirectly would each contribute roughly $7 million to a project, for a rough total of $14 million. It is possible, though unlikely, that GiveDirectly could get funding from this funder by the end of 2016. (Update: As of October 2016, GiveDirectly did not expect this project to happen.) GiveDirectly has had exploratory talks with another large funder."

  GiveWell's non-verbatim summary of a conversation with Paul Niehaus, Carolina Toth, and Ian Bassin, August 12, 2016, Pg 5.

• 21

  "GiveDirectly is offering up to $15 million in matching funds on a first-come, first-served basis to fund these types of projects. GiveDirectly hopes that offering the matching funding will incentivize large funders to move quickly on partnership projects. If all of GiveDirectly’s partnership projects discussions came through, GiveDirectly would need to contribute $23-30 million. While GiveDirectly cannot fund all of the projects it is currently discussing, it would consider talking to partners about opportunities to fund any projects approved by these potential funders that are beyond GiveDirectly's funding limit." GiveWell's non-verbatim summary of a conversation with Paul Niehaus, Carolina Toth, and Ian Bassin, August 12, 2016, Pg 5.

• 22
  • "In practice, we do not think there is much scope for additional senior leadership time devoted to fieldwork to materially improve the quality or efficiency of execution there." GiveDirectly, Update for GiveWell, September 2015, Pg 14.
  • Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015

• 23

  @Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, August 12, 2016@

• 24
  • We are unable to be more specific because GiveDirectly would prefer to keep the particular inputs the algorithm uses confidential, to make it harder for people to game the eligibility requirements.
  • Carolina Toth, email to GiveWell, October 20, 2015

• 25
  • Carolina Toth, conversation with GiveWell, November 12, 2015
  • "A full set of asset questions are oftentimes only relevant when we are re-assessing poverty of a particular region, or assessing it for the first time when we enter a new region. In addition to assets, we may consider other factors such as housing materials, facilities (latrine, roof, floor) etc. The exact set of factors considered changes across communities to reflect the complex variations of poverty. We also continuously test and tweak our set of criteria based on our analysis. This is why you may see different sets of information (assets/facilities etc.) collected across different geographies." GiveDirectly staff, responses to monitoring questions, October 11, 2016, pg. 1.

• 26

  Carolina Toth, conversation with GiveWell, November 12, 2015

• 27
  • "We typically use building materials as eligibility criterion—organic materials like a thatched roof, mud walls, or mud floor have the advantage of being (a) a strong predictor of poverty, (b) easy for community members to understand, and (c) relatively easy to audit in a number of ways, including both digital imagery captured by our field staff and satellite imagery captured remotely." GiveDirectly, FAQs 2015
  • GiveDirectly has tweaked these criteria in the past, e.g., "Dropped mud walls as eligibility requirement." GiveDirectly, Update for GiveWell, October 2014
  • Carolina Toth, email to GiveWell, November 10, 2015

• 28
  • GiveDirectly, Survey for randomized controlled trial
  • "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, Offering Memorandum (January 2012), Pgs 23-24.

• 29

  GiveDirectly, What We Do - Operating Model, see the Uganda tab.

• 30
  • Several recipient households had been selected by GiveDirectly for our visit as representative of how recipients use funds. 2 locations (and the households within them) were selected as a function of GiveDirectly's activities that day -- an area of Rarieda where the end-line survey for the RCT was being implemented and an area of Siaya where enrollment was being undertaken. In both cases, we don't know whether enrollment and surveying activities were taking place elsewhere that day which would have given GiveDirectly discretion in choosing these areas.
  • On the final day of our visit, we asked GiveDirectly whether we could randomly select 3 households to visit. GiveDirectly sent us a list of 15 households in a location in Rarieda where the end-line survey for the RCT was complete and therefore we could question recipients without interfering with the RCT. We don't know whether GiveDirectly had discretion in choosing these 15 households. We selected 5 households from the list using Excel's RAND() function and visited 3 of them. (GiveDirectly made appointments with the households in advance and could not reach 2 of them.)
  • We would characterize all the households we visited -- those that GiveDirectly fully selected for us, those over which GiveDirectly had less discretion, and those we selected randomly -- as extremely poor. We did not see any significant differences in wealth between them.

• 31
  • 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.

• 32
  • @GiveDirectly, Siaya Enrollment Database@
  • GiveDirectly, Google enrollment database
  • GiveDirectly, Nike enrollment database
  • GiveDirectly, RCT Enrollment Database
  • GiveDirectly, Kenya 2M enrollment database, September 2013
  • GiveDirectly, Uganda pilot enrollment database - Kosile
  • GiveDirectly, Uganda pilot enrollment database - Kawo
  • GiveDirectly, Uganda pilot enrollment database - Kanyamutamu
  • GiveDirectly, Uganda pilot enrollment database - Akumure
  • GiveDirectly, Kenya 1.2M enrollment database
  • GiveDirectly gave permission to publish the following databases on the condition that all personally identifying information was removed. Due to the size of the databases, we have not yet anonymized them and therefore have not published them. If you are interested in the content of these databases, please contact us at info@givewell.org.
    • GiveDirectly, Kenya rolling campaign enrollment database - Homa Bay
    • GiveDirectly, Kenya rolling campaign enrollment database - Siaya
    • GiveDirectly, Uganda 2M campaign enrollment database
  • GiveWell, spot checks of Segovia registration sample 2016
  • GiveDirectly staff, responses to monitoring questions, October 11, 2016

• 33

  GiveDirectly, What We Do - Operating Model, October 2016

• 34

  However, they seem to roughly match other data we have seen. Between September 2013 and July 2015, 3.5% of recipients initially eligible after registration were found to be ineligible after the back check or audit stage.

  • See GiveDirectly, Eligibility check, which we downloaded from GiveDirectly's website on September 14, 2015. GiveDirectly, What We Do - Operating Model, Overview tab. Note that the document does not include all households that GiveDirectly has ever enrolled (e.g. there is one household from 2012 and only a sample from the other years).
  • GiveDirectly used to track these metrics in its monthly operations reports. For example, see "Gaming detection" in GiveDirectly, Monthly operations report, October 2014.

• 35
  • "In early 2016, GiveDirectly allocated a fairly large sum of money to test a new implementation model in Kenya. A separate field director and team were hired approximately six months ago, and the experiment is taking place in an area close to GiveDirectly's other field operations. The primary aim is to double the program's size in 2017 without significantly increasing the management structure. The new model seeks to increase throughput per manager by eliminating the token payment and back check steps. GiveDirectly will assess gains in throughput as well as costs, which might occur in the areas of comprehension and fraud. Results and data should be available after a few months of disbursements. By the end of 2016, GiveDirectly hopes to have a blueprint for implementing a similar model in other countries." GiveWell's non-verbatim summary of a conversation with Ian Bassin and Piali Mukhopadhyay, GiveDirectly, August 23, 2016, Pgs 4-5.
  • [GiveWell]: What is GiveDirectly checking to determine the quality of the campaigns with removed steps (especially the Kenya campaign with no backcheck and token payment)?
    [GiveDirectly]:
    • "Recipient Comprehension: With the removal of back check, we are tracking any deviation in recipient comprehension below 90% (our preferred rate). We are tracking this through additional survey questions in both audit and our follow up surveys where we ask recipients their understanding of our program. Additionally, Associate Field Managers will be conducting quality check surveys at audit stage for another data point on recipient comprehension.
    • Transfer Integrity & Adverse Events Detection. Given additional risk of two payment structure, we will be assessing (on a bi-weekly basis) the percent of transfers reversed and percentage of adverse events happening after first payment and after second payment. This will then be compared to our standard quality bar to assess significant deviations. Given a greater need for over the phone assistance, we will also be tracking through our follow up program the percentage of recipients who received no customer service and tried.
    • Fraud Detection. With the removal of back check and a two payment structure that makes each payment riskier, we will be checking the percentage of recipients flagged for additional audit stage and then the percentage of those deemed ineligible after audit is conducted. We also have an internal audit team in place that will be conducting surveys post-payment to see if fraud occurred."

    Piali Mukhopadhyay, COO, International, GiveDirectly, email to GiveWell, August 25, 2016

• 36
  • Piali Mukhopadhyay, COO, International, GiveDirectly, conversation with GiveWell, November 8, 2012
  • GiveWell visit to M-PESA agent, November 8, 2012

• 37

  GiveWell visit to M-PESA agent, November 8, 2012

• 38

  "We then transfer money directly to the recipient's account […] The recipient collects the transfer from a local M-Pesa agent, who is typically a shopkeeper in the village or the nearest town. The recipient transfers his or her electronic M-Pesa balance to the agent using his or her mobile phone in return for cash." GiveDirectly, How it works 2014

• 39
  • "Mobile money payments are subjected to a small, less than 1%, withdrawal fee; GiveDirectly absorbs this cost by increasing the transfer amount accordingly." GiveWell's non-verbatim summary of a conversation with Ian Bassin and Piali Mukhopadhyay, GiveDirectly, August 23, 2016, Pg 4.
  • The withdrawal fee table for M-PESA is here (archive).

• 40

  "Selected MTN as preferred provider in Uganda after assessing performance of Ezee/MTN (building relationship with Airtel so as to have an additional hedge)" GiveDirectly, Update for GiveWell, July 2014, Pg 9.

• 41
  • Observations from GiveWell site visit to GiveDirectly, October 2014, Pg 5.
  • "Mobile money payments are subjected to a small, less than 1%, withdrawal fee; GiveDirectly absorbs this cost by increasing the transfer amount accordingly." GiveWell's non-verbatim summary of a conversation with Ian Bassin and Piali Mukhopadhyay, GiveDirectly, August 23, 2016, Pg 4.
  • The withdrawal fee table for MTN withdrawals is here (archive).

• 42

  "Recipients and agents were able to overcome liquidity constraints, and in Uganda, GiveDirectly distributes $700,000 to $1 million per month without any increases in fraud." GiveWell's non-verbatim summary of a conversation with Ian Bassin and Piali Mukhopadhyay, GiveDirectly, August 23, 2016, Pg 5.

• 43
  • For example, see GiveWell, spot checks of Segovia follow-up data sample, 2016
  • When GiveDirectly first started its "distributed cash out" model in Uganda (instead of hosting "cash out days" GiveDirectly conducted some quick follow-up phone calls with vulnerable recipients in Uganda; in the sample of 67 call records GiveDirectly sent us, only 9 vulnerable recipients had already withdrawn their funds successfully (although many had received the transfer and were planning to withdraw it soon, and 22 responses were ambiguous). GiveDirectly, Distributed cash out follow up with vulnerable recipients. Note that some of the comments indicate that the person surveyed was not the recipient, but someone close to the recipient or the recipient's helper. We are not sure how indicative this data is of difficulties obtaining funds.

• 44

  Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016

• 45
  • GiveDirectly 's blog post on the staff fraud: GiveDirectly blog, Fighting fraud in Uganda
  • "Two GD staff members stole 2% of transfers on Google campaign ($20,500 in total) in form of 50,000 UGX deductions from penultimate or final transfers (85%) or theft of entire final transfers (15%)"GiveDirectly, Check in with GiveWell, September 2014

• 46

  "Discovery of the fraud

  • A GiveDirectly recipient had given their SIM card to the SFO [Senior Field Officer] (whose contract had been terminated in April due to an unrelated issue involving a fraudulent receipt he brought to GiveDirectly for reimbursement). The recipient asked the SFO to replace his SIM card (recipients have to travel about 4 hours round trip to get this done) and the SFO had not returned it. This report was made to the hotline that the OM [Office Manager] was answering three months after the recipient had given over their SIM card. Mr. Skeates audits the logs of these hotline calls.
  • GiveDirectly had been planning a full round of follow-up surveys as part of its normal process, but accelerated the follow-up surveys in response to this issue. GiveDirectly’s backcheck team paused their work on enrollment for the Uganda 2M campaign and called all the recipients in that village (Kosile) to ask whether they had received all of their transfers, had any problems withdrawing, and whether GiveDirectly currently had any of their documents (e.g., SIM cards, IDs).
  • During this process, there were some reports of problems during paydays. Recipients were initially hesitant to come forward.
  • Because of the reports of payday problems, GiveDirectly began calling another village, Kawo, the following day to gather more information. Recipients in Kawo were far more forthcoming with information when asked specific questions about payday problems.
  • GiveDirectly continued follow-ups (conducted by a new Field Officer brought on after the SFO's and OM’s dismissals) until it had spoken to about 92% of its recipients across all villages. GiveDirectly also conducted in-person visits to villages."

  Conversation with GiveDirectly, September 5, 2014

• 47

  Changes implemented in response to staff fraud
  In the Uganda pilot campaign, GiveDirectly cash out days were managed by the Uganda Senior Field Officer, the Uganda Office Manager who also managed the GiveDirectly hotline, and mobile money agents. After these people fraudulently diverted funds from recipients, GiveDirectly implemented a series of changes:

  • Terminated the GiveDirectly staff who had been involved in the fraud; started working with new mobile money agents.
  • Removed all of its staff from the cash out day process except the Uganda Field Director. The Uganda Field Director had previously been making planned visits to oversee some of the cash out days; he now actively manages all of them along with new mobile money agents.
  • Appointed community-nominated monitors to assist the Uganda Field Director on the cash out day with translation, observe transactions between recipients and mobile money agents, and report any issues they see. GiveDirectly compensates the monitors with 10,000 UGX (~$4) for their time during a cash out day.
  • Developed networks of English-speaking informants who are not formally announced within the villages, but are tasked with also reporting any issues they see regarding transfers. To date, 4 of the 9 informants have provided GiveDirectly with helpful information, such as identifying that households in the enrollment process were actually ineligible, and telling GiveDirectly that someone had taken a recipient's phone after the recipient passed away.
  • Moved the GiveDirectly call center (hotline) to Kampala, to increase the separation of call center staff from field staff, who are based in Mbale.
  • Tasked the call center with calling a randomly selected 10% of the village during a cash out day to see if it is going smoothly.
  • Changed the contractual agreement GiveDirectly has with mobile money agents to include an indemnity clause, so that in the case of stolen funds, GiveDirectly could remove funds directly from a mobile money agent's account.

  Conversation with Stuart Skeates, GiveDirectly, October 20-21, 2014

• 48
  • GiveDirectly has piloted a few changes that would increase security, including the use of biometrics (more) and partnering with a banking partner for cash out days (more).
  • In late 2015, GiveDirectly piloted the distributed cash out model in Uganda that it now uses. It is possible that a distributed cash out model is more secure from large-scale crime than a payday model because a) without the cash out days, funds are not as concentrated in one location and b) it's easier to obscure who is a recipient when recipients withdraw their funds at different times from different places. Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015.

• 49
  • Note that sometimes as GiveDirectly scales and moves into new areas, it could end up being less well known. For example, when GiveDirectly moved most of its Kenya operations from Siaya County to Homa Bay County, it experienced a high rate of people refusing to be enrolled. GiveDirectly thinks this may be because many people in Homa Bay had not heard of GiveDirectly before and were suspicious of the program.
  • "GiveDirectly has seen an uptick in the rate of refusal to participate in its cash transfer program in Homa Bay. The root of this development is not clear, and GiveDirectly has not yet identified a solution. In some cases, community members are led by local religious leaders or local government to mistrust the program. In Siaya County, this issue did not arise, possibly because GiveDirectly covered such a large portion of the county that in any new area it entered, people were already aware of the program and knew that it was trustworthy." Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016, Pg 5.

• 50

  The cash out days that GiveDirectly used to administer in Uganda seemed to be particularly easy targets for large-scale theft, as there was a substantial amount of cash in one location (although it is our understanding that GiveDirectly's partners sent security personnel to the cash out days to mitigate this risk). Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015. If GiveDirectly decides to run cash out days again, either in Uganda or a new location, we will slightly increase our concern about theft.

• 51

  GiveDirectly notes: "...we see two possible forms of larger scale crime/interference. The first is interference or expropriation by other institutional actors. As we have relayed previously we have tried to hedge against this by improving governmental contacts. The second is some larger scale organized crime, but we do not see this as a threat that meaningfully increases as we scale as any attempt at theft would still need to target small individual disbursed transactions, which is the same fundamental risk to our current program that we believe our current structure has had a strong track record in mitigating." Ian Bassin and Carolina Toth, email to GiveWell, June 14, 2016

• 52

  Despite the mobile money security measures, Lydia Tala, an Assistant Field Manager 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. Lydia Tala, GiveDirectly Field Assistant, conversation with GiveWell, November 7, 2012

• 53
  • Ms. Tala (an Assistant Field Manager, see footnote above) 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. Lydia Tala, GiveDirectly Field Assistant, conversation with GiveWell, November 7, 2012
  • GiveDirectly told us that it recognizes this issue and maintains a hotline to provide recipients with assistance in navigating the M-PESA system: GiveDirectly helps recipients with issues using M-PESA via our hotline. Staff sometimes contact M-PESA agents to notify them one of our clients will be visiting and may need assistance. Piali Mukhopadhyay, COO, International, GiveDirectly, email to GiveWell, November 23, 2012

• 54

  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.

  • @GiveDirectly, Siaya Verification Stats@
  • GiveDirectly, Rarieda verification stats
  • GiveDirectly, Siaya follow-up data - disaggregated
  • GiveDirectly, Nike follow-up data - disaggregated
  • GiveDirectly, Google follow-up data - disaggregated (LS - long)
  • @GiveDirectly, Rarieda Top-up verification (short)@
  • GiveDirectly, Rarieda verification (top ups), May 26, 2013
  • GiveDirectly, Siaya verification, June 15, 2013
  • GiveDirectly, Google verification, September 2013
  • GiveDirectly, Nike verification (final), September 2013
  • GiveDirectly, Kenya follow up data, November 2014
  • GiveDirectly, Uganda pilot follow up data, April 2014
  • GiveDirectly gave permission to publish the following databases on the condition that all personally identifying information was removed. Due to the size of the databases, we have not yet anonymized them and therefore have not published them. If you are interested in the content of these databases, please contact us at info@givewell.org.
    • GiveWell, GiveDirectly follow up surveys summary - Uganda, September 2015
    • GiveWell, GiveDirectly follow up surveys summary - Kenya, September 2015

  The percentage of recipients who report issues withdrawing funds is consistently low (<5%) across campaigns. See the table below 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 follow-up surveys of recipients in Kenya from 2014, recipients reported receiving various amounts between 37,000 KES – 40,000 KES. This is based on data GiveWell reviewed in 2014. GiveDirectly, Kenya follow up data, November 2014. Other than the mobile phone purchase deduction, we do not know the causes of this variance.

• 55

  "There were four types of issues that were responsible for most of the people who were unable to withdraw funds at the cash out day: […] MTN (the payment provider) had not yet activated the funds in the person's account. Mr. Skeates said that this was not a common problem in the previous campaign in Uganda, but it affected many people at this cash out day. He estimated that people affected by this issue would receive their first installment of funds in another 2-3 weeks. […]" GiveWell site visit to GiveDirectly, October 2014, Pg 6.

• 56
  • A challenge of backchecks is that field officers often end up teaching recipients how to use their cell phones and mobile money accounts, so that they can access their money and are less likely to be scammed. Field officers will teach recipients how to check their balance and distinguish messages that say they received money from other messages. Field officers will sometimes write out instructions for recipients in the local language that describe step-by-step how to operate the phones and mobile money accounts. Recipients often do not understand the importance of keeping their PIN numbers secure. Some elderly recipients do not want a trustee to manage their transfers, but they are unable to remember their PIN numbers or read the messages on their phone, so they are more likely to have issues receiving transfers. Some people are still skeptical that the money will actually come, even after they have received messages on their phone, so they don’t pay attention to the instructions about how to use the mobile money account. Conversation with GiveDirectly field staff, October 20-21, 2014, Pg 3.
  • Mr. Skeates, the Uganda Field Director, made announcements at the start of the event, translated by the 2 community monitors. The announcements included reminders about how to keep account information secure (e.g., after entering your PIN number, make sure to press "send" before handing your phone back to the agent; make sure you have received a confirmation message after withdrawing and that it states the correct amount; count the cash immediately after receiving it.) GiveWell site visit to GiveDirectly, October 2014 Pg 5.

• 57
  • Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015
  • The summary results of these quality audits for Kenya can be seen in some monthly operations reports (e.g. GiveDirectly, Monthly operations report, August 2015). GiveDirectly has sent us results from these audits for the Ug-201503 campaign as well, which we have briefly reviewed but have not published. GiveDirectly, Uganda model variations quality audits - census and GiveDirectly, Uganda model variations quality audits - registration

• 58

  Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015

• 59
  • A "trustee" is someone who is registered for the mobile money payments on behalf of the recipient. A "helper" is someone who is not registered for the payments, but who helps the recipient with the process (e.g. assisting with transportation to the locations one can withdraw cash or helping to use the phone properly).
  • Roughly, the process for choosing a trustee or helper is to get the recipient alone (out of earshot of family) and ask who that recipient trusts the most. This choice is typically validated with some neighbors (ensuring that that person is regarded as trustworthy). Generally, GiveDirectly prefers to choose trustees and helpers who are already recipients themselves, so that they have less of an incentive to steal the transfer and so that GiveDirectly can stop transfers to them if they are not performing their role appropriately.

  Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015. Note that GiveDirectly has offered to send us the protocol used to determine helpers and trustees; we have not yet reviewed this protocol.
  

• 60

  "Following its Google-funded campaign, GiveDirectly surveyed recipients in detail on how they spent their transfers. Given the limitations of this kind of self-reported data, GiveDirectly has not continued this practice. It prefers to rely on more accurate data gleaned through randomized controlled trials (RCTs), and expects to collect more [of] this type of information in future studies or campaigns, such as its ongoing RCT in coffee farming communities." GiveWell's non-verbatim summary of a conversation with Ian Bassin and Piali Mukhopadhyay, GiveDirectly, August 23, 2016, Pg 4.

  • GiveDirectly, Kenya follow up data, November 2014
  • GiveDirectly, Uganda pilot follow up data, April 2014
  • GiveDirectly, Rarieda verification (top ups), May 26, 2013
  • GiveDirectly, Siaya verification, June 15, 2013
  • GiveDirectly, Google verification, September 2013
  • GiveDirectly, Nike verification (final), September 2013
  • GiveWell, GiveDirectly follow up surveys summary - Uganda, September 2015
  • GiveWell, GiveDirectly follow up surveys summary - Kenya, September 2015 (Note: GiveDirectly gave permission to publish this database on the condition that all personally identifying information was removed. Due to the size of the database, we have not yet anonymized it and therefore have not published it. If you are interested in the content of this database, please contact us at info@givewell.org.)

• 61

  GiveDirectly, What We Do - Who We Serve, September 2016

• 62

  GiveDirectly, What We Do - Who We Serve, September 2016 See the chart in the upper left section of the web page.

• 63

  GiveDirectly, What We Do - Who We Serve, September 2016 See the chart in the upper left section of the web page.

• 64

  For full details of our interviews with recipients, see GiveWell Site visit notes.

• 65

  Provided by Google via Citibank N.A. on November 15, 2012.

• 66

  Lydia Tala, GiveDirectly Field Assistant, conversation with GiveWell, November 7, 2012.

• 67

  Provided by Google via Citibank N.A. on November 15, 2012.

• 68

  Ian Bassin and Piali Mukhopadhyay, conversation with GiveWell, August 23, 2016

• 69
  • "The ‘thatch roof, mud walls, mud floor’ eligibility criteria was not going to work in Homa Bay, as <3% households had thatch roofs." Carolina Toth, email to GiveWell, October 20, 2015
  • GiveDirectly has told us that this is because there is very little grass in Homa Bay County. GiveDirectly thinks that people in Homa Bay have spent more money historically on their buildings (because the cost of thatch roofs was not cost-competitive).
  • "However, more people in Homa Bay have metal roofs than in Siaya. This is likely because the grass for thatched roofs does not grow in Homa Bay, so the price of thatch is less competitive." Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016, Pg 6.

• 70

  Paul Niehaus and Ian Bassin, conversation with GiveWell, September 15, 2016

• 71

  "Physically closer to Rarieda than Siaya was
  Poverty rate is higher than in Rarieda (50% vs 46%)"
  GiveDirectly, Update for GiveWell, February 2016, Pg 13

• 72
  • Haushofer and Shapiro 2013 Policy Brief, Table 10, Pg 38.
  • "Additional variables in table 9 show the frequency of any episode of physical, sexual or emotional violence in the last six months, and the percentage of respondents who believe that domestic violence is justified in some instances. The point estimates for these variables suggest a reduction in domestic violence, although none are individually different from zero at conventional significance levels." Haushofer and Shapiro 2013 Policy Brief, Pg 21.

• 73
  • GiveDirectly sent 8 versions of the survey forms it used, as the form was modified over time. For the most recent version we have seen, see GiveDirectly, Kenya verification template, August 2013. We expect that the questions have changed slightly since this version.
  • For earlier versions, see @GiveDirectly, Verification Template (October 1, 2012)@ and @GiveDirectly, Verification Template (November 7, 2011)@ (corresponding data for the latter: GiveDirectly, Verification data (November 17, 2011))

• 74
  • "For example, following concerns about missed inbound calls, it decided to upgrade its call center technology. This process is ongoing; GiveDirectly expects to see progress in this area within the next few months." Ian Bassin and Piali Mukhopadhyay, conversation with GiveWell, August 23, 2016, Pg 2.
  • [GiveWell]: "How did GiveDirectly become aware that it might have been missing some incoming calls to the hotline and how will the new call center technology fix this issue?"
    [GiveDirectly]:
    • "Hotline phones keep a record of missed calls and we were seeing more than usual
    • FOs in the field would hear anecdotally that recipients tried the hotline number and failed to reach
    • The new call center will have a centrally controlled hotline system where inbound calls are routed directly to the first available agent (right now they are being routed sequentially). New technology will also allow us to monitor call volumes and staff the hotline dynamically as certain times of days and days of the month see higher volumes"

    Piali Mukhopadhyay, COO, International, GiveDirectly, email to GiveWell, August 25, 2016

• 75

  GiveWell, spot checks of Segovia follow-up data sample, 2016 Note that we did not specify to GiveDirectly which sample to send and they did not say how they selected this particular sample.

• 76
  • GiveWell, spot checks of Segovia follow-up data sample, 2016. While there were at least 2 events reported for every adverse event that GiveDirectly staff asked about, the rate of other adverse events was effectively 0%.
  • The rates of issues we've seen reported by GiveDirectly are typically also quite low:
    • GiveDirectly's website reports that only 0.3% of recipients in Kenya were asked for a bribe; we are not sure over what time period or from what sample this figure was calculated. GiveDirectly, Performance - Quality of Service, September 2016
    • In August 2016, GiveDirectly mentioned that its Uganda campaign only has a 0.52% complaint rate from follow-up calls; again, we are not sure from what sample this figure is calculated: "The most common complaints/comments are from people seeking transfers, either people hoping GD will come to their area, people seeking a greater transfer, or ineligibles or people whose transfers have been delayed for some reason seeking to receive. The other recently common complaint are people saying the money is evil in some way. For context on size, Uganda rolling currently has a 0.52% complaint rate of for all follow up calls." Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, August 25, 2016
  • Note that GiveDirectly has told us complaints tend to be higher when it first enters a new area: "When GiveDirectly enters a new area, complaint rates tend to be relatively high. This is because GiveDirectly records as "complaints" callers who request payments but are not eligible for its program. When GiveDirectly initially enters a new area, word spreads that GiveDirectly is distributing funds but people misunderstand the program, so these call volumes tend to be high. For example, the initial rate in GiveDirectly's new Rwanda campaign was 30.94%. Field teams are responsible for identifying the source of and addressing high complaint rates." GiveWell's non-verbatim summary of a conversation with Ian Bassin and Piali Mukhopadhyay, GiveDirectly, August 23, 2016, Pg 2.

• 77
  • GiveDirectly, Kenya hotline log, July 2013 (May 2012 – July 2013)
  • GiveDirectly, Follow-up tracker, July 2013 (July – October 2013)
  • GiveDirectly, Follow-up tracker, October 2014 (January 2013-September 2014). This file also contains issues reported through other channels, such as to field staff during field visits and during follow up surveys.
  • GiveDirectly, Kenya top 10 adverse events 2015 (Note: we are unsure if all of the issues reported in this file were reported through the hotline.)
  • GiveDirectly, Uganda top 10 adverse events 2015 (Note: we are unsure if all of the issues reported in this file were reported through the hotline.)
  • GiveDirectly, Kenya randomized sample of adverse events, 2014-2015
  • GiveDirectly, Uganda randomized sample of adverse events, 2014-2015
  • We have not checked to see whether the issues reported in these files are overlapping, though note that the time ranges are overlapping.

• 78

  GiveDirectly, Follow-up tracker, October 2014 Sheet: "Summary" In 2015 we did not ask GiveDirectly to send us a follow-up tracker because it is our understanding that sharing the follow-up tracker databases take a significant amount of effort on GiveDirectly's part (much of the effort goes into anonymizing the entries). Instead, we requested a random sample of adverse events and a sample of some of the most serious adverse events from the previous year. We have reviewed these samples, but have not made them public (they are not anonymized); the issues they cover are broadly similar to the types of issues we have seen in previous years.

• 79

  GiveDirectly, Follow-up tracker, October 2014 Sheets: Summary; GiveWell notes.

• 80

  See our intervention report on cash transfers.

• 81

  Ian Bassin and Carolina Toth, email to GiveWell, June 14, 2016

• 82

  Haushofer and Shapiro 2013 Policy Brief, Table 10, Pg 38.

• 83
  • The RCT of GiveDirectly’s program in Rarieda did not find an increase in crime, so at that scale it does not seem to be an issue. It’s possible that crime would be a more serious problem if GiveDirectly became a substantially larger and better-known organization. Conversation with GiveDirectly, December 7, 2013
  • GiveDirectly has become very well-known in Siaya County, Kenya, but has not seen a significant increase in crime rates there. As GiveDirectly begins to work in Homa Bay County, it expects crime rates to be lower, because the context is similar to Siaya but fewer people know about GiveDirectly in Homa Bay. If GiveDirectly were to start working in more urban areas, where crime rates tend to be higher, GiveDirectly would put more time into strategizing about crime and security. Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015

• 84Example: "The recipient was given all the cash withdrawn as she requested.. then as she {deidentified} she was just outside the house since she's blind and her door is not lockable, she came to find her money missing but she doesn't know who might have stolen the KES."GiveDirectly, Follow-up tracker, October 2014 Sheet: "Tracker" (text removed in deidentification.)

• 85

  Example: "He was phoned by unknown person who posed as GD staff and requested for 500/= bribe to hasten the processing of his transfer."GiveDirectly, Follow-up tracker, October 2014 Sheet: "Tracker" (text removed in deidentification.)

• 86Example: "She lost the phone, and in the process of renewing the line the Agent transfer the money to another line in order to withdraw later."GiveDirectly, Follow-up tracker, October 2014 Sheet: "Tracker" (text removed in deidentification.)
  
• 87

  Some recipients, especially elderly ones, have to learn how to use cell phones for the first time in order to manage the GiveDirectly transfers in mobile money accounts. These people have a more difficult time understanding how to keep their phones secure; for example, they often keep the phone in its original packaging and do not conceal it. Another problem with security is that some recipients will share the PIN numbers for their mobile money accounts, either intentionally or unintentionally by handing the phone to a mobile money agent before pressing "Send" (so the PIN number is still apparent on the screen of the phone.) This makes recipients more vulnerable to people who wanted to steal money from their accounts. Teaching PIN safety has long been a priority, and GiveDirectly has added additional emphasis on the topic (e.g., emphasis during village meetings, additional trainings given by the mobile provider) Improved security is a reason why GiveDirectly is interested in piloting biometric authentication for mobile money accounts, though it does not currently have plans to do so. Conversation with Stuart Skeates, GiveDirectly, October 20-21, 2014, Pgs 2-3.

• 88
  • Conversation with Stuart Skeates, GiveDirectly, October 20-21, 2014 (unpublished)
  • GiveDirectly, Follow-up tracker, October 2014;GiveDirectly, Kenya hotline log, July 2013 (May 2012 – July 2013); GiveDirectly, Follow-up tracker, July 2013 (July – October 2013)

• 89

  In Siaya, GiveDirectly experienced some difficulty with people pretending to live in poorer quality housing: "[GiveWell]: There were multiple comments about recipients switching from iron-roofed houses to grass-roofed houses in order to be enrolled. Is this becoming a more common problem? How does GiveDirectly discover these instances? [GiveDirectly staff]: This was a common problem in Siaya -- where everyone knew, from our work there, that our criteria relied on housing materials, therefore they’d try to pose as living in such a house to be eligible. There are a number of ways this can be discovered -- either by asking neighbors, or observing that a recipient does not have at hand items (like vaccination forms) that would be in their possession if they were actually at their home, suggesting they don’t actually live where they are claiming to live." GiveDirectly staff, responses to monitoring questions, October 11, 2016, pg. 3.

• 90
  • "GiveDirectly stops issuing transfers after two years and clearly informs recipients that they should expect this." GiveDirectly, Offering Memorandum (January 2012), Pg 33.
  • Update [November 2014]: the two year timeline mentioned above is now outdated; transfers are generally sent over a period of 8 months in Kenya and 10 months in Uganda. It is still the case that recipients can only receive one full transfer, and that they are ineligible for additional transfers thereafter. Conversation with Carolina Toth, GiveDirectly, November 20, 2014
  • "Attrition was not a significant concern in this study because it became evident early on in GD’s work in Kenya that respondents were highly interested in maintaining relations with GiveDirectly in the hope of receiving future transfers (although these are never promised)." Johannes Haushofer and Jeremy Shapiro, Welfare Effects of Unconditional Cash Transfers: Pre-Analysis Plan, June 27, 2013, Pgs 5-6.

• 91

  In the Rarieda campaign, 67% (359 of 536) of recipients waited less than a month, 84% (448 of 536) waited 3 months or less, and 6% (34 of 536) waited 6 months or more. In the Siaya campaign (a later campaign), 188 of 193 recipients waited less than a month, and the remaining 5 waited 2-3 months.

  • GiveDirectly, Enrollment speed of distributions - Siaya and Rarieda
  • GiveDirectly commented: "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, Updated data (March 31, 2012)

• 92

  "For its standard Kenya and Uganda programs, GiveDirectly has implemented a rule in Segovia to block payments until the previous one has been confirmed: for example, first and second lump sum payments are blocked until token and first lump sum payments, respectively, have been confirmed via a follow-up call or visit." GiveWell's non-verbatim summary of a conversation with Ian Bassin and Piali Mukhopadhyay, GiveDirectly, August 23, 2016, Pg 4.

• 93
  • Paul Niehaus, GiveDirectly Founder, email to GiveWell, November 20, 2012.
  • Email from Paul Niehaus, President, GiveDirectly, and Joy Sun, COO, Domestic, GiveDirectly, November 18, 2013

• 94
  • GiveDirectly, Monthly operations report, February 2016.
  • GiveDirectly's website notes that, in Kenya, "On average, it takes us 9 weeks from enrolling a recipient to starting his or her transfers." GiveDirectly, Performance - Quality of Service, September 2016. We are not sure over which time period this figure was calculated.

• 95
  • 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.
  • GiveDirectly, Kenya hotline log, July 2013
  • GiveDirectly, Follow-up tracker, July 2013
  • GiveDirectly, Follow-up tracker, October 2014
  • Data from GiveDirectly indicates that on average 11% of recipients in Kenya campaigns are delayed due to registration issues. GiveDirectly, Monthly operations report, August 2015

• 96

  "The main downside to both of the mobile money services in [Uganda] as compared to MPESA in Kenya is that there are fewer mobile money agents in the rural areas that GiveDirectly is targeting. In response, GiveDirectly has been more proactive in coordinating with the mobile money service for the transfers that have begun, for example, by giving the mobile money service advanced notice before sending the funds so that agents could be prepared. In some cases, agents traveled to the villages in which recipients live to reduce recipient travel time." Conversation with Paul Niehaus, President, and Joy Sun, COO, Domestic, GiveDirectly, July 18, 2013

• 97

  Carolina Toth, email to GiveWell, September 14, 2015

• 98

  GiveDirectly, Monthly operations report, February 2016.

• 99
  • GiveDirectly, Monthly operations report, February 2016
  • As of August 2015, GiveDirectly had 60 staff: 3 Field Directors, 3 Field/Finance Managers, 5 Associate Field Managers, 46 Field Officers, and 3 other staff (@GiveDirectly, Monthly Operations report, August 2015@), meaning that it has grown by an additional 50% in just 6 months.

• 100

  GiveDirectly has so far received about six applications for every one FO [Field Officer] position it has open, which it sees as an indicator that the necessary talent is available for it to scale its operations. Conversation with Paul Niehaus, President, and Joy Sun, COO, Domestic, GiveDirectly, July 18, 2013 (unpublished)

• 101
  • Paul Niehaus, GiveDirectly Founder, conversation with GiveWell, October 22 2012.
  • GiveDirectly, Budget summary, July 2013
  • $12 per day seems very roughly to be in line with market value:
    • $12 per day * 5 days a week * 52 weeks per year = $3,120 per year
    • This salary site indicates that lower-skilled workers are paid ~20,000 - 50,000 KES per month ($198 - $497 per month, according to Google as of May 5, 2016), which comes out to $2,376 -$5,964 per year.
    • We would guess that GiveDirectly's Field Officer position is generally lower-skilled (e.g., it involves significant surveying of recipients, which we'd expect to be paid similarly to other types of administrative assistant roles).

• 102

  Conversation with Piali Mukhopadhyay, COO, International, GiveDirectly, October 22, 2013

• 103

  GiveDirectly has told us that it seeks to influence both the official development assistance that high-income countries provide and individual donor contributions. Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016

• 104

  Ian Bassin and Carolina Toth, email to GiveWell, June 14, 2016

• 105

  Some of that evidence must be kept confidential. Note that we have not vetted the examples GiveDirectly has provided.

• 106

  GiveDirectly, Update for GiveWell, May 2015 (the slide with details of the examples mentioned has been redacted).
  GiveDirectly, Update for GiveWell, September 2015 (two slides with details of the examples mentioned have been redacted).

• 107

  Note that this includes Good Ventures: see this blog post.

• 108

  Ian Bassin and Carolina Toth, email to GiveWell, June 14, 2016

• 109

  For example.

• 110

  For example:

  • "Survey of 31 ongoing studies found that 6 have a cash arm currently and 20 would like to add one."
  • "GD declined to participate in impact evaluation of cow distribution; study will proceed, may or may not include a cash arm"
  • "GD declined to pursue implementation of nutrition benchmarking study, but will provide advice."
  • "Discussing multi-country comparison of current conflict & jobs programming to cash transfers, using matching funds"
  • "[W]e are seeing growing momentum behind cash transfers"

  GiveDirectly, Update for GiveWell, September 2015, pgs. 5-6.

• 111

  For example: "Indonesian government and World Bank ([Redacted]). WB pushing for an RCT comparing cash to other approaches with conditional funding from DIV and GDL. Pending Indonesian government’s buy-in. Motivated by GD model, GD visited to present on impacts & methods" GiveDirectly, Update for GiveWell, September 2015, pg. 6.

• 112

  Ian Bassin and Carolina Toth, email to GiveWell, June 14, 2016

• 113

  For example: "Indonesian government and World Bank ([Redacted]). WB pushing for an RCT comparing cash to other approaches with conditional funding from DIV and GDL. Pending Indonesian government’s buy-in. Motivated by GD model, GD visited to present on impacts & methods" GiveDirectly, Update for GiveWell, September 2015, pg. 6.

• 114

  For example: the Brookings Blum Roundtable and a DFID high-level panel on cash transfers. GiveDirectly, Update for GiveWell, September 2015, pg. 6.

• 115

  This is based on GiveDirectly's description of how the project started. Paul Niehaus and Carolina Toth, conversation with GiveWell, May 28, 2015

• 116

  GiveDirectly has told us that, although comparing the cost-effectiveness of the programs involved in the Rwanda benchmarking experiment is part of the experiment, doing so is challenging, in part because one of its partner organizations may not have high quality data on its expenses. Challenges like this make us unsure how likely it is that even experimentation designed to be policy-relevant will end up impacting funders. Paul Niehaus, Carolina Toth, and Ian bassin, conversation with GiveWell, August 12, 2016

• 117

  Paul Niehaus, Carolina Toth, and Ian Bassin, conversation with GiveWell, February 23, 2016

• 118

  GiveWell, GiveDirectly financials - 2016, "2016-efficiency ratio" sheet.

• 119

  Carolina Toth, conversation with GiveWell, November 12, 2015

• 120

  GiveWell, GiveDirectly financials - 2016, "2016-efficiency ratio" sheet.

• 121

  Carolina Toth, email to GiveWell, November 10, 2015 We believe the points apply to our more recent estimates as well.

• 122

  "We are actually aiming to make Rwanda’s retail program more efficient. We are making two changes to achieve this: (1) we are eliminating token payments. Instead, the first payment issued will be the first lump sum, after which we will do follow up calls to ensure proper receipt; (2) we are eliminating backcheck. In its place, we are flagging any discrepancies between census and registration for individual audits and then, on top of that, adding an additional randomized selection of HHs for audit until we achieve 40% of hhs for audit. We think this will be more efficient while still ensuring accuracy and avoiding fraud. We may eventually migrate these changes to other countries but are starting in Rwanda." Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 11, 2016

• 123

  GiveDirectly, Room for funding update for GiveWell, October 2016, Pg 6.

• 124
  • Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 17, 2016
  • GiveDirectly, Room for funding update for GiveWell, October 2016, Pg 6. Note that GiveDirectly had already raised $9.5 million of the $17.5 it expected as of October 2016 (see Pg 3).
  • GiveDirectly, Room for funding update for GiveWell, October 2016, Pg 6. It is our understanding from previous conversations with GiveDirectly that even if it does not raise the full amount it would like for its basic income study ($30 million total), it will move ahead with the project with the funding it has available, though the power of the study will not be as high.

• 125
  • We expect GiveDirectly to raise about $6 million in unrestricted funding available for transfers in 2017 over the rest of its budget year (note our estimate differs from GiveDirectly's).
    • GiveDirectly's estimate: "How much would GD raise through 2/28 absent any recommendation from GW:
      • We estimate absent GW we would raise ~$6.1m in retail revenue through 2/28. Of that, $3m is slated to be transferred before 2/28, leaving us with $3.1m in available funding for 2017.
      • We got this figure by trying to estimate how much of our revenue during the 2015 holiday period came from non-GW related sources, removing a large outlier, and then applying our current rate of YOY growth to project how much that figure is likely to be in 2016. We'd be happy to walk through those figures in detail if helpful.
      • It’s also likely that some donors previously influenced by GW would continue to donate to GD even absent a future GW recommendation. We do not have an estimate for this figure so the true number we would raise would likely be somewhat higher."

      Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 14, 2016

    • GiveWell's estimate:
      • At the end of February 2016, GiveDirectly had about $29.2 available for its standard cash transfers (excluding institutional funders' funding) :
        • $0.2 million was restricted to Kenya.
        • $8.3 million was restricted to "flexible funding" that must be used for cash transfers.
        • $49.5 million was unrestricted. Of that, $25 million was set aside for partnership activities and fundraising, and $1.7 million was set aside for Global Management costs, and another $2.1 was set aside for fundraising, leaving $20.7 million available for standard cash transfers.
        • 0.2 + 8.3 + 20.7 = 29.2.

        GiveDirectly, Update for GiveWell, February 2016 Pgs 5-6.

      • Our understanding is that this was raised in ~September 2015 to end of February 2016 (since funds raised before that were all scheduled to be committed to households before then). We add $1.8m to this to get an estimate of the total GD raised in that period because it looks like about that much was allocated to non-transfer expenses in that period (changes in reserves, global management, and fundraising). Total raised estimate: ~$31 million.
      • The amount we tracked as due to GiveWell in that period, including Good Ventures ($9.8m), two large funders ($9m), and and others ($3.2m): $22m
      • So, the amount that GiveDirectly raised excluding GiveWell-influenced funds: ~$9m ($31 - $22)
      • We then exclude a large $3m donation that GiveDirectly told us was one-off and assume 50% growth over last year: ~$9m [(9-3)*1.5)] GiveDirectly, Room for funding update for GiveWell, October 2016, Pg 6.
      • Finally, GiveDirectly told us that it intended to spent $3 million of what it raised over giving season on cash transfers, bringing us to $6 million (9-3): "We estimate absent GW we would raise ~$6.1m in retail revenue through 2/28. Of that, $3m is slated to be transferred before 2/28..." Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 14, 2016
  • We estimate that GiveDirectly will raise about $9.8 million in unrestricted funding between March 2017 and August 2017.
    • GiveDirectly's revenue between March 2016 and July 2016 was about $12.5 million. Excluding GiveWell-influenced donors ($0.5 million) and grants for partnership projects we believe GiveDirectly received in that time period ($4.5 million and and $2 million), GiveDirectly raised $5.5 million.
    • $5.5 million over 5 months implies that GiveDirectly raises about $1.1 million per month.
    • So, between March 2016 and August 2016, we estimate that GiveDirectly raised about $6.6 million in funding for its standard cash transfer campaigns.
    • Assuming a 50% increase in fundraising next year, we estimate that GiveDirectly will raise $9.8 million (6.6*1.5) between March 2017 and August 2017.

    GiveWell, GiveDirectly financials - 2016, "2016 - Commitments" sheet.

  • $6 million + $9.8 million = $15.8 million.
  • In the past, GiveDirectly has raised significantly more than we expected. For example:
    • In fall 2015, GiveDirectly predicted that it would raise $4 million in retail donations during the 2015 giving season (Sep 2015 - Feb 2016). GiveWell, GiveDirectly financials 2015, Sheet: "2015-RFMF scenarios"
    • Excluding grants from Good Ventures and a grant that GiveDirectly had informed us was expected, it raised roughly $12.2 million in donations. GiveDirectly, Revenue by referral source 2015
    • The $12.2 million figure excludes donations in February; in April 2015, GiveDirectly told us that it raised an additional $1.5 million in February - also more than it expected. Carolina Toth, email to GiveWell, May 3, 2016
    • Note: If GiveWell were to continue recommending GiveDirectly and if GiveWell donations to GiveDirectly grew at approximately the same pace they have grown in previous years, then GiveDirectly would expect to raise $11 million through February 2017. GiveDirectly, Room for funding update for GiveWell, October 2016, Pg 6. Subtract the $17.5 million for the basic income study from $28.5 million raised to arrive at $11 million.

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  This is based on our records of how much we influenced to GiveDirectly last year, when our main recommendation, after accounting for grants from Good Ventures, was to give to the Against Malaria Foundation.

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  Conversation with GiveDirectly, October 6, 2014

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  • GiveDirectly, Room for funding update for GiveWell, October 2016
  • GiveDirectly staff, conversation with GiveWell, October 6, 2016

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  See this spreadsheet for our analysis.

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  You can also see our analysis here.

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  GiveDirectly, Room for funding update for GiveWell, October 2016, Pgs 2 and 4.

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  "$20m and $11m: In both these cases, the damage would potentially be more severe... When successful companies lay off 15% of staff it makes news. Even companies our size make news when they lay off 10% of staff. A contraction like this would require a 33-50% reduction in our staff."
  Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 14, 2016

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  • "$30m: ...This would look similar to the $36m scenario we discussed on the call, but one team would operate at half capacity. It would take roughly half a year to scale back up from a hit this size." Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 14, 2016
  • Our guess about the countries GiveDirectly would operate in and at what capacity is based on GiveDirectly staff, conversation with GiveWell, October 6, 2016.

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  Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 14, 2016

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  "$30m: ...This would look similar to the $36m scenario we discussed on the call, but one team would operate at half capacity. It would take roughly half a year to scale back up from a hit this size." Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 14, 2016
  

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  Two full teams in Kenya, one full team in Uganda, half a team in Rwanda (because the Rwanda team's capacity is partially being used on the Rwanda benchmarking project), and half a team (location unknown) managed by team leads that GiveDirectly expects will be occupied by partnership projects in the latter part of the year. GiveDirectly staff, conversation with GiveWell, October 6, 2016.

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  The 5.5 teams would include: Two full teams in Kenya, two full teams in Uganda, half a team in Rwanda (because the Rwanda team's capacity is partially being used on the Rwanda benchmarking project), and, collectively, a full team (location not known) managed by team leads that GiveDirectly expects will be occupied by partnership projects in the latter part of the year. GiveDirectly staff, conversation with GiveWell, October 6, 2016.

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  • "$20m and $11m: In both these cases, the damage would potentially be more severe... When successful companies lay off 15% of staff it makes news. Even companies our size make news when they lay off 10% of staff. A contraction like this would require a 33-50% reduction in our staff. We would expect the news to be public and could spur a "what went wrong for GiveDirectly?" narrative." Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 14, 2016
  • GiveDirectly told us that it intends to try to end its 2017 budget year with more funding on hand for retail cash transfer campaigns that it has in the past, because its strategy of trying to commit as much to its retail campaigns as it has available leaves it highly dependant on how much it can raise during giving season each year. GiveDirectly staff, conversation with GiveWell, October 6, 2016

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  "What would an aggressive stretch scenario look like in which we'd have a 95% chance of hitting a non-funding related barrier before accomplishing it in full:

  • While it is hard to estimate what growth rate we'd only have a 5% chance of achieving given the many uncertainties (e.g., when and how smoothly the USAID new countries come online, how quickly we can source new team leads, whether any fail to work out after a trial period, etc.), we would have low confidence in our ability to hire 4x our current retail team, or 16 team leads.
  • 16 more teams at 12m each would mean an additional $192m in retail capacity on top of the $66m we presented that we could move in our max scenario ($258m in retail capacity in total, and just over $300m when you add in partnerships).
  • We'd give ourselves a 5% chance of being able to do that if funding were not a constraint."

  Ian Bassin, COO, Domestic, GiveDirectly, email to GiveWell, October 14, 2016

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  See this spreadsheet.

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  We want GiveDirectly to be in a position where it can scale relatively quickly, up to the point where it can transfer $100 million within two years if necessary (i.e., in such a case where our other top charities have limited room for more funding). We believe that at $15 million, GiveDirectly could scale up to $40 million within a year. After scaling to this level, we believe GiveDirectly would be in a good position to potentially hit $100 million the following year.

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  $1.78m/month x 12 months = $21.4m/year. GiveWell, GiveDirectly financials - 2016, "2016-Commitments" sheet.

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  It is our understanding that GiveDirectly has been operating with approximately 3 full teams this year. GiveDirectly, Room for funding update for GiveWell, October 2016, Pg 2.

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  We assume the cost of delivering transfers is an additional 10%; this is what GiveDirectly has suggested we use in the past.

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  We assume that GiveDirectly will have 4 teams for the latter half of the year because it recently started its standard cash transfer campaign in Rwanda. $29 million over 7 months is $4.1 million per month. That's slightly over $1 million per team per month, or a rate of $12.4 million per team per year.

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  GiveDirectly staff, conversation with GiveWell, October 6, 2016.

• 147

  See GiveDirectly, Room for funding update for GiveWell, October 2016, Pg 2. In 2015, GiveDirectly transferred $15.9 million after transferring $10.3 million in 2014, scaling by a factor of 1.5. If GiveDirectly successfully transfers $38.4 million in 2016, it will have scaled by a factor of 2.4.

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  • GiveWell, GiveDirectly financials - May 2016 "2015-Rate of money moved" and "2016 May - Commitments + revenue" sheets.
  • GiveWell, GiveDirectly financials - 2016 "2016-Commitments" sheet.

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  GiveWell, GiveDirectly financials 2015, Sheet: "2015 - Rate of money moved." See chart for "Committed and distributed transfers to date."

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  GiveDirectly staff, conversation with GiveWell, October 6, 2016

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  • Paul Niehaus, Michael Faye, and Piali Mukhopadhyay, conversation with GiveDirectly supporters, August 11, 2015
  • In the past, GiveDirectly has noted that it has a pipeline of several Field Directors whom it could hire if additional Field Directors were needed. It is easy to find additional Field Managers, Assistant Field Managers, and Field Officers in Kenya and Uganda because unemployment rates are high, and many qualified candidates are looking for jobs. Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015
  • GiveDirectly has had more difficulty building up its domestic capacity. Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015

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  GiveDirectly staff, conversation with GiveWell, October 6, 2016

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  GiveDirectly staff, conversation with GiveWell, October 6, 2016

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  "GiveDirectly is also meeting with senior or retired government officials who can provide guidance on navigating the government and connect GiveDirectly to allies on the public sector side." Conversation with GiveDirectly, April 8, 2014, Pg 11.

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  "By now, GiveDirectly understands well the process for seeking government approvals in Kenya and does not see acquiring approvals as a major risk." Conversation with Piali Mukhopadhyay, GiveDirectly, October 20-21, 2014, Pg 3.

• 156

  GiveDirectly staff, conversation with GiveWell, October 6, 2016. As of late 2015, GiveDirectly had obtained permissions to enroll a cumulative capacity of about 100,000 households across Kenya and Uganda:

  • "Bukedia district [Uganda] still has 27,000 un-visited, eligible households, and country-wide registration is in process that will provide approval for all 7.3m households in Uganda." GiveDirectly, Update for GiveWell, May 2015, Pg 3.
  • "County-level government approval equivalent to ~70 K additional eligible households in Siaya and Homa Bay counties" GiveDirectly, Update for GiveWell, May 2015, Pg 3.
  • GiveDirectly already has approval to work in Bukedia district in Uganda, so even if it did not obtain country-wide permission in Uganda, it would still be able to work in Uganda for a long time. Most of the households that GiveDirectly has permission to enroll in Kenya are in Homa Bay County, although GiveDirectly still needs to speak to some of the districts in Homa Bay to get approval at a more local level. GiveDirectly could also go back and enroll the houses that are controls in the General Equilibrium study in Siaya County once that study is complete. Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015

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  GiveDirectly noted that it could go to some counties that were slightly further away from its current offices and that it was planning to open a new office in Kenya, which would allow it to enroll additional households in new areas. In Uganda, GiveDirectly has secured permissions to work in the district where the coffee RCT is taking place, so it could easily expand there and enroll more households for its standard cash transfer campaign if needed. GiveDirectly staff, conversation with GiveWell, October 6, 2016

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  • Political violence and terrorism are both risks in Kenya. Western Kenya has not been impacted since 2008 election violence
  • Operations in Uganda provide an alternative, and funds could be shifted more heavily toward Uganda

  GiveDirectly, Update for GiveWell, October 2014, Pg 16.

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  • "Dependency on a single provider: low risk. In Uganda, we have Ezee Money and Airtel as a back-up, and in Kenya could use Equity Bank."
    GiveDirectly, Update for GiveWell, July 2014 Pg 12.
  • "Selected MTN as preferred provider in Uganda after assessing performance of Ezee/MTN (building relationship with Airtel so as to have an additional hedge)"
    GiveDirectly, Update for GiveWell, July 2014 Pg 9.
  • GiveDirectly continues to seek other mobile money providers who it might want to partner with for future campaigns in Uganda (e.g., Airtel).
    Conversation with GiveDirectly, April 8, 2014 Pg 5.

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  Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015

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  GiveDirectly staff, conversation with GiveWell, October 6, 2016

• 162

  GiveDirectly staff, conversation with GiveWell, October 6, 2016

• 163

  GiveDirectly staff, conversation with GiveWell, October 6, 2016

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  "GiveDirectly has already begun to interview candidates to lead its marketing activities and expects to hire someone for the position by the end of 2015. It expects the rest of the marketing team (3-5 people) to be hired soon after the lead is on board." See here.

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  "GiveDirectly plans to use part of the grant from Good Ventures to hire a vice president of marketing. Progress on finding the right person has been slow, and GiveDirectly has not yet hired anyone for this position. (Update: in September 2016, GiveDirectly hired Matt Johnson, former CMO of Tough Mudder and VP of marketing at Seamless, for this role.) GiveDirectly recently began to work with a recruiting firm to assist with the hiring process."
  GiveWell's non-verbatim summary of a conversation with Paul Niehaus, Carolina Toth, and Ian Bassin, August 12, 2016, Pg 1.

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  There will be a national election in Kenya in 2017. GiveDirectly staff, conversation with GiveWell, October 6, 2016

• 167

  There will be a national election in Kenya in 2017. GiveDirectly staff, conversation with GiveWell, October 6, 2016

• 168

  There will be a national election in Kenya in 2017. GiveDirectly staff, conversation with GiveWell, October 6, 2016

• 169

  "They created GiveDirectly as a private giving circle in 2009 and opened it to the public in 2011 after two years of operational testing." GiveDirectly, FAQs 2015
  GiveDirectly, Team
  Paul Niehaus, GiveDirectly Founder, email to GiveWell, November 20, 2012

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  Conversation with Paul Niehaus, November 14, 2014

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  Paul Niehaus and Carolina Toth, conversation with GiveWell, September 7, 2015