Precision Development - November 2020 Version

Published: November 2020

Summary

What do they do? Precision Agriculture for Development (PAD) provides locally-customized agricultural advice to farmers through their mobile phones (e.g., recommendations to use specific farming practices or inputs, such as seeds and fertilizers, or answers to specific questions posed by farmers). (More)

Does it work? We have completed a preliminary review of the evidence on programs that are implemented by PAD or similar to those implemented by PAD and have relied primarily on a meta-analysis of three randomized controlled trials (RCTs), which finds that mobile-based agricultural advice leads to a 4% increase in farmers’ yields, though the estimated effect has a wide confidence interval. We are highly uncertain about the extent to which the findings will generalize to settings where PAD plans to operate in the future and whether PAD would be able to provide sufficient monitoring and evaluation data to reduce this uncertainty. Our limited understanding is that PAD has some experience with a variety of different monitoring tools and has not yet applied these tools comprehensively across its programs. (More)

What do you get for your dollar? We roughly estimate that it costs PAD $1-2 per year to reach a household with its messaging. Based on our initial cost-effectiveness model, our guess is that PAD's cost-effectiveness is below the range of programs we would consider recommending funding in the near future, but near enough to that range that this conclusion could change as PAD's work evolves, as we get additional information, or due to changes in the amount of highly cost-effective room for more funding that our top charities collectively have available. (More)

Is there room for more funding? PAD reports that it has significant levels of room for more funding to expand its existing services, support new programs that are similar to those studied in the existing evidence, and undertake research and product testing. (More)

PAD is one of our standout charities because of its:

• Unusually strong self-analysis, particularly in supporting RCTs on its program.
• Standout transparency. It has shared significant, detailed information about its program with us.
• Work on a potentially cost-effective program. We have completed an initial cost-effectiveness analysis and provisionally concluded that PAD is less cost-effective than the programs we currently recommend that donors support, but not by a large margin. New information could plausibly lead us to believe that this program is as cost-effective as our top charities.

Major unresolved questions include:

• To date, we have done a limited amount of work to model PAD's cost-effectiveness. Further work or new information could change our conclusion. One potential area for exploration is to focus on a particular form of the program or geographic location that PAD could expand to, in order to determine whether we would estimate this to have higher cost-effectiveness.
• We have not conducted an in-depth review of the information PAD collects from its users on engagement, knowledge, and reported behavior change. If we were to consider funding PAD in the future, we would want to learn more about how programs funded with additional donations would be monitored.
• We have not sought out a strong understanding of how PAD would spend additional funding. We have a general understanding that PAD could absorb more funding than it expects to receive.

Our review process

To date, our investigation process has consisted of:

• Several conversations with PAD.1
• Reviewing available evidence on mobile-based agricultural advice programs to develop our interim intervention report.
• Reviewing documents PAD sent us after our conversations and in response to our queries.

What do they do?

PAD provides personalized agricultural advice to farmers through their mobile phones.2 PAD provides advice through a combination of short message service (SMS) messages (i.e., short, text-based messages) and automated phone calls.3 This advice includes recommending farmers use or not use specific agricultural inputs (e.g., seeds and fertilizers),4 providing decision-support tools to farmers (e.g., on how to deal with pest infestations or which seeds to select given the farmer's land use and agroclimatic zone),5 and answering specific questions posed by farmers.6

PAD’s programs vary in intensity and comprehensiveness across settings. “Light-touch” programs generally provide messages to farmers about a single topic. “High-touch” programs provide advice on a wider set of agronomic issues and—in addition to SMS and voice messages “pushed” to farmers in the "light-touch" model—may include providing a hotline that farmers can call to receive advice from agronomists, access market prices for agricultural commodities, and listen to questions asked by other farmers. Most of PAD's programs fall somewhere in between its "light-touch" and "high-touch" classifications.7

PAD’s general process when starting a new program is to:

• source agricultural advice from agronomic experts on specific crops in the targeted country,8
• gather farmers’ mobile phone numbers, generally from partner organizations,9
• conduct focus groups with farmers to learn more about what content would be most helpful,10
• put the advice in a format that is easy to understand,11
• share advice with farmers via SMS or voice messages at intervals designed to coincide with key decisions points in a cropping cycle,12
• test the effectiveness of variations of the messaging and format,13 and
• conduct monitoring and evaluation activities to measure impact (more below).

In 2019, PAD’s programs reached an estimated 3.5 million farmers across eight countries: India, Kenya, Rwanda, Ethiopia, Pakistan, Uganda, Bangladesh, and Zambia.14 Approximately 55% of these farmers were reached by services that PAD operates for, or in partnership with, governments and other organizations. Another 40% of farmers were reached by services provided by organizations that PAD advises (in order to increase the impact of the existing services). For about 5% of the farmers it served in 2019, PAD operated the service independently.15

Breakdown of spending

PAD’s expenses were $3.9 million in 2019.16 In 2020, it plans to spend 42% of its budget on program staff, 20% on research staff, 20% on global overhead, 13% on operational costs other than staff, 4% on telecommunications, and 1% on user acquisition.17

Does it work?

What is the evidence that the program leads to higher incomes for farmers?

We have completed an interim intervention report in which we discuss the available evidence on the effectiveness of PAD’s program. We have spent limited time to form the initial views presented in our interim intervention report and, at this point, our views are preliminary. Here we briefly summarize the evidence we considered as part of our interim intervention report.

A meta-analysis by Fabregas, Kremer, and Schilbach 2019 of three studies of programs implemented by PAD and similar to those implemented by PAD18 finds that mobile-based agricultural advice leads to a 4% increase in farmers’ yields, though the estimated effect has a wide confidence interval (the range of plausible values).19 We are highly uncertain about the extent to which these findings will generalize to settings where PAD plans to operate in the future and whether PAD would be able to provide sufficient monitoring and evaluation data to reduce this uncertainty.

We view Fabregas, Kremer, and Schilbach 2019 as providing moderate quality evidence for the effect of programs like those implemented by PAD on farmer yields, though we have not conducted a thorough review of the meta-analysis or the studies included. We have a skeptical view that mobile-based agricultural advice programs have a limited effect on farmer behavior and income; overall, we view the evidence from Fabregas, Kremer, and Schilbach 2019 as a modest positive update on this view.

How does PAD monitor its programs on an ongoing basis?

To date, we have done a limited review of the monitoring and evaluation activities PAD uses to test the effectiveness of its programs. We haven't yet sought the level of understanding of PAD's monitoring that we have for our top charities. Our understanding based on our review so far is that PAD has some experience with a variety of different monitoring tools but has not yet applied these tools comprehensively across its programs.20 Based on this, if we were to consider funding PAD in the future, we would want to learn more about how programs funded with additional donations would be monitored.

PAD provided a written summary of its monitoring and evaluation activities and also described its monitoring and evaluation activities in two conversations with GiveWell.21 Here we summarize our current understanding of the monitoring and evaluation activities to measure each of the following:22

1. User engagement with PAD's services (e.g. picking up and listening to calls, reading SMS messages). PAD shared data from programs in five states in India on the percentage of calls users picked up, the average proportion of calls listened to (calculated as the duration of the call that the farmer listened to divided by the total message length), the percentage of calls users rated, and what the average rating was. It also shared data on inbound calls from farmers to PAD's hotline (e.g. number of calls received, average call duration). This data, which PAD shared in September 2020, covers December 2019 to August 2020.23 We have not yet asked PAD for details of how this data was collected and analyzed. For other programs, our understanding is that PAD has not collected data regularly on user engagement.24
2. Improved knowledge and comprehension of recommended agronomic practices and self-reported behavior change. PAD told us that it has surveyed farmers to measure knowledge, comprehension, and reported behavior change in select programs: on an ongoing basis in one of its programs in Kenya,25 in all of its programs in India,26 and in 2018 in Rwanda.27 It has shared select results from its surveys in Kenya, Rwanda, and India and a training guide for its surveys in India.28 As of September 2020, it was analyzing the first survey data from India that was based on this guide.29 We have not yet asked PAD for more detail on the survey data it has collected. For other programs, our understanding is that PAD has not surveyed its users.30
3. Beneficial outcomes for farmers, including increases in yields and net income. PAD has reported results on agricultural yield for its program in Gujarat based on an RCT that was conducted there.31 It expects to collect data on yields and/or net income in the future through an RCT in Odisha,32 and through administrative data on milk production in Kenya.33

What do you get for your dollar?

We estimate that the cost per farmer of PAD’s programs is between $1 and $2 per year.34 Note that our cost-effectiveness analyses are simplified models that do not take into account a number of factors. There are limitations to this kind of cost-effectiveness analysis, and we believe that cost-effectiveness estimates such as these should not be taken literally, due to the significant uncertainty around them. We provide these estimates (a) for comparative purposes and (b) because working on them helps us ensure that we are thinking through as many of the relevant issues as possible.

More details on this estimate and on our preliminary cost-effectiveness analysis for PAD are in our interim intervention report.

Is there room for more funding?

In early 2020, PAD told us that if it had additional funding, it would be able to increase the number of farmers it reaches substantially. It estimated that it could absorb up to $2 million per year for current programs and $9 million per year for new programs that we believe would be similar to those that have been studied with RCTs.35 At the time, its top priorities included programs in Brazil, India, Nigeria, the Democratic Republic of Congo, Pakistan and Rwanda.36 PAD also noted that it is constrained in funding for conducting additional research and development.37 As of November 2020, PAD’s research priorities included "(i) strengthening the evidence base on yields, profitability, averted crop loss, and cost-effectiveness, (ii) understanding barriers to efficient social learning and testing digital interventions to overcome those barriers, (iii) digitizing interventions proven in small-scale studies to increase farmer yields and test their cost-effectiveness at a large scale."38

Sources

• 1

  We have published notes from the following conversations with PAD.

  • GiveWell's non-verbatim summary of a conversation with Precision Agriculture for Development, February 12, 2020
  • GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020
  • GiveWell's non-verbatim summary of a conversation with Precision Agriculture for Development, August 9, 2017

• 2

  “PAD is a non-profit organization with a mission to support smallholder farmers in developing countries by providing customized information and services that increase productivity, profitability, and environmental sustainability. We are establishing a new model for agricultural extension: reaching farmers with personalized agricultural advice through their mobile phones.” PAD, "Our model"

• 3

  “PAD aims to improve the livelihoods of farmers in developing countries by providing them with advice about evidence-backed farming practices that enable them to increase their yields and net income. PAD primarily disseminates this advice through voice calls and SMS messaging.” GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 1. PAD noted in comments on a draft of this report in November 2020 that its phone calls are automated.

• 4

  “This research [on PAD's program in Kenya] revealed that farmers who received recommendations and were advised to use agricultural lime to combat local soil acidity were 10-24% more likely to experiment with the input. Farmers who received the service and were advised that they did not need lime were 25% less likely to purchase it.” PAD, "Kenya: Programs". Examples of seeds and fertilizers was provided by PAD when reviewing a draft of this page in November 2020.

• 5

  Addition provided by PAD in November 2020 in comments on a draft of this report: "providing decision-support tools to farmers to facilitate more informed decision-making (e.g. regarding how to deal with pest infestations or which seeds to select given their land use and agroclimatic zone)."

• 6

  “Building on these successes, we rolled-out our initial service in April 2016. The service, called Krishi Tarang—which means “agriculture wave” or “vibe” in Gujarati and Hindi—started with only 200 farmers, and grew to over 40,000 farmers by mid-2017. Krishi Tarang provides farmers with free, customized information in two ways: via weekly voice messages sent to a farmer’s mobile phone and a direct response to any agricultural question that a farmer logs.” PAD, "India: Programs".

• 7
  • “PAD classifies its program on a range from 'light-touch' to 'high-touch'. PAD's India programs are its most high-touch, and its programs in Kenya and Rwanda in partnership with OAF are especially light-touch. Most of its programs fall somewhere in between these levels of intensiveness.” GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 3.
  • “For its light-touch programs, PAD focuses on identifying high-impact practices backed by agronomic evidence that are underutilized by farmers and designing a campaign to address one specific such topic.” GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 3.
  • “PAD's high-touch programs are essentially an accumulation of many light-touch programs, providing a comprehensive set of advice to farmers about all of the best practices for a particular crop.” GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 3.
  • “In India, where PAD uses an interactive voice response (IVR) system that pushes calls out to farmers, it is able to collect data on how many farmers answer each type of call and how long they listen to the call.” GiveWell's non-verbatim summary of a conversation with Precision Agriculture for Development, February 12, 2020, p. 7.
  • “For PAD India, our advisory content is disseminated through a two-way mobile phone-based platform that delivers customized content to farmers in audio form and in their local language. Farmers receive i) a weekly push call with agricultural advisory information that is customized in line with the crop cycle, each farmer’s location, and land characteristics; and ii) access to a hotline where farmers can record questions that are answered within 48 hours by our team of agronomists, with answers disseminated through pre-recorded voice calls. Farmers who dial into our hotline can also choose to listen to a library of advisory messages and, in some instances, access crop and commodity price information.” Faull, "The Journey to One Million: PAD in India," 2020.
  • “Q&A: Farmers can call in and ask questions, answered by expert. Farmers can listen to questions asked by other farmers.” PAD, Slide presentation, 2017.

• 8

  "When starting a new program, PAD begins by forming partnerships with groups that have agronomic research and content about particular crops in the country, to ensure that it is leveraging the best evidence-backed content that has been validated at the trial level." GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 4.

• 9

  "PAD then looks for a source for farmer phone numbers and data. PAD tries to partner with other groups that are already working with large groups of farmers so that it does not have to acquire users one at a time. [One Acre Fund (OAF)], for example, has an existing population of farmers to which it provides very intensive services. It is straightforward for PAD to add its SMS service on top of OAF's existing services to farmers, which makes user acquisition essentially costless.
  In some cases, telecom companies share numbers for their subscribers. In Colombia, some farmers' cooperatives (e.g. the associations of potato and sugar cane farmers) have databases of farmers. Sometimes, these databases also include other data about the farmers (e.g. land size, crops, etc.). PAD sometimes also sets up new processes for collecting data about farmers, which in some cases involves setting up a call center." GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, pp. 4-5.

• 10

  "Early in its process, PAD tries to hold farmer focus groups to learn about farmers' current farming practices and their most significant needs in terms of advice and information. PAD compares farmers' needs with the agronomic content it has compiled and deprioritizes content that does not appear to be high-priority for farmers." GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, pp. 5-6.

• 11

  "PAD then works to convert its content into a form that will successfully guide farmer behavior. By default, a lot of available content is either not reaching farmers or not being delivered in a form that is easy for them to understand. PAD works with economists and behavioral scientists, and field tests its content with focus groups of farmers, to ensure its content is framed in an understandable and actionable way." GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 6.

• 12
  • "PAD then digitizes its content for delivery. This involves distilling the material into individual messages that focus on a limited amount of content (so as not to overwhelm farmers with too much information at once), condensing those messages into e.g. one- or two-minute voice recordings or 160-character SMS messages, and setting a schedule for when in the season various pieces of content will be delivered. Before the season starts, PAD decides which messages it will send on which weeks." GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 6.
  • Addition provided by PAD in November 2020 in comments on a draft of this page: "customized to coincide with key decision points in a cropping cycle."

• 13

  Addition provided by PAD in November 2020 in comments on a draft of this page: "conduct ongoing research and product improvement activities to iterate the service and increase impact, including surveying, human-centered design research, and quantitatively rigorous a/b testing." See also PAD, Appendix table: Trials conducted by PAD and affiliated researchers, 2020.

• 14

  “PAD is currently working in eight countries: India, Bangladesh, Kenya, Rwanda, Ethiopia, Zambia, Uganda, and Pakistan. In 2019, PAD's work reached 3.5 million farmers.” GiveWell's non-verbatim summary of a conversation with Precision Agriculture for Development, February 12, 2020, p. 1.

• 15

  “In 2019, PAD's work reached 3.5 million farmers. This number includes:

  • those reached directly through services run by PAD (less than 5%)
  • those reached by services PAD runs for or in partnership with state governments or other actors (over 50%)
  • those reached by the services of another organization that PAD is partnering with to add value to the service (about 40%).

  GiveWell's non-verbatim summary of a conversation with Precision Agriculture for Development, February 12, 2020, p. 1

• 16

  See PAD, 2019 Annual Report: Finances, section “PAD spending.”

• 17
  PAD, 2020 budget breakdown for GiveWell
  • $0.28+$0.18+$0.05+$0.02+$0.58+$0.28 = $1.39
  • $0.58/$1.39 = 42%
  • $0.28/$1.39 = 20%
  • $0.28/$1.39 = 20%
  • $0.18/$1.39 = 13%
  • $0.05/$1.39 = 4%
  • $0.02/$1.39 = 1%

• 18

  In response to reviewing a draft of this page in November 2020, PAD noted that some of the programs included in the Fabregas, Kremer, and Schilbach 2019 meta-analysis were implemented by PAD.

• 19
  • Limiting only to three trials measuring an effect on yield where mobile-based agricultural advice is delivered directly to farmers, the effect size is 0.04, with a 95% confidence interval (CI) of -0.03 to 0.10. See Fabregas, Kremer, and Schilbach 2019, p. 4, figure 3, subtotal for “Delivered directly to farmers.”
  • "Figure 3 reports on a complementary meta-analysis measuring the impact of experimentally evaluated digital agricultural extension interventions on farm yields or harvest value (unfortunately we do not have sufficient data on farm costs to estimate impacts on profits). This analysis encompasses four trials of messages delivered purely through mobile phones: two text message interventions with sugarcane farmers in Kenya (48) and two season measures for an interactive voice response (IVR) intervention with cotton farmers in India (46)." Fabregas, Kremer, and Schilbach 2019, p. 4. Note that only these interventions delivered solely through mobile phones are included in the effect size of 0.04 that we refer to above.

• 20
  GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020
  • "PAD would like to monitor all four of the components in its theory of change for all of its programs, though that is not always possible in practice. The degree of evidence PAD has regarding each of these components varies between programs." P. 8.
  • "PAD's theory of change involves four major components, with each ideally leading causally to the next:
    1. User engagement — Farmers engage with PAD's services (e.g. picking up and listening to calls, reading SMS messages).
    2. Improved knowledge — Famers have better knowledge about and comprehension of best agronomic practices.
    3. Improved practices — Farmer behavior shifts towards those recommended practices.
    4. Beneficial outcomes for farmers, including increases in yields and net income." P. 6.
  • "Monitoring user engagement is relatively straightforward for programs which use voice calls because PAD can measure how many farmers pick up the calls and the duration for which they listen to the message...PAD uses surveys to collect data on farmers' knowledge before and after an intervention is implemented...Where possible, PAD tries to obtain administrative datasets that include data on farmer behaviors...PAD's method for measuring farmer outcomes varies. Methods include measuring crop cut, which involves conducting surveys with field workers who visit farmers' fields." Pp. 6-8.

• 21
  • PAD, Report on evidence base and monitoring data, 2020
  • PAD, Appendix table: Trials conducted by PAD and affiliated researchers, 2020
  • GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020

• 22
  • “PAD's theory of change involves four major components, with each ideally leading causally to the next:
    1. User engagement — Farmers engage with PAD's services (e.g. picking up and listening to calls, reading SMS messages).
    2. Improved knowledge — Famers have better knowledge about and comprehension of best agronomic practices.
    3. Improved practices — Farmer behavior shifts towards those recommended practices.
    4. Beneficial outcomes for farmers, including increases in yields and net income."

    GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 6.

  • See GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, pp. 6-8, for a description of PAD’s monitoring activities within each of these components.

• 23
  • See PAD, Sample usage tracker: India, 2020, sheet "Engagment Statistics." Note that hotline calls are referred to in this spreadsheet as "inbound calls."
  • Details on user engagement monitoring in Gujarat and Odisha states: "Gujarat [...] PAD continuously monitors user engagement, and has measured a 53% 'unconditional listening rate' (i.e., the average duration of PAD's voice calls that farmers listen to, including farmers who don't pick up the call at all). [...] Odisha—Currently, PAD is only monitoring user engagement for its larger Odisha program. [...] Pick-up and listening rates vary depending on the time of year." GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, pp. 8-9.

• 24

  PAD shared a list of evidence it has collected: PAD, Appendix table: Trials conducted by PAD and affiliated researchers, 2020. The list includes user engagement metrics in the section "System and message design tweaks" (pp. 2-3). Our read of these metrics is that the data collected was focused on one-off decisions about design options rather than assessing engagement on an ongoing basis.

• 25

  "PAD has data on most aspects of these four components for its larger, high-touch program in Kenya. [...] PAD measured a 10% improvement in farmers' knowledge, as well as an increase in the likelihood that farmers were implementing the practices PAD had recommended." GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 8. See also PAD, Appendix table: Trials conducted by PAD and affiliated researchers, 2020, "Kenya" rows under the "Knowledge and comprehension" and "Adoption behavior" columns.

• 26

  "The India team has implemented a polling survey across all programs to gather data on recollection of messages, self-reported adoption of recommended practices, and satisfaction from a few hundred farmers per program on a bi-weekly basis. The reference time frame for all the questions is preceding two weeks, allowing us to track the changes in farmer reactions to messages. The initial volume of data is currently being analyzed." PAD, Report on evidence base and monitoring data, 2020, p. 2. See also PAD, Appendix table: Trials conducted by PAD and affiliated researchers, 2020, "India (Gujarat)" rows under the "Knowledge and comprehension" and "Adoption behavior" columns.

• 27

  "2018 Rwanda [...] + 18% lime adoption (control mean=0.04)" PAD, Appendix table: Trials conducted by PAD and affiliated researchers, 2020, p. 1.

• 28

  See previous footnotes for select results from Kenya, Rwanda, and India (Gujarat only). Training guide for surveys in India is in PAD, Polling training guide: India, 2020.

• 29

  "The India team has implemented a polling survey across all programs [...] The initial volume of data is currently being analyzed." PAD, Report on evidence base and monitoring data, 2020, p. 2.

• 30

  PAD, Appendix table: Trials conducted by PAD and affiliated researchers, 2020

• 31
  • "2019 India (Gujarat) [...] No significant increase in yield." PAD, Appendix table: Trials conducted by PAD and affiliated researchers, 2020, p. 1.
  • "In Gujarat, data on components 2 through 4 of PAD's theory of change (see above) come from the RCT conducted by Cole and Fernando." GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 8.

• 32
  • "PAD is planning an RCT this year in Odisha which will measure components 2 through 4. (Update: This RCT has been delayed until 2021 due to COVID-19.)" GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020, p. 9.
  • "Due to the variability of yield outcomes by season, collecting panel data [in Odisha] across two seasons will be particularly useful to identify the magnitude of the impact of our services and sensitivity to varying weather and seasonal conditions." PAD, Report on evidence base and monitoring data, 2020, p. 1.

• 33

  "In partnership with established dairy cooperatives in Kenya, PAD plans to conduct an impact evaluation of its dairy advisory services using high-frequency administrative data on milk quantity, quality and income at the farmer level, as available. The findings from this evaluation are expected to be particularly useful due to the high frequency of milk production data. Instead of having to wait for the harvest at the end of a cropping season, when using milk production data we can observe more frequent outcomes and adjust for variability." PAD, Report on evidence base and monitoring data, 2020, pp. 1-2.

• 34

  See our cost-effectiveness analysis of PAD, “PAD” sheet, “Cost per farmer” row.

• 35
  GiveWell's non-verbatim summary of conversations with Precision Agriculture for Development, February 25, 2020 and March 5, 2020
  • "If fully funded, PAD expects these 13 [current] programs combined to reach 3.8 million farmers in 2020.

    PAD's total budget for its current programs in 2020 is $4.7 million, about a quarter of which is covered by its existing dedicated funding. It has plans for an additional $2.8 million of programs if funding were available." p. 12.

  • "PAD is exploring starting new programs this year in:
    • Three to five additional Indian states,
    • one or two additional provinces in Pakistan,
    • the Democratic Republic of the Congo,
    • Nigeria,
    • Colombia, and
    • Rwanda, in partnership with the government.

    If PAD successfully implements all of these programs, it has the potential to reach nearly 7 million farmers in the first year. PAD would need roughly $9 million per year to fund these programs." Pp. 12-13.

  • In its review of a draft of this page in November 2020, PAD noted that it could absorb "up to $2 million per year for current programs."

• 36

  See previous footnote for some of the prioritized locations. In its review of a draft of this page in November 2020, PAD added Brazil to its list of priorities.

• 37

  "We would like to note that research and evidence generation is a core competency of our team, as is a commitment to rigorous inquiry. We aim to generate additional impact evidence for our work across contexts. Our primary constraint in pursuing this, is a limited resource envelope to support additional research. Additional support provided to PAD will support evidence generation." PAD, comment on a draft of our interim intervention report, October 2020 (unpublished). In a subsequent comment, PAD noted that its priorities include program development to increase its impact in addition to research on its impact.

• 38

  Statement provided by PAD in November 2020 in comments on a draft of this report.