Information and the trade-off between food safety and food security in rural markets: Experimental evidence from Malawi

Last registered on August 19, 2021


Trial Information

General Information

Information and the trade-off between food safety and food security in rural markets: Experimental evidence from Malawi
Initial registration date
August 16, 2021

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
August 19, 2021, 10:13 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.



Primary Investigator

Purdue University

Other Primary Investigator(s)

PI Affiliation
Purdue University

Additional Trial Information

Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
We implemented a clustered randomized control trial with experimental auctions among 1,098 rural households in Malawi to evaluate whether providing training about food safety increased demand for safe groundnuts. We tested if demand varied depending on if quality was observable or unobservable and if groundnuts were purchased at harvest or lean season. We found that the control group who was not trained valued observable quality only. At harvest, both trained and untrained consumers placed statistically equal premiums on unobservable quality. However, in the lean season, untrained consumers’ premium for unobservable quality disappeared, while trained consumers’ premium for unobservable quality increased.
External Link(s)

Registration Citation

Nindi, Tabitha and Jacob Ricker-Gilbert. 2021. "Information and the trade-off between food safety and food security in rural markets: Experimental evidence from Malawi." AEA RCT Registry. August 19.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Willingness to pay for groundnuts quality (value in Malawi Kwacha; 1US$=750 MK)
Primary Outcomes (explanation)
Willingness to pay for groundnuts quality (value in Malawi Kwacha; 1US$=750 MK). We compare consumers Willingness to pay bids across three quality grades of groundnuts to determine consumers quality premium for different grades of groundnuts: (i) the unsorted grade, (ii)the sorted but unlabeled grade and (iii) the sorted and aflatoxin safety labeled grade.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our sample included 1,098 farmers from Mchinji district in central Malawi, the major groundnut-producing area in the country . Farmers were randomly selected from a list of members of the National Smallholder Farmers’ Association of Malawi (NASFAM), a farmer-based organization that has over 43 associations across the country. Each NASFAM association had sub-units at the community level, called Group Action Centers (GACs). GACs were typically about 10 to 35 kilometers apart. A single NASFAM association counted 21 GACs (or communities) on average, with each GAC had an average of about 15 farmer clubs. A club was made of 10 farmers who reside within the same village; village were typically 1-5 kilometers apart from each other. We targeted two associations for the study, and we randomly selected 16 GACs from each association to form the study sample. Within each of the 32 GACs, we randomly selected 25 farmers, subject to the condition that at least 2 (and at most 5) farmers were selected in each club. The resulting initial sample included 830 farmers, who participated in auctions twice: in the harvest and lean seasons. To these we added 268 randomly-sampled new farmers in the lean season auction, to control for and test possible learning effects arising from the bulk of our sample bidding in the same auction twice; first in the harvest season and then again in the lean season.

For our intervention, we provided aflatoxin training to the treatment group and the random assignment for our RCT into treatment (received information through training about aflatoxins) or control (did not receive training about aflatoxins) groups was done at the GAC level. We assigned treatment at the GAC level to avoid potential information spillover across clubs (or villages) within the same GAC. This arrangement also ensured cost-effective administration of the study activities (aflatoxins training and auction). Although GACs are far enough apart to limit possible information contamination, GACs that fall within the same association are generally similar in terms of member demographics.

The information provided to treatment group participants included facts about aflatoxins, the crops they affect and the way they affect crops (in the field and during harvest, drying and storage), the health and economic effects of aflatoxins, and how to avoid or reduce aflatoxins contamination (practices available and appropriate for smallholder farmers). In the second round of the auction during the lean season, participants in the treatment group were not given the aflatoxin training again. However, we added some new participants assigned to the treatment group in the second round to control for possible learning effects. These new participants were given the same training as the original treatment group received at harvest. For compliance with IRB requirements, participants in the control group were provided with the training at the end of the study, after completing the auctions in the lean season.

For our outcome variable which is willingness to pay (WTP), we elicit farmers’ WTP for grain quality with incentive-compatible, revealed preference auctions using the Becker-Degroot-Marschak (BDM) mechanism (Becker et al., 1964). The BDM is commonly applied in field experiments in developing countries (Channa et al., 2019; De Groote et al., 2011; De Groote et al., 2016; Prieto et al., 2021) . BDM auctions provide revealed preferences estimates based on bidding real money and actually purchasing the item at the bid price. In our setting, because participants bid on three quality grades of groundnut, one of their three bids was randomly selected as a binding bid.

Participants were first oriented about the BDM goals and procedures, then went through two practice rounds with sweets to ensure they understood the process as well as understood that strategic behavior was not beneficial. Once this was done, participants completed the real auction. All the three groundnut grades were auctioned in one-kilogram units, and participants were allowed to inspect the groundnut before bidding. They then bid on the three grades of groundnut that were presented in random order. Once they bid for all the grades, the enumerator rolled a die in the presence of the participant to determine which of the three grades of groundnut was the binding bid. The participants then drew a paper from a bag that had uniformly distributed numbers around the median market price in each village, as reported by NASFAM farmers. These were used as “offer prices” at which the binding bid was determined. The participant bought the kilogram of groundnut of the selected grade if their bid was higher than the randomly drawn “offer price” from the bag, and they paid the “offer price” rather than the price they bid. Conversely, they did not buy the groundnut if their bid was below the “offer price.” In all analyses, we use the amount that participants bid as our measure of WTP. Participants were given a fixed participation fee at the start of the survey to eliminate liquidity constraints that would limit participation and bias their WTP.

The auction was implemented twice, first during the harvest season (June 2019) when farmers had abundant stocks of grains, and then again targeting the same participants during the lean season (January 2020). In the lean season we recruited an additional sample of 268 farmers (155 in the control group and 113 in the treatment group) during the second auction to tease out possible learning effects among the farmers in the original sample from the repeated auctions.

We purchased all groundnut from a single trader during the 2019 harvest in order to reduce heterogeneity in other grain attributes. The grain was then used to simulate the different grain quality grades prevalent in local markets (i.e., sorted and unsorted grain) for both auctions. Appendix B shows pictures of the three quality grades. For the auction implemented in the lean season, we used the same grain that was purchased during the harvest season and stored in hermetic (airtight) bags to ensure minimal variation in grain quality (Baributsa et al., 2017). Aflatoxins testing of groundnut was done by a laboratory in Malawi’s capital, Lilongwe (Appendix C). The aflatoxins-safe certificate was shown to participants when they were presented with the 1-kg sample of aflatoxins-safe groundnut on which they bid. All groundnut used in the auctions came from the same sample, in which the aflatoxins level was 2.1 ppb (below the 15 ppb limit in Malawi and the 4 ppb limit in the European Union); the aflatoxins level was not mentioned when presenting participants with the samples of unsorted and sorted grades
Experimental Design Details
Randomization Method
Randomization done in office by a computer
Randomization Unit
Group Action Centers (GACs). These are community groups within the farmer organization (i.e., the National Smallholder Farmers Association of Malawi
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
16 GACs per group with a total of 32 GACs
Sample size: planned number of observations
400 farmers per group with a total of 800 farmers for the study
Sample size (or number of clusters) by treatment arms
1098 farmers
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Since our outcome variable is WTP for groundnut, we use baseline data from another study involving the same households, implemented in 2018, to get an estimate of mean and standard deviation of groundnut purchase prices for the harvest and lean season (see Nindi, Ricker-Gilbert and Bauchet 2021 for details). These data indicated an intra-cluster correlation coefficient within GAC of 0.02. Power calculations used 80 percent power and 95 percent confidence intervals. Calculations suggested that 32 total clusters (GACs) including 23 farmers per cluster would ensure a minimum detectable effect (MDE) of 0.32 standard deviations between treated and control households. This is generally considered a small-to-medium effect size (Cohen, 1988; Duflo et al., 2008). Our sample included 830 participants in the harvest season auction, and 1,013 participants in the lean season auction (745 repeated study participants + 268 new participants in the lean season). In total 85 households who were surveyed at harvest could not be found in the lean season.

Institutional Review Boards (IRBs)

IRB Name
Purdue University HRPP IRB
IRB Approval Date
IRB Approval Number
Protocal No. 1802020251


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
January 31, 2020, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
February 28, 2020, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
16 GACs per group with a total of 32 GACs ( GACs are community groups under the National Association of Smallholder Farmers in Malawi)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
1098 farmers
Final Sample Size (or Number of Clusters) by Treatment Arms
In total: 498 farmers in treatment group and 600 farmers in the control group harvest season auction: 830 farmers total : 385 farmers in treatment group and 445 farmers in the control group Lean season auction: 1013 total farmers of which 448 farmers in treatment group and 565 farmers in the control group (745 farmers repeat participated from harvest, 85 attrited: 50 farmers in treatment group and 35 farmers in control group; 268 farmers added in lean season to tease out learning effects,( 155 farmers in control and 113 farmers in treatment group)
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials