The welfare effects of switching to sustainable farming

Last registered on April 17, 2023


Trial Information

General Information

The welfare effects of switching to sustainable farming
Initial registration date
March 02, 2023

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
March 13, 2023, 8:43 AM EDT

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

Last updated
April 17, 2023, 2:18 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.


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Primary Investigator

University of Passau

Other Primary Investigator(s)

PI Affiliation
University of Passau

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
The intervention provides information and two rounds of training on organic farming practices. The intervention is implemented as a randomised controlled trial (RCT). Whereas a first study has focused on the short term effects with respect to knowledge, perceptions, awareness and experimentation (Grimm and Luck, 2023), this study will take a longer horizon and focus an the adoption of organic farming practices, conversion from conventional to organic farming and the effects on farmers’ welfare conditional on adoption. Welfare will be measured through agricultural profits and revenue, nutritional security, subjective wellbeing and health. This study can rely on a four-wave panel data set (baseline, two midline and endline survey) and substantial qualitative field research.
External Link(s)

Registration Citation

Grimm, Michael and Nathalie Luck. 2023. "The welfare effects of switching to sustainable farming." AEA RCT Registry. April 17.
Sponsors & Partners

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Experimental Details


The intervention provided information and two rounds of training on organic farming practices.

After the baseline data collection, we invited the 20 interviewed farmers in each treatment village to participate in a three-day training on organic farming, with farmers receiving seven hours of training per day. Based on the insights from the theoretical framework, our training intervention addressed experience, beliefs and risks. It offered extensive information about the costs and benefits of organic farming practices and hands-on training to maximize the learning effect and minimize the risk of usage. Raising awareness, changing perceptions and implementation at the community level are intended to address social risks. The training provided farmers with an introduction to organic farming and included information on potential marketing channels. Particular emphasis was placed on practical activities such as making organic fertilisers and pesticides. The training was designed by AOI in cooperation with the research team from Germany. AOI, together with its institutional members (local NGOs), delivered the training, which was held in the villages to minimize travel time for respondents. The farmers received IDR 50,000 (around USD 3.5) for each day of the training (only if they attended) to cover any transport costs and to compensate them for potentially forgone earnings. A first round of training was rolled out at the end of March 2018 and completed in May 2018. On average, 17 farmers out of the 20 invited farmers attended each training day.

A second round of training was rolled out in July 2022 and completed in August 2022. We invited the same farmers, i.e. the treatment group, to the training as in 2018. The training was designed together with the Indonesian Soil Research Institute and trainers from two P4S centers with a focus on organic farming. P4S are self-help agricultural and rural training centers. These institutions are owned and managed by farmers. They exist in most districts in Indonesia and receive financial resources from the local government. During the training, trainers provided partly a refresher training of the first training. They further augmented the training by a discussion of soil management in organic farming and by training on soil tests. Based on the soil tests that each farmer could conduct for his or her own soil, trainers provided fertilizer recommendations according to organic principles.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Agricultural yields, revenue, profits, labor
• Agricultural revenue (per ha) during the last season measured at the respondent level & separately for rice
• Agricultural profits (per ha) during the last season measured at the respondent level & separately for rice (considering revenues, input costs, land rent costs and labor cost)
• Rice yields (per ha) during the last season at the respondent level (for those respondents that grow rice)
• Average respondent and family labor during the last season per ha
(we will pay particular attention to rice plots because around 85% of respondents in previous waves cultivated at least 1 rice plot. Looking at the same commodity across respondents will increase comparability)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Income and wealth
• Satisfaction with household income: measured on a scale from 1 (not satisfied at all) to 10 (very satisfied)
• Asset ownership index (motorcycle, car, fridge, washing machine, Laptop, TV)
• Electricity expenditures per HH member (in 000 IDR)
• Financial distress: Binary variable =1 if respondent answers that HH was in financial distress anytime during the last 6 months (financial distress: unable to fulfil usual daily expenditures)
• Nutritional insecurity: Binary variable =1 if respondent answers that HH faced with a situation when there has not been enough food to feed the HH during the last 6 months

• Health perception: Respondents perception of own current health on a scale from 1 to 10. 1 means the worst health the respondent can imagine and 10 means the best health the respondent can imagine.
• Perceived health complaints: skin irritation (itchy), skin irritation (hurt), sore throat, cough, dizziness, diarrhea during the last 2 months. Binary variables=1 if respondent reports yes for the respective complaint. We will also measure this as an index variable ranging from 0 (no complaints) to 6 (suffered from all 6 complaints)

Perception & satisfaction
• Perceptions farming:
o Perspective future generations: For the youth it is worth to engage in farming (binary=1) if respondent agrees /agrees very much
o Perspective business person: A successful farmer is regarded like a successful business person (binary=1) if respondent agrees /agrees very much
o Perspective income opportunities: Farming is a good opportunity to become wealthy (binary=1) if respondent agrees /agrees very much
• Satisfaction:
o Satisfaction being a farmer: measured on a scale from 1 (not satisfied at all) to 10 (very satisfied)
o Satisfaction with amount and quality of free time: measured on a scale from 1 (not satisfied at all) to 10 (very satisfied)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We applied a three-stage random sampling design to select 1,200 respondents. In the first stage, we randomly selected 60 villages, 30 villages in Yogyakarta and 30 villages in Tasikmalaya. In the second stage, we randomly drew farmer group(s) in selected villages. Farmer groups in Indonesia function both as social group but also as task groups for government programmes and the allocation of subsidies.
In each village, we selected a minimum of one and a maximum of three farmer groups until the total number of registered farmer group members from the selected groups was equal to or larger than 60. We set the minimum to 60 members to ensure that a sufficient number of farmers would attend our information sessions (assuming that only a fraction of the members is interested) from which we drew our study participants. After identifying the farmer groups, the members of the selected farmer groups were invited to an information session on organic farming, which was held in their village. These information sessions served two purposes: (1) to facilitate self-selection based on initial interest in organic farming and the willingness to participate in farmer group events; and (2) to collect contact details on prospective respondents. The information sessions were run by AOI. In the third sampling stage, we randomly drew 20 farmers among the attendees of each information session. These 1,200 farmers, 20 from each of the 60 villages, constituted the respondents of our survey. If there were fewer than 20 attendees at the information session, we asked the farmer group head to nominate additional farmer group members.
The treatment was randomised at the village level and consisted of training on organic farming methods and principles. Farmers from groups in control villages did not receive any training. As baseline data was not available at the time of the randomisation, we used publicly available regional data for the stratification. Specifically, we stratified the sample according to urban and rural status and the reported size of agricultural land area per village. In Tasikmalaya, we used ‘travel distance to the district capital’ as an additional stratification criterion as this region is characterised by less developed infrastructure.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer,
Randomization Unit
The treatment was clustered at the village level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
60 villages.
Sample size: planned number of observations
1200 farmers (minus attrition since 2018).
Sample size (or number of clusters) by treatment arms
30 villages control, 30 villages training.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power calculations are for ITT effects. For the power calculations are estimated based on a 95% confidence interval and a power of 80% for three primary outcomes of interest. The power calculations are based on the full sample size minus the expected attrition. Based on the previous attrition rates, we expect that we will be able to interview around 1,000 respondents in 2023. Assumptions regarding the R2 are based on the adjusted R2 derived from regressing the respective outcome in 2019 on the baseline outcome as well as on a few control covariates such as age and years of schooling using only the control group sample. For example, the baseline data show a mean of 33 percent of farmers applying organic fertilizer other than manure, with a standard deviation of 0.471 and an intra-cluster correlation of 0.13. Given our average cluster size of 16.7 individuals per cluster (adjusted by attrition) and 60 clusters in total, we are powered to detect a minimum effect of 13 percentage points or 0.289 standard deviations. This decreases further if we account for additional explanatory variables that absorb some of the variance in the data.

Institutional Review Boards (IRBs)

IRB Name
Ethical Review Board of the University of Passau
IRB Approval Date
IRB Approval Number
IRB Name
Indonesian Government (BRIN)
IRB Approval Date
IRB Approval Number