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Got (Good) Milk? Part II - Cleanliness and Collective Action in Indian Dairies
Last registered on May 06, 2015

Pre-Trial

Trial Information
General Information
Title
Got (Good) Milk? Part II - Cleanliness and Collective Action in Indian Dairies
RCT ID
AEARCTR-0000700
Initial registration date
May 06, 2015
Last updated
May 06, 2015 3:25 AM EDT
Location(s)
Region
Primary Investigator
Affiliation
MIT
Other Primary Investigator(s)
PI Affiliation
Stanford University
PI Affiliation
Columbia University
PI Affiliation
UC Berkeley
Additional Trial Information
Status
On going
Start date
2014-07-01
End date
2015-07-30
Secondary IDs
Abstract
We propose a two stage randomized controlled trial that seeks to evaluate the effect of incentives to dairy cooperatives, on their quality of milk and governance. We will evaluate the extent to which dairy cooperatives respond to clean milk incentives and randomly varied exposure to community based monitoring.We expect the treatments to have direct effects on the governance and performance of dairy cooperatives. Data will come from scientifically validated milk testing procedures, participant surveys, and financial audits.
External Link(s)
Registration Citation
Citation
Breza, Emily et al. 2015. "Got (Good) Milk? Part II - Cleanliness and Collective Action in Indian Dairies ." AEA RCT Registry. May 06. https://doi.org/10.1257/rct.700-1.0.
Former Citation
Breza, Emily et al. 2015. "Got (Good) Milk? Part II - Cleanliness and Collective Action in Indian Dairies ." AEA RCT Registry. May 06. https://www.socialscienceregistry.org/trials/700/history/4225.
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Experimental Details
Interventions
Intervention(s)
Dairy represents an important income source in the lives of the rural poor. As a result, organizational innovations that raise productivity or quality in the dairy sector could have deep implications for a broad range of people.

Rural smallholders are generally organized into village cooperatives where they take their milk each day. At the co-op level, the milk of all member producers is combined to aggregate fixed storage/ shipping costs and sold to a regional dairy, which then chills, tests, and packages the milk for distribution. The purchase price at the dairy is based on quality, which is a composite measure of fat content and solid non-fats (SNFs), without including enough penalties for increased microbial load that significantly affects the quality.

The cooperative structure generates both collective action and coordination problems within villages. Losses due to these failures are particularly noticeable in terms of sanitary conditions associated with milk collection practices at the local village level Dairy Cooperative Societies (DCS). This has been revealed through our pilot studies and consultations with the Karnataka Milk Federation (KMF), a quasi-governmental dairy that is the largest federation of local DCSs in the Indian state of Karnataka. Most DCSs pay a flat procurement price to each farmer based on volume produced, with not much variation based on individual quality. The only potential incentive is that a cooperative may lose its entire payment for a day if milk is found to be spoilt on arrival at the district level union. Such punishments are very indirectly passed on to farmers, and most are unaware when the cooperative doesn’t receive payment. This procurement strategy may generate incentives for individuals to free-ride, avoiding time-intensive clean milking practices. Additionally, the structure also fails to monitor the accountability at the DCS level for proper washing and disinfection of milk pails, trays and other equipment used for milk procurement.

We will work with the Karnataka Milk Federation (KMF) to raise average dairy hygiene through reforms in the incentive scheme for local level institutions (DCS). Within the state of Karnataka, we plan to implement under the jurisdiction of Dharwad Milk Union, a second-tier organization in the federation as per recommendation from KMF.

We plan to implement a randomized control trial (RCT) to assess mechanisms to address collective action failure through incentive channels that may affect dairy hygiene. The KMF may redesign their payment schedule and village-level services in accordance with our findings.

Our experimental design intends to measure the effect of incentive structure and the consequent changes in members’ bargaining power on microbiological quality of milk. We propose three treatments to evaluate how a given incentive structure influences the DCS behaviour towards dairy hygiene. We will also disseminate information on clean milk production in all groups (including the control group) through posters, to eliminate any confounding effects caused by awareness gaps.

(0) Control: In the control group, we will test pooled milk samples from a DCS. No monetary incentives will be paid.

Treatment Groups:

(1) T1. We will pay an incentive based on a pre-determined scale to the DCS’ bank account for each round of testing. We will make it explicit that we will not be sharing this information with any producers (members).

(2) T2. We will pay an incentive based on a pre-determined scale to the DCS’ bank account for each round of testing. Prior to the date of testing, we will communicate to the DCS that producers will be informed of the DCS’ performance and realized monetary rewards ex-post. This claim will be credibly carried out through a poster and distribution of flyers.

(3) T3. We will pay an incentive based on a pre-determined scale to the DCS’ bank account for each round of testing. Prior to the date of testing, we communicate to the DCS that producers will be informed of rewards associated with DCS’ results ex-ante, and of the DCS’ performance and realized monetary rewards ex-post. Both claims will be credibly carried out. The endline survey will measure the extent to which well—informed producers can discipline local level institutions.

In all treatments, we will measure the microbial load in milk through a test called Methylene Blue Reduction Test (MBRT). For all tests, samples of milk will be collected by surveyors employed by JPAL South Asia and testing will be done by a third party vendor. Confidentiality norms mandated by the IRB will be met as samples will not carry any personally identifiable information but rather be referred through unique identifiers (UID). The intervention comprises 2-3 rounds of testing.

Baseline surveys:
We propose to introduce the following survey instruments to gather baseline data on Dairy Cooperative Societies’ (DCSs) institutional structure and to target specific experiments:

(a) Baseline survey for Directors: This survey will be answered by directors of DCSs. Each DCS has a managing committee comprising 11 directors. In our experimental design, we propose two treatments to incentivize these directors’ participation in clean milk procurement. This survey includes questions on socio-economic characteristics, their centrality within their social network, peer evaluation, and awareness of clean milking practices.
(b) Baseline survey of Testers/Helpers: This survey will be answered by testers (or helpers) of DCSs who are responsible for measuring milk quality and for equipment upkeep. This survey will measure baseline level of testers’ performance and degree of accountability to other institutional actors.
(c) Baseline survey of Secretaries: This survey will be answered by secretaries of DCSs, who are responsible for day-to-day operations of the society. This survey will measure baseline level of secretaries’ performance and degree of accountability to other institutional actors.
(d) Baseline survey of Producers: This survey will be answered by a subset of dairy producers who are the pouring members of the DCS. This survey will measure producers’ evaluation of their directors, tester, and secretary on a number of performance and personality measures. At end-line, we propose to examine if our interventions have affected any changes in these perceptions.

An endline survey is currently being designed.
Intervention Start Date
2015-04-27
Intervention End Date
2015-05-27
Primary Outcomes
Primary Outcomes (end points)
Indicators of interest:

1. Milk quality at the individual and the DCS levels

2. Investment in local level dairy infrastructure

3. Income from dairy activities

4. Use of retained earnings

5. Total milk procurement
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Design

In our intervention, 51 DCSs will be randomized into one or more of the following groups over two rounds of intervention. Minimally, the intervention involves collection of pooled milk samples from all DCSs. Additional group-specific protocols are outline below:

1) Control: No incentives will be paid.

2) Treatment 1: We will pay an incentive based on a pre-determined scale to the DCS’ bank account for each round of testing. We will make it explicit that we will not be sharing this information with any producers (members).

3) Treatment 2: We will pay an incentive based on a pre-determined scale to the DCS’ bank account for each round of testing. Prior to the date of testing, we will communicate to the DCS that producers will be informed of the DCS’ performance and realized monetary rewards ex-post. This claim will be credibly carried out through a poster and distribution of flyers.

4) Treatment 3: We will pay an incentive based on a pre-determined scale to the DCS’ bank account for each round of testing. Prior to the date of testing, we communicate to the DCS that producers will be informed of rewards associated with DCS’ results ex-ante, and of the DCS’ performance and realized monetary rewards ex-post. Both claims will be credibly carried out. The endline survey will measure the extent to which well-informed producers can discipline local level institutions.

This randomized controlled trial will follow a rotation design to make the most meaningful comparisons of DCSs’ behaviour under different ex-ante beliefs.

In addition, a poster on clean milk production will be distributed to all DCSs in the sample, to standardize any differences in baseline levels of knowledge on clean milk production.In all treatments, we will measure the microbial load in milk through a test called Methylene Blue Reduction Test (MBRT). For all tests, samples of milk will be collected by surveyors employed by JPAL South Asia and testing will be done by a third party vendor. Confidentiality norms mandated by the IRB will be met as samples will not carry any personally identifiable information but rather be referred through unique identifiers (UID). The intervention comprises 2-3 rounds of testing.
Experimental Design Details
Randomization Method
In round 1, the dairy cooperative societies will be randomized into one of the 4 groups, in office, by a computer. In round 2, we will rotate them to other groups, as per design.
Randomization Unit
The randomization unit is the dairy cooperative society.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
51
Sample size: planned number of observations
2500
Sample size (or number of clusters) by treatment arms
Round 1:

Control- 19 DCSs
Treatment 1-19 DCSs
Treatment 2-7 DCSs
Treatment 3-6 DCSs

Round 2:
Control- 7 DCSs
Treatment 1-12 DCSs
Treatment 2-12 DCSs
Treatment 3-20 DCSs
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
MIT Committee on the Use of Humans as Experimental Subjects
IRB Approval Date
2014-10-31
IRB Approval Number
120400505
IRB Name
IFMR Human Subjects Committee
IRB Approval Date
2014-01-23
IRB Approval Number
IRB00007107
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers