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The Impacts of Drought Tolerance on Local Labor Markets in India
Last registered on April 19, 2017


Trial Information
General Information
The Impacts of Drought Tolerance on Local Labor Markets in India
Initial registration date
April 18, 2017
Last updated
April 19, 2017 11:51 AM EDT
Primary Investigator
Other Primary Investigator(s)
PI Affiliation
UC Berkeley
PI Affiliation
Tufts University
PI Affiliation
International Rice Research institute
Additional Trial Information
On going
Start date
End date
Secondary IDs
Drought is a significant problem that affects rainfed agriculture in many parts of South Asia and Africa. While it is well known that drought has negative impacts on producers, the impacts of drought on farm workers are not as well understood. Given that farm workers rely critically on an abundant harvest for work opportunities, and that their geographical mobility is notably low, technologies that stabilize harvests can in theory impact farm workers positively - one of the most marginalized populations.

We ask whether new drought-tolerant rice varieties have impacts on local labor markets. Specifically, can these technologies provide insurance to landowners and at the same time provide insurance to the landless laborers? In a well-known article, Jayachandran (2006) showed that weather-induced productivity shocks in Indian villages translate into large decreases in wages due to inelastic labor supply. Sharp fluctuations in wages in response to weather shocks thus help insure landowners at the cost of farm workers. If reducing the magnitude of these shocks with technology also affects labor markets, then this study will demonstrate that the effects on labor markets need to be considered when measuring the aggregate beneficial impact of these new agricultural technologies. Risk-reduction via technological change may thus make a major contribution to reducing vulnerability and poverty among the most marginal rural inhabitants.

Wages are the main channel of impact for the population of farm workers. Therefore, measurement of local wages will be of first-order importance for the study. We will also measure labor supply effects. For landowners, we will measure productivity gains at the plot level. We can therefore estimate the direct impact of the technology on them. In addition, we will measure labor demand for a variety of production stages from land preparation to harvesting. We expect to measure additional outcomes - both for the population of landowners and landless laborers. In particular, we will measure aggregate income, consumption, and school attendance of children.
External Link(s)
Registration Citation
Dar, Manzoor et al. 2017. "The Impacts of Drought Tolerance on Local Labor Markets in India." AEA RCT Registry. April 19. https://doi.org/10.1257/rct.2162-1.0.
Former Citation
Dar, Manzoor et al. 2017. "The Impacts of Drought Tolerance on Local Labor Markets in India." AEA RCT Registry. April 19. http://www.socialscienceregistry.org/trials/2162/history/16681.
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Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
For landless agricultural workers: wages, aggregate income, consumption, school attendance of children, local labor supply effects;

For agricultural landowners: productivity gains at the plot level, demand for labor at different stages of agricultural season
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The PIs will conduct a randomized field experiment to measure the impact of drought-resistant rice adoption on agricultural wages and productivity. Studies such as Jayachandran (2006) suggest that weather shocks can sharply reduce wages for agricultural workers, while Mobarak and Rosenzweig (2013) suggest crop insurance for landowners can worsen worker vulnerability to weather shocks. This experiment examines whether new agricultural technologies can insure both agricultural landowners and landless workers against weather shocks, and how a risk-reducing technology affects local labor markets.

In Jharkhand State of India, 200 villages will be randomized into either a treatment or a control arm. In each village, enumerators will consult with village elders to identify study participants - twenty landowners and ten landless agricultural workers, three of whom will be women. Participant landowners in the 100 treatment villages will be provided with a 2 kg package of IR64 drought-resistant rice seeds, which should generate a conservative estimate of ~100 kg of harvestable seeds. Distribution of the drought-resistant seeds is conditional on the landowner agreeing to sell or trade some of their resulting harvest with at least two other farmers in the village. This condition is to lower barriers to adoption of the drought-resistant variety of IR64. In the 100 control villages, landowners will be given a 2 kg package of IR64 rice seeds that are not drought-resistant, conditional on agreeing to sell or trade some of their harvest to at least two other farmers in the village. After baseline interviews, landowners will complete three follow-up surveys at the ends of the next three harvests. The landless agricultural workers will also complete follow-up surveys after the harvests, as well as phone interviews conducted throughout the agricultural season.
Experimental Design Details
Randomization Method
Randomized in office by computer
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
200 villages
Sample size: planned number of observations
4000 cultivators (land owners) 2000 landless agricultural workers
Sample size (or number of clusters) by treatment arms
In treatment arm: 2000 cultivators; 1000 landless agricultural workers
In control arm: 2000 cultivators; 1000 landless agricultural workers
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Agricultural Wages: For 200 villages and a power of .8, the minimum detectable effect size is 9% Productivity: For 20 cultivators per cluster and a power of .8, the minimum detectable effect size is 24%
IRB Name
Committee for Protection of Human Subjects, UC Berkeley
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)