The Impacts of Drought Tolerance on Local Labor Markets in India

Last registered on April 19, 2017

View Trial History

Pre-Trial

Trial Information

General Information

Title

The Impacts of Drought Tolerance on Local Labor Markets in India

RCT ID

AEARCTR-0002162

Initial registration date

April 18, 2017

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

April 19, 2017, 11:51 AM EDT

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

Locations

Country

India

Region

Jharkhand

Primary Investigator

Name

Elisabeth Sadoulet

Affiliation

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Alain Janvry

PI Affiliation

UC Berkeley

Contact Investigator

PI Name

Kyle Emerick

PI Affiliation

Tufts University

Contact Investigator

PI Name

Manzoor H. Dar

PI Affiliation

International Rice Research institute

Contact Investigator

Additional Trial Information

Status

On going

Start date

2014-06-01

End date

2017-05-31

Keywords

Agriculture, Labor

Additional Keywords

Drought, rice, labor market

JEL code(s)

Secondary IDs

Abstract

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)

J-PAL summary page

Registration Citation

Citation

Dar, Manzoor H. 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 H. et al. 2017. "The Impacts of Drought Tolerance on Local Labor Markets in India." AEA RCT Registry. April 19. https://www.socialscienceregistry.org/trials/2162/history/16681

Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2014-06-01

Intervention End Date

2017-05-31

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

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

Village

Was the treatment clustered?

Yes

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%

Supporting Documents and Materials

IRB