Adaptation to Environmental Change in Agriculture

• Closed to further applications

Proposal Description:

Climate change is hitting poor countries hard. Farmers in countries that are already hot will see production fall and may have little margin to adapt and remain in agriculture. To what extent can farmers adapt their production to extreme environmental change? How does this adaptation depend on local common resources and policy regimes?

We will study farmer adaptation to man-made environmental change with two projects on agriculture in India. The first project is “Rationing the Commons.” This project analyzes data on farmer production to relate farm productivity to the use of groundwater resources. Farming with groundwater yields higher profit at lower risk for Indian farmers, but groundwater is growing scarce over time, in a classic tragedy of the commons, as farmers use cheap electricity to pump more water out of the ground. This project studies how both farmers and the government respond to water scarcity using survey data on agricultural production and geodata on water scarcity.

The second project is “Direct Benefit Transfers for Electricity” (DBTE). This project will analyze data from randomized experiments on reforms to the current regimes for groundwater management in India. The DBTE reform exchanges inefficient price subsidies for agricultural power use for targeted lump-sum subsidies, with the goal of incentivizing power and water conservation. We analyze the farmer response to this incentive and compare the results of the experiment to the long-run estimates on adaptation to water scarcity obtained from the first project. The pre-doctoral fellow will therefore acquire skills related to both structural econometric methods and the analysis of data from large-scale randomized experiments.

Requisite Skills and Qualifications:

The position would be for one year with the possibility of extending it for a second year. The fellow will be based at Yale University under the direction of Professor Nicholas Ryan. The fellow will be involved in all parts of the research process from data cleaning and analysis to the presentation of results.

Candidates should have a bachelor’s degree in economics, statistics, mathematics, computer science, engineering, political science or related fields showing strong quantititative skills. Coding skills in statistical languages such as Matlab, R and Stata are expected. GIS experience a plus but not a requirement. Interests in development economics, energy economics and industrial organization are all helpful.

Please apply with a cover letter, resume, transcript, two letters of reference and a code sample of something that you wrote yourself. Applicants must be either U.S. citizens, permanent residents, or have a valid work visa or OPT status. Applications are received and reviewed on a rolling basis.