Specific Objectives of the Project:

The project’s objectives were to answer the following research questions:

1. Under a wide range of climate models and GHG policy futures, what will be the geographically distinct impacts of climate change on yields of key agricultural products (maize, soy, rice, wheat, sorghum, and cassava)?

2. What is the role of farmer adaptation to a changing climate, as well as changing incomes, in mitigating the effects of climate change on yields?

3. How much do the costs of farmer adaptation offset any adaptation gains they might realize?

Summary of Results:

Over the time period of the GF grant we estimated the responsiveness of spring and winter wheat to temperature and precipitation shocks, accounting for heterogeneity over local climate (long-run temperature and long-run precipitation), local income, and local access to irrigation. We additionally completed a Monte Carlo uncertainty analysis of the impacts of climate change on yields of six staple crops at global scale, accounting for adaptation: corn, soybean, rice, wheat, cassava, and sorghum. We found that adaptation is at least partially protective for all crops, but global productivity losses ranging from 25-45% percent (point estimates) persist for all crops except rice, for which adaptation is fully protective.

Specific Objectives of the Project
Estimate the effects of different school meal vendors on academic achievement, with a particular interest in whether healthy vendors have larger impacts than other vendors.

Project Report/Summary of Results
The project assigned each vendor in our sample a “standard” or “healthy” vendor classification based on information published by the vendors. We then estimated our main specifications and found that contracting with a healthy meal vendor increases test scores by 0.03 standard deviations (relative to keeping meal preparation “in house”). The result is highly significant and robust to the inclusion of all our available control variables. We also found that contracting with a healthy vendor has almost twice as large an effect on economically disadvantaged students (0.05 standard deviations) as it does on non-disadvantaged students.

Specific Objectives of the Project:
Original: Evaluate how changes to the WIC program have affected consumers and the foods that they purchase using scanner data from a large chain of grocery stores.
Amended: Estimate the effects of different school meal vendors on academic achievement, with a particular interest in whether healthy vendors have larger impacts than other vendors.

Project Report/Summary of Results:
The original project proved to be infeasible as the coverage of the available data was not sufficiently rich during the periods that the WIC program changed.
The amended project assigned each vendor in our sample a “standard” or “healthy” vendor classification based on information published by the vendors. We then estimated our main specifications and found that contracting with a healthy meal vendor increases test scores by 0.03 standard deviations (relative to keeping meal preparation “in house”). The result is highly significant and robust to the inclusion of all our available control variables. We also found that contracting with a healthy vendor has almost twice as large an effect on economically disadvantaged students (0.05 standard deviations) as it does on non-disadvantaged students.

Do changes in food commodity prices have asymmetric effects on retail grocery prices? For years, farmers, consumer advocates and others have argued that grocery store prices rise rapidly in response to increases in commodity prices, but do not fall equally rapidly when commodity prices drop. We examine pricing in both stores that have regular sales and those that use everyday low pricing and rarely have sales. For both types of stores, we find very little evidence for asymmetric price adjustment. We believe that some earlier studies found asymmetric adjustments because they did not use narrowly defined products, control for all the main factor prices, and use state-of-the-arts estimation procedures.