We study the impact of child work on cognitive development in four Low- and Middle-Income Countries. We advance the literature by using cognitive test scores collected regardless of school attendance. We also address a key gap in the literature by controlling for children's complete time...

We study the relationship between child work and cognitive development in four Low and Middle Income Countries. We address a key weakness in the literature by including children's full time-use vector in the analysis, which leads to different findings from previous studies which do not...

We study potential impacts of future climate change on U.S. agricultural productivity using county-level yield and weather data from 1950 to 2015. To account for adaptation of production to different weather conditions, it is crucial to allow for both spatial and temporal variation in the...

We study the impact of child work on cognitive development in four Low- and Middle-Income Countries. We advance the literature by using cognitive test scores collected regardless of school attendance. We also address a key gap in the literature by controlling for children's complete time...

We propose new methods to model behavior and conduct welfare analysis in complex environments where some choices are unlikely to reveal preferences. We develop a mixture-of-experts model that incorporates heterogeneity in consumers' preferences and in their choice processes. We also develop a...

We provide a simple survey of the literature on weak instruments, aimed at giving practical advice to applied researchers. It is well-known that 2SLS has poor properties if instruments are exogenous but “weak.” We clarify these properties, explain weak instrument tests, and examine how...

We study the impact of child work on cognitive development in four Low- and Middle-Income Countries. We advance the literature by using cognitive test scores collected regardless of school attendance. We also address a key gap in the literature by controlling for children’s complete time...

Predicting the impact of climate change on crop yield is difficult, in part because the production function mapping weather to yield is high dimensional and nonlinear. We compare three approaches to predicting yields: (i) deep neural networks (DNNs), (ii) traditional panel-data models, and (iii)...

We study potential impacts of future climate change on U.S. agricultural productivity using county-level yield and weather data from 1950 to 2015. To account for adaptation of production to different weather conditions, it is crucial to allow for both spacial and temporal variation in the...

We study the relationship between child work and cognitive development in four Low and Middle Income Countries. We address a key weakness in the literature by including children’s full time-use vector in the analysis, which leads to different findings from previous studies which do not...