The U.S. retail trade sector underwent a massive restructuring and reallocation of activity in the 1990s with accompanying technological advances. Using a data set of establishments in that sector, we quantify and explore the relationship between this restructuring and reallocation and labor productivity dynamics. We find that virtually all of the labor productivity growth in the retail trade sector is accounted for by more productive entering establishments displacing much less productive exiting establishments. The productivity gap between low-productivity exiting single-unit establishments and entering high-productivity establishments from large, national chains plays a disproportionate role in these dynamics. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

This paper applies the recently developed econometric methods of panel unit root tests and nonlinear mean reversion to investigate price convergence in China--the largest transitional economy in the world. We find that prices did converge to the law of one price in China for an overwhelming majority of goods and services, based on a large panel data set. The finding sheds light on the extent of the market economy in China, and casts doubt on Young's proposition that the economic reform has led to the fragmentation of Chinese domestic markets.

Abstract Although economists have long been aware of Jensen's inequality, many econometric applications have neglected an important implication of it: under heteroskedasticity, the parameters of log-linearized models estimated by OLS lead to biased estimates of the true elasticities. We explain why this problem arises and propose an appropriate estimator. Our criticism of conventional practices and the proposed solution extend to a broad range of applications where log-linearized equations are estimated. We develop the argument using one particular illustration, the gravity equation for trade. We find significant differences between estimates obtained with the proposed estimator and those obtained with the traditional method.

We link farmland values to climatic, soil, and socioeconomic variables for U.S. counties east of the 100th meridian, the historical boundary of agriculture not primarily dependent on irrigation. Degree days, a nonlinear transformation of the climatic variables suggested by agronomic experiments as more relevant to crop yield, gives an improved fit and increased robustness. Estimated coefficients are consistent with the experimental results. The model is employed to estimate the potential impacts on farmland values for a range of recent warming scenarios. The predictions are very robust, and more than 75% of the counties in our sample show a statistically significant effect, ranging from moderate gains to large losses, with losses in the aggregate that can become quite large under scenarios involving sustained heavy use of fossil fuels.

We link farmland values to climatic, soil, and socioeconomic variables for counties east of the 100th meridian, the historic boundary of agriculture not primarily dependent on irrigation. Degree days, a non-linear transformation of the climatic variables suggested by agronomic experiments as more relevant to crop yield gives an improved fit and increased robustness. Estimated coefficients are consistent with the experimental results. The model is employed to estimate the potential impacts on farmland values for a range of recent warming scenarios. The predictions are very robust and more than 75% of the counties in our sample show a statistically significant effect, ranging from moderate gains to large losses, with losses in the aggregate that can become quite large under scenarios involving sustained heavy use of fossil fuels.