Knowledge that Transforms

We survey and apply several techniques from the statistical and computer science literature to the problem of demand estimation. To improve out-of-sample prediction accuracy, we propose a method of combining the underlying models via linear regression. Our method is robust to a large number of regressors; scales easily to very large data sets; combines model selection and estimation; and can flexibly approximate arbitrary non-linear functions. We illustrate our method using a standard scanner panel data set and find that our estimates are considerably more accurate in out-of-sample predictions of demand than some commonly used alternatives.

I study an economy where asymmetric information about the quality of capital endogenously determines liquidity. Liquid funds are key to relaxing financial constraints on investment and employment. These funds are obtained by selling capital or using it as collateral. Liquidity is determined by balancing the costs of obtaining liquidity under asymmetric information against the benefits of relaxing financial constraints. Aggregate fluctuations follow increases in the dispersion of capital quality, which raise the cost of obtaining liquidity. An estimated version of the model can generate patterns for quantities and credit conditions similar to the Great Recession. (JEL D82, E22, E24, E32, E44, G01)

Following FCC pressure to end bill shock, cellular carriers now alert customers when they exceed usage allowances. We estimate a model of plan choice, usage, and learning using a 2002–2004 panel of cellular bills. Accounting for firm price adjustment, we predict that implementing alerts in 2002–2004 would have lowered average annual consumer welfare by $33. We show that consumers are inattentive to past usage, meaning that bill-shock alerts are informative. Additionally, our estimates imply that consumers are overconfident, underestimating the variance of future calling. Overconfidence costs consumers $76 annually at 2002–2004 prices. Absent overconfidence, alerts would have little to no effect. (JEL D12, D18, L11, L96, L98)

In Capital in the Twenty-First Century, Thomas Piketty uses the market value of tradable assets to measure both productive capital and wealth. As a measure of wealth this is problematic because it ignores the value of human capital and transfer wealth, which have grown enormously over the last 300 years. Thus the constancy of the wealth/income ratio as portrayed in his data is an illusion. Further, the types of wealth that he does not measure are more equally distributed than tradable assets. The approach also incorrectly identifies capital gains due to reduced discount rates as increases in the capital stock.

The ability of web-based retailers to learn about and provide targeted consumer experiences is touted as an important distinction from traditional retailers. In principal, web-based insurance exchanges could benefit from these advantages. Using data from a large-scale experiment by a private sector health insurance exchange we estimate the returns to experimentation and targeted messaging. We find significant improvements in conversions in one treatment tested. Underlying the average impact were both intertemporal and demographic heterogeneity. We estimate that learning and targeted messaging could increase insurance applications by approximately 13 percent of the baseline conversion rate.

Gary Becker was one of the greatest thinkers of the 20th century. He advanced social science by introducing economic thinking into areas that were thought to be off limits. Because his theory was motivated by his desire to explain the world, his analyses were highly policy relevant. His work on discrimination, deterrence of crime, fertility, human capital, and the family all produced implications that were testable and verified by his and others' empirical research. Equally important, each research area provided policy guidance and many of his ideas have been implemented by government and non-government organizations.

We study the procompetitive gains from international trade in a quantitative model with endogenously variable markups. We find that trade can significantly reduce markup distortions if two conditions are satisfied: (i) there is extensive misallocation, and (ii) opening to trade exposes hitherto dominant producers to greater competitive pressure. We measure the extent to which these two conditions are satisfied in Taiwanese producer-level data. Versions of our model consistent with the Taiwanese data predict that opening up to trade strongly increases competition and reduces markup distortions by up to one-half, thus significantly reducing productivity losses due to misallocation. (JEL D43, F12, F14, L13, L60, O47)

It has been proposed that geography influences economic growth for many reasons. Previous analyses of comparative development seem to have sidestepped the question of location-dependent depreciation. However the construction of new measures of tropical cyclone exposure enables us to consider the potential impact of this single source of capital depreciation. Using an estimate of asset destruction due to tropical cyclones, we identify the “sandcastle depreciation” rate, and find support for location-dependent depreciation by looking at average growth rates. This leads us to propose that heterogeneous and geographically-dependent depreciation rates may play an important role in global patterns of economic development.

Violence against women is a critical problem across the world. In this paper, we exploit state and temporal variation in alcohol control in India to examine the impact of prohibition on alcohol consumption and violent crimes against women. We first use detailed household survey data to show that prohibition policies are associated with substantially lower rates of drinking among men and domestic violence. Next, we provide evidence that alcohol prohibition reduces aggregate violence against women in officially reported crime data. The results suggest that policies that restrict access to alcohol may help reduce gender violence.

Andreoni and Sprenger (2012a,b) observe that utility functions are distinct for risk and time preferences, and show that their findings are consistent with a preference for certainty. We revisit this question in an enriched experimental setting in which subjects make intertemporal decisions under different risk conditions. The observed choice behavior supports a separation between risk attitude and intertemporal substitution rather than a preference for certainty. We further show that several models, including Epstein and Zin (1989); Chew and Epstein (1990); and Halevy (2008) exhibit such a separation and can account for the overall experimental findings. (JEL C91, D81, D91)