This paper provides an analysis of the role of prices in determining food purchases and nutrition using very detailed transaction-level observations for a large, nationally-representative sample of US consumers over the period 2002-2007. Using product- specific nutritional information, we...

This paper provides an analysis of the role of prices in determining food purchases and nutrition using very detailed transaction-level observations for a large, nationally-representative sample of US consumers over the period 2002-2007. Using product- specific nutritional information, we...

This paper proposes new ℓ1-penalized quantile regression estimators for panel data, which explicitly allows for individual heterogeneity associated with covariates. We conduct Monte Carlo simulations to assess the small sample performance of the new estimators and provide comparisons of new...

This paper considers the finite sample distribution of the 2SLS estimator and derives bounds on its exact bias in the presence of weak and/or many instruments. We then contrast the behavior of the exact bias expressions and the asymptotic expansions currently popular in the literature, including...

Big Data refers to data sets of much larger size, higher frequency, and often more personalized information. Examples include data collected by smart sensors in homes or aggregation of tweets on Twitter. In small data sets, traditional econometric methods tend to outperform more complex...

This paper provides a cautionary tale about claiming environmental costs and benefits when justifying the use of public funds. Using the example of a dynamic pricing policy, we show that the resulting impact on short-term operating costs and emissions is at best ambiguous. Moreover, it is hard...

This paper proposes a quantile regression estimator for a panel data model with interactive effects potentially correlated with the independent variables. We provide conditions under which the slope parameter estimator is asymptotically Gaussian. Monte Carlo studies are carried out to...

In this paper we introduce a new flexible mixed model for multinomial discrete choice where the key individual- and alternative-specific parameters of interest are allowed to follow an assumptionfree nonparametric density specification while other alternative-specific coefficients are assumed to...