For the estimation of many econometric models, integrals without analytical solutions have to be evaluated. Examples include limited dependent variables and nonlinear panel data models. In the case of one-dimensional integrals, Gaussian quadrature is known to work efficiently for a large class...

We use firm-level data to investigate the impact of taxes on the international location of targets in M&A allowing for heterogeneous responses by companies. The statutory tax rate in the target country is found to have a negative impact on the probability of an acquisition in that country. In...

Despite increasing popularity, quality improvement programs (QIP) have had modest and variable impacts on enhancing the quality of physician practice. We investigate the heterogeneity of physicians' preferences as a potential explanation of these mixed results in France, where the national...

This paper empirically investigates the household's decision to reside and work either inthe central metropolitan area, or in the surrounding nonmetropolitan area, or to commutebetween the two regions. As economic theory suggests the location decisionamounts to trading off wages, housing costs,...

For the estimation of many econometric models, integrals without analytical solutions have to be evaluated. Examples include limited dependent variables and nonlinear panel data models. In the case of one-dimensional integrals, Gaussian quadrature is known to work efficiently for a large class...

In this paper we use mixed logit specifications to allow parameters to vary in the population when estimating the value of time for long-distance car travel. Our main conclusion is that the estimated value of time is very sensitive to how the model is specified: we find that it is significantly...

This paper investigates and extends the computationally attractive nonparametric random coefficients estimator of Fox, Kim, Ryan, and Bajari (2011). We show that their estimator is a special case of the nonnegative LASSO, explaining its sparse nature observed in many applications. Recognizing...

This paper investigates and extends the computationally attractive nonparametric random coefficients estimator of Fox, Kim, Ryan, and Bajari (2011). We show that their estimator is a special case of the nonnegative LASSO, explaining its sparse nature observed in many applications. Recognizing...

We propose a simple mixtures estimator for recovering the joint distribution of parameter heterogeneity in economic models, such as the random coefficients logit. The estimator is based on linear regression subject to linear inequality constraints, and is robust, easy to program, and...