This paper makes three contributions. Firstly, it uses copula functions to obtain a flexible bivariate parametric model for non-negative integer-valued data (counts). Secondly, it recovers the distribution of the difference in the two counts from a specified bivariate count distribution....

Microeconometrics Using Stata, Revised Edition, by A. Colin Cameron and Pravin K. Trivedi, is an outstanding introduction to microeconometrics and how to do microeconometric research using Stata. Aimed at students and researchers, this book covers topics left out of microeconometrics textbooks...

This paper makes three contributions. First, it uses copula functions to obtain a flexible bivariate parametric model for nonnegative integer-valued data (counts). Second, it recovers the distribution of the difference in the two counts from a specifed bivariate count distribution. Third, the...

Our empirical investigation confirms the common belief that retail gasoline prices react more quickly to increases in crude oil prices than to decreases. Nearly all of the response to a crude oil price increase shows up in the pump price within 4 weeks, while decreases are passed along gradually...

In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM, that provcides cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the standard cluster-robust...

Researchers have increasingly realized the need to account for within-group dependence in estimating standard errors of regression parameter estimates. The usual solution is to calculate cluster-robust standard errors that permit heteroskedasticity and within-cluster error correlation, but...

This presentation provides an overview of the subset of methods for panel data and the associated Stata xt commands most commonly used by microeconometricians. First, attention is focused on a short panel, meaning data on many individual units and few time periods. Examples include longitudinal...

This talk considers robust inference for regression models where data are clustered, with correlation of observations in the same cluster (such as state) and independence across clusters. The talk will range from the simplest case of heteroskedastic-ro bust (one individual per cluster) through...