The extant literature using household scanner data to estimate consumer choice models has identified two key sources of bias in estimated mean responses to marketing variables. Omitted heterogeneity may bias mean responses towards zero. At the same time, omitted time-varying characteristics of...

We study changes in markups across 72 product markets from 2006 to 2018. A growing literature has documented a rise in markups over time using a production function approach; we instead employ the standard microeconomic method, which is to estimate demand and then invert firms' first-order...

We propose a generalized estimating equations approach to the analysis of the mean and the covariance structure of a bivariate time series process of panel data with mixed continuous and discrete dependent variables. The approach is used to jointly analyze wage dynamics and the incidence of...

We propose four different GMM estimators that allow almost consistent estimation of the structural parameters of panel probit models with fixed effects for the case of small T and large N. The moments used are derived for each period from a first order approximation of the mean of the dependent...

In this paper we discuss tests for residual cross section dependence in nonlinear panel data models. The tests are based on average pair-wise residual correlation coefficients. In nonlinear models, the definition of the residual is ambiguous and we consider two approaches: deviations of the...

The bivariate probit model is frequently used for estimating the effect of an endogenous binary regressor (the treatment) on a binary health outcome variable. This paper discusses simple modifications that maintain the probit assumption for the marginal distributions while introducing non-normal...

We develop a simulated ML method for short-panel estimation of one or more dynamic linear equations, where the dependent variables are only partially observed through ordinal scales. We argue that this latent autoregression (LAR) model is often more appropriate than the usual state-dependence...

We study entrepreneurs’ behavioral responses of effort (moral hazard) to avoid business failure.This is done in the context of an unemployment insurance scheme for self-employed, wherewe estimate how much of the transition probability to unemployment can be causally attributedto being insured....

We specify and estimate a dynamic structural life-cycle model of labor supply, retirement and savings decisions of single-adult and couple households. Drawing on our model, we study the interplay between family labor supply and public insurance mechanisms. By including family labor supply, we...

In applied microeconometric panel data analyses, time-constant random effects and first-order Markov chains are the most prevalent structures to account for intertemporal correlations in limited dependent variable models. An example from health economics shows that the addition of a simple...