We consider estimation in a particular semiparametric regression model for the mean of a counting process under the assumption of “panel count” data. The basic model assumption is that the conditional mean function of the counting process is of the form E{N(t)|Z} = exp(θ′Z)Λ(t) where Z is a vector of covariates and Λ is the baseline mean function. The “panel count” observation scheme involves o...

A simulation study designed to evaluate the pseudo-R2T proposed in an earlier paper by Spiess and Keller suggests that, for the models considered, this measure represents the goodness of fit not only of the systematic part, but also of the assumed correlation structure in binary panel probit models.

The degree of mobility in incomes is often seen as an important measure of the equality of opportunity in a society and of the flexibility and freedom of its labor market. However, estimation of mobility using panel data is biased by the presence of measurement error and non-random attrition from the panel. This paper shows that dynamic pseudo-panel methods can be used to consistently estimate ...

OBJECTIVES The US ranks ninth in obesity in the world, and approximately 7% of US adults experience major depressive disorder. Social isolation due to the stigma attached to obesity might trigger depression. METHODS This paper examined the impact of obesity on depression. To overcome the endogeneity problem, we constructed pseudopanel data using the Behavioral Risk Factor Surveillance System ...

This paper proposes a new approach to estimate panel data models with group specific parameters when group membership is not known. We first create a set of “pseudo” threshold variables based on time series estimation of the individual specific parameters. We then use these variables to stratify individuals. The problem of parameter heterogeneity is turned into estimation of a panel threshold m...