The literature that tests for U-shaped relationships using panel data, such as those between pollution and income or inequality and growth, reports widely divergent (parametric and non-parametric) empirical findings. We explain why lack of identification lies at the root of these differences. To...

This paper uses micro data from four OECD countries (the United States, Spain, Italy, and the Netherlands), to assess the determinants of household debt holding and to investigate whether or not credit constraints are important for household debt holding. We extend the existing literature in...

We investigate the presence of moral hazard and advantageous or adverse selection in a market for supplementary health insurance. For this we specify and estimate dynamic models for health insurance decisions and health care utilization. Estimates of the health care utilization models indicate...

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....

An exact maximum likelihood method is developed for the estimation of parameters in a nonlinear non-Gaussian dynamic panel data model with unobserved random individual-specific and time-varying effects. We propose an estimation procedure based on the importance sampling technique. In particular,...

(Spatial) panel data are routinely modelled in discrete time (DT). However, there are compelling arguments for continuous time (CT) modelling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an...

We propose a dynamic clustering model for studying time-varying group structures in multivariate panel data. The model is dynamic in three ways: First, the cluster means and covariance matrices are time-varying to track gradual changes in cluster characteristics over time. Second, the units of...

An exact maximum likelihood method is developed for the estimation of parameters in a nonlinear non-Gaussian dynamic panel data model with unobserved random individual-specific and time-varying effects. We propose an estimation procedure based on the importance sampling technique. In particular,...

In this paper we consider modeling and forecasting of large realized covariance matrices by penalized vector autoregressive models. We propose using Lasso-type estimators to reduce the dimensionality to a manageable one and provide strong theoretical performance guarantees on the forecast...

Distorted performance measures in compensation contracts elicit suboptimal behavioral responses that may even prove to be dysfunctional (gaming). This paper applies the empirical test developed by Courty and Marschke (2008) to detect whether the widely used class of Residual Income based...