In this paper we examine the panel data estimation of dynamic models for count data that include correlated fixed effects and predetermined variables.

This chapter reviews developments to improve on the poor performance of the standard GMM estimator for highly autoregressive panel series. It considers the use of the system GMM estimator that relies on relatively mild restrictions on the initial condition process. This system GMM estimator...

less skilled workers has deteriorated, either through their ability to secure jobs and/or their ability to earn a decent wage. Some have linked this decline to modern computing technologies. This paper surveys the evidence on the effects of technical change on skills, wages and employment by...

We use matched employee-employer data from the UK to highlight the importance of social skills, including the ability to work well in a team and communicate effectively with co-workers, as a driver for individual wage growth for workers with few formal educational qualifications. We show that...

This paper investigates the relationship between product market competition (PMC) and innovation. A Schumpeterian growth model is developed in which firms innovate ѳtep-by-stepҬ and where both technological leaders and their followers engage in R&D activities. In this model, competition...

How does firm entry affect innovation incentives in incumbent firms? Micro data suggest that there is heterogeneity across industries. Specifically, incumbent productivity growth and patenting is positively correlated with lagged greenfield foreign firm entry in technologically advanced...

This paper gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are...

We consider a number of unit root tests for micro panels where the number of individuals is typically large, but the number of time periods is often very small. As we discuss, the presence of a unit root is closely related to the identification of parameters of interest in this context....

Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. Two step GMM is biased. Generalized empirical likelihood (GEL) has smaller bias but the usual standard errors are too small. In this paper we use alternative asymptotics, based on many weak moment...

ExpEnd is a Gauss programme for non-linear generalised method of moments (GMM) estimation of exponential models with endogenous regressors for cross section and panel data. The estimators included in this package are simple Poisson pseudo ML; GMM for cross section data using moment conditions...