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....

In this paper we examine the properties of a simple criterion-based, likelihood ratio type test of parameter restristions for standard GMM estimators in autoregressive panel data models. A comparison is made with recent test proposals based in the continuously-updated GMM criterion (Hansen,...

We consider to what extent the empirical failings of the Q model of investment can be attributed to the use of share prices to measure average q. We show that the usual empirical formulation may fail to identify the Q model when stock market valuations deviate from the present value of expected...

We derive robust predictions on the effects of uncertainty on short run investment dynamics in a broad class of models with (partial) irreversibility. When their environment becomes more uncertain firms become more cautious and less responsive to demand shocks. This result contrasts with the...

Cobb Douglas production function parameters are not identified from cross-section variation when inputs are perfectly flexible and chosen optimally, and input prices are common to all firms. We consider the role of adjustment costs for inputs in identifying these parameters in this context. The...

Despite a long history of reports and initiatives on the harmonisation of corporate income taxes within the European Union, the 15 EU countries still operate their own national corporate income taxes, with only limited co-ordination between them. However, the increasing integration of economic...

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...

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...

We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using Generalised Method of Moments (GMM). These include standard asymptotic Wald tests based on one-step and two-step GMM estimators; two bootstrapped versions of these...