This paper introduces a dynamic panel data model in which the intercepts and the coefficients on the lagged endogenous variables are specific to the cross section units, while the coefficients on the exogenous variables are assumed to be normally distributed across the cross section. Thus the model includes mixture of fixed coefficients and random coefficients, which I call the “MFR” model. The...

This paper proposes a method for estimating a censored panel data model with a lagged latent dependent variable and individual-specific fixed effects. The main insight is to trim observations in such a way that a certain symmetry, which was destroyed by censoring, is restored. Based on the restored symmetry, orthogonality conditions are constructed and GMM estimation is implemented. Valid asymp...

The two-step GMM estimators of Arellano and Bond (1991) and Blundell and Bond (1998) for dynamic panel data models have been widely used in empirical work; however, neither of them performs well in small samples with weak instruments. The continuous-updating GMM estimator proposed by Hansen, Heaton, and Yaron (1996) is in principle able to reduce the small-sample bias, but it involves high-dime...

In a patent thicket licensing provides a mechanism to either avoid or resolve hold-up. Firms’ R&D incentives will differ depending on how licensing is used. In this paper we study the choice between ex ante licensing to avoid hold-up and ex post licensing to resolve it. Building on a theoretical model of a patent portfolio race, firms’ choices of licensing contracts are modelled. We derive seve...

This paper analyzes self-employment dynamics in West Germany over the time period 1984-2004. Using dynamic multinomial logit panel data models with random effects we are able to analyze the mobility between selfemployment, wage employment and non-employment. This allows us to draw conclusions about state dependence and cross-mobility patterns. The results indicate strong true state dependence i...

This paper develops a method for testing for the presence of a single structural break in dynamic panel data models with a multi-factor error structure. The test statistic is developed by combining a modified version of the GMM approach of Robertson and Sarafidis (2015) with the testing procedure of De Wachter and Tzavalis (2012). We focus on the case where N is large and T fixed. The asymptoti...

We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the cross-sectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models and derive the limiting distributions of the QML estimators under different assumptions on the initial observations. We propose a residual-based bootstrap met...

This paper establishes the almost sure convergence and asymptotic normality of levels and differenced quasi maximum-likelihood (QML) estimators of dynamic panel data models. The QML estimators are robust with respect to initial conditions, conditional and time-series heteroskedasticity, and misspecification of the log-likelihood. The paper also provides an ECME algorithm for calculating levels ...

The system GMM estimator developed by Blundell and Bond (1998) for dynamic panel data models has been widely used in empirical work; however, it does not perform well with weak instruments. This paper proposes a variation on the system GMM estimator, based on a simple transformation of the dependent variable. Simulation results indicate that, in finite samples, this transformed system GMM estim...

regarding the decentralization of credits management, this study examined the effect of fiscal policies on gross domestic product of the iranian provinces over the period 2001-2009. therefore, we used dynamic panel data and employed gmm-sys method to examine the model. the results show that the government expenditure and tax multiplier coefficients are less than one in short - run but greater t...