We estimate the speed of income convergence for a sample of 196 European NUTS 2 regions over the period 1985-1999. So far there is no direct estimator available for dynamic panels with strong spatial dependencies. We propose a two-step procedure, which involves first spatial filtering of the variables to remove the spatial correlation, and application of standard GMM estimators for dynamic pane...

Estimation of the dynamic error components model is considered using two alternative linear estimators that are designed to improve the properties of the standard firstdifferenced GMM estimator. Both estimators require restrictions on the initial conditions process. Asymptotic efficiency comparisons and Monte Carlo simulations for the simple AR(1) model demonstrate the dramatic improvement in p...

This paper derives explicit expressions for the asymptotic variances of the maximum likelihood and continuously updated GMM estimators under potentially misspecified models. The proposed misspecification-robust variance estimators allow the researcher to conduct valid inference on the model parameters even when the model is rejected by the data. Although the results for the maximum likelihood e...

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 instrumental variable settings. In this paper we give a new variance estimator for GEL that addresses this problem. It is consistent under the usual asymptotics and under ...

Missing data is one of the most common challenges facing empirical researchers. This paper presents a general GMM framework for dealing with missing data on explanatory variables or instrumental variables. For a linear-regression model with missing covariate data, an efficient GMM estimator under minimal assumptions on missingness is proposed. The estimator, which also allows for a specificatio...

We modify a previously suggested GMM estimator in a spatial panel regression model by taking into account the difference between disturbances and regression residuals and derive its asymptotic properties. Simulation results and an empirical application to Indonesian rice data illustrate the improvement in finite samples. JEL Classification: C13, C21

We estimate the speed of income convergence for a sample of 196 European NUTS 2 regions over the period 1985-1999. So far there is no direct estimator available for dynamic panels with strong spatial dependencies. We propose a two-step procedure, which involves first spatial filtering of the variables to remove the spatial correlation, and application of standard GMM estimators for dynamic pane...

JEL classification: F12

in this paper, the effect of trade openness on growth is examined across the members of organization of the islamic conference (oic) by using convergence-growth equation and gmm-system dynamic panel data estimator over the period 1980-2009. the results show that the overall trade, the trade with non-oic countries, and the investment in physical and human capital stimulate economic growth. in co...

This paper discusses likelihood-based estimation of panel data models with individualspecific effects and both lagged dependent variable regressors and additional predetermined explanatory variables. The resulting new estimator, labeled as sub-system LIML (ssLIML), is asymptotically equivalent to standard panel GMM as N →∞ for fixed T , but tends to present smaller biases in finite samples as i...