We present in this paper the panel econometrics estimation approach of measuring the technical change and total factor productivity (TFP) growth of 30 Chinese provinces during the period of 1993 to 2003. The random effects model with heteroscedastic variances has been used for the estimation of...

We present in this paper the panel econometrics estimation approach of measuring the technical change and total factor productivity (TFP) growth of 30 Chinese provinces during the period of 1993 to 2003. The random effects model with heteroscedastic variances has been used for the estimation of...

This paper analyzes the effect of time aggregation on estimates of the elasticities of output with respect to employment and to average hours of work. The main goal is to get accurate estimates of production function parameters. Low frequency data generate better estimates of output- employment...

We employ a two-step approach in investigating the dynamic transmission channels under which globalization factors foster technical efficiency by combining a dynamic efficiency analysis in the stochastic frontier framework, and a time series approach based on VAR and spectral analysis. Using the...

This paper, using the Bewley (1979) transformation of the autoregressive distributed lag model, proposes a novel pooled Bewley (PB) estimator of long-run coefficients for dynamic panels with heterogeneous short-run dynamics, in the same setting as the widely used Pooled Mean Group (PMG)...

This paper proposes nonparametric kernel-smoothing estimation for panel data to examine the degree of heterogeneity across cross-sectional units. We first estimate the sample mean, autocovariances, and autocorrelations for each unit and then apply kernel smoothing to compute their density...

The finite sample behaviour is analysed of particular least squares (LS) and method of moments (MM) estimators in panel data models with individual effects and both a lagged dependent variable regressor and another explanatory variable which may be affected by lagged feedbacks from the dependent...

This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic relationships within a longitudinal data setting. The discussion surveys approaches for characterizing the micro dynamics of continuous dependent variables both over time and across...

In this paper we explore a new approach to estimation for autoregressive panel data models, based on projecting the unobserved individual effects on the vector of observations on the lagged dependent variable. This approach yields estimators which coincide with known generalised method of...

This paper investigates the estimation and inference of spatial panel data models in which the regression coefficient vector is a trending function. We use time differences to eliminate the individual effects and employ GMM estimations for regression coefficients with both linear and quadratic...