Abstract
This chapter contains an empirical study that investigates growth and convergence in labor productivity across the different provinces in mainland China during the period of 1982–2010. Based on the theoretical framework of the Solow growth model, this study advocates a panel data approach, and shows that this panel data approach, in which the familiar equation for testing convergence is reformulated into a dynamic panel data model, leads to results that are significantly different from those obtained from cross-section regressions. In this empirical study of the Chinese provinces, the panel data approach has resulted in higher rates of conditional convergence and lower values of the elasticity of output with respect to capital, compared with cross-section estimations. The analysis in this chapter brings to the fore the fact that, even with similar rates of saving and population growth, a Chinese province can directly improve its long-run economic position by achieving improvements in the various factors that underlie its total factor productivity.
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