Growth and convergence in a multi‐country empirical stochastic Solow model
使用102个国家1960-1989年的面板数据，构建随机索洛增长模型，发现传统β趋同估计存在显著偏误，且各国稳态增长率差异很大，导致β估计值高于文献共识但精度低、难解释。
The paper considers international per capita output and its growth using a panel of data for 102 countries between 1960 and 1989. It sets out an explicitly stochastic Solow growth model and shows that this has quite different properties from the standard approach where the output equation is obtained by adding an error term to the linearized solution of a deterministic Solow model. It examines the econometric properties of estimates of beta convergence as traditionally defined in the literature and shows that all these estimates are subject to substantial biases. Our empirical estimates clearly reflect the nature and the magnitude of these biases as predicted by econometric theory. Steady state growth rates differ significantly across countries and once this heterogeneity is allowed for the estimates of beta are substantially higher than the consensus in the literature. But they are very imprecisely estimated and difficult to interpret. The paper also discusses the economic implications of these results for sigma convergence. © 1997 John Wiley & Sons, Ltd.