Cross-country convergence in a general Lotka–Volterra model
Jan Ditzen
Abstract
Jan Ditzen
Abstract
This paper uses a general Lotka–Volterra model to estimate convergence for 93 countries over the period 1960–2007. It employs an equation with a spatial time lag and common factors. The spatial lag controls for spatial dependence, while the common factors control for strong cross-sectional dependence. As spatial weights matrices, the shares of high-skilled migrants, trade shares and foreign direct investments are used. A simultaneous least squares estimator and a dynamic common correlated effects (DCCE) estimator are employed. The DCCE estimator finds conditional convergence. The paper highlights the importance of controlling for both types of cross-sectional dependence.
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This paper uses a general Lotka–Volterra model to estimate convergence for 93 countries over the period 1960–2007. It employs an equation with a spatial time lag and common factors. The spatial lag controls for spatial dependence, while the common factors control for strong cross-sectional dependence. As spatial weights matrices, the shares of high-skilled migrants, trade shares and foreign direct investments are used. A simultaneous least squares estimator and a dynamic common correlated effects (DCCE) estimator are employed. The DCCE estimator finds conditional convergence. The paper highlights the importance of controlling for both types of cross-sectional dependence.
Key concepts: Estimator, Lag, Convergence (economics), Econometrics, Mathematics, Spatial dependence, Least-squares function approximation, Statistics