Evidence and Strategy on Economic Distance in Spatially Augmented Solow-Swan Growth Model

TL;DR

This paper investigates whether economic distance matrices are endogenous in the spatially augmented Solow-Swan growth model, using empirical tests and data from 1960-2010, revealing the importance of endogeneity for spatial externalities.

Contribution

It provides an empirical strategy to determine the endogeneity of economic distance in spatial growth models, highlighting the significance of endogenous spatial weights.

Findings

Endogenous $W$ models show significant positive externalities.

Exogenous $W$ models do not show these effects.

Economic shocks influence the choice of distance measures.

Abstract

Economists' interests in growth theory have a very long history (Harrod, 1939; Domar, 1946; Solow, 1956; Swan 1956; Mankiw, Romer, and Weil, 1992). Recently, starting from the neoclassical growth model, Ertur and Koch (2007) developed the spatially augmented Solow-Swan growth model with the exogenous spatial weights matrices ($W$). While the exogenous $W$ assumption could be true only with the geographical/physical distance, it may not be true when economic/social distances play a role. Using Penn World Table version 7.1, which covers year 1960-2010, I conducted the robust Rao's score test (Bera, Dogan, and Taspinar, 2018) to determine if $W$ is endogeonus and used the maximum likelihood estimation (Qu and Lee, 2015). The key finding is that the significance and positive effects of physical capital externalities and spatial externalities (technological interdependence) in Ertur and Koch (2007) were no longer found with the exogenous $W$, but still they were with the endogenous $W$ models. I also found an empirical strategy on which economic distance to use when the data recently has been under heavy shocks of the worldwide financial crises during year 1996-2010.