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Peru's Regional Growth and Convergence in 1979-2017: An Empirical Spatial Panel Data Analysis

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This paper analyzes the process of spatial convergence of growth in Peru’s 24 regions over 1979-2017. We perform an exploratory analysis of spatial data with global and local statistics, such as Moran I, to provide empirical evidence of spatial dependencies in regional per capita GDP. We then estimate the convergence equation using spatial panel models that control for spatial heterogeneity and spatial interdependence, as well as other structural economic features at the regional level. The empirical results show that spatial convergence is a very reliable conclusion over this period, and prove that spatial regional per capita GDP spillovers play an essential role in determining growth at the local level. Furthermore, the Spatial Durbin model is preferred in the formation of four clusters of convergence. The first cluster is highly productive and dynamic; the second cluster is composed by Jungle and negative-productivity regions; the third cluster is formed by moderately productive and Coast regions; and the fourth cluster is composed by stagnating and Highland regions. Finally, these results may be instrumental in giving greater focus to long-run government policies targeting stagnant and poor regions.


Regional Convergence, Regional Spillovers, Spatial Dependence Modeling, Spatial Panel Data Models, Clusters of Convergence.

JEL Classification

C21, C23, R11