Regional disparities and heterogeneous convergence in Indonesia: A multiscale geographically weighted regression approach

Abstract

This paper employs a Multiscale Geographically Weighted Regression (MGWR) model to examine the spatial variation of regional income convergence across Indonesia. This new MGWR model provides a multiscale analysis of spatial heterogeneity. Given the large socioeconomic, demographic, and geographic differences across Indonesian islands, models based on spatial heterogeneity are likely to provide a more accurate and realistic assessment of a regional convergence process. Most previous studies have largely ignored the role of spatial heterogeneity. They usually report a common convergence speed for all subnational regions. In contrast, this paper departs from the assumption of a common convergence speed and aims to identify multiple spatial clusters that characterize the heterogeneity of the regional convergence process of Indonesia.

Date
May 28, 2021 10:10 AM
Location
Virtual Conference
Carlos Mendez
Carlos Mendez
Associate Professor of Development Economics

My research interests focus on the integration of econometrics, spatial data science, and machine learning methods to understand and inform the process of development of countries, regions, and industries.

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