Human Capital Constraints, Spatial Dependence, and Regionalization in Bolivia: A Spatial Clustering Approach

Carlos Mendez,Erick Gonzales

doi:10.18800/economia.202101.007

Abstract

Using a novel dataset, this article studies the spatial distribution of human capital constraints across 339 municipalities in Bolivia. In particular, five human capital constraints are evaluated: chronic malnutrition in children, non-Spanish speaking population, secondary dropout rate of males, secondary dropout rates of females, and inequality in years of education. Through the lens of principal components, spatial dependence, and regionalization methods, the municipalities are endogenously classified according to their similarity in human capital constraints and geographical location. Results from the spatial dependence analysis indicate the specific location of significant hot spots (high-value clusters) and cold spots (low-value clusters). A regionalization analysis of the constraints indicates that Bolivia can be regionalized into seven or eight geographical regions. The article concludes discussing the potential complementary of these two analyses and their usefulness in identifying the location of policy priorities.

Highlights

Human capital is central for understanding individual earnings, inequality, and economic growth (Becker et al, 1990; Barro, 2001; Gemmell, 1996; Collin and Weil, 2020; Mincer, 1984; Psacharopoulos and Patrinos, 2018)
Using the novel dataset of SDSN-Bolivia (2020), we evaluate the spatial distribution of chronic malnutrition in children, non-Spanish speaking population, secondary dropout rate of males, secondary dropout rates of females, and inequality in the years of education
A spatial dependence analysis based on the local indicators of spatial association framework of Anselin (1995) allows us to identify local spatial clusters for each human capital constraint

Summary

Introduction

Human capital is central for understanding individual earnings, inequality, and economic growth (Becker et al, 1990; Barro, 2001; Gemmell, 1996; Collin and Weil, 2020; Mincer, 1984; Psacharopoulos and Patrinos, 2018). We apply principal components, spatial dependence, and regionalization methods to identify clusters of municipalities facing similar human capital constraints. Using the novel dataset of SDSN-Bolivia (2020), we evaluate the spatial distribution of chronic malnutrition in children, non-Spanish speaking population, secondary dropout rate of males, secondary dropout rates of females, and inequality in the years of education. The first component (PC1) mostly summarizes the regional variation in malnutrition in children, inequality of education, and non-Spanish speaking; while the second component (PC2) summarizes variation in the dropout rates

Objectives

Methods

Results

Discussion

Conclusion