Influence of Spatial Factors on Human Development: The Peruvian Case

Abstract

The objective of this study was to estimate the influence of spatial factors on the Human Development Index (HDI) using a spatial econometric model, specifically the SARAR model (Spatial Autoregressive with Autoregressive Errors), which incorporates both the spatial effect of the dependent variable and the spatial lag of errors. The data used comes from the report of the United Nations Development Program (UNDP), the National Institute of Statistics and Informatics (INEI) and the Ministry of Energy and Mines, covering a total of 1,872 districts of Peru in 2019. The results reveal that the HDI of a district is positively related to accumulated public investment, urban population agglomeration, and mining district status. On the contrary, the HDI is negatively affected by the altitude of the district capital and the geographical distance between the district capital and the nearest district. On average, mining districts have a higher HDI compared to non-mining districts. In addition, a positive relationship is observed between the HDI of a district and that of its geographically close neighbors (p<0.01), evidencing a spatial contagion effect. These findings underscore the importance of considering space as a key element for the design and implementation of public policies that promote equitable and sustainable human development.