“Determinantes de la desigualdad por ingresos: estudio a nivel cantonal en Ecuador usando modelos espaciales durante el periodo 2010 - 2019” - Quito Pizarro, Byron Alejandro (2021)
Inequality is a problem that remains latent throughout generations, despite the growth of countries and the mechanisms they have implemented to mitigate it. In the world about the richest 10% of the world's population earns up to 40% of total income, in Latin America between 2002 and 2014 it fell 1.0% per year, between 2014 and 2018 the fall was 0.6% per year, slowing in recent years; while, in Ecuador as of December 2020, the Gini coefficient at the national level is 0.500, in the urban area it is 0.485 and in the rural area it is 0.474. Despite the large number of investigations, the study of inequality has not been appreciated from other perspectives such as the spatial one, for this reason, this study estimates the determinants of income inequality at the cantonal level, through the use of spatial models during the period 2010 - 2019 at the cantonal level for Ecuador. The study panel collects information from official sources such as the Institute of Statistics and Census (INEC), the Central Bank (BCE) and the Superintendency of Banks (SPI). Where the dependent variable is the Gini coefficient and the independent variables are both the per capita production and the specialization indexes of each sector. In addition, the use of control variables. Subsequently, using descriptive analysis, panel data models and spatial models are used in order to estimate the determinants of income inequality. The approach indicates that the current level of per capita growth of production allows decreasing the levels of inequality, likewise, each of the sectors that constitute the economy, would generate different effects on inequality. These results were found to be significant in the panel and spatial estimations, in addition to the other aggregate determinants in the study. Finally, decision makers should direct resources towards improving the specialization of the primary and manufacturing sectors of the cantons with less human capital and financial inclusion, as these are capable of generating a reduction in inequality.