Linear and Non-linear Relationships Between Growth, Inequality, and Poverty in a Panel of Latin America and the Caribbean Countries: A New Evidence of Pro-poor Growth

The relationships between growth, inequality, and poverty is widely discussed area in the development economics, which fairly overcrowded by linear and non-linear growth components, however, while developing an index for pro-poor growth, the non-linearity portion of growth has been widely ignored that address in this study by using a panel of 18 selected Latin America and the Caribbean countries from 1981 to 2012. The study proposed a new measure of pro-poor growth index, called ‘Poverty Interdependence Growth Index (PIGI)’, which further extended in order to satisfy the monotonicity criterion of pro-poor growth and poverty reduction, called ‘Poverty Interdependence Equivalent Growth Rate (PIEGR)’. The results show that the impact of per capita survey income and income inequality on poverty measures are ‘linear’ in nature when controlling the non-linear components of growth, however, if this assumption is relaxed, the study doesn’t established either ‘U-shaped’ and/or ‘asymptotic’ relationship between the variables. The non-poverty measures including educational expenditures, health expenditures and population growth significantly increases F–G–T measures of poverty. The estimates of PIGI and PIEGR reveal that out of 18 countries, there are 4 countries shows highly pro-poor growth, 11 countries shows negative pro-poor growth index (i.e., immiserizing growth scenarios, where a positive growth increases poverty), and the remaining 3 countries shows pro-rich. The study illustrates that our new measure of pro-poor growth index fairly provides conclusive findings.