Understanding the Interplay of Poverty, Inflation, and Unemployment: An Empirical Analysis

Abstract

The primary objective of this study is to explore the presence of long-term relationships among poverty, inflation, and unemployment. To achieve this goal, the study utilizes the Autoregressive Distributed Lag (ARDL) approach for empirical analysis. By employing data spanning from 1975 to 2016 sourced from the World Development Indicators (WDI), the study aims to identify and analyze long-term relationships among these key economic indicators. Through the ARDL approach, the study seeks to uncover any enduring connections between poverty, inflation, and unemployment over the specified time period. This methodological framework allows for a comprehensive investigation into the dynamics and interdependencies of these variables, thereby contributing to a deeper understanding of their relationship and implications for economic policy and management. In this study, the reverse of the Human Development Index (HDI) serves as a proxy for measuring multidimensional poverty. This index is constructed in a manner similar to the HDI developed by the United Nations Development Programme (UNDP). It incorporates four key indicators: life expectancy, infant mortality, per capita income, and mean years of schooling. By utilizing the reverse of the HDI, which essentially reflects the opposite end of human development, the study aims to capture and assess the multidimensional aspects of poverty. This approach allows for a comprehensive evaluation of poverty that goes beyond traditional income-based measures, considering factors such as health, education, and standard of living. By leveraging the HDI framework and its associated indicators, the study provides a nuanced understanding of poverty that accounts for various dimensions of human well-being. The study considers several independent variables, including unemployment, inflation, dependency ratio, population growth, government expenditures on education, trade openness, and remittances. Through empirical analysis, the study validates the use of the Autoregressive Distributed Lag (ARDL) approach and confirms the existence of a long-run relationship between poverty, inflation, and unemployment. This finding underscores the interconnectedness of these variables and their impact on poverty dynamics over time. By examining a range of economic and demographic factors, including government spending, trade openness, and remittances, the study provides a comprehensive understanding of the determinants of poverty. The study's findings indicate that unemployment and inflation are associated with an increase in poverty levels. Moreover, the analysis reveals that factors such as dependency ratio, remittances, and population growth also exert significant impacts on poverty over the long term. Importantly, these results are not only applicable in the long run but also hold true in the short run. These findings underscore the complex interplay between various economic and demographic factors in shaping poverty dynamics. Addressing unemployment and inflation appears crucial for poverty alleviation efforts, while policymakers should also consider the effects of dependency ratio, remittances, and population growth on poverty outcomes. Furthermore, the persistence of these relationships in both the short and long term highlights the importance of adopting holistic and sustained approaches to poverty reduction. By addressing multiple factors simultaneously, policymakers can effectively combat poverty and promote sustainable development.