An Application of VECM to Investigate the Role of Socio-Economic Factors in Poverty: New Evidence from Pakistan

Abstract

Poverty is a crucial and worldwide phenomenon. The main purpose of the study is to investigate the relationship exists between socio-economic factors, social factors, and poverty, the relative influence of economic and social factors on poverty and to describe causality between time series in the VAR system. This study utilized the Vector Error Correction Model (VECM) by using quarterly time-series data, 1994Q1 to 2018Q4, that have been collected from the world development indicators (WDI) and Economic Survey of Pakistan. The study identified education, unemployment, inflation as economic factors while zakat and rainfall as social factors that can reduce poverty. The findings of this study indicate that inflation and unemployment have a positive and significant relationship with poverty in the long run in Pakistan while education, rainfall, social welfare programs, and zakat has a negative relationship in the long run with poverty. Besides, the study also found that in the short run, there is no relationship between economic and social factors with poverty. Moreover, the study found that in the long run that the relative contribution of education and rain increases, 28% and 20%, is greater than the contribution of inflation, social welfare programs, unemployment and zakat, 3.8%, 0.5%, 2.5%, and 0.08%. Similarly, its contribution to poverty reduces up to 44% in the long run. This study helps policymakers to take important decisions about economic and social factors while designing policies to reduce poverty. The results suggest that the state bank of Pakistan should adopt a contractionary monetary policy to control inflation and policymakers can develop policies like education for all. The government should develop a business environment to create more employment opportunities.

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