A Time Series Analysis of Forieng Aid and Income Inequality in Pakistan
Keywords:
foreign aid, growth rate, foreign direct investment, labor force, stationarity, cointegration, causality
Abstract
Pakistan economy is one those economies that has received a huge amount of foreign aid. Foreign aid has been considered to help capital-deficient economies to fulfill the desired levels of finances to generate growth, increase employment and income, and furthermore, it helps to alleviate poverty levels in the recipient economies. Present study focuses on the analysis of impact of foreign aid on income inequality in Pakistan. Since time series data is used for the analysis so the ADF and Phillip-Perron unit root test are applied to find out each of the time series to be stationary at its first difference. Johansen contegration test and vector error correction models are employed to examine the long run and short run impacts of growth, foreign aid, foreign direct investment, and labor force participation rate on income inequality, respectively. The cointegration test results confirm negative impact of economic growth on income inequality whereas foreign aid, foreign direct investment and labor force participation rate are concluded to have inequality increasing impacts. The results are statistically significant. Vector error correction model results showed long run causality as the coefficient of error correction term has the negative and significant coefficient. The Engle-Granger causality test showed bidirectional causality between aid and growth. The study also draws some conclusions and policy recommendations.
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Published
2013-05-15
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Copyright (c) 2013 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.