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Financial Development, Domestic Savings and Poverty Reduction in Pakistan: Using Cointegration and Granger Causality Analysis

Author

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  • Muhammad Shahbaz

    (Department of Management Sciences, COMSATS Institute of Information Technology,Lahore, Pakistan)

  • Talat Afza

    (Department of Management Sciences, COMSATS Institute of Information Technology,Lahore, Pakistan)

  • Muhammad Shahbaz Shabbir

    (University of Illinois at Urbana Champaign, Champaign, USA)

Abstract

The aim of the paper is to explore the association between financial development, domestic savings and poverty in case of Pakistan. The study has employed annual time series data over the period of 1971-2005. The ARDL bounds testing approach has been used for cointegration and Vector Error Correction Model (VECM) for the direction of causality for long-and-short runs. Unit root problem is handled by the use of Ng-Perron unit root test. Our results inidacte that feedback effect is found between finnacial development and poverty reduction in the long run but strong cuasality is running from fall in poverty to financial development in the short run. This paper opens up new directions for policy makers to reduce poverty with the help of viberant finacial sector in the country.

Suggested Citation

  • Muhammad Shahbaz & Talat Afza & Muhammad Shahbaz Shabbir, 2013. "Financial Development, Domestic Savings and Poverty Reduction in Pakistan: Using Cointegration and Granger Causality Analysis," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 1(5), pages 59-73, May.
    • Handle: RePEc:ijr:journl:v:1:y:2013:i:5:p:59-73
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    More about this item

    Keywords

    Financial Development; Poverty; Pakistan;
    All these keywords.

    JEL classification:

    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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