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2010•Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)Requires access

The Causal Relationship between Corruption and Poverty: A Panel Data Analysis

Vahideh Negin, Zakariah Abd Rashid, Hesam Nikopour

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Abstract

Most of the studies which have investigated the link between corruption and poverty may draw conclusions on causality in the form of models that only show correlation. This study is set out to investigate the Granger causal relationship between corruption and poverty. It uses dynamic panel system GMM estimators, focuses on capability poverty using human poverty index (HPI) and is based on a sample of 97 developing countries during 1997-2006. The empirical findings reveal that corruption and poverty go together, with bidirectional causality.

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What this paper is about

Most of the studies which have investigated the link between corruption and poverty may draw conclusions on causality in the form of models that only show correlation. This study is set out to investigate the Granger causal relationship between corruption and poverty. It uses dynamic panel system GMM estimators, focuses on capability poverty using human poverty index (HPI) and is based on a sample of 97 developing countries during 1997-2006. The empirical findings reveal that corruption and poverty go together, with bidirectional causality.

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Available abstract

Most of the studies which have investigated the link between corruption and poverty may draw conclusions on causality in the form of models that only show correlation. This study is set out to investigate the Granger causal relationship between corruption and poverty. It uses dynamic panel system GMM estimators, focuses on capability poverty using human poverty index (HPI) and is based on a sample of 97 developing countries during 1997-2006. The empirical findings reveal that corruption and poverty go together, with bidirectional causality.

Key concepts: Poverty, Panel data, Causality (physics), Language change, Econometrics, Estimator, Economics, Index (typography)

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