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Corruption and Related Socioeconomic Factors: A Time Series Study

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  • Steven F. Brown
  • Joshua Shackman

Abstract

This study examines corruption in relation to political, legal, and economic factors to see how these factors impact corruption over time and to test the direction of causality between these variables. To assess causality, cointegration analysis using an error correction model on data from over 100 countries spanning over 20 years was performed. Three antecedent variables are analyzed in relation to corruption. Over the long‐term, increases in these variables result in decreases in corruption. However, there is no evidence that changes in corruption impact any of these same variables. Interestingly, increases in GDP per capita are found to increase corruption over the short‐term while leading to a long‐term reduction in corruption.

Suggested Citation

  • Steven F. Brown & Joshua Shackman, 2007. "Corruption and Related Socioeconomic Factors: A Time Series Study," Kyklos, Wiley Blackwell, vol. 60(3), pages 319-347, August.
    • Handle: RePEc:bla:kyklos:v:60:y:2007:i:3:p:319-347
    DOI: 10.1111/j.1467-6435.2007.00374.x
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    References listed on IDEAS

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    1. Mr. Carlos A Leite & Jens Weidmann, 1999. "Does Mother Nature Corrupt? Natural Resources, Corruption, and Economic Growth," IMF Working Papers 1999/085, International Monetary Fund.
    2. Mr. Vito Tanzi & Mr. Hamid R Davoodi, 1997. "Corruption, Public Investment, and Growth," IMF Working Papers 1997/139, International Monetary Fund.
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    Cited by:

    1. René Ruske, 2015. "Does Economics Make Politicians Corrupt? Empirical Evidence from the United States Congress," Kyklos, Wiley Blackwell, vol. 68(2), pages 240-254, May.
    2. Jens K. Perret, 2015. "Comments on the Impact of Knowledge on Economic Growth across the Regions of the Russian Federation," EIIW Discussion paper disbei207, Universitätsbibliothek Wuppertal, University Library.
    3. Gökhan R. Karahan & R. Morris Coats & William F. Shughart, 2009. "And the Beat Goes On: Further Evidence on Voting on the Form of County Governance in the Midst of Public Corruption," Kyklos, Wiley Blackwell, vol. 62(1), pages 65-84, February.
    4. Andrey V. Aistov & Elvina Mukhametova, 2015. "Determinants Of Corruption Perceptions: Transitional Vs. Developed Economies," HSE Working papers WP BRP 89/EC/2015, National Research University Higher School of Economics.
    5. Harbi, Sana El & Anderson, Alistair R., 2010. "Institutions and the shaping of different forms of entrepreneurship," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 39(3), pages 436-444, June.
    6. Gebka, Bartosz & Kanungo, Rama Prasad & Wildman, John, 2024. "The transition from COVID-19 infections to deaths: Do governance quality and corruption affect it?," Journal of Policy Modeling, Elsevier, vol. 46(2), pages 235-253.
    7. Guoyao Yan & Yu Hao & Yunxia Guo & Haitao Wu, 2022. "Are environmental problems a barometer of corruption in the eyes of residents? Evidence from China," Kyklos, Wiley Blackwell, vol. 75(2), pages 337-361, May.
    8. Jana Zausinová & Martin Zoričak & Marcel Vološin & Vladimír Gazda, 2020. "Aspects of complexity in citizen–bureaucrat corruption: an agent-based simulation model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 527-552, April.
    9. Török, Ádám, 2007. "A versenyképesség egyes jogi és szabályozási feltételei Magyarországon [Legal and regulatory conditions for competitiveness in Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1066-1084.

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