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Women and corruption: evidence from multinational panel data

Author

Listed:
  • Yu Hao

    (Beijing Institute of Technology)

  • Chun-Ping Chang

    (Shih Chien University at Kaohsiung
    Xi’an Jiaotong University)

  • Zao Sun

    (Xi’an Jiaotong University)

Abstract

In this paper we investigate whether the ratio of female population is related with lower corruption, utilizing a multinational panel data with 80 countries for the period 2000–2012 and employing the Generalized Method of Moments as well as the ordered probit regression methods. This is the first study on the impacts of different female groups on corruption. Overall speaking, the estimation results are pluralistic. Higher female ratios in the legislative branch and in the labor force are significantly associated with a lower level of corruption, while the female ratio in secondary enrollment is positively related with corruption; however, the female ratio of the whole population has insignificant impacts on corruption. The policy implications are that a simple enhanced female ratio and educational level are not the effective way to inhibit corruption in our sample countries, whereas improvements of the female ratio in the legislative branch and the labor force contribute to controlling corruption. These results are basically robust for the two estimation methods and for the two subsamples of developed and developing countries. As a result, the estimation results on the relationship between corruption and gender might vary remarkably when different indicators for the female groups are utilized, which should some light on future studies.

Suggested Citation

  • Yu Hao & Chun-Ping Chang & Zao Sun, 2018. "Women and corruption: evidence from multinational panel data," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1447-1468, July.
  • Handle: RePEc:spr:qualqt:v:52:y:2018:i:4:d:10.1007_s11135-017-0530-7
    DOI: 10.1007/s11135-017-0530-7
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    More about this item

    Keywords

    Female ratio; Corruption; Multinational panel data; Generalized method of moments (GMM); Ordered probit regression;
    All these keywords.

    JEL classification:

    • H1 - Public Economics - - Structure and Scope of Government
    • K4 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior
    • H3 - Public Economics - - Fiscal Policies and Behavior of Economic Agents

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