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Measurements, determinants, causes, and consequences of corruption: lessons from China’s anti-corruption campaign

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Abstract

Corruption is a widespread phenomenon in many developing and transitional economies. China is a country in profile both in the prevalence of corruption and in its attempts to root out corruption. The recent anti-corruption campaign in China, which started in December of 2012 when President Xi Jinping took power, is unprecedented in its magnitude and time length. It has had lasting impact on the functioning of the Chinese bureaucracy and on the behavior of firms and consumers. It also provides unusual amount of data to study the causes and consequences of corruption, which will have implications for other countries and economies. In this review, I discuss the definition and measurement of corruption with a particular focus on the measurements that highlight the city-level heterogeneity of corruption in China and present simple frameworks to understand the determinants of corruption by government officials and the causes and consequences of corruption and anti-corruption. I summarize the key findings regarding how the anti-corruption campaign affects the behavior of a host of decisions makers in the economy, including firms and bureaucrats, and on the resource allocation in general, and argue that the lessons from China’s anti-corruption campaign are useful to other developing countries.

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Notes

  1. See Olken and Pande (2011) for a detailed review.

  2. Other studies using the cross-checking approach include Tella and Schargrodsky (2003) who quantify corruption in hospital procurements, and Olken (2006) and Antonossava et al. (2008) who both estimate corruption in food distribution programs in developing countries.

  3. Similar event studies using market inference include Faccio (2006) and Khurana et al. (2012).

  4. See Sect. 4.1 for a detailed description of Xi’s anti-corruption campaign.

  5. See the corruption perception index compiled by Transparency International.

  6. See World Bank (2020) for a detailed manual to fight corruption in the public sector.

  7. See Stephenson (2015) for a comprehensive review of the literature on the relationship between democracy and corruption.

  8. Several other countries have also launched in recent anti-corruption campaigns, including Brazil, South Korea, India, Nigeria, Vietnam, among others.

  9. We can easily allow \(Q(\cdot )\) to depend on the bribe and anti-corruption campaign intensity.

  10. Alternatively, we can assume that the bureaucrats choose only the regulatory regime \(r\in \left\{ H,L\right\}\) and each firm chooses \(b_{i}\) and \(p_{i}\) given the regulatory regime chosen by the bureaucrats. In such a case, the only way anti-corruption campaigns will affect the level of bribes, and firm performance is that the bureaucrats choose a different regulatory regime. For simplicity, we have assumed only two regulatory regimes, H and L;  but we assume that there is a continuum of regulatory regimes indexed by \(\kappa ,\); then, similar qualitative conclusions can be obtained in this alternative model as well.

  11. Cong et al. (2019) document that the credit stimulus of 2009–2010 favored state-owned firms and firms with lower returns to capital.

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Acknowledgements

This review is prepared for a special issue of International Tax and Public Finance, and is based on a keynote talk I gave in the International Institute Public Finance (IIPF) Annual Congress at Linz, Austria (August 2022). I would like to thank the Congress Scientific Committee chairs Anne Brockmeyer and Juan Carlos Suarez Serrato for giving me the opportunity to synthesize my understanding of the important topic of corruption and anti-corruption in emerging economies. I am grateful to Hongbin Cai and Lixin Colin Xu with whom I collaborated on my first paper on the measurement of local corruption in China (Cai et al., 2011). My research on the topic benefits from the insights from my coauthors, Panle Jia Barwick, Hongbin Cai, Haoyuan Ding, Quanlin Gu, Shi Kang, Shangjun Li, Shu Lin, Ming Li, Zhe Li, Wei Xiong, Nianhang Xu, Hongjun Yan, Lixin Colin Xu, and Li-An Zhou. Any errors are my own.

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    Hanming Fang

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Fang, H. Measurements, determinants, causes, and consequences of corruption: lessons from China’s anti-corruption campaign. Int Tax Public Finance 31, 3–25 (2024). https://doi.org/10.1007/s10797-023-09803-y

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