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Collusive versus coercive corporate corruption: evidence from demand-side shocks and supply-side disclosures

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A Correction to this article was published on 31 May 2022

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Abstract

We examine whether and how collusive and coercive forms of corporate corruption influence firm value. Our identification strategy exploits (i) the exogenous criminal prosecutions of regional government officials as part of China’s anti-corruption campaign as demand-side shocks and (ii) the unique reporting of entertainment and travel costs by Chinese firms as supply-side disclosure of corruption-related spending. Among firms for which corruption is likely to be perceived as collusive (coercive) by investors, we find that exposure to corruption-related political risk measured by abnormal entertainment and travel costs has a significantly negative (positive) relation with market reactions to the anti-corruption prosecutions. These findings are consistent with investors’ anticipation of a future decline in potential benefits (costs) arising from rent-sharing collusion (rent-extracting coercion). We also find that the collusion (coercion) effect is more pronounced for firms in regions with greater government economic intervention (in industries with stronger business competition). Furthermore, we provide evidence that the ex ante market reactions corroborate with the direction of changes in ex post operating performance of firms. Overall, our results suggest that investors can recognize differences in the economic consequences between collusive and coercive corruption and that the disclosure of corruption-related spending could help investors assess a firm’s exposure to corruption-related risk.

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Notes

  1. The form of corporate corruption that we examine in this study is the corrupt relationships between businesses (supply-side) and government officials (demand-side), rather than the corrupt relationships either within or between businesses (Castro et al. 2020).

  2. Although “corruption” can refer to a broader range of behavior than just bribery, we use the term to refer specifically to bribery.

  3. Although Lin et al. (2018) and Ke et al. (2018) both examine the market reaction to Chinese President Xi Jinping’s announcement on December 4, 2012, to launch the national-level anti-corruption campaign, the former study finds a positive effect and the latter finds no evidence of an effect. The analyses based on this single event date may not generate strong and reliable inferences for two reasons. First, the Chinese central government has a long history of announcing anti-corruption reforms, beginning well before 2012, and similar announcements in the past did not necessarily lead to prosecutions. As such, the market was unlikely to be surprised by the 2012 announcement, and it is with the benefit of hindsight that we now appreciate its policy significance. Second, on the same date that President Xi announced the anti-corruption campaign, the Chinese Security Regulatory Commission also made an important policy announcement regarding a set of stock market reforms (http://jingji.cntv.cn/2012/12/04/ARTI1354585707083333.shtml). Thus it would be difficult to determine whether it is the anti-corruption campaign or the stock exchange reforms driving the observed market reactions on the shared event date.

  4. There is media speculation that anti-corruption charges tend to target regional officials that have either fallen out of favor with or are opponents of the central government’s leaders (https://www.washingtonpost.com/world/asia_pacific/in-china-investigations-and-purges-become-the-new-normal/2018/10/21/077fa736-d39c-11e8-a275-81c671a50422_story.html). Accordingly, market reactions to actual prosecutions of regional officials could be affected not only by anticipation of a reduction in corruption demand but also by expectations of increased political costs. Nevertheless, the latter effect is expected to exert a stronger negative impact on the firm value of non-state-owned enterprises than that of state-owned enterprises, and this would thus introduce into our study a conservative bias against finding evidence supporting our hypotheses.

  5. The arguments that (i) the market is not informationally efficient, (ii) the estimation of firm-specific corruption-related political risk is very noisy, and (iii) the prosecuted officials may not be sufficiently influential to affect investor behavior all suggest our empirical analysis is biased against finding evidence in support of our predictions.

  6. In general, the framework of collusive versus coercive corruption stipulates that the former is motivated by rent-sharing opportunities with corrupt officials that help decrease overall business costs and the latter is motivated by rent-extraction pressure by officials that increases business costs (Alexeev and Song 2013; Sequeira and Djankov 2014; Sequeira 2016). Therefore the question of how a specific instance of corruption is classified as collusive or coercive depends largely on two factors: (i) the incentive that instigates the corruption and (ii) how it affects the briber’s overall business costs. For example, in the context of bribery when bidding for government contracts or to hurt competitors, collusion would arise when an unqualified bidder or underperforming firm bribes corrupt officials to win the contract or prevent the leading bidder from winning, even without the briber’s substantial further investment to qualify for the bid or outperform the competitors. In such contexts, coercion would occur when the leading bidder must still offer bribery to corrupt officials to be awarded the contract or to prevent a less qualified and underperforming competitor from winning. It may therefore be difficult to apply the framework of collusive and coercive corruption in cases where it is difficult to identify the underlying incentives and influence on overall business costs. For instance, even without explicit and immediate rent-sharing opportunities or rent-extraction pressures, firms may sometimes still bribe to manage their political costs and policy uncertainty, either on a proactive basis to appease newly appointed officials or on a reactive basis to keep up with similar practices by peers.

  7. Early initiatives include the 1978 establishment of the Central Commission for Discipline Inspection in the Communist Party, the 1989 declaration by the Supreme People’s Court to penalize corrupt officials, and the 1995 establishment of the anti-corruption bureau in the Supreme People’s Procuratorate.

  8. An example of rent-sharing collusion between SOEs and a corrupt official is the case of Zhubing Chen, who was a former director of the Ministry of Finance. On March 21, 2013, he was sentenced to life imprisonment for receiving bribes totaling RMB 24.54 million from various sources. In one case, Chen received RMB 2.2 million in bribes from Gezhouba Group, which is a listed SOE owned by the central government with annual net profit for 2012 of over RMB 1 billion. In return Chen exercised his authority to exempt this firm from over RMB 5 million of interest payments on government loans. In another case, Chen was paid RMB 1.3 million in bribes from Beijing Sanyuan Food Co. Ltd., which is a listed SOE owned by regional government with annual net profit for 2012 of RMB 32.8 million. In exchange Chen used his authority to exempt this firm from payments of over RMB 11.84 million. In these cases, the SOEs received substantial reductions in business costs, and the corrupt official received significant personal gain, all at the expense of government income, which incurred lost interest payments on business loans (http://jjckb.xinhuanet.com/invest/2013-08/09/content_460708.htm).

  9. An example of rent-extraction coercion of a non-SOE by a corrupt official is the case of Chint Electric Co. Ltd., a listed company with annual profit for 2014 of over RMB 1 billion. In seeking assistance from local government in Quzhou city, Zhejiang province, to acquire suitable land for solar energy investment projects in 2014, the firm was asked to pay bribes worth over RMB 10 million by Liantu Liu, a former director of the Quzhou Forestry Bureau, to help facilitate the land search process. In this case, the corrupt official acquired significant personal gains, and, although government income was not affected, the firm incurred substantial incremental business costs for soliciting service from a local government authority that is intended to assist business development and promote green energy. In 2019, this official was sentenced to 11 years’ imprisonment (https://www.jiemian.com/article/4636846.html).

  10. The assumption that SOEs (non-SOEs) with higher levels of abnormal entertainment and travel costs are more likely to engage in collusive (coercive) corporate corruption is made on a general basis, and the effect is assumed to dominate, on average, even if the alternative coercion (collusion) may also exist among some firms. The existence of the alternative effect is likely to bias against finding evidence in support of our main prediction.

  11. Abnormal returns are calculated based on market model-adjusted returns, for which we require at least 254 daily return observations during days −294 to −41 to estimate the firm-specific beta value. The market portfolio is based on all A-share category listed stocks on the Shanghai and Shenzhen stock exchanges in China.

  12. See http://news.sina.com.cn/c/nd/2015-11-11/doc-ifxkniup6319586.shtml and http://politics.people.com.cn/ywkx/n/2014/1222/c363762-26255448-2.html

  13. We winsorize all continuous variables at the 1% level in both tails to mitigate the effects of outliers.

  14. In robustness tests (untabulated for brevity), we further strengthen the inference of our baseline findings in the following ways. First, we show the effects are statistically significant, even when we implement the analysis using only the treatment group, thus ensuring the results are not driven by an unidentified effect associated with the control group. Second, we show that the effects are robust to using an alternative measure of abnormal stock returns based on the market model. Third, the effects are no longer observable when we apply placebo event dates counterfactually assigned as five months before the actual event dates.

  15. We interpret the positive relation between abnormal ETC and market reactions to the anti-corruption prosecutions as evidence among non-SOEs that investors respond favorably to news of a reduction in the future likelihood of coercive corporate corruption through rent extraction by corrupt officials. An alternative explanation for this positive relation is that the anti-corruption prosecutions signal a leveling of the playing field for non-SOEs, relative to the SOEs. However, in additional tests (not tabulated for brevity), we observe that the positive relation among non-SOEs is statistically insignificant more pronounced among firms with SOE-based competitors in the same sector and province. Therefore, although the alternative explanation is intuitively plausible, we do not acquire supporting evidence in our research setting. We suggest that this could be considered as an avenue for future research.

  16. Our research design generally assumes that SOEs (non-SOEs) are suspected of collusive (coercive) corporate corruption due to their innate ties to the Chinese government, and the main inferences based on our hypothesis tests are consistent with this conjecture. Despite this, some SOEs (non-SOEs) with relatively weaker (stronger) firm-specific political connections might also engage in the alternative form of corruption under coercion by (in collusion with) corrupt officials. However, there are reasons why the alternative form of corruption may not be highly observable, even in our additional test identifying variations in firm political connections, reported in Table 9. First, among SOEs, investors might not necessarily perceive coercive corruption to be a disadvantage because government ties may ensure that any incremental business costs incurred due to coercion could be indirectly compensated by other forms of financial support, such as state subsidies. As such, even among SOEs with weaker political connections that experience coercion, share price responses to anti-corruption prosecutions may not necessarily be as favorable as among non-SOEs. Second, among non-SOEs, investors might perceive that opportunities for collusive corruption only generate transitory benefits, because political connections established through executives’ personal links may diminish when they leave the firm or when their contacts in government change jobs or become disfavored. Thus, even among non-SOEs with stronger political connections that may collude, share price responses to prosecutions of corrupt officials may not be as unfavorable as among SOEs. Therefore, although the alternative form of corruption is plausible, we do not acquire strong supporting evidence in our research setting, and, to strengthen the findings of our study, we suggest that this be considered as an avenue for future research.

  17. We report findings based on analysis with balanced firm-year observations both before and after the prosecutions to maximize comparability. According to our results (untabulated for brevity), the post-prosecution period reductions in average level and volatility of AETC are also observed when the analysis is carried on unbalanced firm-year observations or only among firms in the treatment group.

  18. Although our study draws on anti-corruption prosecution events as exogenous demand-side shocks to corporate corruption, our evidence focuses primarily on the supply-side impact, based on the firm perspective. One limitation of our study is that it cannot provide evidence from the perspective of government officials, particularly in terms of their preference and concerns regarding the two forms of corporate corruption. This is due to our lack of access to empirically observable data from the side of government officials that could capture their opinions and behavior. Another limitation of our study is that we do not provide in depth analysis of the specific anti-corruption allegations associated with our prosecution events, especially in terms of their relevance to the two forms of corporate corruption and their impact on the corruption demand. This is because detailed information from specific investigations is not publicly available, largely to protect personal privacy and corporate reputations. We encourage future research to address these interesting and important issues in the broader context of corporate corruption.

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Acknowledgments

We thank Russell Lundhohm (editor) and the anonymous referee for helpful suggestions and comments. Jeong-Bon Kim acknowledges partial financial support from the GRF grant of the HK SAR government (No. 9042767). Junsheng Zhang thanks financial support from the National Natural Science Foundation of China (No.71790603, No.71672205 and No.72132010) and Xiaojian Tang thanks financial support from the Humanities and Social Sciences Fund of the Ministry of Education of China (No.20YJC790125).

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Authors and Affiliations

  1. Department of Accountancy, City University of Hong Kong, Hong Kong, China

    Jeong-Bon Kim

  2. Alliance Manchester Business School, University of Manchester, Manchester, UK

    Edward Lee

  3. College of Finance, Nanjing Agricultural University, Nanjing, China

    Xiaojian Tang

  4. School of Business, Sun Yat-Sen University, Guangzhou, China

    Junsheng Zhang

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  1. Jeong-Bon Kim
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  2. Edward Lee
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  3. Xiaojian Tang
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  4. Junsheng Zhang
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Correspondence to Junsheng Zhang.

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Kim, JB., Lee, E., Tang, X. et al. Collusive versus coercive corporate corruption: evidence from demand-side shocks and supply-side disclosures. Rev Account Stud 28, 1929–1970 (2023). https://doi.org/10.1007/s11142-022-09678-0

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