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Too Cynical: why the Stock Market in China Dismissed Initial Anticorruption Signals

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Abstract

Political leaders in China regularly launch anti-corruption campaigns to win public support. But how are anti-corruption signals perceived? We use event study to examine the case of Xi Jinping’s anti-corruption campaign – an unprecedented effort in China to fight corruption. Contrary to expectations, we find that for the firms with connected officials later investigated, the initial anti-corruption signals – speeches from the top leadership and earlier crackdowns on other senior officials – did not decrease their stock prices. We argue that the perceived high costs of following through and repeated campaigns in the past paradoxically nurtured cynicism. We exploit the case of Zhou Yongkang and Ling Jihua – the two officials who were alleged to be involved in the power struggle and whose downfall had circulated widely since 2012. We find that when the targets of earlier crackdowns were connected to Zhou or Ling, the stock prices of the firms went down only if their connected and later investigated officials were in the same faction; the stock prices of the other firms, however, went up. We interpret the results as investors’ misperceptions of the campaign in the beginning. Our findings suggest that even real efforts in campaign-style enforcement can be dismissed.

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Notes

  1. On 13 December 2018, for the first time, the party declared a sweeping victory over corruption, which has been six years since Xi launched the campaign. See “China’s Xi declares an ‘overwhelming victory’ over graft: state media”, Reuters, 15 December 2018. During 2013 to 2018, the number of investigations on both senior officials and the rank and file soared relative to the numbers in previous years.

  2. For example, see “Special report: The power struggle behind China’s corruption crackdown”, Reuters, 23 May 2014; “China’s Xi Jinping denies House of Cards power struggle but attacks ‘conspirators’”, Guardian, 4 May 2016; “Xi move on faction suggests China elite struggle: experts”, Daily Mail, 29 April 2016.

  3. Stock market is a good fit to test the anticipation effects because how the campaign would evolve in the future is what matters most for investors.

  4. Wang [51] has noted, almost 90% of listed firms are politically connected, leaving very few variations to compare listed firms with or without political connections.

  5. The CCP has launched at least seven waves of anti-corruption campaigns in the reform era. Manion [33] has documented the anti-corruption campaigns in 1982, 1986, 1989, 1993, and 1995. In 2006, the CCP launched an anti-corruption investigation against the then Shanghai Party Secretary Chen Liangyu. In December 2012, Xi Jinping launched the most recent anti-corruption campaign.

  6. An exception is Mei and Pearson [36], they find that the deterrent threats from the hold-to-account campaign were dismissed by local officials.

  7. See Paternoster [40] and Williams and Hawkins [56] for reviews.

  8. The announcement of “under investigation” was the earliest date when these cases went public before formal trials.

  9. For example, before 17 May 2013, only two senior officials with sub-provincial (ministerial) ranks or above were investigated.

  10. See “Retail traders’ hold on China’s stock market slips as institutions rise”, Financial Times, 25 February 2021.

  11. See “Uncover the model of Sino Life”, Caixin Weekly, 29 April 2016, https://weekly.caixin.com/2016-04-29/100938109.html (in Chinese).

  12. The list of officials was obtained from the official website of the Central Commission for Discipline Inspection

    http://www.ccdi.gov.cn/. We also validated the list from Wikipedia and Baidu Baike.

  13. The media often published in-depth reports following the investigations of senior officials. Most of these reports covered the officials’ connections with firms. We also explicitly searched the names of the officials with the key- words such as “firm”, “listed firm”, “business”, and “state-business relationship”. The political connections included bribing, political-business allies, relatives, or managers of state-owned firms.

  14. For more information on the CSMAR database, see http://us.gtadata.com/.

  15. They are calculated as\(\frac{P_t-{P}_{t-1}}{P_{t-1}}\times 100\), where Pt is the closing price at date t.

  16. For the firms listed in the Shanghai and Shenzhen stock market, we used the Shanghai and Shenzhen A-shares index, respectively.

  17. In the regression model, we interact the firm-specific dummies with beta to get the firm-specific βi.

  18. If k equals 1, the coefficients are daily abnormal returns.

  19. 12 firms whose connected officials were investigated in 2013 are dropped at some points.

  20. We use a relatively short event window because we expect the stock market to react to anti-corruption signals immediately.

  21. The k-day cumulative abnormal returns are calculated by summing the k-day daily abnormal returns in Table A.6. We calculate the standard errors using the variance covariance matrix of the estimated daily abnormal returns.

  22. For the case of Bo Xilai, see an article by Yuhua Wang, “Bo Xilai and the dilemma of China’s anti-corruption campaign”, CNN, 25 September 2013. For the case of Chen Liangyu, see Joseph Kahn, “Shanghai’s Party Leader, Mistrusted by Hu, Is Purged”, The New York Times, 26 September 2006. For the case of Chen Xitong, see Patrick E. Tyler, “Beijing Party ‘Decapitated’ By President”, The New York Times, 8 May 1995.

  23. Zhou Yongkang operated a “petroleum” faction, Ling Jihua formed a secret faction called “Xishan Society”, which consists of prominent politicians and businessmen from Shanxi Province. Zhou Yongkang and Ling Jihua were announced to be under investigation on 29 July 2014 and 22 December 2014, respectively.

  24. “Chinese Security Official is Focus of Corruption Inquiry”, New York Times, 21 December 2013.

  25. “Senior Chinese Official Falls Under Scrutiny as Some Point to Larger Inquiry”, New York Times, 1 September 2013.

  26. See Tables 3 and 4 in the Appendix for details.

  27. Figures 5 and 6 in the Appendix report the results for each individual announcement of the earlier investigations.

  28. Relationships with market returns are estimated using an estimation window from 1 November 2011 to 1 November 2012. We did the same for the synthetic control analysis.

  29. We use 1 November 2011 to 1 November 2012 as the estimation window. We follow the original synthetic control method [1] to estimate the weights.

  30. The direction of the effects is unclear. If the uncertainty diffuses within the industry, the stock prices of the control firms in the same industry will drop. If investors perceive that the firms that are likely to survive in the anti-corruption campaign can benefit from the hit on their competitors, the stock prices of the control firms will increase.

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Authors and Affiliations

  1. Department of Government and Politics, University of Maryland – College Park, 3140 Tydings Hall, College Park, MD, 20742, USA

    Xiaonan Wang

  2. Department of Methodology, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, UK

    Yan Wang

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Appendix

Appendix

Anti-Corruption Events

Table 2 Anti-corruption Speeches from the Top Leadership
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Table 3 Crackdowns on Senior Officials between May 2013 and December 2013
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Event Firms and Their Connected Officials

Table 4 Information of Event Firms
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Descriptive Statistics

Table 5 Descriptive Statistics of Daily Stock Returns
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Results of Event Study

Table 6 Daily Abnormal Returns Around Anti-corruption Signals
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Table 7 Average Cumulative Abnormal Returns Around Anti-corruption Signals
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Table 8 Daily Abnormal Returns Around Anti-corruption Signals by Connection to Zhou Yongkang and Ling Jihua
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Table 9 Average Cumulative Abnormal Returns Around Anti-corruption Signals by Connection to Zhou Yongkang and Ling Jihua
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Fig. 5
figure 5

Daily Abnormal Returns around Each Earlier Crackdown Related with Zhou/Ling

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Fig. 6
figure 6

Three-day Average Cumulative Abnormal Returns for Each Earlier Crackdown

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Robustness Check: Sign Test

Table 10 Sign Test Results for Daily Abnormal Returns around Anti-corruption Signals
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Robustness Check: Synthetic Control

Table 11 Number of Estimation Period and Control Firms for Each Event Firm
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Fig. 7
figure 7

Abnormal Returns and Synthetic Abnormal Returns in the Estimation Period

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Fig. 8
figure 8

Actual and Synthetic Daily Abnormal Returns around Anti-Corruption Speeches

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Fig. 9
figure 9

Actual and Synthetic Daily Abnormal Returns around Earlier Crackdowns on Other Officials

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Robustness Check: Excluding Connections Formed Through Bribery

Table 12 Daily Abnormal Returns Around Anti-Corruption Signals Excluding Bribing Connections
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Table 13 Average Cumulative Abnormal Returns around Anti-Corruption Signals Excluding Bribing Connections
Full size table

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Wang, X., Wang, Y. Too Cynical: why the Stock Market in China Dismissed Initial Anticorruption Signals. J OF CHIN POLIT SCI 27, 681–717 (2022). https://doi.org/10.1007/s11366-021-09778-9

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