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The Effectiveness of Public Enforcement: Evidence from the Resolution of Tunneling in China

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Abstract

This paper examines the effectiveness of public enforcement by studying the effects of regulatory intervention to curb tunneling through intercorporate loans in China. Specifically, we explore whether public enforcement efforts in 2006 (blacklisting and sanctions) resulted in less tunneling, and ultimately in increased performance for tunneling firms. We show that tunneling is among the dominant factors increasing the likelihood of becoming blacklisted. We also find that firms’ tunneling mechanisms decreased significantly after the regulatory shock, and that their performance increased significantly compared to non-tunneling firms after the regulatory shock. Finally, we find a positive market reaction to the public announcement of tunneling both for firms that have been blacklisted and other tunneling firms that are not blacklisted. Collectively, these results suggest that public enforcement in the presence of a credible threat succeeds in deterring the effect on tunneling behavior in China.

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Notes

  1. We do not focus here on studies that model the private benefits of control/expropriation of minority shareholders by controlling shareholders (for the theoretical grounds behind this line of reasoning, see Grossman and Hart (1988); for further developments, see, e.g., Shleifer and Wolfenzon 2002). We also do not address the empirical estimates of the value of these private benefits (Zingales 1994, Nenova 2003, Atanasov 2005), which includes, but is not limited to, the benefits of tunneling.

  2. Focusing on loans in a different context, La Porta et al. (2003) examine the effects of related lending for Mexican banks and find that related lending takes place on better terms than arm’s-length lending, is 33 % more likely to default and, when they do, have lower recovery rates (30 cents/dollar less) than unrelated ones.

  3. The results do not change if we include 2006 in the pre-regulation period.

  4. Our results are not sensitive to using the average ORECTA decile in the pre-regulation period instead of an above-median dummy.

  5. See the appendix for variable definitions.

  6. We present regression estimates for Eqs. (2) and (3) using robust standard errors clustered by firm as well as by firm and year. All of our inferences remain unchanged when we cluster by firm and year and include year fixed effects.

  7. Our results are not sensitive to using other performance metrics such as, ROA, defined as “Net Income”/“Total Assets,” or ROS, defined as “Net Income”/“Sales.”.

  8. Our inferences remain unchanged when we use a dummy variable equal to 1 if a blacklisted firm has above median ORECTA compared to other blacklisted firms one year prior to the blacklisting.

  9. Untabulated results for wider windows reveal an increased market reaction, suggesting there is some information leak as well as a lower level of investor sophistication in the Chinese market (Jiang et al. 2010). Moreover, non-blacklisted tunneling firm returns are significantly larger than non-tunneling firm returns.

  10. Our inferences remain unchanged when we re-estimate this analysis using ORECTA. That is, for firms not included in the blacklist, the market reaction is a function of ORECTA.

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Acknowledgments

We are grateful for comments from two anonymous referees, the guest editors, Douglas Cumming, Wenxuan Hou, Edward Lee, the discussant, Hua Zhang, conference participants at the Journal of Business Ethics Special Issue Conference in Beijing, seminar participants at the Hong Kong Polytechnic University and Matthias Breuer, Agnes Cheng, Martin Conyon, Xiaomin Lin and Oliver M. Rui.

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Authors and Affiliations

  1. Lancaster University Management School, Lancaster University, Lancaster, LA1 4YX, UK

    Lars Helge Haß

  2. Schulich School of Business, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada

    Sofia Johan

  3. WHU – Otto Beisheim School of Management, Burgplatz 2, 56179, Vallendar, Germany

    Maximilian André Müller

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Correspondence to Lars Helge Haß.

Appendix: Variable Definitions

Appendix: Variable Definitions

BLACK

Equal to 1 if a firm has been blacklisted by the SSE/SZSE, and 0 otherwise

TUNNEL

Equal to 1 if a firm has above median yearly ORECTA in the pre-period, i.e. when POST is equal to 0, and 0 otherwise

POST

Equal to 1 for the years 2007–2010, and 0 for years 2001–2005

ORECTA

Other receivables divided by total assets. This variable is annually winsorized at the 1 % level (item a001121000 divided by a001000000 from GTA/CSMAR)

ROA

Operating profit divided by total assets. This variable is annually winsorized at the 1 % level (item b001300000 divided by a001000000 from GTA/CSMAR)

SIZE

Natural logarithm of total assets (item a001000000 from GTA/CSMAR)

LEV

Total debt divided by total assets. This variable is annually winsorized at the 1 % level (item a002000000 divided by a001000000 from GTA/CSMAR)

NEG

Equal to 1 if a firm reports negative net income (item b002000000 from GTA/CSMAR) or equity (item a003000000 from GTA/CSMAR), and 0 otherwise

BLOCK

Shares of the largest shareholder divided by total shares (item s0301b from GTA/Corporate Governance)

STATE

State shares divided by total shares (item nshrstt from GTA/Corporate Governance)

NON_NEGO

Proportion of restricted shares (item nshrnn from GTA/Corporate Governance) divided by non-restricted shares (item nshrn from GTA/Corporate Governance)

CAR

Cumulative abnormal return around the window T1 and T2 (using items dretwd and cdretwdtl from GTA/CSMTB).

CER

Cumulative excess return around the window T1 and T2 (using items dretwd and cdretwdtl from GTA/CSMTB)

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Haß, L.H., Johan, S. & Müller, M.A. The Effectiveness of Public Enforcement: Evidence from the Resolution of Tunneling in China. J Bus Ethics 134, 649–668 (2016). https://doi.org/10.1007/s10551-014-2389-z

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