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From State to State Improving corporate governance when the


									Agency Conflicts, Expropriation and Firm Value:
                Evidence from
    Securities-Market Regulation in China

     Henk Berkman Massey University, Auckland
     Rebel A. Cole DePaul University, Chicago
     Jiang Fu      The University of Auckland
        Summary and Key Findings
• Event study of regulatory changes intended to
  improve corporate governance in China
• Announcement of regulations to protect investors
  resulted in higher firm valuations. (LLSV JF 2002)
• Securities-market regulation created significant value
  for investors in a civil-law country with weak judicial
  enforcement (Glaeser, Johnson and Shleifer QJE
• In a rule-based civil law country, regulation in form of
  “bright lines” are more effective than “broad
  standards.” (Black and Kraakman HLR 1996)
 Placement in the Finance Literature:
       Corporate Governance
• Shleifer and Vishny (JF 1997): How do
  minority shareholders and creditors ensure
  that they receive a pro-rata return on their
• Johnson, La Porta, Lopes de Silanes and
  Shleifer (AER 2000): How can minority
  investors be protected from “tunneling,” which
  they define as ”the expropriation of profits and
  assets by controlling shareholders.”
            The Changing Focus
         of Corporate Governance:
• Old Focus: Solutions to principal-agent
  problems arising from the separation of
  ownership from control.
  – How do we align interests of a firm’s managers
    with those of the firm’s shareholders?
  – Research focused on firms located in the U.S.,
    where diffuse ownership is the norm.
  – Jensen and Murphy (HBR 1990): Median CEO
    ownership of U.S. firms was only 0.25%.
            The Changing Focus
         of Corporate Governance:
• 1990s: (U.S.) researchers became aware that,
  outside of the U.S. and Japan, dispersed
  ownership is the exception rather than the
• Instead, ownership is concentrated in the
  hands of a few families or the State.
• “Corporate Ownership Around the World,”
  – La Porta, Lopez de Silanes, Shleifer and Vishny
    (JF 1999)
            The Changing Focus
         of Corporate Governance:
• Where ownership is characterized by controlling
  shareholders, the focus of corporate
  governance shifts:
• New Focus: Protection of the rights of minority
• How to prevent controlling shareholder, rather
  than the firm manager, from expropriating the
  wealth of minority shareholders.
                   The State
         as the Controlling Shareholder
• Of particular interest is the case where the controlling
  shareholder is the State.
• La Porta et al. (JF 1999) report that the State is the
  largest block holder for at least one quarter of the 20
  largest traded firms in the 27 wealthy countries that
  they study.
• Even in the U.S., there are large SOEs:
   –   U.S. Postal Service: largest U.S. employer
   –   Amtrack, the commuter railroad system
   –   Air Traffic Control System
   –   Public school systems across the U.S.
                  The State
        as the Controlling Shareholder
• Jones, Megginson, Nash, and Netter (JFE 1999):
  Share-issuance privatization (SIP) is the primary
  method for privatizing SOEs, and the State maintains
  control in most SIPs.
   – 1977-97: 556 SIPs, raising $232 Billion.
   – Mean/median size: $556 million / $104 million
   – Mean/median float: 43.9% / 35.0%.
• This means that the State remained the controlling
  block holder in the majority of all SIPs.
• Bottom Line: The State remains an important player
  in the control of many large and important firms
  around the world.
                The State
      as the Controlling Shareholder
• State control creates a principal-agent
  problem because cash-flow rights are
  separated from control rights.
  – Government officials hold of the control rights.
  – Cash-flow rights belong to the taxpayers.
  – How do we protect the taxpayers from
    expropriation by government bureaucrats?
                   Law and Finance:
    La Porta, Lopez-de-Silanes, Shleifer and Vishny

• JFE 2000: “. . . legal protection of investors as a
  potentially useful way to think about corporate
   – Stronger protection => Better governance
• JF 2002: Better governance => Higher valuation
• JPE 1998: investor protection is largely a function of
  legal protection and the quality of enforcement.
   – Common law countries provide superior protection relative to
     civil law countries
   – Countries with poor investor protection develop substitutes,
     such as regulations mandating or prohibiting certain actions.
         Law and Finance in China

• Stock markets developed during the 1990s, as more
  than 1,000 SOEs were privatized through share
• Civil-law tradition with weak investor protection.
• Developing judicial system, where courts have been
  reluctant to step in to protect investors.
• Relatively strong securities market regulator: the
  China Securities Regulatory Commission (CSRC)
      Regulation and Finance:
 Regulatory vs. Judicial Enforcement
• Glaeser, Johnson and Shleifer (QJE 2001): “ . . .
  Government regulation may be the cheapest way to
  bring about efficient allocation of resources.”
   – Securities market regulation can protect minority investors
     from expropriation by controlling shareholders.
   – “In economies with a developing judicial system, . . . the cost
     of regulatory enforcement may be cheaper than that of
     judicial enforcement.”
   – Empirical evidence from comparison of financial regulation in
     Czech Republic and Poland during 1990s. Stricter
     enforcement in Poland relative to Czech Republic led to
     superior development of financial markets.
       Regulation and Finance:
 “Bright Lines” vs. “Broad Standards”
• Black and Kraakman (Harvard LR 1996):
  “Bright-Line” regulations are preferable to “Broad-
  Standard” regulations in transitional economies with
  civil law judiciaries.
• Bright Lines: provide clear boundaries as to what is
  required and what is legal.
• Broad Standards: set forth murky boundaries as to
  what is required and what is legal, relying upon the
  judicial interpretations by the courts to adapt the
  standards to an evolving regulatory environment.
       Regulation and Finance:
 “Bright Lines” vs. “Broad Standards”
• Civil-Law judiciaries are less likely than Common-
  Law judiciaries to provide needed interpretations of
  “Broad-Standard” regulations, leaving regulations
• Regulations should rely upon enforcement by direct
  participants (e.g., shareholders and directors) to
  reduce the need for enforcement by indirect
  participants such as the judges and lawyers.
                 Why Study China?

• At least 1.3 billion reasons . . . .
• Second largest economy on PPP-adjusted basis.
• Chinese stock market expected to surpass Nikkei as
  second largest world equities market.
• China makes a most interesting contrast to
  disastrous privatization efforts undertaken in the
  former Soviet Bloc:
   – Mass privatization in Eastern Europe using vouchers failed
   – Why has China’s approach worked so much better?
         What went wrong in Russia?

• Black, Kraakman, Tarassova (Stanford LR 2000)
• Need for time to develop institutions/infrastructure.
   – Legal system that protects minority shareholders
     and creditors
   – Accountants to audit financial statements
   – Prosecutors to go after law breakers
   – Judges and courts to arbitrate disputes
   – Informed investors to allocate capital
   – Securities regulators to set and enforce rules
   Why did China’s approach to privatization
                work better?

• Staged privatization:
  – Slowly develop the necessary infrastructure and
  – Give these institutions time to “practice” and
    develop expertise while the State maintains
    ultimate control and prevents wholesale looting.
       Staged Privatization in China:
Numbers and Market Caps of Listed Firms 1993
 Staged Privatization in China:
State Ownership of Listed Firms
    Key CSRC Regulatory Changes:
• New regulations for annual shareholder meetings that
  improved the voting rights and other powers of
  minority shareholders.
• Prohibition against issuance of debt guarantees to
  shareholders or subsidiaries owned by shareholders.
• Limitations on asset transfers between related
• Requirement that each listed firm include
  independent directors on its Board and provide them
  with resources necessary to carry out their duties.

• Stock price data from Datastream for 500
  trading days ending June 5, 2001.
• Accounting data from 1999 annual reports.
• In total, we have data for 850 firms.
• Event windows: 1 day before CSRC issuance
  of each regulation through 1 day after first
  published report in financial press.
         Event-Study Methodology
• We estimate cumulative mean-adjusted returns:
  Market Return t = β0 + β1 * Event 1 + β2 * Event 2
                    + β3 * Event 3 + β4 * Event 4 + ε t
   – Market Return t is the return on the equally
     weighted market portfolio of firms listed only on the
     Chinese stock exchanges on day t (excludes firms
     also listed in Hong Kong).
   – β 0 captures the mean return.
   – β J , J = 1 to 4, estimate cumulative mean-adjusted
     returns associated with each event window.
      Event-Study Methodology

– Event J , J = 1 to 4, are dummy variables that take
  on a value of 1/N for each event window, where N
  is the number of days included in the window.
– This definition means that the betas are the total
  CARs and not the average daily CAR, which would
  be the case if we used simply zero-one dummies.
– We also estimate CARs using a market model,
  where the return on a portfolio of 24 Chinese firms
  that trade only on the Hong-Kong exchange serve
  as the market proxy.
                Table 2:
       Cumulative Returns by Event
Intercept                     0.000     -0.000
                               (0.09)   (0.97)
Event 1: Shareholder meeting 0.095 a    0.109 a
                               (0.01)   (0.01)
Event 2: Related Guarantees    0.008     0.001
                               (0.83)   (0.98)
Event 3: Asset Transfer        0.032    0.024
                               (0.57)   (0.68)
Event 4: Independent Directors 0.026    0.021
                               (0.37)   (0.48)
Hong-Kong Return                        0.075 a
 Cross-Sectional Differences in CARs

• Market-wide changes in value may obscure
  differential impacts upon firms with strong and
  weak governance.
• Our Hypothesis: Firms with weak governance
  are more reliant upon legal and regulatory
  protection than are firms with strong
• Shareholders of firms with weak governance
  should benefit disproportionately from the new
  regulations improving investor protection.
 Cross-Sectional Differences in CARs

• To test this hypothesis, we first calculate a
  firm-specific measure of governance based
  upon firm value as measured by Tobin’s Q.
• Based upon Gompers, Ishii and Metrick (QJE
  2003), who model Tobin’s Q as a function a
  vector of firm characteristics W i and a vector
  of corporate governance variables X i:
      Qi=a+bXi+cWi +ei
 Cross-Sectional Differences in CARs

• First, we estimate b X i by orthogonalizing Q
  against W i , which we proxy by standard
  explanatory variables that appear in the
  literature: size, leverage, growth prospects
  and industrial classification.
• What is left, we call Corporate Governance Q,
  or CG-Q. (see eq. 4 and Table 3.)
• Bertrand, Mehta and Mullainathan (QJE
  2002) use a similar approach in one of their
  tests of tunneling at Indian firms.
 Cross-Sectional Differences in CARs

• Next, we estimate CARs for each firm using
  the same approach as in Table 2.
• We then estimate a WLS regression of the
• CAR i, event j = γ 0 + γ 1 CG-Q i + e i
• The weights are the standard errors from the
  regressions used to estimate CAR for each
• Results appear in Panel A of Table 4.
                    Table 4 Panel A

               Event 1:     Event 2:   Event 3:       Event 4:
            Shareholder      Related      Asset   Independent
               Meeting    Guarantees   Transfer      Directors

Intercept       0.001        0.002      0.004         0.002
                (0.30)       (0.34)     (0.26)        (0.21)

              -0.002 c     -0.004 a    -0.005 a       0.000
CG-Q            (0.09)       (0.01)      (0.01)       (0.99)
 Cross-sectional Differences in CARs:
     Econometric Considerations
• We also use a portfolio time-series regression to test
  the cross-sectional differences in CARs.
• This approach deals with the cross-correlations in
  firm returns that are likely to occur when the event
  date and event window are the same for all firms.
• It provides unbiased estimates of coefficients along
  with standard errors that fully account for the cross-
  sectional heterosckesticity and cross-security
  dependence. (Sefcik and Thompson JAR 1986).
                CARs for
     “High CG-Q - Low CG-Q” Portfolio
• We sort our sample firms into quantiles based on
• We then calculate daily returns for a portfolio that
  is long on the highest quantile and short on the
  lowest quantile.
• Hence, this portfolio return measures the
  difference in returns on the high CG-Q quantile
  portfolio and the low CG-Q quantile portfolio.
• For quantiles, we use 5, 3 and 2 (fifths, thirds and
               CARs for
    “High CG-Q - Low CG-Q” Portfolio
Return (CG-Q Hight – CG-Q Lowt ) =
        β0 + β1 * Event 1 + β2 * Event 2
           + β3 * Event 3 + β4 * Event 4 + β5 * Market Returnt + ε t
   QHight is the return for day t on an equally weighted portfolio of
      the highest quantile firms based upon industry-adjusted Q;
   QLowt is the return for day t on an equally weighted portfolio of
      the lowest quantile firms based upon industry-adjusted Q
   Market Return t is one of two proxies for the market return:
      the return on the HK portfolio.
    For each event, we expect β J to be negative.
               Table 4 Panel B

              Event 1:   Event 2     Event 3:        Event 4:
           Shareholder   Related        Asset    Independent
              Meeting Guarantees     Transfer       Directors
5 Groups       -0.024 c   -0.032 a    -0.054 a         -0.001
                 (0.07)     (0.01)      (0.01)          (0.92)
3 Groups       -0.018 c   -0.025 a    -0.049 a         0.001
                 (0.07)     (0.01)      (0.01)         (0.91)
2 Groups      -0.015 b    -0.022 a    -0.049 a         0.001
                (0.04)      (0.01)      (0.01)         (0.85)
    Multivariate Cross-Sectional Analysis
•   We also examine how CARs co-vary with several directly
    observable firm characteristics, including several proxies for the
    quality of corporate governance.
•   Following La Porta et al. 2002, we assume that the “ultimate
    owner” of the firm has effective control over the firm.
•   We then consider three variables that might mitigate the ultimate
    owner’s incentive or ability to expropriate minority shareholders.
    1. Cash-flow rights of the ultimate owner
    2. Control rights of the ultimate owner relative to other block
    holders (specifically, the 2nd and 3rd largest block holders).
         - ln [ (Shares Largest) / (Shares 2nd and 3rd Largest) ]
    3. The issuance of B-shares to primarily institutional foreign
    Multivariate Cross-Sectional Analysis
•   We also test whether ultimate State control is a plus or minus by
    including a dummy variable indicating State control.
•   Xu and Wang (China Ec Rev 1999) suggest that the State is
    more likely to expropriate minority shareholders than are private
    block holders.
•   The theoretical model of Perotti (AER 1995) suggests the
    opposite, as does empirical research on privatization in the
    former Soviet bloc countries (Black et al (SLR 2000); Coffee (J
    Corp Law 1999)).
•   Our hypothesis: Cash-flow rights belong to taxpayer rather than
    government officials who exercise control rights, so the State is
    less likely to expropriate than a private controlling block holder.
•   Firm size and leverage are included as control variables.
Multivariate Cross-Sectional Analysis
First, we estimate the following WLS regression model:
CARi, event J = β0 + β1,J * CF-Rights of Ultimate Owner i
                   + β2,J * Large Shareholder Dominance Ratio i
                   + β3,J * State is Largest Dummy i
                   + β4,J * B-Shares Dummy i
                   + β5,J * Leverage i
                   + β6,J * ln (Assets) i
                  + εiJ
Results appear in Table 5 in the WLS columns.
   Multivariate Cross-Sectional Analysis:
        Econometric Considerations
• As before, there are econometric problems with this
  WLS regression approach.
• Given the contemporaneous event periods for the
  sample firms, there is cross-correlation in the firm
  return processes from which the CARs are estimated.
• More complicated here than with CG-Q because we
  have multiple explanatory variables.
• Sefcik and Thompson (1986) propose a method to
  obtain unbiased estimates of the cross-sectional
  regression coefficients, along with standard errors
  that fully account for cross-sectional
  heteroscedasticity and cross-security dependence.
   Multivariate Cross-Sectional Analysis:
     Portfolio Time-Series Regression
This portfolio time-series approach involves three steps:

1. Orthogonalize each of our six explanatory variables
   against the others and a set of 25 industry dummies.
2. For each of the six orthogonalized variables OV, we
   form a portfolio that is long the highest quantile of
   that variable and short the lowest quantile of that
3. Regress the returns of this high-long/low-short
   portfolio on the market return and a set of four
   dummy variables representing each event window:
   Multivariate Cross-Sectional Analysis:
     Portfolio Time-Series Regression
So our regression model is:
      Return (High Quantile) t – Return (Low Quantile) t
             + β 1 * Event 1
             + β 2 * Event 2
             + β 3 * Event 3
             + β 4 * Event 4
             + β 5 * Market Return t
             + εt
The betas from these time-series regressions are
  equivalent to the cross-sectional betas from the WLS
  regression of CARs on the explanatory variables.
Multivariate Cross-Sectional Analysis:
  Portfolio Time-Series Regression
• In aggregate, the four regulatory events we study
  resulted in a statistically significant 16 percent
  increase in firm value.
• Moreover, firms with weak governance benefited
  disproportionately relative to firms with strong
• For three of the four events, we find statistically
  significant cross-sectional differences in CARs that
  are supportive of theories of corporate governance.
• Only for our “broad-standard” event, the requirement
  of independent directors, do we fail to find significant
• Our results provide new evidence supporting the
  theoretical model of La Porta et al. 2002, which
  predicts that better investor protection is rewarded
  with higher firm valuations.
• Our results demonstrate that regulations to protect
  minority shareholders in a civil-law country with a
  weak judiciary can create significant value for
  minority shareholders, consistent with Glaeser,
  Johnson and Shleifer (2001)
• Our results are consistent with Black and Kraakman
  (1996), who argue that “bright-lines” regulations are
  preferable to “broad standards” in a transitional
  economy with a weak judiciary.

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