Corporate Governance Quality: Trends and Real Effects

WP/06/293


Corporate Governance Quality: Trends
and Real Effects

Gianni De Nicol⃲, Luc Laeven, and
Kenichi Ueda

---

---

© 2006 International Monetary Fund
WP/06/293


IMF Working Paper


Research Department

Corporate Governance Quality: Trends and Real Effects

Prepared by Gianni De Nicolò, Luc Laeven, Kenichi Ueda¹

Authorized for distribution by Laura Kodres and Eswar Prasad

December 2006

Abstract

This Working Paper should not be reported as representing the views of the IMF.
The views expressed in this Working Paper are those of the author(s) and do not necessarily represent
those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are
published to elicit comments and to further debate.

This paper constructs a composite index of corporate governance quality, documents its
evolution from 1994 through 2003 in selected emerging and developed economies, and
assesses its impact on aggregate and corporate growth and productivity. Our investigation
yields three main findings. First, corporate governance quality in most countries has overall
improved, although to varying degrees and with a few notable exceptions. Second, the data
exhibit cross-country convergence in corporate governance quality with countries that score
poorly initially catching up with countries with high corporate governance scores. Third, the
impact of improvements in corporate governance quality on traditional measures of real
economic activity—GDP growth, productivity growth, and the ratio of investment to GDP—
is positive, significant, and quantitatively relevant, and the growth effect is particularly
pronounced for industries that are most dependent on external finance.

JEL Classification Numbers: G30, G34
Keywords: Corporate governance, disclosure, transparency, economic growth, productivity
Authors’ E-Mail Addresses: gdenicolo@imf.org, llaeven@imf.org; kueda@imf.org

¹ Excellent research assistance by Nese Erbil, Juanita Riano, Junko Sekine, and Wellian Wiranto is gratefully
acknowledged. We would like to thank Franklin Allen, Patrick Bolton, Stijn Claessens, Simon Johnson, Laura
Kodres, Paolo Mauro, Jonathan Ostry, Eswar Prasad, Raghuram Rajan, René Stulz, Shang-Jin Wei, and seminar
participants at the International Monetary Fund and the IMF/World Bank annual meeting in Singapore for
comments on earlier drafts of this paper.

---

2
Contents Page

I. Introduction .......................................................................................................................... 4

II. The CGQ Index ................................................................................................................... 6

A. Accounting Standards ............................................................................................. 6
B.
Earning
Smoothing.................................................................................................. 7

C. Stock Price Synchronicity ....................................................................................... 7

III. Trends in Corporate Governance Quality........................................................................ 10

IV. The Real Effects of Corporate Governance Quality........................................................ 11

A. Impact on Growth, Productivity and Investment .................................................. 12

B. Impact on Growth of Financial Dependent Industries .......................................... 17

V. Conclusion ........................................................................................................................ 20

References.............................................................................................................................. 39

Figures
1.
CGQ Index, Subperiod Averages .............................................................................. 21
2.
CGQ Index in Asia..................................................................................................... 22
3.
Earning Smoothing Indicator, Sub-Period Averages................................................. 23
4.
Stock Price Synchronicity Indicator, Sub-Period Averages ...................................... 24
5.
Accounting Standards Indicator, Sub-Period Averages............................................. 25

Tables
1. Changes
in
Shareholder’s
Rights in Asia Before and After the Asian Crisis............ 26
2.
Changes in Creditors Rights in Asia Before and After the Asian Crisis ................... 26
3.
Aggregate Economic Activity and Corporate Governance: Benchmark Model ....... 27
4.
Aggregate Economic Activity and Corporate Governance: Excluding “Crisis”

Country Years Observations................................................................................... 28
5.
Aggregate Economic Activity and Corporate Governance: Accounting for

Complex Dynamics................................................................................................. 29
6.
Aggregate Economic Activity and Corporate Governance: Accounting for

Financial Development ........................................................................................... 30
7.
Industry Growth, Financial Dependence, and Corporate Governance ...................... 31
8.
Industry Growth, Financial Dependence, and Corporate Governance: Excluding

Crisis Countries....................................................................................................... 32
9.
Controlling for Financial Development ..................................................................... 33

---

3
Appendix Tables
A1.
Corporate Governance Quality Index ........................................................................ 34
A2.
Accounting Standards Indicator................................................................................. 35
A3.
Earnings Smoothing Indicator ................................................................................... 36
A4. Stock
Price
Synchronicity Indicator .......................................................................... 37
A5.
Summary Statistics of Main Variables in Industry Panel Regressions...................... 38

---

4
I. INTRODUCTION
Corporate governance reform has ranked high on policymakers’ agendas in many countries
since the late 1990s. New laws and regulations aimed at improving corporate governance
have been introduced in many countries, and particularly in several Asian countries in the
aftermath of the East Asian financial crisis of 1997-98.2

Yet, have governance practices actually improved? And, do improvements in corporate
governance contribute to higher output, investment, and productivity growth in the corporate
sector? To date, these key questions have not been addressed in the literature. This paper
addresses these questions. We first construct a composite corporate governance quality
(CGQ) index and document its evolution for major emerging markets and developed
economies during the period 1994-2003. We then assess the impact of measured
improvements in corporate governance quality on output growth, productivity, and
investment at a country level, and on industry growth.

Our CGQ index is constructed at a country level using accounting and market data of
samples of nonfinancial firms listed in the relevant domestic stock markets. Hence, it
captures corporate governance quality specific to a universe of firms which are likely to be
comparatively more exposed to market discipline. For this reason, the finding of no
improvement in governance for these firms would likely signal the lack of improvements for
the corporate sector as a whole. On the other hand, the finding of improvements for these
firms could signal either that improvements have occurred in the corporate sector as a whole,
or that improvements are likely to be found especially among firms subject to market
discipline. In either case, the evolution of the index is informative about changes in
governance in the corporate sector.

The CGQ index is a simple average of three proxy measures of outcomes of corporate
governance in the dimensions of accounting disclosure and transparency. Disclosure and
transparency are necessary, albeit not sufficient, conditions of good corporate governance,
since the extent of information asymmetries among managers and stakeholders pointed out
by the corporate governance literature are likely to be less severe with enhanced transparency
and disclosure.3 By focusing on indicators capturing necessary conditions for good corporate
governance, we aim at capturing in a parsimonious, yet informative way, the dynamics of
dimensions of corporate governance quality that are likely to be correlated with other
determinants of efficient governance arrangements. As detailed below, these indicators are
derived from selected studies in the finance and accounting literature.
Considering outcome-based measures of corporate governance, as opposed to de jure
measures, is advantageous and informative for at least two reasons. First, tracking changes

2 See Claessens and Fan (2003), OECD (2003), and Cheung and Jang (2005).
3 For reviews of the literature on corporate governance, see Shleifer and Vishny (1997), Zingales (1998), Tirole
(2001, 2006), Becht and others (2003), and Berglof and Claessens (2006).

---

5
in corporate governance with de jure measures is difficult, since improvements may not
necessarily occur because of lags in implementation and/or enforcement, as stressed by
Berglof and Claessens (2006). Second, firms may indeed choose to improve their corporate
governance prior to or independently of the enactment of new rules whenever the benefits of
good corporate governance, especially in terms of easier and less costly access to finance, are
critical for their growth prospects.

In essence, corporate governance quality may be viewed partly as an “endogenous” firm’s
choice, as pointed out by Himmelberg, Hubbard, and Palia (1999) and Coles, Lemmon, and
Meschke (2003). Ultimately, shareholders’ or stakeholders’ values will be maximized when
managerial incentives are set in a right direction, and a good corporate governance helps it
happen, if not necessary (e.g., Jensen 1986, and Tirole 2001). Thus, it is a broad set of
underlying rules and practices that determine corporate governance and influence managerial
incentives .Our aim is not to identify and quantify each of these underlying factors and the
specific channels through which they operate to affect corporate governance and managerial
incentives. Our contribution is to develop an outcome-based corporate-governance measures
based on accounting and market data, as those data measure the outcomes of managerial
decisions.

We investigate the relationship between corporate governance quality and economic
performance at the country level, although most of the literature relates measures of
corporate governance to firm-level performance (see, for example, Gompers, Ishii, and
Metrick, 2003). Our choice is supported by empirical evidence in Doidge, Karolyi, and Stulz
(2004b) who show that most of the variation in firm level governance can be explained by
country-level characteristics. Furthermore, Core, Guay, and Rusticus (2006) show that
investors discount values of weakly governed firms and that weak governance does not cause
poor stock market returns at the firm level.

Our investigation yields three main findings. First, the CGQ index exhibits improvements in
corporate governance quality in most countries considered since 1994, with the exception of
few countries, where either no significant changes have occurred, or a worsening is recorded.
Corporate governance quality has improved especially in the dimension of transparency,
while improvements in accounting disclosure have been more limited. Second, the data
exhibit cross-country convergence in corporate governance quality with countries that score
poorly initially catching up with countries with high corporate governance scores.

Third, improvements in corporate governance quality affect the aggregate economic
activities positively and significantly, as shown in regression analysis of per capita GDP
growth, Total Factor Productivity (TFP) levels and growth, and the ratio of investment to
GDP on the CGQ index. Moreover, when we gauge the impact of changes in corporate
governance quality on sales growth and growth opportunities of firms grouped by industry,
we find a positive effect of improvements in corporate governance on the growth of
financially dependent industries. This result is consistent with the idea that improvements in
corporate governance quality benefit most those industries whose growth crucially depends
on external finance.

---

6
Overall, the answers to the two questions we wished to address are both positive. Actual
improvements in corporate governance, as captured by our indicators, have indeed occurred
in most countries, although in varying degrees and with some notable exceptions. More
importantly, improvements in corporate governance quality yield tangible benefits in terms
of enhanced growth, productivity and investment, and these benefits are large for those
industries which rely most on external finance. Thus, effective implementation of corporate
governance reform appears to be an important contributing factor to countries’ well-being.

The remainder of the paper is composed of three sections. Section II details the construction
of the CGQ index and its components. Section III depicts the evolution of our measures of
corporate governance quality within and across countries and regions. Section IV presents
country and industry regressions relating the CGQ index and its components to measures of
growth, productivity and investment for the economy and the corporate sector. Section V
concludes.

II. THE CGQ INDEX
The CGQ index is a simple average of three indicators, called Accounting Standards (AS),
Earning Smoothing (ES), and Stock Price Synchronicity (SPS). These indicators are
constructed from accounting and market data for samples of non-financial companies listed
in stock markets taken from the Worldscope and Datastream databases.

A. Accounting Standards
The first indicator is a simple measure of the amount of accounting information firms
disclose, and is constructed similarly to the index reported by the Center for International
Financial Analysis and Research (CIFAR) until 1993.
CIFAR uses information based on the top 8 to 40 companies (depending on data availability)
and on 90 items selected by professional accountants (CIFAR, 1993). Our indicator is given
by the number of reported accounting items as a fraction of 40 accounting items selected
from CIFAR’s 90 items based on availability in the Worldscope database. We use
information for the top ten manufacturing companies in terms of total asset for each year and
in each country.4

4 We checked the robustness of the AS indicator by constructing variants in several ways. For example,
eliminating the accounting items that are reported by 95% of all firms in 1995, we construct the index using
only those 16 items that are reported by less than 95% of all firms. This index has more variation, compared to
original index that is based on 40 accounting items, but the correlation with the original index is very high,
more than 0.95. We also constructed an alternative index using the percentage of the 10 largest firms in each
country (in terms of market capitalization) that reports all of the 24 items that are reported by 95% or more of
all firms, but there is very little variation. We calculate these two variants using a threshold of 85 percent
instead of 95 percent 85%, but this does not alter our findings. Finally, we constructed an index based on the
100 largest firms (or less when not available) instead of the 10 largest firms, but sample selection bias appears
severe, as the number of firms covered by Worldscope typically grows over time in emerging market
economies.

---

7
B. Earning Smoothing
The second indicator is a measure of “earnings opacity” proposed by Leuz, Nanda, and
Wysocki (2003) and Bhattacharya, Daouk, and Welker (2003). It tracks the extent to which
managers may conceal the true performance of firms using accruals to smooth fluctuations of
annual profits. Specifically, it is the rank correlation between cash flows (before any
accounting adjustments) and profits (after accounting adjustments) across a set of firms at
each point in time. This indicator is an important complement to the first indicator, since a
large number of reported accounting items may be meaningless if accounts are seriously
manipulated or misrepresented.

Unlike these authors, who use a pooled cross section data for each country, our measures are
calculated for each year and each country. Accruals (AS) are estimated as

AS = (∆CA − Cash
∆
) − ( CL
∆
− ST
∆ D − ∆TP ) − Dep ,
ikt
ikt
ikt
ikt
ikt
ikt
ikt

where CA denotes current assets, Cash is cash and cash equivalents, CL are current
liabilities, STD is short-term debt and the current portion of long-term debt, TP is income tax
payable, and Dep denotes depreciation and amortization.

Since cash flow statements are not widely reported in many developing countries, cash flow
from operations (ECF) are estimated by subtracting accruals (AS) from operating income
(OI) : ECF = OI − AS . Cross-sectional earnings smoothing is then measured by a
ikt
ikt
ikt
Spearman rank order correlation between changes in accruals and changes in estimated cash
flow (both normalized by total asset). It is defined for each year and each country as

2
N ⎛
⎛ AS
∆
⎞
⎛ ∆ECF ⎞⎞
6
ikt
ikt
∑⎜Rank⎜
⎟ − Rank ⎜
⎟⎟
TA
TA
i,t ⎝
⎝
ikt 1
− ⎠
⎝
ikt 1
⎠
EarningSmoothing 1
−
⎠
= −

2
N (N −1)

The ES indicator is standardized so that its values fall in the unit interval and increases as
earning smoothness declines (i.e. firm performance is less opaque). Thus, an increase of this
indicator signals an improvement in transparency.

C. Stock Price Synchronicity
The third indicator is a measure of stock price synchronicity proposed by Morck, Yeung, and
Yu (2000), given by the average goodness-of-fit ( 2
R ) of regressions of each company’s
stock return on country-average return in each year.5 These authors show that after
controlling for other drivers of co-movements in stock prices not necessarily related to

5 Morck, Yeung, and Yu report a second measure, given by the share of stocks whose prices move in the same
direction (either up or down). Our results are invariant to the use of this measure.

---

8
corporate governance,6 more synchronous stock prices are found in countries in which
corporate governance is poor and financial systems are less developed. More recently, Jin
and Meyers (2006) analyze a larger data set and find a positive relationship between stock
price synchronicity and lack of transparency. Intuitively, if the accounting information is
opaque, investors find it difficult to distinguish good performers from bad performers.
Ceteris paribus, in the event of a shock to the market or the arrival of new information, the
inability of investors to discriminate among firms would induce them to trade most stocks,
prompting movements in stock prices to become more synchronous.

We should note that synchronicity can also occur if there is cross-subsidization among firms
belonging to the same group. Cross-subsidization may stem from optimal allocation of funds
in internal capital markets. Yet, in a poor governance environment, cross-subsidization is
likely to be associated with inefficient connected lending: this governance-specific feature is
likely captured by the SPS indicator, but it is not by the AS and ES indicators. In this sense,
the SPS indicator complements the two indicators previously described.

For each year, the SPS indicator is computed in five steps. First, we calculate weekly return
r for each firm (t = week), dropping firms with less than 30 weeks observation, and
ikt
dropping an observation if the absolute value of r is greater than 0.25. Second, we calculate
ikt
market capitalization-weighted weekly returns for each country k, ρ , using weekly stock
kt
price indexes is from Datastream, and weekly net exchange rate appreciation rates for each
country, e Third, for each firm we run the regressions: r = α + β ρ + γ (ρ
+ e ) + ε ,
kt.
ikt
i
i
kt
i
USt
kt
it
and retrieve the relevant goodness of fit 2
R .
ik

2
T ⎛
1 T
⎞
Fourth, we calculate the total variation for each firm, given by SST = ∑ r − ∑r
,
ik
⎜ ikt
ikt ⎟
t 1
= ⎝
T t 1=
⎠
∑( 2
R × SST
ik
ik )
and compute the country level common variation, given by: 2
i
R =
k
∑
. To avoid
SSTik
i
sample selection bias, 2
R is computed for the same sample size over years (but possibly for
k
different companies) based on the rank order of market capitalization. Finally, the SPS
indicator is standardized so that its range is the unit interval, it increases as synchronicity
declines (i.e. transparency improves), and is computed based on an equal number of (but
different) firms selected by their market capitalization at each date.7

6 Synchronicity may be observed if a country specializes in specific industries. In this case, industry specific
shocks would drive overall movements of stock prices, in contrast with the case of a highly diversified country.
In addition, if aggregate shocks are large (e.g., overall boom and bust, oil shocks, or currency crisis), then stock
prices may move more in those countries which are most sensitive to aggregate shocks.
7 This selection criterion takes into account changes in stock price synchronicity due to changes in the number
of firms that are listed in the stock exchange at each point in time. This is important especially in the case of
countries that experienced a crisis. By construction, a balanced sample would not reflect exits of bankrupt firms
(continued…)

---