Corporate Ownership & Control / Volume 9, Issue 4, 2012 ...

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Corporate Ownership & Control / Volume 9, Issue 4, 2012, Continued - 2

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CORPORATE OWNERSHIP & CONTROL Volume 9, Issue 4, 2012, Continued - 2

CONTENTS

THE RELATIONSHIP BETWEEN TRADING VOLUME AND STOCK RETURNS IN THE JSE SECURITIES EXCHANGE IN SOUTH AFRICA 199 Raphael T Mpofu CORPORATE GOVERNANCE, AGENCY COSTS AND INVESTMENT APPRAISAL: AN ASSESSMENT 208 Baliira Kalyebara, Abdullahi D. Ahmed THE INFLUENCE OF CULTURAL VALUES ON THE BOARD OF DIRECTORS: LESSONS FROM FIVE CORPORATIONS 221 Elsa Satkunasingam, Aaron Yong Sern Cherk DETERMINING WHICH MANAGEMENT LEVEL MAKES DECISIONS WHEN OUTSOURCING THE DISTRIBUTION FUNCTION 230 Johan Muller, Louise van Scheers CRIME, SECURITY AND FIRM PERFORMANCE IN SOUTH AFRICA 241 Busani Moyo OWNERSHIP STRUCTURE AND DEBT POLICY OF TUNISIAN FIRMS 253 Hentati Fakher, Bouri Abdelfettah THE INTRA-INDUSTRY EFFECTS OF CHAPTER 11 FILINGS: EVIDENCE FROM ANALYSTS’ EARNINGS FORECAST REVISIONS 262 Gary L. Caton, Jeffrey Donaldson, Jeremy Goh

THE RELATIONSHIP BETWEEN TRADING VOLUME AND STOCK RETURNS IN THE JSE SECURITIES EXCHANGE IN

SOUTH AFRICA

Raphael T Mpofu*

Abstract

This study examines the relationship between trading volume and stock returns in the JSE Securities Exchange in South Africa. The study looked at the price and trading returns of the FTSE/JSE index from July 22, 1988 till June 11, 2012. The study revealed that stock returns are positively related to the contemporary change in trading volume. Further, it was found that past returns were not affected significantly by changes in trading volumes. The results present a significant relationship between trading volume and the absolute value of price changes. Autoregressive tests were used to explore whether return causes volume or volume causes return. The results suggest that volume is influenced by a lagged returns effect for the FTSE/JSE index. Therefore, return seems to contribute some information to investors when they make investment decisions. Keywords: South Africa, FTSE/JSE, Trading Volume, Stock Returns * Associate Professor, Department of Finance & Risk Management and Banking, University of South Africa, PO Box 392, Pretoria, 0003, South Africa Fax: (+27) 12 429-4553 Tel.: (+27) 12 429-4497 E-mail: mpofurt@unisa.ac.za

1. Introduction

Since Eugene Fama (1970) proposed the efficient

markets hypotheses, a number of studies have been

done in various markets to determine the validity of

these hypotheses. The three types of efficiency

proposed by Fama were that of the strong-form; semi-

strong form and weak-form efficiency. In the weak

form efficiency, Fama proposed that it is not possible

for investors to profit from historical share price

information. With the semi-strong form, he stated that

investors could only profit from historical share prices

if they had access to all the information required for

asset selection reflected all publicly available

information. Finally, in the strong-form efficiency,

Fama stated that for investors to profit from historical

share price movements, all information, including

private information, should be incorporated in the

share price. The discussion on market efficiency

therefore looks at how information is factored in share

prices and the hypothesis of market efficiency can be

tested by looking at the relationship between share

prices and expected returns and for investors to make

profitable asset allocations based on that historical

information.

Since Fama points out that a market is weak-

form efficient if all the information contains in past

stock prices fully reflect in current prices (Fama,

1970, 1991), this implies that past share prices cannot

be used to predict the future price changes and

therefore invalidates the use of technical analysis in

asset selection and asset allocation decisions. This

however goes against the grain of current investment

decisions as a number of investors rely heavily on

technical analysts who base their decisions on the

movement of historical share prices.

Given the important role of technical analysts in

investment decisions as per findings of Karpoff

(1987); that volume drives prices; that there are

positive relations between the absolute value of daily

price changes and daily volume for both market

indices and individual stocks (Rutledge, 1984); the

role of trading activities in terms of the information it

contains about future prices (Gervars, Kaniel and

Mingelgrin, 2001), this study sought to determine the

existence of the weak-form market efficiency.

Literature reveals that most of the studies on volume-

price relationships have been based on developed

markets. Therefore this study is to empirically test the

trading volume-price relationships in the JSE

Securities Exchange.

Although there has been extensive research into

the empirical and theoretical aspects of the stock price

– volume relationship, this research has focused

mostly on developed countries financial markets.

Since there seems to be no consensus on the

relationship, this study sought to seek further insights

by investigating the relationship in an emerging

market.

This study looked at the price and trading returns

of the FTSE/JSE index from July 22, 1988 till June

11, 2012. The subsequent sections look at a summary

of related literature, the data collection methods used

and a detailed analysis of monthly time-series data

covering a period of 24 years. The last section

presents the conclusions from the data analysis and

the limitations of the study as well as proposals for

future research on the volume-return trade-off.

2. Review of Related Literature

The literature on trading volume and share price

returns is very extensive. Maury Osborne was the first

researcher to publish the hypothesis that price follows

a geometric Brownian motion and was responsible for

the earliest literature identifying that price deviation is

proportional to the square root of time (Osborne

1959). Most of the early studies find positive

correlation between the daily price changes and daily

volume for both market indices and individual stocks.

Karpoff (1986, 1987) provides a theory that links

returns with trading volume and leads to an

asymmetric relationship between volume and price

change. This is supported by studies from Jain and

Joh (1988); Epps (1975) and Jennings, Starks and

Fellingham (1981).

Some early studies using daily and weekly stock

data conclude that prices and volume are virtually

unrelated and that price changes follow a random

walk (Granger and Morgenstern, 1963; Godfrey et al,

1964). In contrast, using daily and hourly price

changes for both market indices and individual stocks

Crouch (1970a, 1970b) finds a positive correlation

between volume and the magnitude of returns.

Examining the relation between volume and

returns, a positive contemporaneous correlation has

been found by Rogalski (1978) using monthly stock

and warrant data and by Epps (1975), (1977) using

transactions data. To explain such results, Epps

proposes a theoretical framework consistent with his

findings and supported by Smirlock and Starks (1985)

and by Assogbavi, Khoury, and Yourougou (1995).

Granger and Morgenstern conducted an early

empirical study based on the New York Stock

Exchange (NYSE) composite index from 1939-1961

(Granger and Morgenstern, 1963). While their

findings indicated that there is no relation between

absolute value of daily price changes and daily

volume, subsequent studies did find a relationship

between absolute price change and volume change

(Crouch, 1970; Epps and Epps, 1976; Haris, 1986).

Studies done in the last decade have also found a

relation between stock returns and trading volume

(Chen, Firth and Rui, 2001; Khan and Rizwan, 2001;

Lee and Rui, 2002; Pisedtasalasai and Gunasekarage,

2008). Other authors have included Admati and

Pfleiderer (1988), Barclay, Litzenberger and Warner

(1990), Barclay and Warner (1993), Brock and

Kleidon (1992), Easley and O'Hara (1987), Foster and

Viswanathan (1990) and Kyle (1985).

Miller (1977) also looked at the relationship

between stock price and volume. He hypotheses that

when investors differ in their opinions about the value

of a stock, the traders who hold the stock show

optimism about its value by driving demand up, hence

leading to an increase in the stock price. Miller’s

argument is that when investors have mixed beliefs

about a stock and face a shortage of that stock, the

stock’s price will reflect the opinion of the optimistic

investors forcing the price of the stock to rise

(Harrison and Kreps, 1978; Mayshar 1983; Morris,

1996). One can conclude from this hypothesis that if

there is a wide difference of opinion on the value of a

stock among investors, that stock is likely to trade at a

premium (Chen, Hong and Stein, 2002). Similarly,

Diether, Malloy, and Scherbina (2002) have also

shown that a stock that has a higher divergence of

opinion is normally followed by a lower future stock

return.

In examining the relationship between volume

and returns, a positive concomitant correlation has

been found by Epps (1975, 1977) using transactions

data. Epps proposes a theoretical framework that

implies that the ratio of volume to returns should be

greater for price increases than for price decreases.

This conclusion is also supported in studies by

Smirlock and Starks (1985) who employed individual

stock transactions data and found a strong positive

lagged relation between volume and absolute price

changes. Bhagat and Bhatia (1996) found evidence

that price changes lead to volume changes but did not

find evidence that volume changes lead to price

changes. Hiemstra and Jones (1995) found a

significant positive relation going in both directions

between returns and volume. Tse (1991) in his study

of the Tokyo Stock Exchange found significant

positive correlation in some series and not in others.

He concluded that the relationship between price

changes and volumes is weak. Chan and Tse (1993)

found that there was implicit positive correlation

between price and volume through their residuals.

Volume is a measure of the quantity of shares

that change amongst owners of a given stock. The

amount of daily volume on a security can fluctuate on

any given day depending on the amount of new

information available about the company. Of the

many different elements affecting trading volume, the

one which correlates the most to the fundamental

valuation of the security is the new information

provided. This information can be a press release or a

regular earnings announcement provided by the

company, or it can be a third party communication,

such as a court ruling or a release by a regulatory

agency pertaining to the company. So in considering

the price-volume relationship, Karpoff (1987)

suggests the following four possible reasons.

First, it adds insight to the structure of financial

markets. The correlations which are found can

provide information regarding rate of information

flow in the marketplace, the extent that prices reflect

public information, the market size, and the existence

of short sales and other market constraints. Second,

studies that use a combination of price and volume

data to draw inferences need to properly understand

this relationship (also Beaver, 1968). The third is that

understanding the price-volume relationship is vital

for one to determine why the distributions of rates of

return appear kurtosic. The fourth is that price

variability affects trading volume in futures contracts.

(See also Karpoff, 1987; Gallant, Rossi, and Tauchen,

1992; and Blume, Easley, and O’Hara, 1994). This

interaction determines whether speculation is a

stabilizing or destabilizing factor on futures prices.

Given the diversity of viewpoints, this study

therefore sought to investigate the relationship

between stock price and trading volume in the JSE

Securities Exchange, an emerging market. The next

section looks at the data and the model used for data

analysis, which is then followed by a discussion and

interpretation of the results, leading to a conclusion

and recommendations.

3. Materials and Methods

3.1. The data

The dataset used in this study consists of daily time

series of the FTSE/JSE stock index of all listed firms

on the JSE Securities Exchange for the period July 22,

1988 to June 11, 2012. The variables used in the study

are all the daily closing prices and trading volume of

the FTSE/JSE index.

3.2. Methodology

The price-volume relationship was examined by

looking at the relation between changes in stock price

to trading volume. The contemporary correlation

between changes in volume-return is examined by

looking at correlation between the natural logarithms

of volume changes (V) and the natural logarithms of

absolute value of the stock returns| |. The variable

stock returns will be used throughout the rest of the

article. The second hypothesis looked at is the

relationship between past trading volume and future

stock returns.

The returns were calculated using the following

approximation:

where is the closing price of the index on

day t.

The following formula is used to compute the

daily trading volume changes.

( ) (2)

where is the trading volume of the index on

day t.

In order to avoid survivorship bias, (if stocks

with poor performance are dropped from calculation,

it often leads to an overestimation of past returns) all

stocks that were traded during the study period were

included. Tauchen and Pitts (1983) point out that a

price variability-volume study can be very misleading

if the volume is strongly trended over the sample

period. In line with their recommendations, volume

data was tested for stationarity using Said and

Dickeys' (1984) augmented Dickey-Fuller (ADF) test.

The results confirmed that the volume data are non-

stationary for the FTSE/JSE index over the study

period and this is consistent with the alternative

hypothesis that the volume data are non-stationary.

This test for stationarity ensures that the study on the

price change-volume relationship on the JSE does not

give misleading inferences.

A number of researchers and traders in financial

markets hold the view that volume has a strong

influence on prices movements. This has been found

to be true in studies by Crouch (1970), Clark (1973),

Tauchen and Pitts (1983), and Jain and Joh (1988)

who concluded that there was a positive correlation

between absolute price change and volume. In this

study, parametric tests for the price change-volume

relationship were done by regressing the price change

against the absolute price change against trading

volume. The regression equation is:

| | (3.1)

| | = absolute price change in day t

= trading volume for day t

=error term in the regression model,

= trading volume change in day t.

4. Results and Discussion

4.1. Descriptive analysis

Figure 1 shows the time plots of monthly log returns

and monthly log trading volumes of the FTSE/JSE.

As expected, the plots show that the basic patterns of

log returns are as expected.

Figure 1. Price-Volume Trend 1988 to 2012

Table 1 provides the summary statistics for the

variables in this study. The FTSE/JSE stock market

price index shows very low volatile with a standard

deviation measure of 0.011 and the trading volume of

the stock index shows a very high standard deviation

of 2.41. There is also evidence of negative skewness

for both stock returns and trading volume at -0.411

and -1.533 respectively. The kurtosis value for stock

returns exceeds the normal value of three to four for

stock returns at a value of 6.272 but is in line with

findings from other research studies. The kurtosis

value for trading volume at 2.76 is within the

acceptable range for normality. In addition, the low

skewness value for trading volume supports a normal

distribution of the time series and also supports the

apriori condition of a random walk model in the weak

or strong form.

Table 1. Descriptive statistics for FTSE/JSE index stock returns and trading volume

Statistics

PRICE VOL

N Valid 5959 5959

Missing 0 0

Mean .000554 10.982349

Std. Error of Mean .0001534 .0311615

Std. Deviation .0118438 2.4054975

Variance .000 5.786

Skewness -.411 -1.533

Std. Error of Skewness .032 .032

Kurtosis 6.272 2.760

Std. Error of Kurtosis .063 .063

4.2. Testing for stationarity

The first test that was done was the stationarity test of

the time series using the Dickey– Fuller (1979) ADF

test. The results are reported in Table 2 and indicate

that all series are non-stationary and hence it was

concluded that price change and volume change series

are non-stationary. The implication of this finding is

that testing for causality between price and volume

should be based on unrestricted VARs in first

differences. The next step, therefore, was to determine

whether or not futures prices and volumes were

cointegrated. The results of the cointegration tests

indicate the absence of cointegration in both cases.

Thus, testing for causality will be based on

unrestricted VARs, hence the next test will test for

white noise or stationarity.

Years PRICE VOL

Table 2. Testing for stationarity of price changes and trading volume changes: Estimation Method – VARMAX Least

Squares Estimation

Equation Parameter Estimate Standard

t Value Pr > |t| Variable

VOL CONST1 1.69588 0.09317 18.20 0.0001 1

AR1_1_1 0.49585 0.01214 40.84 0.0001 VOL(t-1)

AR1_1_2 -0.72744 1.59041 -0.46 0.6474 PRICE(t-1)

AR2_1_1 0.35003 0.01212 28.87 0.0001 VOL(t-2)

AR2_1_2 -0.77895 1.59031 -0.49 0.6243 PRICE(t-2)

PRICE CONST2 0.00040 0.00076 0.52 0.6008 1

AR1_2_1 0.00022 0.00010 2.19 0.0284 VOL(t-1)

AR1_2_2 0.08530 0.01295 6.58 0.0001 PRICE(t-1)

AR2_2_1 -0.00021 0.00010 -2.10 0.0355 VOL(t-2)

AR2_2_2 0.01939 0.01295 1.50 0.1345 PRICE(t-2)

A time series is called a white noise if it is a

sequence of independent and identically distributed

random variables with finite mean and variance. In

particular, if the series is normally distributed, all the

ACFs are zero. Based on Table 2, the daily returns of

the FTSE/JSE index are close to white noise with

ACFs close to zero in both single and second lags.

The p-values of these test statistics are all close to

zero. In finance, price series are commonly believed

to be non-stationary, but the log return time series

depicted as in equation 2 and used in the calculations

in this study shows that the series in stationary. In this

case, the log price series is unit-root non-stationary

and hence can be treated as an ARIMA process. A

Dickey-Fuller test produced the statistics shown in

Table 2 above. The t-test statistic for price was 0.52

with a p-value of 0.6, while the t-value for trading

volume was 18.20 with a p-value close to zero. Thus,

the unit-root hypothesis cannot be rejected at any

reasonable significance level. But the parameter

estimates were found not significantly different from

zero at the 5% level. In summary, for the time period

considered, the log series of the index contains a unit

4.3. Testing for Autocorrelation

A necessary condition for testing for a

contemporaneous relationship between returns and

trading volume based on a Vector Autoregressive

(VAR) model, it was necessary to first necessary to

test for the presence of autocorrelation. The Durbin-

Watson test is a widely used method of testing for

autocorrelation. The first-order Durbin-Watson test in

Table 3 is highly significant with p < .0001. Once it

was determine that autocorrelation correction was

needed, stepwise autoregression was utilised to

determine the number of lags required. This resulted

in the second-order lags as implemented in the next

stages.

Table 3. Testing for Autocorrelation using the Durbin-Watson Test

The AUTOREG Procedure: Ordinary Least Squares Estimates

SSE 34474.4496 DFE 5957

MSE 5.78722 Root MSE 2.40566

SBC 27388.2215 AIC 27374.8362

MAE 1.81181152 AICC 27374.8382

MAPE 26.9036754 Regress R-Square 0.0000

Total R-Square 0.0000

Durbin-Watson Statistics

Order DW Pr < DW Pr > DW

1 0.4686 <.0001 1.0000

2 0.5370 <.0001 1.0000

3 0.5327 <.0001 1.0000

4 0.5293 <.0001 1.0000

Variable Approx DF Variable

Estimate

Standard

Error t Value Pr > |t| Label

Intercept 1 10.9817 0.0312 352 <.0001

PRICE 1 1.1102 2.6314 0.42 0.6731 PRICE

NOTE: Pr<DW is the p-value for testing positive autocorrelation, and Pr>DW is the p-value for testing negative

autocorrelation.

4.4. Testing for contemporaneous relationship

The next analysis involved testing whether trading

volume does have a significant impact on stock

returns movements on the JSE Securities Exchange.

Table 4 presents the contemporaneous relationship

between returns and trading volume based on a

Vector Autoregressive (VAR) model. The F-statistics

and their corresponding level of significance are

indicated. The table shows the results for the test of

the null hypothesis that returns do not Granger-cause

volume and their F-statistics are significant at a 5 per

cent level for the FTSE/JSE index. The hypothesis is

accepted. This finding implies that past returns and

trading volume adds some significant predictive

power for future returns and trading volumes in the

JSE Securities Exchange. This suggests that trading

volumes are influenced by returns or price in the JSE

Securities Exchange. The tests revealed that there is a

significant correlation between monthly return and

trading volume.

Table 4. The AUTOREG Procedure: Dependent Variable – Trading Volume

Ordinary Least Squares Estimates

SSE 34474.4496 DFE 5957

MSE 5.78722 Root MSE 2.40566

SBC 27388.2215 AIC 27374.8362

MAE 1.81181152 AICC 27374.8382

MAPE 26.9036754 Regression R-Square 0.0000

Durbin-Watson 0.4686 Total R-Square 0.0000

Variable DF Estimate Standard-Error T Value Pr > |t| Label

Intercept 1 10.9817 0.0312 352.00 <.0001

PRICE 1 1.1102 2.6314 0.42 0.6731 PRICE

Estimates of Autocorrelations

Lag Covariance Correlation -1 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 1

0 5.7853 1.000000 |********************|

1 4.4209 0.764167 |*************** |

2 4.2167 0.728873 |*************** |

Preliminary MSE 2.1149

Estimates of Autoregressive Parameters

Lag Coefficient Standard Error t Value

1 -0.497987 0.012147 -41.00

2 -0.348328 0.012147 -28.68

Table 4 shows the results of Volume being

regressed on price with the errors assumed to follow a

second-order autoregressive process. The Yule-

Walker estimation method was used in conjunction

with the maximum likelihood method. The first part

of Table 4 shows the Ordinary Least Squares (OLS)

results followed by estimates of the autocorrelations

calculated from the OLS residuals. The

autocorrelations are also displayed graphically.

The Maximum Likelihood Estimates (MLE) are

then shown in Table 5, which shows the preliminary

Yule-Walker estimates used as starting values for the

calculation of the maximum likelihood estimates.

The diagnostic statistics and parameter estimates

in Table 5 have the same form as the OLS output

shown in Table 4, but the values shown are for the

autoregressive error model. The MSE for the

autoregressive model is 2.103 compared to an OLS

MSE value of 5.787 and hence a much improved

model which is closer to zero. The total R2 statistic

calculated from the autoregressive model residuals is

0.6367, reflecting the improved fit from the use of

past residuals to help predict the next value of trading

volume. The t-value of 88.17 is also significant.

The regression results in Table 5 indicate that

contemporaneous return explains a relatively large

portion of trading volume in the JSE Securities

Exchange FTSE/JSE index as evidenced by the high

R-square of 0.63. The Durbin-Watson statistic given

in Table 5 has a value of 2.1855, and, given that the

Durbin-Watson statistics has a range from 0 to 4 with

a midpoint of 2, the value obtained here confirms that

the model is good.

Table 5. The AUTOREG Procedure: Dependent Variable – Trading Volume

Maximum Likelihood Estimates

SSE 12524.1337 DFE 5955

MSE 2.10313 Root MSE 1.45022

SBC 21372.9088 AIC 21346.1382

MAE 1.07760286 AICC 21346.1449

MAPE 13.2054636 Regression R-Square 0.0001

Durbin-Watson 2.1855 Total R-Square 0.6367

Intercept 1 10.9707 0.1244 88.17 <.0001

PRICE 1 0.7638 1.3938 0.55 0.5837 PRICE

AR1 1 -0.4981 0.0121 -41.06 <.0001

AR2 1 -0.3511 0.0121 -28.92 <.0001

Autoregressive parameters assumed given

Intercept 1 10.9707 0.1244 88.17 <.0001

PRICE 1 0.7638 1.3938 0.55 0.5837 PRICE

The parameter estimates in Table 4 show the

MLE estimates of the regression coefficients and

includes two additional rows for the estimates of the

autoregressive parameters, labelled AR1 and AR2.

The estimated model is:

The signs of the autoregressive parameters

shown in the above equation for are the reverse of

the estimates shown in Table 5. The estimates of the

regression coefficients with the standard errors are

recalculated on the assumption that the autoregressive

parameter estimates are equal to the true values.

Trading volume on the other hand seems to explain a

relatively small portion of returns in the FTSE/JSE

index as evidenced by the low R-square of 0.008. This

indicates that the effect of stock returns on trading

volume is stronger than the effect of trading volumes

on stock returns.

5. Conclusion and recommendations

This article investigated the relationship between

stock returns and trading volume for the FTSE/JSE

stock index. Using daily data, price return was

regressed on trading volume and significant

relationship was found. The statistical evidence

indicated that there is a positive correlation between

trading volume and stock returns. In addition, it was

also found that stock returns tend to lead trading

volumes, but not vice-versa. This result indicates that

while South Africa is an emerging market, it exhibits

similar behavioural facets as other developed markets

like the United States as shown by the studies

highlighted earlier

The Autoregressive model was estimated for

testing the casual relationship between stock return

and trading volume variables. The result implies that

there is feedback prevailing in the JSE Securities

Exchange. Therefore, the evidence indicates a

stronger stock return causing volume than volume

causing returns. The findings suggest that there is a

positive association between return variance and

lagged trading volume for the JSE. The results of the

causality test show that the relationship between

trading volume and stock return is statistically

significant. While this result is consistent with

findings from earlier studies, it is recommended that

further studies are conducted on individual stock

behaviours so as to enhance a better understanding of

the JSE Securities Exchange.

References

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Corporate Governance, Agency Costs and Investment Appraisal: An Assessment

Baliira Kalyebara*, Abdullahi D. Ahmed**

Abstract

Undoubtedly, capital markets have an impact on investment appraisal decisions through interest rates (cost of capital) charged and debt covenants stipulated in debt contracts. However, the extent of influence of their interactions in shaping and determining a firm’s corporate governance policy, agency costs, investment decisions and firm value has been overlooked or not duly emphasised in the literature to date. This lack of interdisciplinary research in areas such as finance, accounting, capital markets and corporate governance may lead financial managers making wrong interpretation of the current empirical evidence. This may result into suboptimal decisions in capital budgeting decisions. There are various existing studies that have discussed the relation between corporate governance and one or two other business topics this paper is assessing. However, questions have persisted about the role capital markets’ interactions play in determining firm’s corporate governance, minimizing agency costs, long term investment decisions and firm value. The recent high profile global company collapses mainly due to poor corporate governance mechanisms have rekindled the interest in the role capital market interactions play in formulating firm’s corporate governance rules and policies and their impact on agency costs, investment appraisal decisions and firm value. This study intends to assess this issue and critically evaluates these related issues. The impact of multiple objectives on long-term investment decisions is also discussed. We find that capital market interactions have a significant impact in the way firms formulate their corporate governance, identify and control agency costs, optimize multiple objectives, make investment decisions and determine firm value. In a nutshell, there is a consensus among researchers that capital markets impact on capital investment decisions and firm value through interest rates, debt covenants that impact on managers’ self-interest behaviour, corporate governance policies and agency costs. Keywords: Corporate Governance; Capital Markets; Multiple Objectives, Investment Appraisal and Agency Costs JEL Classification: G29; G31; G32; M14 * School of Commerce and Law Central Queensland University, Rockhampton, Australia ** Corresponsing author, School of Commerce and Law, Central Queensland University, Rockhampton, Australia, Bruce Highway, Rockhampton QLD 4702 Australia Fax: +61749309700 Tel.: +61749232854 E-mail: A.ahmed@cqu.edu.au.

1. Introduction

The role capital markets’ interactions play in

influencing firm corporate governance mechanisms,

agency costs and investment appraisal decision

making is currently overlooked in the existing

literature. The current status quo may cause a

significant challenge to the financial managers in

interpreting the current literature. This study critically

examines the existing literature on the impact of

interdisciplinary interacts of capital markets,

corporate governance, agency costs and capital

budgeting decisions on firm value. (Shleifer & Vishny

1997) confirm that corporate governance policies

impact firm value. This assertion is supported in

(Ramly & Rashid 2010) that good corporate

governance mitigates managers’ self-interest

behaviours which in turn improves the firm’s quality

and flow of information, and firm value. Similarly,

(Ruiz-Porras & Lopez-Mateo 2011) and (Tian &

Twite 2011) conclude that capital market interactions

including interest rates (cost of debt) and debt

covenants impact corporate governance mechanisms,

agency costs, capital budgeting decisions and hence

firm value. The current literature recognizes that firms

have two main external sources of capital – equity and

debt (Whitehead 2009). The debt capital bears a

specified interest rate from day one that determines

the primary cost of debt. Thus the cost on debt is

known and factored in the calculation before

investment decisions are made.

Nevertheless, the impact on long term

investment decisions as a result of minimization of

agency costs and the inclusion of debt covenants is

not considered. Debt capital is mainly supplied by

capital markets including commercial banks and other

financial institutions such as insurance companies,

superannuation funds, etc. The company (the

borrower) and the financial institution (the lender)

enter into a contractual relationship that explicitly

specifies the conditions of the debt capital that include

the interest rate to be charged and other restrictive

debt covenants that have to be complied with during

the life of the debt. Through the interest charges and

specified debt covenants the capital markets influence

the firm’s corporate governance, managers’

behaviour, debt equity ratio, agency costs, capital

budgeting decisions and firm value. The capital

markets’ monitoring of firm performance improves

corporate governance, mitigates the managers’ self-

interest behaviours and reduces negative earnings

management inclination.

However in practice, the impact of various

capital markets’ interactions are not all incorporated

in the investment appraisal decision making

techniques such as net present value (NPV) or internal

rate of return (IRR). Therefore, making capital

budgeting decisions using the traditional capital

budgeting techniques of NPV without considering the

impact of capital market interactions ignores one of

the significant factors that influence investment

appraisal decisions and firm value. This oversight

provides financial managers with wrong information

on which they base their interpretation of the current

empirical financial evidence and more often leads to

suboptimal decisions in long term investment decision

making. Figure 1 illustrates the impact of capital

markets interactions through debt capital, corporate

governance, agency costs, investment decision

making and the firm value.

Figure 1. Impact of debt capital on firm value and ownership structure

Capital markets

Debt Capital

Interest Rate

Cost of Debt

Debt Covenants

Positive and/or Negative

Firm’s Corporate Governance

Debt/equity Ratio

used as proxy for

(Agency costs)

Investment Appraisal Decisions

Firm value

Mitigate Financial Managers’

Self-interest Behaviours

EPS Optimal level

of ownership

Value-maximizing

governance structures

2. Objectives and Motivation of the Study

The purpose of this study is to analyse the impact of

interdisciplinary interactions and in particular the

capital markets interactions on investment appraisal

decisions. The study addresses the role capital

markets play in determining capital budgeting

decisions through determining the level of interest

rates and devising debt covenants (positive and

negative). It also discusses the impact of debt

covenants on formulating the firm’s corporate

governance policy about capital budgeting decision

making. This study intends to add knowledge to the

existing theoretical and practical issues in the

literature about the impact of capital markets’

interactions on long-term investment decisions and

help financial managers make optimal investment

decisions that maximize firm value.

The conflict of interest that emanates from

separation of ownership and control and subsequent

agency problems, calls for efficient firm’s corporate

governance to enhance investors’ and shareholders’

confidence that management is making optimum

investment decisions that maximize firm value (Watts

& Zimmerman 1990). The capital markets’ covenants

and interest rates significantly shape and contribute

towards achieving efficient firm’s corporate

governance that impacts the firm’s level of debt

equity ratio (Debt equity ratio is calculated by

dividing firm’s net borrowings by shareholders’

funds) which in turn influences the firm’s cost of

capital and long-term investment decisions. The ratio

shows how much of debt capital is used to finance the

operations and long term investments of the firm

compared to equity capital. The higher the percentage

the higher the cost of capital and the more risky the

firm is able to meet its debt commitments. There are

other financial metrics that impact on the debt equity

ratio such as liquidity ratios and the level of net cash

flow. General business consensus believes that debt

equity ratio of 50% and below is regarded as

acceptable considering the nature of business. A firm

with debt equity ratio above 100% is regarded highly

geared and not financially healthy to the firm.

However, some companies in some industries have

astronomical high debt equity ratio as shown in Table

1. The magnitude of debt equity ratios of corporations

listed on the Australian Stock Exchange (ASX)

highlights how much capital markets are prepared to

lend to some companies and hence how much

influence they have on firm’s investment decisions

and firm value. For example, the debt equity ratios of

listed companies in Australian range between 0.001%

and 26,193.9% (http://asxiq.com/index.php. Accessed

14/07/2012). Table 1 below lists the top twenty

companies listed on ASX that have the highest debt

equity ratios.

Table 1. Debt Equity Ratios of Top Ten Companies Listed on ASX

Name Debt Equity Ratios

1 Becton Property Group 26193.9%

2 Redcape Property Group 10683.5%

3 Montec International Limited 7036.9%

4 Redbank Energy Limited 3603.4%

5 RGH Limited 28324.7%

6 World Reach Limited 2334.9%

7 Pearl Healthcare Limited 1630.9%

8 AACL Holdings Limited 1256.0%

9 TZ Limited 1216.9%

10 FirstFolio Limited 1152.0%

11 Central West Gold NL 1105.1%

12 Metroland Australia Limited 929.99%

13 Homeloans Limited 847.2%

14 Oldfields Holdings Limited 819.7%

15 Namoi Cotton Co-operative Ltd 692.7%

16 Prince Hill Wines Limited 690.1%

17 Energy and Minerals Australia Limited 506.8%

18 Farmworks Australia Limited 498.9%

19 Wide Bay Australia Ltd 464.4%

20 FSA Group Limited 441.0%

Source: http://asxiq.com/index.php. Accessed 14/07/2012.

It is clearly important to note from Table 1 that

if capital markets are willing to finance the operations

of some firms to the extent shown in the Table 1 then

they are entitled to safeguard their assets through

covenants and interest rates that impact on the firm’s

corporate governance and long-term investment

decisions. Likewise it is in the interests of the

borrowers (firms) if they require maintaining a good

financial relationship with their lenders (capital

markets) then they is required to comply with the

terms and conditions included in the debt agreement

and meet their debt commitments promptly. Non-

compliance of the terms and conditions in the

agreement jeopardises their chances of securing debt

capital from capital markets in the future. The

compliance of the terms and conditions of the debt

agreements clearly impact on the firm’s operations,

corporate governance, the investment decisions and

hence firm value. Therefore, it is necessary to

consider the impact of capital markets interactions.

This study uses debt equity ratio as a proxy for good

corporate governance when making long-term

investment decisions. The impact of using debt equity

ratio on firm value has not been comprehensively

emphasised in the literature.

3. Capital markets

Companies have two main sources of capital, debt and

equity. Debt is obtained from capital markets and

equity is from shareholders. When companies apply

for debt from capital markets, elements in both the

capital market and the borrowing firm such as market

conditions, interest rates, firm’s corporate

governance, operation interactions and accounting

practices impact on capital market’s decisions and

hence affect the investment appraisal decisions of the

borrowing firm. Before a loan application is

approved, it is common practice for capital markets to

consider and assess the firm’s corporate governance

when estimating the firm’s potential level of default

risk. The higher the estimated default risk, the higher

the interest rate charged by the financial institution,

which translates into higher cost of capital to the firm

(Chen, Chen & Wei 2011), (Schauten & Blom 2006);

(Piot & Missonier-Piera 2007). The higher cost of

capital leads to reduction in the net cash inflows,

which leads to reduced NPV and hence a reduction in

the firm’s value. One of the ways of assessing the

firm’s corporate governance is determining whether

the firm’s accounting practices conform to the

national and international accounting standards, since

the capital markets’ operations are internationalised to

allow global competition (Wolk, Dodd & Rozycki

2008).

Capital markets are described as financial

institutions that lend the customers’ savings (savers)

that include corporations, households and

governments to the borrowers (corporations,

households and governments) for long-term

investments at a higher interest rates than those paid

to the savers. The long-term investments that are

financed by capital markets include investing in

equity, corporate debt and government debt (Viney

2011). They are supported by the foreign exchange

markets and derivatives markets. They also act as

conduits between savers and borrowers that comprise

of both domestic and international markets. The

participants in the capital markets encompass stock

exchanges, stock brokers, stock dealers, fund

managers, interest rates speculators, interest rates

hedgers, intermediary investors and service providers

(Viney 2011). They are significantly integrated with

banks, insurance companies, credit unions and other

financial institutions. In a nutshell, their main

contribution to the economy is to:

channel capital to the most efficient long-term

investments that yield the highest economic

returns;

provide access to depth and liquidity of the

market which allows investors to share and

manage risk efficiently; and

collect and disseminate significant financial

information that allows investors make informed

decisions in long-term investments.

Capital markets charge interest rates on the debts

lent out. The level of interest rates charged depends

on the level of default risk the firm borrowing is

estimated to have. Also the fact that debt capital is

invested in long-term risky projects, it is a normal

practice for the capital markets to insert debt

covenants in the terms and conditions section of the

debt contracts to safeguard their assets and mitigate

agency costs. Debt conditions serve the interests of

both the lender and the borrower. The nature of debt

covenants may be both positive and negative. For

example positive covenants may require the borrower

to maintain enough liquid assets to cover the debt

commitments whereas the negative one also referred

to as restrictive, may prevent certain activities such as

disposal of an asset unless agreed to by the lender.

According to (Alcock, Finn & Tan 2012) and

(Frankel & Litov 2007) capital debt is always

provided with restrictive covenants to mitigate debt

equity agency costs. From the definitions and

descriptions of corporate governance and capital

markets, it is evident that firms’ corporate governance

and capital markets through debt covenants aim at

maximizing firm value. There is evidence in the

literature that the integration of capital markets

principles and corporate governance principles is one

of the significant factors contributes to firm value

maximization. Debt covenants as determined by

capital markets lead to improved corporate

governance and better capital budgeting decision

making and firm value. However, the impact of the

integration of capital markets and corporate

governance on long-term investment decisions and

firm value has not been widely and emphatically

discussed in the literature

4. Corporate governance

Banks (2004, p. 3) defines corporate governance as

‘the structure and function of a corporation in relation

to its stakeholders generally, and its shareholders

specifically …’. In Australia, the (ASX 2007) defines

corporate governance as the system used by

management to direct and manage companies to

maximise the firm value. The Economist Intelligence

Unit, (2002, p.5) defines it as:

Corporate governance is the system by which

business corporations are directed and

controlled. The corporate governance structure

specifies the distribution of rights and

responsibilities among different participants in

the corporation, such as the board, managers,

shareholders and other stakeholders, and spells

out the rules and procedures for making

decisions on corporate affairs. By so doing, it

also provides the structure through which the

company objectives are set, and the means of

attaining those objectives and monitoring

performance.

The three definitions are similar. The ultimate

aim is maximizing firm value. Two of the three

definitions above acknowledge that the interests of

non-financial stakeholders are as important as the

interests of financial shareholders. However, the

emphasis is on financial shareholders’ interests. In

April 2006, the UN launched the Principles for

Responsible Investment (PRI) at the New York Stock

Exchange. They were launched and endorsed by the

UN Secretary-General, Ban Ki-moon. These

Principles help in guiding financial managers to make

optimal strategic investment decisions to maximize

multiple objectives including shareholder wealth thus

in turn firm value. The Principles have become a

global benchmark for responsible investing. A large

number of international institutional investors have

become members of PRI by signing and complying

with them when making long term investment

decisions. The market value of the economy

controlled by the signatories of these Principles in the

first year of their establishment was said to have been

greater than US$8 trillion (UNEP, Finance &

Initiative 2006). As at 25/04/2012 there are a total of

1036 signatories to PRI worldwide including 249

asset owners, 611 investment managers and 176

professional service partners (PRI 2006)1. The signing

of the Principles by high profile international

organisations demonstrates support from the top-level

decision makers for sustainable investment. The

application of the Principles leads to better long-term

financial returns and a closer relationship between

investors, management and the community. These

Principles also have the potential of minimising

agency costs too. The extract of the message delivered

by the UN Secretary-General when launching the

Principles said among other things:

“By incorporating environmental, social and

governance criteria into their investment

decision-making and ownership practices, the

signatories to the Principles are directly

influencing companies to improve performance

1 See http://www.unpri.org/signatories., accessed 05/05/2012.

in these areas (see, UNEP Finance & Initiative

2006, p. 1). This, in turn, is contributing to our

efforts to promote good corporate citizenship

and to build a more stable, sustainable and

inclusive global economy”.2

The signatories commit to adopt and implement

the six Principles contained in the UN document.

Broadly, the members commit to:

(1) incorporate environmental, social and corporate

governance (ESG) issues into analysis and

decision-making processes;

(2) be active owners and incorporate ESG issues

into their ownership policies and practices;

(3) seek appropriate disclosure on ESG issues by the

entities in which they invest;

(4) promote acceptance and implementation of the

Principles within the investment industry;

(5) work together to enhance their effectiveness in

implementing the Principles; and

(6) each report on their activities and progress

towards implementing the Principles.

A decade before the UN Principles were

launched in 1996, the Australian Stock Exchange

(ASX) introduced a requirement that all listed

companies should include a statement of corporate

governance in their annual reports under the Listing

Rule 4.10.3. The ASX Corporate Governance Council

lists ten essential corporate governance principles,

which include among others that the board should add

value to the firm, recognise and manage risk, and

encourage enhanced performance (Shailer 2004).

These principles are broad allowing firms to pick and

choose sections of the Listing Rule that send positive

messages or good news to the stakeholders and reflect

the company in a good light to the public. However,

the intention of introducing the inclusion of corporate

government statement in the annual reports is good to

maximize firm value.

In the UK, investment management best

practices are contained in the Hermes Principles

Statement (Pitt-Watson 2002, pp. 6-11). The

statement contains ten principles. Principles 2 and 3

are directly related to this paper.

Principle 2 states that ‘Companies should have

appropriate measures and systems in place to

ensure that they know which activities and

competencies contribute most to maximizing

shareholder value’.

Principle 3 states that ‘Companies should ensure

all investment plans have been honestly and

critically tested in terms of their ability to deliver

long-term shareholder value’.3

The two principles above summarise the main

goal of most capital investment decisions in UK, be it

private or public investments. Also good corporate

2 See http://www.unpri.org/secretary-general-statement/index.php., accessed 05/05/2012. 3 See http://www.ecgi.org/codes/documents/ hermes_principles.pdf, accessed 05/05/2012.

governance helps to mitigate tunnelling activities4

(Gao & Kling 2008) or negative earnings

management. Tunnelling activities include excessive

executive compensation, dilutive share prices, asset

sales, personal loan guarantees and empire building.

These activities are common with investors in

emerging markets similar to South Asia countries or

developing economies where government and

regulatory controls may not be in place or not

advanced enough to stop the practice from occurring.

A similar theory to tunnelling is the entrenchment

management theory.5 Management entrenchment is

part and parcel of corporate governance. However, it

is necessary to distinguish between illegal (negative)

and positive management entrenchments. The bad

entrenchments such as empire building destroy firm

value whereas positive entrenchment may include

protecting against a hostile turnover that does not

harm the firm value (Lu, Reising & Stohs 2007).

Corporate governance has became a buzz phrase

in the modern economic after the collapse of high

profile companies in the 1990s, including Arthur

Andersen, Global Crossing, Enron, WorldCom in the

US, and HIH in Australia, etc. In the same period,

WorldCom defaulted on US$23 billion of debt – the

largest default in history (Banks 2004, p. 8). In 2002,

234 companies with US$178 billion worth of assets

filed for bankruptcy (Banks 2004, p. 390). In 2001,

257 public companies with US$258 billion in assets

also filed for bankruptcy in the US. After witnessing

the kind of losses and bankruptcies that occurred in

the late 1990s and early 2000s, stakeholders including

shareholders lost confidence and trust in financial

reports, directors’ statements and external auditors’

reports (Keasey, Thompson & Wright 1997). A loss

of trust and confidence in the companies’ official

documents impacts negatively on the reliability of

financial accounting numbers used as inputs in the

investment appraisal decision making. The loss of

trust and confidence in the company’s ability to invest

shareholders’ money efficiently prevents new

investors from buying shares in the company, existing

shareholders may divest and new debts are charged at

higher interest rates because of the higher investment

risk expected. All these factors increase the total cost

of running the company including cost of capital, thus

reducing the net operating income, net cash flow

hence reducing firm value. Surprisingly, from the

reviewed literature in capital budgeting (Dean 1951);

(Weingartner 1967); (Seitz & Ellison 1999); (Bierman

& Smidt 2007), there is evidence that the boards of

4 Tunnelling may be described as illegal business practices in which a majority shareholder or high-level company management directs company assets to themselves, see http://investopedia.com/terms/t/tunneling.asp., accessed 05/05/2012. 5 Managerial entrenchment refers to anti-takeover efforts that are motivated by managers’ self-interests in keeping their jobs rather than in the best interests of shareholders.

directors do not significantly pay special attention to

long-term investments. Their focus is on short term

performance. (Banks 2004) listed and discussed a

sample of 339 significant companies that had

governance problems ranging from improperly

recognising advertising revenues of US$190 million

in 2002. All these 339 companies in the US were

forced to restate their revenues and earnings in 2002.

This confirms that corporate governance has direct

link to the figures reflected in the financial statements.

It strengthens the ‘moral fibre of the firm’ through

emphasising:

greater leadership by example

return to basic value systems

building corporate governance framework for

redefining value creation

maximizing firm value.

Therefore, there is need for a study like this one

to analyse the impact of integrating capital markets

interactions, agency costs’ minimization and

corporate governance principles on capital budgeting

decision making decisions and firm value.

5. Investment appraisal

This paper uses the term capital budgeting

synonymously with investment decision making and

investment appraisal. Making capital budgeting

decisions is one of the most important strategic

policies a firm makes. There are different definitions

of capital budgeting but the main focus of all of them

is maximizing firm value. The following are some of

the definitions of capital budgeting or how it is

described. (Aggarwal 1993) asserts that capital

budgeting decisions are important, that individually

they are the most crucial decisions a firm makes

because of their long-term impacts on the firm’s

financial position. The effects of capital budgeting

decisions extend into the future to encompass the

whole organisation, and therefore the firm endures

them for a longer period of time, beyond the

consequences of operating expenditure. (Seitz &

Ellison 1999) briefly define capital budgeting as ‘the

process of selecting capital investments’. According

to (Agarwal & Taffler 2008) capital budgeting

decisions possess the distinguishing characteristics of

exchange of funds for future benefits, investment of

funds in long- term activities and the occurrence of

future benefits over a series of years. In a nutshell,

capital budgeting process is concerned with the

allocation of scarce financial resources to most

efficiently managed long-term activities in the hope

that the aggregate future benefits will exceed the

initial investment with the main goal of maximizing

firm value.

The main purpose of preparing a formal capital

budgeting process is to be able to identify those

investments that have the best chances of generating a

rate of return that exceeds the rate of cost of capital.

Heavy operating costs that exceed cash in lows for a

long time may render an organisation unsustainable.

Again, the fact that the firm needs to raise and commit

‘large sums of money’ and invest it in long-term

capital projects, makes capital budgeting decisions

one of the most important strategic decisions,

requiring careful planning and implementation

(Brealey, Myers & Allen 2011). Therefore, capital

budgeting process is one of the crucial strategic

company policies in the life of the firm.

Unequivocally, it is correct to say that a company’s

future direction, survival and the pace of future

growth start with capital budgeting decisions. There

are not many companies that grow without making

long-term investments of any kind. Hence, capital

budgeting is the most critical decision of any

organisation that plans to grow, efficiently compete

and thrive for a long time. Sub-optimal capital

budgeting decisions don’t maximize firm value in the

long run. The value of listed companies is often

measured in term of share prices or market

capitalisation. The rate of return on capital

investments can also be measured using extra net cash

inflow that is discounted to present value using

appropriate determined discount rate. The cash flows

are the most important liquid resources for any

business because other resources can be bought if the

cash inflows exceed cash outflows. Share prices

quoted on stock exchanges are next to cash flows in

terms of liquidity because they can be converted into

cash flows quickly. It is acknowledged that viable

capital investments generate net cash flows in excess

of its initial cash flow to increase the overall value of

the organisation, in other words, a viable investment

should have a positive NPV or the NPV should be

greater than zero so as to add to firm value.

The following are some of the reasons that

support the assertion that capital budgeting is

one of the crucial policies a firm makes.

Long-term implications: Capital budgeting

decisions have an impact on the firm as a whole

for a long time span. They affect the firm’s

future capital structure, cash flows and growth.

A wrong decision may damage the firm’s long-

term growth and survival. However, if a firm

does not invest in log-term projects its

competitiveness may be weakened and its goal

of maximizing firm value may not be achieved.

Therefore, capital budgeting decisions determine

the future destiny of a firm.

Large amounts of money involved: Capital

budgeting decisions require significant amounts

of money as initial capital outlay. This factor

emphasizes the need for prudence, expertise in

capital budgeting process and well-thought

analysis and decisions because a wrong decision

may not only result in losses in that selected

project but also negatively impact on

opportunity costs that are available that could

not be undertaken at the time.

Irreversible decisions: Capital budgeting

decisions are often irreversible because they are

designed and tailored to suit a particular project

and involve investing huge amounts of money in

long-term projects that are directly related to that

particular firm. These projects are not easily

marketable or saleable because they are not

suitable for other available projects. The

purchase of unwanted long-term capital assets

results in wrong capital allocation and heavy

operating costs to the firm (Aggarwal 1993). The

only alternative available to redress wrong

capital purchases is to write-off the value of the

capital asset and to make a heavy capital loss.

Risk and uncertainty: Capital budgeting process

involves estimating future cash flows and future

rate of cost of capital (discount rate) for the

whole life of the project. The future is uncertain

and full of risks. The longer the period of the

project, the higher the risk and the higher the

uncertainty may be. All or some of the estimated

future cash flows and cost of capital may not

come to be correct. This factor suggests that

capital budgeting decisions may not be accurate

and reliable.

Difficult to make: Capital budgeting decision

making is a difficult and complicated

management exercise. It requires huge amounts

of money, expertise in the area and it requires a

lot of time to implement. Also there are not

many firms around that can afford the costs

involved in the exercise. The process may

require a cost benefit analysis before a capital

budgeting exercise is undertaken.

Optimal decisions in capital budgeting optimise

a firm’s main objective of maximizing the firm value

and also help the firm to stay competitive as it grows

and expands. These decisions are some of the integral

parts of overall corporate financial management and

corporate governance. A company grows only when it

invests in capital projects, such as plant and

machinery, to generate future revenues that are worth

more than the initial cost (Ross et al. 2011) and

(Shapiro 2005).

6. Capital markets and corporate governance

The two main sources of capital for companies are

debt and equity. Debt is acquired from capital markets

and equity is from shareholders. Sustainable

developed economies have developed and efficient

capital markets ((Viney 2011); (Ross et al. 2011) and

(Hunt & Terry 2011). Capital markets charge interest

rates (cost of capital) and insert debt covenants in the

debt contracts based on the estimated level of default

risk of the borrower in order to safeguard their assets.

Companies assessed to have high default risk attract

high interest rates and vice versa. High interest rates

translate into higher cost of capital to the borrower

(Chen, Chen & Wei 2011); (Schauten & Blom 2006);

(Piot & Missonier-Piera 2007).

Capital market lending prerequisites include

channelling capital to the most efficient investments

that yield the highest economic returns. Therefore, the

level of cost of capital that is determined by the

capital markets and the type of covenants stipulated in

the debt agreements impact on the investment projects

the firm selects thus mitigating the managers’ self-

interest investment decisions. Collectively, these

conditions impact on the firm’s corporate governance,

agency costs, investment appraisal decisions and firm

value (Tian & Twite 2011).

Efficient capital markets play a vital role in the

growth and health of the economy through pooling

domestic and international savings and channelling

them towards the most productive investments (Viney

2011). Furthermore, they collect and disseminate

significant financial information to investors that is

used by investors to make informed investment

decisions. They also provide access to financial depth

and liquidity of the capital market that allows

investors to share and manage the risk efficiently. In

the modern economy, all governments regulate and

monitor the financial activities and operations of

financial institutions because of the important role

they play in influencing the direction of country’s

economy (Fabozzi, Modigliani & Jones 2009). The

level of importance the capital markets have on the

economy is reflected in the kind of regulations the

government enact to supervise the industry because

any operational and strategic economic failure in the

capital markets significantly impact negatively on the

country’s economy. Recently there have been capital

markets’ failures such as Lehman Brothers that

exacerbated the global financial crisis (GFC). This

has impacted on the economies of many countries like

Portugal, Ireland, Greece and Spain (PIGS) and its

impact is still spreading especially in the European

Union member states and the world over. The

Telegraph of 19/05/2012 reported that the credit

rating agency, the Moody’s had downgraded the long-

term debt and deposit ratings of sixteen Spanish

banks. This will negatively impact on the borrowing

and lending ability of these banks both in domestic

and international capital markets. . In turn it will

impact on investments in Spain, the Spanish economy

and further make the GFC worse.

In summary, the government through physical

and monetary policies and the capital markets impact

on the whole economy through influencing the

interest rates (cost of capital) charged on borrowings

by corporations, governments and households to

finance capital projects and consumable goods. This

helps to manage and control the level of inflation in a

desirable range.

7. Corporate governance and investment appraisal

The main goal for firms to formulate company

policies that direct and control (corporate governance)

its operational and strategic decisions is to maximize

firm value (Banks 2004). In order to maximize firm

value firms need to invest in long-term capital

projects. Similarly, the main goal for capital

budgeting decisions is to maximize firm value (Banks

2004). Good corporate governance conforms to the

structure and function of a corporation in relation to

its stakeholders generally, and its shareholders

specifically by aligning conflicting interests such as

those which may arise during investing decisions. It

instils monitoring and bonding measures, a sense of

ethics, encouraging transparency and mitigates

managers’ self-interest behaviours such as negative

earnings management. The benefits of good

governance may include accessing reliable flow of

funds, improved access to lower interest rate sources

of funds, better credit ratings, better reputation and

more business opportunities that lead to lower debt

funding costs, higher share price, lower agency costs

and improved firm value. The lower debt funding

costs impact on future cash flows and NPV because

the future cash flows are discounted at a lower

discount rate (cost of debt). The following studies

confirm this assertion that good corporate governance

can reduce inter and intra-firm agency problems

((Shleifer & Wolfenzon 2002) and is also associated

with higher firm value ((Gompers, Ishii & Metrick

2003). Figure 2 below shows the relationship between

capital budgeting and corporate governance.

Figure 2. Relationship between corporate governance and capital budgeting

Since the collapse of high profile companies in

the US such as Enron, WorldCom, etc., management

decisions both operational and strategic have come

under scrutiny. The common factor in these

companies is the astronomical executive remuneration

and compensations – agency costs. The executives,

Capital Budgeting Maximize: NPV

Maximize

firm value Corporate Governance Minimize: Agency Costs

Optimize: Debt equity ratio

whose compensation is based on the annual

performance (profits), will want to maximise annual

profits in the short term, so that they can receive large

amounts of bonuses quickly before their contracts

expire. Such executives will be reluctant to make

investment appraisal decisions which will bring in

profits after their contract period has expired. The

minimization of the short-term executive

compensation (agency costs) and introducing long-

term executive compensation such as share options

may persuade executives to invest in profitable long-

term capital projects. Therefore, there is a need to

integrate corporate governance principles, including

minimization of agency costs, to improve

management investment appraisal decisions. Table 2

shows selected and recent literature illustrating the

link between corporate governance and firm value.

Table 2. Summary of the literature on the link between corporate governance and firm value

Author(s) Sample, coverage & year Focus of the

study Key findings

Ammann, Oesch and

Schmid (2012)

Examine whether product market competition as a proxy of

corporate governance in 14 countries in European Union impact firm

value.

CG & firm value CG impacts firm

O’Connor (2012) Used 2784 firms of IFC Emerging Market Database (1980-2000) CG & firm value CG impacts firm

Gaeremynck and

Renders (2012)

The study examines the impact of principal-principal agency

problems on the quality and effectiveness of corporate governance

structures in listed companies from 14 European countries between

1999 and 2003.

Abbasi, Kalantari and

Abbasi (2012)

The research examined the effect of corporate governance on firm

value in food industry for companies listed on the Tehran Stock

Exchange (TSE) from 2002-2011.

Bayrakdaroglu, Ersoy

and Citak (2012)

The research examined the relationship between corporate

governance and value-based financial performance measures in

Turkey as an emerging market for 1998-2007.

CG & firm

performance

CG impacts firm

performance

Nini, Smith and Sufi

(2011)

Securities and Exchange Commission’s fillings of all US non-

financial firms (1996-2008) CG & firm value

CG impacts firm

Dharmapala and

Khanna (2011) Used a sequence of reforms in India (Clause 49) enacted in 2000. CG & firm value

CG impacts firm

Eberhart (2011)

Used Panel Data of 103 firms in Japan to examine the value

differences between Japanese firms selecting one of two legally

systems (1999-2007).

Chung and Zhang

(2011)

All stocks listed on the

NYSE, AMEX, and NASDAQ (2001-06).

institutional

ownership

CG influences share

prices and hence firm

Yang (2011) The research examined the impact of corporate governance on firm

value using panel data from 2004-2008.. CG & firm value

CG impacts firm

Al-Najjar (2010) All (86) non-financial Jordanian listed firms (1994 -03)

investment

decisions

CG impact

investment decisions

Chung, Elder & Kim

(2010)

Used 24 out of 51 corporate governance standards in Institutional

Shareholder Services (ISS) data from Best Practices User Guide and

Glossary (2003).

CG & stock

liquidity

CG impacts on stock

liquidity

Toledo, P (2010) Governance index constructed based on Spanish Code of Best

Practices

CG and firm

CG impacts on firm

Ammann, Oesch and

Schmid (2010)

6,663 firm-year observations from 22 developed economies over the

period from 2003 to 2007.

CG and firm

CG impacts on firm

Berthelot, Morris and

Morrill (2010)

The paper examined whether corporate governance rankings

published are reflected in the values investors accord to firms.

CG and firm

CG impacts on firm

Chong and Lopez-De-

Silanes (2006)

Used data available on external financing in Mexico to analyse the

link between CG and firm performance

CG & firm

performance

CG impacts on firm

performance

Black et al. (2006) 515 firms, Korea (2001) CG & firm value CG impacts on firm

Kumar (2005) 2,000 Indian firms (1994-00) CG & firm

financing

CG impact firm

financing

Drobetz, Schillhofer &

Zimmermann. (2004) 91 Germany firms (2002)

CG and share

performance

CG impacts on share

performance

Klapper and Love

(2004) 374 firms from 14 emerging economies (2000)

CG and firm

performance

CG impacts on

performance and firm

valuation

Gompers et al. (2003) 1,500 large firms (S&P) (1990) CG & equity

CG impacts on equity

prices and firm value

Lemmon and Lins

(2003) 800 non-financial firms, East Asian (1997) CG & firm value

CG impacts on firm

8. Capital markets, corporate governance, investment appraisal and firm value

The main goal for firms formulating corporate

governance policies and making long-term

investments is maximizing the firm value (Banks

2004). Capital budgeting principles aim at sound

corporate financial management to maximize the

firm value (Seitz & Ellison 1999). Both sets of

principles of corporate governance and capital

budgeting aim at improving the firm’s

performance and overall responsibility of the

organisation that lead to maximizing firm value

(Allen, Carletti & Marquez 2009). Thus capital

budgeting and corporate governance are

interrelated and complement each other.

However, the existence of agency problems

hinders the achievement of firm value

maximization. The agency problems are caused

by the separation of ownership and control

inherent in many firms. Sometimes management

who make investment appraisal decisions, do not

pursue the firm’s objective of maximizing its

value, but seek to maximize their own interests

causing the firm agency costs. Agency costs

arise because of the conflict of interest that

exists between the firm’s management and its

shareholders. There are steps and decisions the

organisation can make to force or incites

management to act in its interests; colloquially

these decisions are sometimes referred to as the

‘stick and carrot’. They can be in the form

punishment or incentives or both. These

decisions cost money, and they are some of the

examples of agency costs.

As discussed earlier in the paper capital markets

charge interest rates (cost of debt capital) and

insert debt covenants in the debt contracts to

safeguard their assets (money lent to the firm)

and mitigate debt agency costs. Corporations

with good corporate governance are said to have

lower default risk and as a result they are

charged lower interest rates thus lowering the

cost of debt capital. The level of interest rates

charged and the type of debt covenants inserted

in the debt agreement influence the extent of

achieving the objective of maximizing firm

value in the same way as corporate governance

and investment appraisal decisions discussed

earlier.

Agency costs are divided into three main

categories, bonding costs, monitoring costs and

residual loss ((Deegan 2009); (Jensen &

Meckling 1976). Monitoring costs include those

costs incurred to control the managers’

behaviour through the firm’s board of directors

by watching the decisions management make to

ensure that management decisions maximize

firm value. Examples of this type of costs may

include directors’ fees, financial statements

issuance costs, ensuring the agents do their jobs,

external audit fees, communicating with the

referees, establishing incentives for good

performance and employee stock options costs.

(Jensen & Meckling 1976) show that bonding

costs are incurred by the agent in an effort to

ensure the principal that the agent will not take

actions that will reduce firm value and that if

such actions are taken, the principal should be

compensated. Hence bonding costs tend to

reduce agency costs. Examples of bonding costs

may include annual membership payment to

maintain professional registration, offering

written guarantee and buying and dressing in

acceptable attire. (Jensen & Meckling 1976)

define residual loss as the reduction in the firm

value due to agency cost. It is caused by the

inherent self-interest behaviours of managers of

maximizing their own wealth.

The aggregate impact of agency costs on

organisations’ survival is financially

significantly high because any stakeholders in

control of the organisation through making

financial decisions (most times management

does), try to maximize their own wealth. The

high level of agency costs coupled with failure

to maximise stakeholder interests, including

shareholder wealth, has driven many companies

to bankruptcy in recent memory. For example,

the results in a study conducted by

(Schlingemann 2004) that analysed the value of

agency costs of overvalued equity in three days

surrounding the announcement of acquisitions in

the period of 1998-2001 show that the acquiring

firms lost a total of $240 billions compared to a

total loss of $4.2 billion in the all of the 1980s

period.

In 2001 in Australia, the collapse of Ansett

Airlines was caused by a combination of airline

industry deregulation, poor management in Air

New Zealand, high agency costs, lack of

managerial flexibility and the dissatisfaction of

its employees (Easdown & Wilms 2003). When

the industry was deregulated Ansett Airlines

could not compete effectively with the new low

cost entrants such as Virgin Blue Airlines and

Compass Airlines. The financial situation

worsened when it built an unprofitable $300

billion tourist resort on Hayman Island. This is a

type of significantly costly residual loss agency

cost – investing in a project that has a negative

NPV. The last straw of Ansett’s collapse was the

prolonged pilots’ strike (Easdown & Wilms

2003) that reflected poor management in

ignoring the interests of one of the stakeholders.

This paper has already established that capital

markets through interest rates and debt

covenants improve corporate governance and

mitigate agency costs. As a result of agency

costs being reduced, net cash flows improve and

hence firm value increases. Also the paper has

already discussed above that the main goal of

company policy formulation of corporate

governance is maximizing firm value. Since

capital markets impact on firm’s corporate

governance and in turn corporate governance

impacts on agency costs, capital budgeting

decisions and firm value then it is imperative

that a proxy of corporate governance in any form

such as debt equity ratio used in this study

should be incorporated investment appraisal

decisions. The objective of both corporate

governance and capital budgeting decisions is to

maximize firm value therefore both are

important to the performance and growth of a

company and form the basis of investors’

confidence and trust. Investors’ confidence and

trust in a company influence the investor

decisions – whether to invest or not to invest in

the company. Good corporate governance leads

to efficient financial management which boosts

investors’ expectation for better future

performance which in turn boosts new capital

investments (Ruiz-Porras & Lopez-Mateo 2011).

It ultimately results in investors investing more

in the organisation. New investments in projects

with positive NPV result into maximizing firm

value.

9. Conclusion and future research

According to most finance textbooks including

(Parrino et al. 2011; Gitman, Juchau & Flanagan

2011; and Ross et al. 2011) the discounted cash flow

(DCF) techniques are the most preferred methods

used in investment appraisal decision making in both

theory and practice. In theory NPV is the most

popular of the three DCF methods, but IRR is

preferred in practice. However, non-DCF techniques

are still used in some countries including Japan and

New Zealand. Some of the advantages of NPV

include the use of cash flow (being a measure of

wealth); considering time value of money (a dollar

today has more value than a dollar in the future) and

using a risk-adjusted discount rate. However, NPV as

a technique has limitations. They include:

difficulty in accurately forecasting the future

cash flows;

no universal or standard method of determining

the discount rate;

assuming the estimated discount rate will remain

the same for the life of the capital project;

ignoring the impact the different sizes of

amounts invested have on the NPV – a capital

project that has a high NPV may not necessarily

be the best if it requires larger sums of money

than other capital projects;

ignoring the impact of unequal lives of the

capital projects on the NPV – a capital project

that has a longer life may not necessarily be the

best if it requires longer life than other capital

projects;

inability to factor in financial, technological and

management flexibility and changes that are

common in a modern economy;

it is a one-off time investment metric –

economic conditions do not stay the same

throughout the life of capital projects;

it does not handle multi-criteria problems or

multiple objectives; and

it does not factor in agency costs’ impact.

Therefore, NPV has many restrictions. The focus

of this paper is about the last weakness above – the

failure to consider the impact (minimization) of

agency costs on capital budgeting decision making.

The paper has already discussed the significance of

the impact of the minimization of agency costs on

capital budgeting decision making. The investment

appraisal decisions can be improved by

complementing the use of NPV with the minimization

of agency costs which in turn should improve firm

value. Capital budgeting techniques, both naïve or

advanced, have the following common limitations,

they both:

consider each project as an individual

undertaking as opposed to considering the

project as part of the overall organisation

structure; and

fail to consider the relationship among the new

investments and the impact they may have on

the firm as a whole.

The assessment above has highlighted the

weakness that exists in theory and practice. The

review also found that the impact of capital markets’

interactions on investment appraisal decisions is

significant but is not considered in investment

appraisal decisions. Although the use of NPV has

been increasing, it is deficient in that it ignores the

impact of the capital markets, corporate governance,

financial and managerial flexibility, and agency costs

on investment appraisal decisions. It must be noted

that the studies reviewed in this paper were conducted

in different timeframes, in different countries, used

different samples, applied different valuation

techniques but all endeavoured to identify one capital

investment technique that maximizes firm value. The

NPV’s failure to consider the impact of agency costs,

financial and managerial flexibility, capital markets

interactions justifies a new study to develop a new

integrated approach in the form of multiple objective

linear programming (MOLP) model to value long-

term capital investments. This suggested new

approach is urgently needed for industries that have

inherently high information technology (IT) risk and

are dominantly IT-based such as the e-commerce

sector and the airline industry that use IT as major

source of company information. Significant amount of

research on capital markets, corporate governance,

agency costs, multiple objectives, investment

appraisal has been conducted but no one study has

integrated the impact of these disciplines to find their

influence on the investment appraisal decisions.

This proposed new integrated approach or

framework for investment appraisal decision-making

in the area of capital market interactions research in

finance will be a significant improvement over the

existing models in capital budgeting decisions. To our

knowledge, this approach will be the first of its kind

to integrate different elements of capital markets such

as interest rates, debt covenants, corporate

governance, agency costs and multiple objectives in

investment appraisal decisions. It will also provide a

plausible solution to many existing capital budgeting

problems. It can be applied to various real life capital

investment projects in general and be able to factor in

different individual firm characteristics.

Another area for future research in investment

appraisal could look at, is developing an inclusive

“Social Welfare Maximisation model” rather than an

exclusive “Shareholder Wealth Maximisation Model”.

In this modern economy that is regarded as one global

village, another significant variable that should be

considered to improve investment appraisal decisions

of multinational companies in modifying and

improving existing investment appraisal techniques is

the inclusion of political risk of various countries in

which the organizations operate.

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THE INFLUENCE OF CULTURAL VALUES ON THE BOARD OF DIRECTORS: LESSONS FROM FIVE CORPORATIONS

Elsa Satkunasingam*, Aaron Yong Sern Cherk**

Abstract

The Malaysian Code of Corporate Governance 2000 emphasises the monitoring role of the Board of Directors, especially that of independent directors. It has not however taken into account the cultural values in Malaysia which do not encourage differences of opinion or criticisms and has failed to provide sufficient safeguards for directors to exercise their role effectively. As a result, it is relatively easy for dominant Chairmen or CEOs especially in government-linked companies or CEO dominated companies to control the Board or senior management with very little opposition. This paper will discuss several incidences of financial mismanagement in companies caused by dominant directors with very little opposition from the rest of the board. It will highlight that the law has to take cultural values more seriously in order to equip the Board and especially independent directors with the ability to challenge dominant Board members. Keywords: Board of Directors, Cultural Values, Chairman/CEO Control * Senior Lecturer, School of Business, Monash University, (LL.B, LL.M, PhD) Tel.: 603- 55146391 E-mail: Elsa.Satkunasingam@monash.edu ** Bachelor of Business and Commerce (Honours) Monash University E-mail: aaronyong7337@gmail.com

Introduction

The Malaysian Code of Corporate Governance 2000

(MCCG) subscribes to the agency theory by

emphasising the monitoring role of the Board,

especially independent directors (INEDs). The Code

was enacted by the High Level Finance Committee on

Corporate Governance (Finance Committee) formed

by the Malaysian Government to establish a new

framework for corporate governance when it became

clear that poor governance had contributed to the

Asian Financial crisis (Kim, 1998). The Finance

Committee referred to the literature in British and

American jurisdictions which justified the increased

role played by an independent Board based upon the

agency theory (Clarke, 2007; Cox 2003) and designed

the MCCG along similar lines. The MCCG applies a

‘comply or explain’ best practice rule intended to

assist corporations in designing their own approach to

corporate governance (Clarke, 2007). When

transplanting the provisions of the MCCG which were

based on the United Kingdom Hampel Report and

Combined Code, the Finance Committee referred to

specific problems faced by boards such as dominance

of the Board by Chairmen who were founders of the

corporation, politically connected or members of

royalty. The problem is acute in the Malaysian capital

market where many corporations are either family or

government owned. When this is viewed in light of

cultural values in Malaysia, the consequence is that

the rest of the board including INEDs are rarely able

to withstand directors who are dominant personalities

or those with political connections. There is a need to

ensure that laws take this into account.

The nomination committee’s role in selecting INEDs

The Board of Directors of a corporation is required to

participate in the decision making process and

monitoring tasks (Cox, 2003) but INEDs have a

special role to monitor the Board and management

effectively as executive directors (EDs) are involved

with daily operational details that may tend to

undermine their monitoring responsibilities and non-

executive directors (NEDs) may represent interests of

certain and not all shareholders. The appointment of

INEDs has been one of the main responses to CEO

dominance and agency problems (Clarke, 2007) as a

CEO dominated board affects its efficiency

(Shivdasani and Yermack, (1999). They are also

expected to carry out unbiased oversight of

management and the Board to detect and prevent

mismanagement (Sale, 2006). In addition, they must

warrant that the Board and management carry out

their duties in the most efficient and effective manner

without negligence thus enhancing corporate

performance because they can proactively examine

corporate affairs (Fairfax, 2010). The extent to which

INEDs perform their duties well depends upon their

level of independence (Fama, 1980; Fama and Jensen,

1983), their degree of knowledge and skills (Hendry,

2005) and the authority given to them under capital

market regulations to carry out their role. In addition

to these important requirements cultural values in

society play a part in directors’ ability and willingness

to perform their role; a factor which is often ignored.

A plethora of codes recommend appointing more

INEDs on the board to safeguard corporate

responsibility, provide oversight of a corporation’s

financial reporting practices (Persons, 2006) and

protect shareholder interests (Hermalin and Weisbach,

2003). The expectation that transparency and

accountability will increase with independence of the

Board is so pervasive that INEDs have been placed in

important roles on Board Committees namely the

nomination, remuneration and audit committees. The

MCCG recommends that the role of INEDs is

increased through similar committees.

The key task of the nomination committee is to

ensure that the corporation recruits and retains the

best available executive and non-executive directors.

Powerful CEOs or Chairmen rather than shareholders,

often select directors (Van Ees and Postma, 2004)

which may result in a board that is more amenable

and compliant (Hermalin and Weisbach, 1988)

although this is not in line with the MCCG.

Shareholders may have the final vote in electing

directors to govern the corporation, but are often

cornered into either accepting the proposed candidates

or initiating a proxy challenge which is time

consuming and costly (Vafeas, 1999). It is therefore

important to have a nomination committee that is

independent from senior management and powerful

enough to make independent recommendations to

ensure that directors appointed to the board possess

the necessary skills and leadership to accomplish their

roles (Ruigrok, Peck, Tacheva, Greve and Hu, 2006)

and also to prevent board domination by individuals

or certain groups.

Although the role of INEDs on board

committees is emphasised in the MCCG, no other

code or legislation regulating the Malaysian capital

market emphasises their role. As the MCCG applies

on a ‘comply or explain’ basis, corporations often

have nominal committees without reporting whether

these committees are working in an effective manner.

There are no legal sanctions for failing to operate

effective board committees although audit committees

provide more comprehensive information in annual

reports due to Bursa Malaysia’s Listing

Requirements.

Threats to independence of INEDs

Conventional wisdom dictates that INEDs play a large

role in corporate governance but there is no common

definition of ‘independence’ in relation to directors in

Malaysia (Brudney, 1982). The most common term

that defines ‘independence’ is in Bursa Malaysia’s

Listing Requirements which defines independent

directors as persons without a business or family

relationship that will be deemed in conflict of interest

with the corporation (Borowski, 1982). From this

stance, INEDs must not be employees of the

corporation, outsiders who have a substantial

economic relationship with the corporation or family

ties with its management or other directors (Zattoni

and Cuomo, 2010). However it is difficult to find a

method of ensuring independence in substance over

At times INEDs serving on the Board longer

than usual will form opinions about other directors on

the Board and may even develop friendships which

may affect their independent judgement even if they

fulfil the legal definition of an independent director

(Adams and Ferreira, 2007; Hwang and Kim, 2009).

This creates structural bias which makes it difficult

for them to arrive at fair and objective assessments

(Elson and Gyves, 2003). “Structural bias" refers to

bias resulting from board members’ familiarity and

ongoing interactions with each other after joining the

board (Velasco, 2004). When working together as a

group, board members tend to form collective

alliances. Hence, it is noted that structural bias can

have a big effect on decision-making within the

boardroom, spurring board members to protect each

other from legal sanctions (Cox and Munsinger,

1985). Similarly, structural bias could undermine

directors’ ability to be critical towards their fellow

directors. Enron’s Board was an example of a

homogenous and highly cohesive group that had a

strong affiliation to each other especially as most of

the board members had served for extended terms

(O’Connor, 2003).

Another threat to independence is ‘group think’

which is where Boards technically comply with

Listing Requirements and the definition of

‘independence’ but recruit members from a close

circle of friends or supporters resulting in directors’

reluctance to raise questions and scrutinize

performance of the Board (Hwang and Kim, 2009).

‘Group think’ poses a major problem in the Malaysian

capital market (Lin, 2011). Bursa Malaysia’s

Corporate Governance Guide (BM CG Guide) warns

against mixing collegiality with blind conformity

while the Corporate Governance Blueprint 2011 (CG

Blueprint) issued by the Malaysian Securities

Commission highlighted it as a major problem with

the definition of ‘independence’. The CG Blueprint

2011 stressed on board diversity such as different

ethnicity, gender and nationality to prevent ‘group

think’.

Although structural bias and group think is

common to all directors regardless of whether they

are independent or executive directors, it is

particularly acute where INEDs are concerned as the

whole purpose underlying their appointment is to

bring fresh views without bias or influence of other

directors.

Cultural Values

The problems with structural bias and group think are

faced by corporations in all societies but are

compounded by cultural values in Malaysia. Power

distance collectivism and assertiveness are some of

the cultural values that may prevent directors from

carrying out their role effectively.

Power distance

Hofstede defines power distance as ‘… the extent to

which the less powerful members of institutions and

organisations within a country expect and accept that

power is distributed unequally.’ (Hofstede, 2005; p46)

This refers to the interpersonal power of influence

between two people as perceived by the less powerful

(Hofstede, 2001; p83). If the powerful person’s power

can be exercised at his or her whim and the powerless

person cannot really resist, then power distance is said

to be high.

The level of power distance in a particular

society can be used to measure the authoritarianism

prevalent in that society. When a person is invested

with power, there is a tendency to identify with this

power and to increase the distance between himself or

herself and the people without this power. The greater

the power distance between the two, the more the

powerful person will try to increase it and the less the

powerless person will resist it. If the power distance

between the two people or groups was never great to

begin with, the person with less power will struggle

more to reduce the distance (Mulder, 1977).

Many relationships are divided into the more

powerful and less powerful. Those who have power

are entitled to privileges and use their power to

accumulate more wealth and in turn more power

while the less powerful are not used to enforcing their

rights. The social aspect of power distance reveals

that power and inequality in society is accepted as the

norm in societies with high power distance and the

type of power exercised is coercive power and power

based upon the power-holder’s charisma. The

powerless are deferent towards the powerful and this

is inculcated into society (Hofstede, 2001; pp100 –

113). Power distance can also be described as the way

in which people within a particular culture deal with

inequalities.

Cultures where power is exercised through

coercion and to pursue personal goals have high

power distance. McClelland referred to two ways in

which power can be exercised. The first is where

power is personalised to obtain dominance and pursue

personal goals. The second is where it is used to

further the goals of groups (McClelland, 1970). In

cultures where power distance is high there is little

resistance to power that is personalised. It is up to the

powerful in those cultures whether they wish to

exercise their power to further the goals of the group.

In societies with low power distance practices, the

powerful are expected not to exercise their power

arbitrarily to promote their own ends (Hofstede, 2005;

Hofstede’s Power Distance Index Values for 53

Countries and Three Regions (known as the PDI

index) has an average score of 57. Malaysia had a

score of 104 which shows a high level of power

distance. However the Global Leadership and

Organisational Behaviour and Effectiveness Research

Programme (GLOBE) which was conducted recently

shows that Malaysia‘s score for power distance was

5.17 which was also the average score. This shows

that power distance exists in Malaysian society albeit

not at very high levels.

The Finance Committee commented in the

prelude to the MCCG that there was a tendency for

Boards to be dominated by powerful Chairpersons

due to their social status, political links or because

they were the founders of the corporation. The MCCG

recommended separation of the role of Chairman and

CEO but did not prevent the Chairman or CEO from

becoming a member of important board committees,

for example the audit committee although it

recommended that INEDs should form the majority of

the audit committee. This is not ideal in a society

where there is deference to well-connected or

dominant personalities which could result in board

committees that are complicit with the CEO or

Chairman’s directives even if it transgresses good

governance. In other words the MCCG did not do

enough to prevent dominant Chairmen or directors

from being in a position to manipulate the Board.

Collectivism

In-group collectivism which refers to great

loyalty to family members and in-groups is

pronounced in Malaysia which obtained a score of

5.51 which was above the average score of 5.13 in

GLOBE’s study (Gelfand, Bhawuk, Nishi and

Bechtold, 2004). In societies with high in-group

collectivism, a sense of belonging to an ‘in-group’ is

important and therefore conflicts are ‘swept under the

carpet’ and in most cases face-to-face confrontations

are rare (Triandis, 1988). Criticism is not deemed to

be constructive unlike in less collectivist societies.

The concept of maintaining ‘face’ is important and

criticism is often seen as a weapon used by the critic

to cause ‘loss of face’ to the person being criticized

(Ho, 1976). Those who have opinions that differ from

their group are expected not to air their views but to

remain loyal to their own group and treat those within

their own group better than those outside the group

(Hofstede, 2001; p227).

Triandis states that the culture of a society

influences how people within that culture view their

‘self’. If a culture is collectivist then it influences

people to view the public and collective self more

than their private self which means that they are more

concerned with how others perceive them (Triandis,

1990). In Asian cultures, where people are

interdependent there is a greater tendency among

people to perceive themselves in light of their public

and collective self (Triandis, 1989). People in

collectivist cultures behave according to norms and

interests of in-groups and value in-group goals

(Hofstede, 2005). They are interdependent because of

their definition of ‘self’ and will accept a high level of

demands from their in-groups. Social relations are

more enduring and occur in large groups. They also

value in-group goals and often place these goals over

their personal goals. For example, if family members

are seen as in-groups, the goals of these members will

take precedence over the individual’s goals. Their

sense of duty guides them towards observing social

norms and they are less concerned with personal

attitudes and values (Triandis, Leung, Villareal and

Clark, 1985). For these reasons directors in Malaysian

companies may face difficulties in presenting views

that differ from the majority especially when they

differ with the Chairman or CEO.

Assertiveness

The level of assertiveness in a society reflects

willingness of individuals to assert their views and to

speak up about issues that they are concerned about.

Cultures with low levels of assertiveness generally

view assertiveness as socially unacceptable and value

modesty. These cultures emphasise ‘face-saving’ and

indirect speech when dissenting with others and also

emphasise tradition, seniority and experience. In such

cultures, a person’s status is important and respect is

accorded to those with high status.

Trompenaars and Hampden-Turner studied

various societies’ adaptability to their surroundings

and found that societies have two orientations towards

nature which determines their level of assertiveness.

They either believe that they can control and

subjugate their surrounding environment or they have

to maintain harmony with it and sometimes subjugate

themselves to it (Trompenaars and Hampden Turner,

1997). Societies in the former category are ‘inner

directed’ or internal because they look within

themselves to take charge and actively control their

environment (Schein, 1992). Control is often exerted

through science. Societies in the latter category are

‘outer-directed’ or external as they believe in a

supernatural being that controls nature.

Trompenaars’ and Hampden-Turner’s studies

reveal that most Western societies fall into the former

group and Asian societies fall into the latter group. A

society’s cultural orientation towards nature affects

the manner in which that society conducts itself on a

day-to-day basis. Where a society believes that it has

to maintain harmony and subjugate itself to nature, it

will try to assert itself in a manner that is not

aggressive. Societies that believe that they can control

nature by obtaining knowledge about the laws of the

universe and using it to control their surroundings are

assertive to the point of being aggressive. Such

societies thrive on competition. The focus is on ‘self’

and conflict and resistance are seen as part of

controlling ones’ destiny. Their research reveals that

Western societies are more assertive while Asian

societies believe that maintaining peace and

compromising in order to maintain peace is a sensible

way to approach life, as there is no point in fighting

forces over which one has no control. However as

societies become developed, they do not subscribe to

the concept that they should subjugate themselves to

nature but seek to control it instead and in the process

become more assertive (Den Hartog, 2004).

GLOBE’s study indicated that Malaysia’s level of

assertiveness is 3.87 and is below the average global

level of 4.14 which reflects that submissiveness is

strong cultural trait.

The levels of power distance, collectivism and

assertiveness in Malaysia poses a challenge to the

board as a whole and the independence of INEDs as it

supports group think and structural bias although

independent directors are meant to be free of such

influence. Directors who are assertive and refuse to

acknowledge the status or power of the Chairman or

CEO may not be re-elected on the grounds that they

are not team-players. In a similar manner, low levels

of assertiveness in Malaysia means that individual

directors may be reluctant to assert their role as

monitors of the corporation especially in government-

linked or family owned corporations. These cultural

values could hamper the role of directors even in non

family or government owned Malaysian corporations

(Fontaine and Richardson, 2005).

Cultural Values and Compliant Boards: Lessons from Five Corporations

In recent years there have been instances of corporate

mismanagement due in part to poor board oversight.

The following discussion will emphasise the boards’

in particular INEDs’ failure to highlight financial

mismanagement although there was evidence pointing

to its existence. The mismanagement was due to a

variety of reasons which the board may not have been

able to prevent. The discussion will only highlight the

contribution of high power distance, in-group

collectivism and lack of assertiveness in government

linked and non-government linked companies which

resulted in compliant boards.

Government linked companies refers to

companies which have government investment

agencies as substantial shareholders. This occurred in

the 1980s when state enterprises were privatised as

part of an exercise undertaken by former Prime

Minister Mahathir Mohamed, to create Malay

capitalists. Malay individuals identified by the

government were given management and control over

privatised state enterprises as a wealth creation

exercise. The result was that GLCs approximated

almost 40% of market capitalization and a class of

Malay capitalists who had close ties with politicians

was created (Tan 2008: 56-57, Gomez and Jomo

1999: 81-87). Family-owned companies also

comprised a considerable approximation of the capital

market in common with other Asian capital markets

(Lim, 1981; p113). In light of the ownership structure

of many corporations in Malaysia, there is a greater

likelihood of the existence of structural bias and

group think. A study of the top 20 corporations in

2010 in Malaysia according to market capitalization

excluding banks and financial institutions revealed

that many directors including independent directors

had served on the board of the same corporation for

an average of 19 years (Yong, 2011). The annual

reports of GLCs in 2010 also revealed that a large

section of the board in these corporations comprised

male Malay directors whereas ethnic Chinese family-

owned corporations had boards comprising mostly

male Chinese directors.

There are many instances of GLC boards that

were not assertive enough to withstand powerful

CEOs especially if they were aligned to politicians.

Proton, Malaysia’s national car-maker was the brain

child of former Prime Minister Mahathir Mohamed

who continued as Proton’s advisor even after his

tenure as prime minister ended in 2003. In 2005 the

CEO of Proton who was widely regarded as Dr

Mahathir’s appointee made a decision to acquire MV

Agusta a motorcycle manufacturer for RM 370

million in order to use Agusta’s technology (K

Hepworth, 2004). Proton spent approximately RM500

million to start the project before deciding a year later

to sell MV Agusta for RM 4.48 (1 Euro) to Italy’s

Gevi SpA on the grounds that Agusta was on the

verge of declaring bankruptcy which would expose

Proton to a debt of RM256 million (Moses, 2006).

The Board of Proton stated that they were unaware

that Agusta was in debt when they purchased it or that

a cash advance was made without controlling rights

although Proton owned more than 50% shares in

Agusta. They also claimed that they were misled into

believing that the cash advance was working capital

meant to be used to manufacture motorcycles

although it was used to settle Agusta’s debts. Dr

Mahathir argued that the main shareholder of Proton,

Khazanah Nasional, a government investment agency

had agreed to the purchase of Agusta and it had been

discussed by the Board. However one of the former

Board members stated that the decision was sent by

the CEO ‘straight to the top’ referring to the

government, bypassing the Board (Abdullah, 2006)

Sime Darby (Sime) is another example of a

government linked corporation where the dominant

shareholder, Permodalan Nasional Berhad, controlled

the selection of executive directors including the

CEO. In 2010 Sime disclosed losses incurred due to

cost overruns from the Bakun Hydroelectric Project

and both of its Qatar Petroleum (QP) and Maersk Oil

Qatar (MOQ) projects which amounted to almost RM

2 billion. Sime’s internal auditor issued a report in

2008 on the losses incurred by the oil and gas

segment which was brought to the attention of the

audit committee but the losses were deemed

immaterial after the committee requested an

explanation from the CEO. No further investigations

were conducted although its external auditor delayed

signing off on the accounts. Sime also denied reports

of cost overruns of RM800 million in 2009 even

though its internal auditor issued another report

voicing grave concerns over losses in the oil and gas

segment. In 2010 its external auditor recommended to

Sime’s Chairman, a former deputy Prime Minister of

Malaysia that it was necessary to form a working

group to investigate the extent of losses. It was

discovered that although the Board was aware of the

situation, they relied on Sime’s CEO’s explanation

regarding the delays in the project and the cost

overruns (Ng, 2010).

Malaysia Airlines (MAS) another government-

linked company suffered losses amounting to RM 8

billion when it was under the control of its executive

chairman Tajuddin Ramli who was appointed by the

government. He obtained controlling interest over the

airline in 1994 by obtaining a personal loan from a

syndicate of local banks amounting to RM 1.79

billion to purchase MAS shares from the Central

Bank. During this period he relocated MAS cargo

operations in Europe from Amsterdam and Frankfurt

to Hahn through Advanced Cargo Logistics Centre, a

company that was connected to his family. This

proved to be inefficient as cargo had to be transported

by land to Frankfurt for customs clearance. As Hahn

was not equipped to deal with large aircraft, outgoing

cargo was transported on smaller aircraft resulting in

losses amounting to RM10 to 16 million per month

(Jayasankaran, 2010). In 1998 Tajuddin sold MAS

aircraft to MAS Capital a new company under his

control. MAS Capital leased back the aircraft to

MAS. The book value of the aircraft was RM 9.5

billion but due to the depreciation of the ringgit, its

actual value amounted to RM14 billion. MAS Capital

refinanced the aircraft and used the surplus to pay

Tajuddin a combination of cash and shares amounting

to RM 739 million for stake in two of his companies.

The sum paid to Tajuddin was used to clear part of his

personal debt. When objections were raised by

investors former Prime Minister Dr Mahathir stated

publicly that this was a normal process (Pereira,

1998). In 2001, the government re-nationalised MAS

by purchasing Tajuddin’s stake at the same price at

which he had bought it from the Central Bank

although the market value was less than half that

amount. Tajuddin failed to service his personal loan to

the syndicate of banks and the non-performing loan

was purchased by Pengurusan Danaharta which was

established by the government to deal with non-

performing loans during the Asian financial crisis.

Danaharta was awarded RM589 million by the High

Court and in his defence, Tajuddin claimed that he

was asked by Mahathir and former Finance Minister

Daim Zainuddin to purchase MAS in 1994 in order to

rescue the Central Bank which had suffered losses in

currency trading. In August 2011, the government

instructed Danaharta and all other government linked

companies to cease civil action against Tajuddin on

the grounds that they wanted to pursue an out of court

settlement (Ng, 2011). The major decisions in MAS

appear to have been made by the Chairman, Tajuddin

and the government with little reference to the Board.

The failure to question powerful CEOs or

Chairmen is not peculiar to government linked

companies. In the last 5 years, there have been multi-

million ringgit losses in several Malaysian

corporations namely Linear, Kenmark and Transmile

due to fraud or mismanagement. These corporations

had several things in common namely the founders

remained on the Board either as CEO or Chairmen

and were also members of the audit committee.

The Executive Director of Linear who was also

its founder issued a public statement in 2009 that it

had been awarded RM1.66 billion contract by a

Seychelles-based corporation, Global Investment

Group Inc (GIG) to build a district cooling system for

a project known as the “King Dome” project in

Malaysia. The value of the contract was said to be

worth US$5 billion. Linear did not have the capacity

to carry out a project of such magnitude but the Board

did not question the announcement by the executive

director. It was subsequently discovered by the

special auditor appointed to undertake an independent

probe into Linear’s affairs that its financial statements

from 1999 to 2008 were overstated as Linear’s

announcements of sales of solar energy panels and

cooling tower parts to foreign corporations could not

be proven and there was also no proof of the King

Dome project. The Executive Director who had been

instrumental in the purported projects had transferred

RM36 million to Linear’s Prime Savings & Trust

accounts in Sweden without prior approval from the

Board purportedly as a guarantee for performance to

facilitate the King Dome project (Tee 2011). Linear is

now placed in the Bursa Malaysia’s PN17 list which

is for corporations facing liquidity problems. The

directors of Linear, including INEDs did not inquire

into the details of the project and did not form a risk

committee to assess if Linear was over-exposed when

undertaking the project although there were warnings

from analysts that there was a lack of transparency in

the manner in which the project was announced.

The failure of the audit committee to introduce

strong internal controls resulted in losses to Transmile

Group Berhad (Transmile) where the founder Gan

Boon Aun, remained a dominant player on the Board

even after Transmile was listed in 1997. Transmile

was an investment-corporation which had subsidiaries

involved in the provision of air transportation

services. In 2005, Transmile’s auditors were unable to

obtain the supporting documents from the

management to satisfy itself as to the fairness of the

trade receivables and related sales to several

corporations. Investigations revealed that there were

no documents to support payments of RM341 million

made for the purported purchase of property, plant

and equipment from Transmile. Furthermore, the

investigation revealed that CEN Worldwide Sdn Bhd

(CEN) which was owned by Gan’s nephew continued

to be given credit although it owed Transmile RM103

million in unpaid debts (Rahman and Salim, 2010;

p99). Khiuddin Mohammed an executive director of

CEN was also an executive director of Transmile and

member of its audit committee. Gan and Khiuddin

played a large role in Transmile’s business

transactions until the financial losses were uncovered.

Transmile’s losses amounted to RM530 million due to

overstatements and it was subsequently delisted from

Bursa. Khiuddin was recently convicted for his role in

Transmile’s fraudulent transactions (Nazlina, 2011).

Furthermore the Board including the other audit

committee members did not question Khiuddin’s role

on the Board of CEN and the transactions between

CEN and Transmile.

Kenmrk Industrial Co Ltd (Kenmark) is another

recent example of a corporation where a dominant

director who was also its founder was able to control

the Board and management. Kenmark was established

by James Hwang, a Taiwanese who together with two

other Taiwanese directors owned almost 50% of

shares in the corporation. In May 2010 letters of

demand amounting to over RM60 million were issued

to Kenmark as guarantor for loans obtained by its

wholly owned subsidiaries. Hwang, Kenmark’s

managing director together with the other executive

directors who were his relatives and friends were not

contactable for a week. The INEDs who did not know

of these demands were alerted only when it was

highlighted by the Press. They were unable to answer

questions posed by the regulators or the Press on

Kenmark’s status (Goh, 2010). Hwang later

engineered active trading of the shares due to

misleading statements in the Press and disappeared

once he had divested himself of most of his shares.

The INEDs admitted that Hwang held information

‘close to his chest’ and did not keep them informed

about Kenmark’s financial transactions. The INEDs

attended Board meetings dominated by Hwang and

his family members and friends and were unaware of

the company’s risky financial position. Kenmark has

since been de-listed from Bursa Malaysia.

Boards should be prepared to demand more

accountability or transparency from senior

management and executive directors. Independent

directors who should not have strong connections to

the Board are ideally placed to make such demands.

However the levels of power distance, collectivism

and assertiveness in Malaysia make it difficult for

them to challenge the founder or dominant director in

these situations. In the cases mentioned above there is

a strong likelihood that some of the INEDs were not

independent in mind and had structural bias towards

their colleagues on the Board especially in the case of

Sime where one director had served for 28 years. It is

also likely that ‘group think’ resulted in the selection

of directors who were less inclined to be suspicious of

people like them. The majority of the Board of Sime,

MAS and Proton comprised former civil servants or

government investment agency appointees. Many

members of the Board moved in similar social, work

and political circles and were possibly inclined to

accept the assurances of the CEO or Chairman who

came from the same background, that there was no

financial mismanagement in spite of red flags raised

by the auditors. It is difficult for them to demand

more accountability when the Chairman or CEO is a

person with strong political connections which raises

the issue of power distance. Many of the Board

members in government linked companies are Malays

and in Malay culture, criticisms and challenges

against those in authority or from a higher social

hierarchy are considered rude and causing loss of face

is often avoided. Criticisms if any, is only tendered in

mild language and often after showering the powerful

person with praises (Pye, 1985). Power distance may

also inhibit directors from criticising founders of the

Board to whom they may owe their position.

Furthermore in-group collectivism results in directors’

tendency to sweep matters under the carpet as

pursuing controversial issues may compromise their

loyalty to their in-groups. Pye notes that there is a

strong tendency to defend in-groups even in the face

of overwhelming evidence that someone in that in-

group has committed a wrong. This is because loyalty

is highly valued.

Malaysian Code of Corporate Governance 2012

The Securities Commission launched the Corporate

Governance Blueprint in 2011 and indirectly

addressed cultural values through proposed reforms in

Malaysian Code of Corporate Governance 2012

(MCCG 2012) making it easier for directors

especially INEDs to carry out their monitoring duties.

The reforms are addressed below.

Maintaining independence

An important step in maintaining independence of

directors has been to limit the tenure of all non-

executive directors including INEDs as there appears

to be a serious problem in this area in Malaysia. The

UK Code of Corporate Governance 2010 has taken

this step and stipulated that if NEDs serve more than

nine years they should be subjected to annual re-

election. The Singapore Code states that a period of

nine years is appropriate tenure but leaves it to the

Nomination Committee to justify if a director remains

independent beyond the nine years of his or her

service. Limitation of tenure will prevent structural

bias in INEDs who have served for many years and

while the flexibility of permitting the nomination

committee to justify employing a director beyond this

period may be maintained, the MCCG 2012 has

adopted the period of 9 years as the norm. There is no

guarantee that limiting the tenure of directors will

ensure that they are independent throughout their

tenure but it may reduce instances of structural bias

especially as the Code requires INEDs to be assessed

annually to determine their independence.

The MCCG 2012 maintains the requirement that

one third of the board should comprise INEDs but has

adopted similar provisions to the Singapore Code

which states that half the Board must comprise INEDs

when the Chairman of the Board and the CEO is the

same person or the Chairman is not an INED. This

change may address the problem of powerful

Chairmen or CEOs who dominate the Board and will

also take into account the high level of power distance

and low assertiveness in Malaysia. An increase in the

number of independent directors under such

conditions may result in greater assertiveness as they

would be able to put forward their views as a group.

This should also be implemented where the

corporation’s founder holds an influential position on

the Board even if he or she is not CEO or Chairman

as they appear to wield great influence over the Board

as in the case of Linear, Kenmark and Transmile.

Nevertheless this will not always ensure independent

and vocal boards as half the Board of Sime comprised

INEDs, but this did not prevent its financial losses.

The main reason for this is due to ‘group think’ as

almost all the members of the board moved in the

same work, social and political circles. This problem

should be addressed through greater board diversity.

The MCCG 2012 stipulates the need for diverse

boards and the CG Blueprint 2011 recommends that

more women should be appointed to the board. Spain

and Norway require corporations to increase the share

of female directors to 40% although there is much

debate on whether a quota will achieve its purposes as

corporations have been unable to meet the target or

have simply propelled women to the board to fulfil

the target without a comprehensive training plan to

ensure that they are properly equipped to take on the

role. Australian corporations have increased the

number of women on boards from 8% in 2008 to 14%

by April 2012 through a mentoring programme

initiated by the Australian Institute of Company

Directors (AICD) which identified capable women

and selected leading chairmen and directors of ASX

200 companies to mentor them until they were ready

to serve on the board. This is a sustainable method of

appointing women directors and will ensure that the

appointees provide value other than diversity to the

board.

There is sufficient diversity in Malaysia due to

the presence of different ethnic groups comprising

Malays, Chinese, Indians, Kadazan and Ibans as well

as other minority groups. The levels of power

distance, in-group collectivism and assertiveness

among the major ethnic groups comprising Malays

and Chinese is not very different (Lim, 1998; Sendut,

Madsen and Thong, 1990) although there are lower

levels of power distance and higher assertiveness

among the Chinese (Abdullah, 1992). In-group

collectivism is high among both these groups which

creates a greater tendency for ‘group think’. While

Boards should comprise members of various ethnic

groups in Malaysia who bring different viewpoints,

the similarity of cultural values indicates that it may

be an added advantage to appoint foreign directors

where possible as they have different cultural values

and may not be as susceptible to ‘group think’. It

would also be an advantage to appoint women

directors who bring different perspectives to the

Board and are more meticulous about certain aspects

of internal controls (Adams and Ferreira, 2009) but

the number of women and board members from

diverse ethnic backgrounds should not be mandated.

Instead the Board should be evaluated every three

years to assess its effectiveness and diversity. Bursa

Malaysia’s Corporate Governance Disclosure Guide

2012 permits the Exchange to reject the nomination of

directors if it is of the opinion that it does not enhance

Board diversity. This may force corporations to

examine whether they have a diverse boards or risk

interference by the Exchange.

Conclusion

The significance of this research is that it highlights

that structural bias and group think which is a

problem faced by capital markets in general is

compounded by cultural values in Malaysia. It also

highlights that due to pervasive cultural values,

Malaysia directors including INEDs may not resist

dominant directors and as a result may not insist on

strong internal controls as this is perceived as a lack

of trust. Criticisms are often perceived as personal

attacks and directors who persist in criticising

members of the Board especially the Chairman and

CEO may find themselves isolated or even removed

from the Board on the grounds that they are not good

team players. There is also a natural inclination to

form in-groups which may affect the independence

and professionalism of some directors. INEDs are

placed in a difficult position of having to act as

monitors of the Board and senior management under

conditions where cultural values uphold in-group

collectivism and high power distance.

The MCCG 2012 has taken steps to address this

problem to a certain extent by emphasising the role of

INEDs, requiring the nomination committee to assess

their independence annually and limiting their tenure,

as well as emphasising board diversity. It attempts to

drive the message that INEDs have a clear role to play

which the board has to recognise even if it does not

resonate with cultural values in Malaysia. While there

is no guarantee that this will prevent structural bias

and group think, it sends a clear message that these

practices are discouraged. While it may take time to

change board practices, the provisions in the MCCG

2012 are a step in the right direction.

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DETERMINING WHICH MANAGEMENT LEVEL MAKES DECISIONS WHEN OUTSOURCING THE DISTRIBUTION

FUNCTION

Johan Muller, Louise van Scheers*

Abstract

Outsourcing is one of the widest used methods of facilities management employed by organisations for doing business in today’s global economy. The main purpose of the research is to evaluate consensus amongst the different levels of management to outsource the distribution function at a South African steel retailer. The research survey was done in the form of a questionnaire utilising statements with a quantitative. The population selected was the first three levels of management across all six of the business units. Analysis of the data was done with the statistical package of social sciences SPSS and the applied pedometric techniques such as Chi-square and ANOVA. Findings and results from the analysis indicate that management are positive towards adopting outsourcing. Keywords: Outsourcing, Distribution Function, Retailer, Different Levels of Management, Top, Senior and Middle Management Levels Corresponding author, Marketing and Retail Department, School of Business Management, University of South Africa, PO Box 329

Unisa 0003 Tel.: 012 429 4938 E-mail: Dr.louisevsc@gmail.com, vscheml@unisa.ac.za

1 Introduction

Driven by political and economic dynamic changes,

facilities management was borne to enable reacting to

change. Doing business in today’s global economy

requires exceptional skills from management in order

to be competitive and to have a specific competitive

advantage over competitors are even more

demanding. One of the widest used methods of

facilities management deployed by organisations is

that of outsourcing in various forms (i.e. I.T., H.R.,

Distribution, Warehousing, etc.) for various different

reasons (i.e. reduce costs, improve quality, focus on

core business, etc.). In order for outsourcing to be

successful, it needs to add benefits to profits,

efficiency or effectiveness ethic. Outsourcing assists

management to gain a competitive advantage over

competitors within their specific industries as part of

their organizational strategies and developing or

strengthening core competencies at the same time

(Taplin, 2008). Outsourcing the distribution function

involves hiring a third party to store and distribute

your products through its national or international

distribution network; this party provides the staff,

warehouses, and distribution centre and transportation

fleet. Distribution is not the core competency for this

steel retailer therefore management decided to

outsource this function to allow them to focus on your

mission-critical activities. However it seems that there

are differences in consensus amongst the different

levels of management to outsource this function.

This research aims to determining the

management level which makes decisions when

outsourcing the distribution function at South African

steel retailer. The steel company is a privately owned

industrial management group. The group is

represented in the UK, Australia, USA and South

Africa where it manages a diverse portfolio of small-

to-medium sized enterprises focussed on addressing

niche segments.

2 Problem statement

Following the changes in the South African political

dispensation and the launch of the Broad Based Black

Economic Empowerment policy, organizations were

forced to revisit their structures and policies. A score

card was devised whereby organizations earn points

in different categories of the company, i.e.

shareholding, management structure, supply partners,

development & training programs, upliftment

programs, welfare participation contributions, etc.

This will categorise an organisation in terms of what

level of Black Economic Empowerment contributor

the company is for doing business. Fuelled further

with the economic recession globally, organizations

faced downscaling, retrenchments and restructuring

the way they used to do business in order to create

sustainability and compliance. These changes forced

the steel retailer to outsource some of the non-core

functions to stay competitive. One of the various

outsourcing options implemented by the steel retailer

was to break down the head office structure by

relocating the finance related functions resources to

business units for better control and optimisation and

also outsourcing of the distribution function to an

external company. This was however left to the

demise of each business unit manger’s own decision

instead of a group strategy to which company they

will be outsourcing and on what basis this will be

structured.

3 Aim and Objectives

The main purpose of the research is to evaluate

differences in consensus amongst the different levels

of management to outsource the distribution function

at a South African steel retailer. The objectives are:

Determining the management level which makes

decisions when outsourcing the distribution

function

Gathering perceptions on views of the top,

senior and middle management on outsourcing

the distribution function

The following hypnoses were formulated:

H₁ = There is a positive correlation between the

general importance of outsourcing and the

opinion of the retailer toward outsourcing of

distribution.

H₂ = There is a positive correlation between the

retailer’s opinion toward outsourcing and the

potential improvement that outsourcing can

bring.

H₃ = There is a positive correlation between the

improvement of the retailer and the financial and

revenue implications to the retailer.

H₄ = There is positive correlation between the

financial and revenue reasons and the cost of

outsourcing distribution.

H₅ = There is a positive correlation between the

cost and the risks associated with outsourcing.

H₆ = There is a positive correlation between the

risks and the level of satisfaction with the

current situation.

H7 = There is a positive correlation between cost

driven reasons to outsource and level of

satisfaction with current situation

4 Research Methodology

A quantitative approach was used with a survey

questionnaire as the method for collecting the data

between 15 October and 15 November 2010. The

design for this research will be a quantitative

approach and the instrument available for data

collection will be a survey questionnaire. The

population for the research survey is the South

African steel retailer and the sample consists of the

three different levels of management classified as

Level 1, Level 2 and Level 3 as per the Organogram

of the organization. Table 1 represents a breakdown

of the management classification, the total

participants involved in the research and the number

of respondents within the three different levels.

Table 1. Research Participants and Classification

Management Classification Total Participants Number of

Respondents

Level 1 (Top Management) 7 7

Level 2 (Senior Management) 21 21

Level 3 (Middle Management) 33 33

Total 61 61

Source: The steel retailer S.A. Outsourcing Survey

Level 1 participants consists of top management

in the Group (all directors on the board) whose

responsibility mainly relates to strategic decision-

making within the Group and/or business unit.

Level 2 participants represent the top

management within the business units (directors and

senior managers at business unit level) and whose

responsibility mainly relates to strategic and/or

operational decision-making for the specific business

Level 3 participants represent the senior

management within the business units and whose

responsibilities mainly relates to operational decision-

making for those business units.

The questionnaire comprises 37 statements that

revolve around six important aspects of the

outsourcing phenomenon. The 37 statements of the

questionnaire measure the opinion of the three levels

of management based on a 5-point balanced Likert-

type scale.

5 Literature Review

Different organizations will outsource different

operations which could include mostly noncore

functional areas i.e. I.T., Distribution, Warehousing,

etc. relevant to their specific organizational needs.

There is different models available in order to assist

management in their decision making process for the

specific function to be outsourced. Outsourcing is the

process of purchasing goods or services on

specification from an external supplier that were

previously produced in-house (Mol, 2004:585).

Outsourcing can involve the transfer of an entire

business function to a supplier or the transfer of some

activities associated with the function whilst some are

kept in-house. Wisner, Tan and Leon (2009:116) use

the term co-sourcing for the partially outsourcing of

functions or activities. We also find that vertical

integration or disintegration is associated with

outsourcing. Vertical disintegration is concerned with

the decision on whether to perform an activity

internally or source it from outside. Another term that

is often used in a manufacturing context is ‘make-or-

buy’ (McIvor, 2005:7).

Outsourcing

There is no certainty as to when outsourcing (the

concept of employing specialized skills from outside

the company to perform a specific function for the

organization for a period of time or indefinitely)

started, but this term was invented by the Information

Systems Trade Press during the late 1980’s. The term

was used to describe the trend that developed amongst

large organizations to transfer their information

systems to external service providers (Greaver, 1999).

According to Roman Seidl (2007) emerging research

was seen to have examined several aspects of

outsourcing and its impact on “why” and “how”. The

primary reason for outsourcing is found to have

changed from cost cutting to focussing on their core

business. A possible assumption is that today’s

companies analyse and categorise their processes

according to core and non-core processes,

consequently the sharpened company focus has

become the main reason for outsourcing.

One of Porter’s Generic Strategies (Porter, 1980)

is access to lower costs; which can be achieved

through optimal outsourcing and vertical integration if

executed smartly with the necessary research,

investigations and careful selection of sourcing

partners. Porter (Porter, 1998) also recognises the

value chain as useful in outsourcing decisions. By

understanding the linkages between activities it can

lead to more optical make-or-buy decisions that can

result in either a cost advantage or a differentiation

advantage. Readings from Bendor-Samuel (2000)

makes it clear that all over the world companies are

facing increasingly competitive markets and need to

improve organizational operations to stay ahead of

competitors and he maintains that outsourcing of non-

core activities is the main alternative management

tool available to achieve this goal.

Reasons to Outsource From the researcher’s various readings, Greaver

(1999), Badenhorst-Weis and Nel (2008), Rosenberg

& Macaulay (1993), IAOP (2009a), Dimension Data

(2009), Atos Origin (2004), Think180 (2008c) &

Seidl (2007), the following summary of reasons were

identified but are not limited to these:

Focusing in-house resources on more strategic

business issues and/or new technology and

systems;

Increased competition, need to improve

competitive advantage;

Globalization of markets;

Reorganization and streamlining;

Availability of necessary skilled workforce;

Different organizations will have different needs

and in-house skill sets for variation in reasons and

methods for outsourcing. Some organizations will

also make use of insourcing as appose to outsourcing

for a period of time depending on the requirements

and the level of in-house skills.

6 Research Findings

Overall summary of Management Mean Score

analysis:

Table 2. Overall Summary of Management Mean Score Analysis

Table 2 reflects the overall situation with the

seven grouped categories (Factors) pertaining to the

outsourcing concept at a South African steel retailer,

displaying the mean averages obtained by each

management group four each of the seven factors and

an overall measure for the factors. From the data in

Table 2 it becomes evident that Top Management is

the least positive with outsourcing but not at any

significance levels. Further investigation will explore

more in-depth analysis to interpret these summarised

results more intensely.

Table 3. Cronbach’s Alpha coefficient

Summary of Quantitative Data

Cronbach’s Alpha Coefficient

Statistically spoken, a Cronbach value of

between 0.6 and 0.8 is of an acceptable level (the

internal consistency is adequate) and a value of

between 0.8 and 1.0 is considered good. From table 3

it is apparent that factor 2 of the data analysed is just

below the minimum requirement due to the low mean

scores of questions 5 to 7 which is a concern for this

research results.

Table 4. Correlations between the 7 Factors

Correlations between the Seven Factors:

Correlation is a measure of linear association

between 2 variables. A correlation coefficient of 1

indicates perfect correlation, and a correlation

coefficient of 0 indicates a total lack of any linear

association. In Table 4 the highlighted correlations

indicate where the correlation is significant between

two factors of the analysis i.e. the correlation between

Financial and Revenue Driven Reasons to outsource

and that of General Importance of Outsourcing is

0.019 which is below the level of 0.05 and is therefore

significantly different from “0”.

Hypotheses Testing

H₁ = There is a positive correlation between the

general importance of outsourcing and the opinion of

the organization toward outsourcing of distribution.

General Importance of outsourcing (F1)

Organizationally Driven reason to outsource (F2) =

The correlation between F1 and F2 is closer to

zero and indicates a lack of linear association.

This indicates that the organization as a whole

does not deem outsourcing to be of general

importance. The results show that the H₁ hypothesis

was rejected and the alternative is accepted. Ha₁ =

There is a Negative correlation between the general

importance of outsourcing and the opinion of the

organization toward outsourcing of distribution.

Middle and senior management agree more than top

management to the general importance of

outsourcing, because middle management especially

has to handle the distribution function.

H₂ = There is a positive correlation between the

organizations opinion toward outsourcing and the

potential improvement that outsourcing can bring.

Organizationally Driven reason to outsource

(F2) Improvement driven reasons to outsource

(F3) = 0.004

zero and indicates a lack of linear association.

Generally the organization feels that outsourcing

won’t improve their business. The results show that

the H2 hypothesis is rejected, thus accepting the

alternative. Ha2 = There is a negative correlation

between the organizations opinion toward outsourcing

and the potential improvement that outsourcing can

bring.

Middle and senior management believes that

outsourcing is important but won’t improve the

organization.

Middle and top management are more involved

with the distribution and believes that outsourcing the

distribution function will definitely improve the

organization.

H₃ = There is a positive correlation between the

improvement of the organization and the financial

and revenue implications to the organization.

Improvement driven reasons to outsource (F3)

Financial and revenue driven reasons to outsource

(F4) = 0.000

The correlation between F3 and F4 is at the

lowest point of the scale, indicating a total lack of

linear association, indicating that there is a complete

lack of association between the improvement of the

business and the financial and revenue implications.

This indicates that the H₃ hypothesis is rejected and

the alternative is accepted. Ha₃ = There is a negative

correlation between the improvement of the

organization and the financial and revenue

implications to the organization. Top management

obviously wants to improve the state of the

organization but they are not willing to spend money

on outsourcing distribution.

Top management’s opinion is very neutral

towards the statement that outsourcing will cause

general improvement, while middle management

believes that it will make a significant difference. Top

management is involved with the management of the

resources (financial and other) and they are not

involved with the operational functions.

H₄ = There is positive correlation between the

financial and revenue reasons and the cost of

outsourcing distribution.

Financial and revenue driven reasons to

outsource (F4) Cost driven reasons to outsource

(F5) = 0.176

zero and indicates a lack of linear association. There

is little linear association between the cost and the

financial and revenue driven reasons. Therefore the

H4 hypothesis is rejected and the alternative is

accepted. Ha4 = There is negative correlation between

the financial and revenue reasons and the cost of

outsourcing distribution. Middle management is of the

opinion that there are positive financial consequences

to spending money on outsourcing distribution, while

top management is not willing to spend money on

outsourcing as they believe that it is better to spend

the money on something else.

H₅ = There is a positive correlation between the

cost and the risks associated with outsourcing.

Cost driven reasons to outsource (F5)

Reasons not to outsource and risks associated with

outsourcing (F6) = 0.755

The correlation between F5 and F6 is close to

one and therefore indicates a more perfect linear

association.

The belief is that it costs more not to outsource.

This indicates that it is more cost effective to

outsource distribution than to handle internally. The

results show that the H₅ hypothesis was accepted.

Middle, senior and top management’s opinions are

very close together and are above average toward the

cost involved not outsourcing distribution.

H₆ = There is a positive correlation between the

risks and the level of satisfaction with the current

situation.

Reasons not to outsource and risks associated

with outsourcing (F6) Level of satisfaction with

current situation (F7) = 0.534

The correlation between F6 and F7 is close to

the halfway mark, but indicates a closer to perfect

linear association. There is an above average opinion

toward the risks involved with outsourcing and the

level of satisfaction with the current situation. They

are a little hesitant to take on risks to improve their

current situation. This indicates that the H₆ hypothesis

can be accepted. Top management is not satisfied

with the current situation but is a little hesitant to take

on risks associated with outsourcing. The two factors

that have the most perfect linear association with each

other are F7 and F5.

H7 = There is a positive correlation between

cost driven reasons to outsource and level of

satisfaction with current situation

F5 = Cost driven reasons to outsource F7 =

Level of satisfaction with current situation = 0.906

The general feeling is that they want to improve

the current situation but keep the costs to a minimum.

The two factors with the most lack of linear

association with each other are F3 and F4.

Analysis pertaining to the three levels of Management

Ideally the mean scores should have a low standard

deviation; the Levene Test bigger than 0.05 and the

ANOVA bigger than 0.05.

Table 5. General Importance of Outsourcing Analysis by Management Level

The data in Table 5 reflects an overall mean

score of 3.5458 with a standard deviation of 0.67568;

Levene’s test for homogeneity of variances with

P=0.859 versus 0.05 (no significant differences in

variances) and ANOVA significance value P=0.199

versus the alpha value of 0.05 (Management Level

has no significance upon the mean score of Factor 1).

The level of dispersion within the management levels

are however not good, standard deviation too high–

difficult to come to any conclusions.

Table 6. Data analysis of Factor 3 by Race classification within Management

Table 6 shows that apart from three outliers, the

non-white box-plot analysis indicates a narrow spread

between the 100% and nil % margins, but with the

White management there is a too wide spread and

needs to be further analysed.

Table 7. Data analysis of Factor 3 for Whites by Management Level

Table 7 indicates a fairly good spread with

Middle Management and Top Management apart

from the outlier, but with Senior Management we see

a too wide spread. There is thus significant statistical

difference with White Senior management. Taken into

account that there are 17 people in Senior

Management from a total of 43, they can have a

statistical influence on the results of White

Management in general.

6 Conclusion

Management consensus and perceptions on outsourcing the distribution function

General Importance of Outsourcing

An average mean score of 3.5458 (table 5) indicates

that management in general realizes the importance of

outsourcing and acknowledges that outsourcing

should and will form part of the organization’s

business strategy. The middle management reflects

the strongest opinion of 3.65 versus that of senior

management at 3.52 and top management less

convincing with a score of 3.14 (a ‘not sure’ per the

Likert scale).

Middle management who is closer to the action

on the floor realises the benefits of outsourcing and

top management should take note of this and

investigate why middle management is so much more

positive towards outsourcing. This is reflected in

statement 3 (table 5) with the highest mean score of

4.1 towards freeing up management time to focus on

core competencies whilst developing current or new

competencies.

Organizationally Driven Reasons to Outsource

The analysis indicates an even stronger sense of

importance of outsourcing and also a much higher

cohesiveness amongst all three levels of management

with senior management the most positive towards

organizationally driven reasons to outsource with a

mean score of 3.85 versus middle management of

3.83 and top management of 3.74 (see table 5).

The highest mean score of 4.0 attained for factor

2 reflective in statement 7 (see table 6) in that

management should consider outsourcing in order to

obtain specialized services to ensure flexibility within

the organization. This reinforces management’s

seriousness of the role that outsourcing can play in the

organization’s business strategies.

Statements 5 and 8 representing focussing on

customer needs attracted the lowest mean scores

(3.733 & 3.567 per table 5) but still indicating

management is convinced that outsourcing can

improve customer relations or service levels to

customers.

Indications are present that management agrees

that outsourcing will enhance organizational

effectiveness by focussing on core activities, obtain

specialised services through outsourcing to ensure

flexibility within the organization and should they not

be able to attract the correct skills to perform a

specific function.

Improvement Driven Reasons to Outsource

From the data in Table 4 it becomes evident that

factor 3 has the lowest mean score rating of all the

factors (excluding factor 7) of 3.475 and very low

level of Levene (0.056) and unacceptable level of

ANOVA (0.016) versus significance level of 0.05 as

minimum standard.

Indications from Table 5 is that statements 10,

13, 14 and 15 have very low mean scores (‘not sure’)

indicating management is less positive towards

outsourcing improving the organization’s image by

linking to credible providers in the market place,

improving the quality factor regarding services

provided to customers, broadening the existing skills

base within the organization and improving the risks

management function by transferring certain functions

to service providers.

Further analysis per Table 6 and Table 7

indicates that White Management and in particular

Top Management are less convinced towards

improvement driven reasons to outsource. From the

graph (see Table 18) top management’s 50th

percentile is below Likert scale of 3 (‘not sure’) and

although senior management’s 50th

percentile is just

below 3.5 of the Likert scale, the 100% and nil% is at

the 4.5 and 2.2 ratings respectively with an outlier at 2

indicating high levels of difference in opinion

amongst senior management. The research indicates

that the individuals in the age bracket 25 – 35 yrs are

mostly convinced towards outsourcing for

improvement with age bracket 36 – 45 yrs also more

than 3.5 per the Likert scale indicating a high positive

attitude towards outsourcing for improvement. The

research study revealed that the three levels of

management in general 16.77% of the statements per

the outsource questionnaire were answered negative

towards outsourcing, 15.58% “not sure” and

overwhelming 67.75% in agreement with utilising

outsourcing as a management tool. This indicates that

the management team of steel retailer recognizes the

importance of outsourcing and the implementation

therefore regarding non-core activities associated with

the organization and the impact thereof on operational

aspects of the business strategy.

The aim of the research was to establishing

whether there is consensus between top, senior and

middle management on outsourcing the distribution

function. The research concluded that there is no

consensus between top, senior and middle

management on outsourcing the distribution function.

The research reflects that middle management is

overall far more inclined to outsourcing than that of

top management in all of the 6 factors pertaining to

the questionnaires. Top Management is ‘not sure’

about four of the six factors leaving the impression

that they are not in favour of outsourcing. The

average mean score for all management is inclined to

outsourcing for five of the six factors and middle

management six out of the six factors. This leaves the

situation with a big gap between top and middle

management regarding outsourcing as a management

tool improving business processes and strategies.

It would thus appear that Top Management is

too far removed from the operations and lost touch

with the rest of the management team and are not

acting responsibly towards the long-term future of the

Group.

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CRIME, SECURITY AND FIRM PERFORMANCE IN SOUTH AFRICA

Busani Moyo*

Abstract

We use cross sectional data from the World Bank enterprise surveys gathered in 2007 in South Africa’s four cities (Johannesburg, Cape Town, Durban and Port Elizabeth) to assess the impact of business related crimes on firm performance proxied using firm sales. Using Ordinary Least Squares (OLS) and Tobit model, we find that crime in the form of theft, robbery, arson and vandalism has a negative effect on sales and hence firm performance. However the impact of domestic shipment crime is mixed and varies from city to city depending on the magnitude of losses incurred by firms in each city. Results also show that crime is regressive in nature because crime related losses are relatively higher among small firms than large firms. The prevalence of crime amongst small firms and its negative effect on firm performance suggest the need for government and the business community to come together and develop security systems that are effective and affordable to small businesses. This is because, supporting small businesses is important for growth and employment creation. Keywords: Crime, Security, Firm Performance * Senior Lecturer in the Department of Economics at the University of South Africa, Preller Street, Muckleneuk Ridge, Pretoria: P.O. Box 392 UNISA 0003 South Africa Tel.: +27 12 429 6191, +27 84 526 9216: E-mail: moyob@unisa.ac.za, myxbus001@gmail.com

1 Introduction

According to the results of a global survey carried out

by PricewaterhouseCoopers in 40 countries between

April and July 2007 as well as November 2009, fraud

was found to be one of the most problematic issues

for business worldwide. The 2007 survey which

covered about 103 companies (of which 71% were

listed) found that South African companies have been

the subject of more crime than most other countries in

the world. According to the survey, 72% of these

companies uncovered fraud over the last two years,

compared to 43% of the businesses surveyed

worldwide6. The same pattern was also replicated in

2009 with about 52% of South African firms falling

victim to economic crime compared to 30% globally.

The most common crimes in South Africa,

according to the 2007 and 2009 surveys were asset

misappropriation (theft), product piracy and

counterfeiting, bribery and corruption as well as

financial misrepresentation. The surveys also found

that larger companies with more than 1000 employees

are most vulnerable to fraud, and that the financial

services companies reported more incidence of fraud

than any other industry.

6 The African continent also tops the list in terms of having the highest level of economic crime worldwide at 51%, followed by North America with 41%.

These findings were partly confirmed by the

World Bank enterprise survey data carried out on

1057 establishments in the manufacturing and

services sector of South Africa in 2007. Thus about

38% of firms identified crime, theft and disorder as a

major hindrance to doing business compared to a

regional average of 28% in the whole of Sub Saharan

Africa and 25% worldwide (see table 1 below). The

severity of crime in South Africa is also reflected by

the number of firms that have invested in systems and

controls to detect and deter economic crime. Thus

about 76% of firms have spent money on security

systems compared to the regional average of 60% in

whole of SSA.

Given the above findings the question then that

comes to mind is: Why is the level of crime so high in

South Africa? Schönteich and Louw (2001) argue that

there is no single satisfactory answer to this question

but a number of reasons have been given to explain

these high crime levels plaguing the country.

Table 1. South Africa Crime related statistics, 2007

Africa

Region

% of firms paying for security 76.38 60.45 56.76

Losses due to theft, robbery, vandalism and arson against the firm (%

of sales)

1.01 1.68 1.03

If there were losses, losses due to theft, robbery, vandalism and arson

against the firm (% of sales)

2.39 6.14 4.71

Security costs (% of sales) 1.58 1.81 1.45

Security costs if the establishment pays for security (% of sales) 2.07 3.32 2.82

Products shipped to supply domestic market lost due to theft (%) 0.83 0.93 0.91

% of firms identifying crime theft and disorder as major constraint 38.04 27.68 25.53

% of firms identifying corruption as major constraint 16.87 34.65 36.59

Value lost due to power outages (% of sales) 1.60 5.84 4.90

Source: World Bank enterprise surveys

Table 2. South Africa Crime related statistics by major cities, 2007

Johannesburg Cape

Elizabeth

Durban

% of firms paying for security 73.57 90.34 53.03 63.78

Losses due to theft, robbery, vandalism and arson

against the firm (% of sales)

3.61 3.77 1.00 3.74

Security costs (% of sales) 3.41 1.55 1.00 1.13

Products shipped to supply domestic market lost due to

theft (%)

5.58 2.62 1.02 5.07

% of firms identifying robbery theft and disorder as

major constraint

33.66 56.69 28.28 30.30

% of firms identifying corruption as major constraint 25.31 37.80 22.07 34.85

% of firms identifying courts as major problem

Value lost due to power outages (% of sales)

Security costs in ZAR (if establishment pays for

security)

249 271

136 148

177 544

187 601

Source: World Bank enterprise surveys

Their explanations consider the impact of the

country’s ongoing political and socio-economic

transition, the impact of the proliferation of firearms,

the growth in organized crime, changes in the

demographic composition of the country, and the

consequences of a poorly performing criminal justice

system. They argued that South Africa is a heavily

armed society and according to the police Central

Firearms Registry, 3.5 million South Africans legally

possess about 4.2 million firearms of which slightly

more than half are handguns. It is also estimated that a

similar number of illegal firearms is circulating in the

country. Schönteich and Louw (2001) also went on to

argue that high levels of gang activity and availability

of firearms is evident in urban areas and is a factor

behind violent crimes or robberies committed in these

places. They also argued further that, South Africa is

the third most urbanized country in Sub Saharan

Africa and because of rural urban migration;

overcrowding, competition for limited resources,

greater stress and increased conflict have also

contributed to high crime levels both on business and

individuals in the country.

The PricewaterhouseCoopers survey findings

however, identified staff reductions because of the

recent global recession, poor or ineffective corporate

governance structures and weak internal audit and risk

management systems as some factors behind business

crime in the country. Thus the 2009 survey found that

89% of respondents believed that management’s

focus on survival strategies under the current harsh

economic environment has led firms to resort to staff

reductions7, resulting in fewer resources being

deployed on internal controls.

A corporate governance structure with vigorous

escalation procedures where employees can

7 Staff reductions result in reduced segregation which in turn impacts on the organisation’s ability to maintain a sound control environment creating gaps in the system.

assertively report their concerns confidentially and in

which perpetrators are dealt with seriously by

management is a powerful deterrent tool. However,

the fact that 71% of South African respondents

reported that increased pressure and incentives were

the most likely causes for the greater risk of fraud

should therefore raise alarm in most organisations8.

The survey also found that the majority of economic

crimes were perpetrated from within (62%) whilst

38% were external perpetrators. This should not be

shocking because employees have a greater

understanding of the company and the internal

controls in place designed to prevent fraud and so

weak internal audit and risk management controls

make it easy for employees to defraud the company.

The aim of this study therefore is to examine

how these high crime levels in South Africa have

affected the performance of firms in the

manufacturing and services sectors. Our argument

here is that crime result in firms redirecting resources

away from productive activities to financing security

systems thereby compromising firm performance9.

Thus, instead of simply producing their products,

companies feel driven to spend more on preventing

theft, fraud and robberies as well as securing their

premises and other assets. The other motivation is that

there are very few studies that have been done in this

area (using firm level data) particularly on Africa.10

Studies that tended to relate crime with economic

variables have been done largely at macro level and

these related crime to economic growth, employment,

income distribution and even foreign direct

investment (FDI) (see Detotto and Otranto, 2010;

Josten, 2000; Antoni et al, 2007; Daniele and Marani,

2008; etc). Our argument is that, when studying

crime, it is more appropriate to do the analysis at firm

and individual or household level because these are

the economic agents directly affected by criminal

behaviour. This is important for developing

theoretical models of crime.

Additionally, macro level studies also assume

that crime levels are the same across the country when

8 71% of South African respondents felt that increased pressure and incentives were the most likely causes for the greater risk of fraud compared to 68% globally. The most significant contributors to increased pressure and incentives were targets that are more difficult to achieve (54%) and the fear that people might lose their jobs (31%). 9 In addition to leading to greater uncertainty, a high incidence of crime may induce enterprises to exit from the market place or relocate to safer locations (World Bank, 2003 on Jamaica). Crime may also have a detrimental effect on potential entry of firms (local and foreign) and their expansion (Krkoska and Robeck (2006). 10 Some enterprise notes in this area have been written by Amin M from the World Bank but they are all on Latin America and Eastern Europe and Central Asia whilst Krkoska and Robeck (2006) also carried out a similar study using 34 European and Asian countries.

in actual fact they may be interesting variations

depending on the size and level of urbanisation of the

each area, effectiveness of the local policing units and

even income growth and unemployment levels in each

Given that a number of firms in this study spend

funds on establishing and strengthening security

measures, we also want to find out whether these

security expenditures minimise the impact of crime on

firm performance. In carrying out our analysis, we

will control for other firm specific factors like firm

size, age and whether the firm export or not. City and

sectoral dummies will be used to capture variation in

the prevalence of crime according to where the firm is

located and in which sector it operates11

This paper is organised as follows: Section one

covers introduction whilst section two is on literature

review. The empirical methodology and descriptive

analysis of data are covered in sections three and four

respectively. Section five covers results and

conclusions.

2 Literature Review

According to Krkoska and Robeck (2006), the

literature on crime is grouped into three strands

namely institutions, economics of crime and the

unofficial economy12

. Research on institutions

includes enterprise experience with crime as one of

several indicators to measure the quality of an

institutional set up. Hay and Shleifer (1998) and Frye

and Zhuravskaya (2000) studied the impact of weak

institutions on the enterprise sector and showed crime

as one symptom of general institutional weakness.

They argued that crime thrives where the state is

unable to exert power over public administration,

protect property rights or provide institutions that

support the rule of law. Frye and Schleifer (1997)

found that enterprises in Russia rely on private

protection either through employment of legal

protection agencies or through payments to organized

crime to substitute weak law enforcement.

The main focus of the economics of crime

literature is on law enforcement aspects of the fight

against criminal activities as well as factors which

explain the decision to commit crime. This area is

divided into theoretical and empirical literature.

Eeconomists in this realm agree that a person

commits an offense if the expected utility to him

exceeds the utility he will get by using his time and

other resources at other activities. Thus people

11 Descriptive statistics showed that most firms in Cape Town and those in the textile and garment sector complained more about crime than firms in other cities and sectors. 12 The third strand of crime literature which relate to unofficial economy is defined to include irregular and illegal activities and mainly covers tax evasion.

become criminals not because their basic motivation

differs but because their benefits and costs differ.

A prime example of theoretical papers analyzing

the economic impact of crime is the seminal paper by

Becker (1968). Becker modeled general crime as a

type of economic activity that is immoral, but

nevertheless, can be analyzed by standard economic

tools. He used a model that related crime and

punishment to develop optimal public and private

policies including the optimal amount of resources

and level of punishment to minimize social loss from

crime. Assuming that crime is an economic activity

carried out by individuals who balance costs and

benefits, offenders will refrain from entering the

criminal business when the risk or cost of high

punishment is too high. He argued that many theories

agree that the increase in the probability of conviction

or punishment if convicted generally decreases the

number of offenses committed and that a change in

this probability has a greater effect on the number of

offenses than a change in punishment.

Studies that examine the economic impact of

crime from an empirical perspective include Glaeser

and Sacerdote (1999). They looked at the relationship

between crime and economic growth and argued that

factors of production tend to avoid places where the

risk of expropriation through crime is high and that

the location decisions of well educated households are

particularly sensitive to local crime rates. They also

argue that one potential channel through which

growth might affect crime is the labor market. If it is

relatively easy to find a job even for less educated

people, the relative attractiveness of crime as an

economic activity goes down and faster-growing

regions should therefore experience less crime. Using

a panel data for U.S. Metropolitan Statistical Areas

(MSAs) between 1987 and 2006 and using lagged

abortions to instrument for crime, they found strong

evidence for a growth depressing effect of crime.

Their estimates suggest that, reducing the annual

crime rate by five crimes per 1,000 people (for the

period from 1987 to 2006, this is equivalent to

lowering crime in the average MSA by 10 percent) is

associated with an increase in per-capita earnings

growth by about 0.5 percentage points. Taken

together, these results suggest that crime is costly to

growth because of its adverse effects on local

production.

Gaviria (2002) used survey data gathered by the

World Bank and the Inter American Development

Bank in 1999 on 29 countries from Latin America and

the Organisation of Economic Cooperation and

Development (OECD). He looked at effects of

corruption and crime on firm performance using

ordinary least squares method and found that crime

has a noticeable effect on the economic outcomes of

firms or reduces firm competitiveness. He also found

that the prevalence of corruption and crime differs

substantially from one country to another and that

both phenomena are closely associated. Another

World Bank (2003) study on economic development

in Jamaica paid particular attention to the issue of

crime. The study found crime to be one of the main

reasons for weak economic development in Jamaica

due to its substantial costs on business in the country.

Descriptive statistics analysed by Amin (2009a)

using World Bank survey data show that a third of the

firms in 14 Latin American countries experienced at

least one incident of crime during 2005. 72.8% of all

firms lost money either due to crime or expenses on

security, which together average 2.7% of annual sales

for a typical firm. He also found that firms in Latin

America are as likely to be victims of crime as much

as individuals and households (33% vs. 38% for

households are reported in a study by Gaviara and

Pages, 2002). Amin (2009a) also found that, large

firms are more likely to be victims of crime than

small firms (42.4% vs. 31.4%), but however losses

due to crime as a percentage of annual sales are much

higher for small firms than large firms (1.4% vs.

0.65%). This burden on smaller firms contradict

findings by Gavaria and Pages (2002) as well as

Glaeser and Sacerdote (1999), who found that

relatively better off (larger firms in this case) suffer

more from crime than the rest. Finally, Amin (2009a)

also found that the incidence of crime is higher in

bigger cities compared to smaller ones. He argued that

this could be because criminals prefer bigger cities

where it is easier for them to remain anonymous and

there is more wealth to steal. The enterprise survey

data showed that this result holds only across cities

within a country not across countries, hence what

matters is how big or small a city is relative to other

cities in the same country with absolute size of the

city being irrelevant. In this case, natural population

growth should not call for more resources but a

reallocation from the slower to faster growing cities.

Bourguignon et al (2002) looked at the

relationship between income distribution and crime

using a simple theoretical model and panel data in

seven Colombian cities over a period of 15 years.

They were trying to explain the factors that drive

individuals to engage in both social and business

related economic crimes. They found that would be

criminals are common among those people living in

households where income per capita was below 80%

of the mean. Distributional changes among those

people who are above this limit are not likely to have

no significant influence on the crime rate. These

findings by Bourguignon et al (2002) are similar to

what was found by Ehrlich (1973) in what probably

was the first empirical paper on the economics of

crime. Ehrlich (1973) found using cross sectional data

a significant relationship between the crime rate and

the share of the population below half the median

income across the US states. However Freeman

(1996) mentions that no significant effect was found

in a cross section of time series for various

metropolitan areas in the US after controlling for

fixed effects.

Krkoska and Robeck (2006) also used the World

Bank enterprise survey data conducted in 34 countries

in Europe and Asia to explain business characteristics

that make firms vulnerable to crime. They found that

high rates of crime are particularly associated with the

weak development of micro enterprises in the services

sector, operating in large countries with high

unemployment. Their paper also highlighted the

deterrent effect of crime on FDI inflows and job

creation especially in less advanced transition

countries.

3 Empirical Methodology

The methodology that we are going to use to examine

the nature of the relationship between crime and firm

performance in South Africa borrows largely from the

work of Gaviria (2002). The estimated equation

which also takes into account other firm

characteristics is presented as follows:

ijijijij ZCrimeX 310 (1)

where ijX stands for sales of firm i in city/

region j

and ijZ is a vector of firm characteristics

like firm size, firm age, location and sector, whether

the firm exports or not. ij is a random error term.

The crime variable used in this study would be

measured using a dummy taking the value of one if

the firm has experienced losses as a result of theft,

robbery, vandalism and disorder and zero otherwise.

A negative value of 1 indicates that crime

negatively affects firm performance. Several

mechanisms can explain the adverse effect of crime

on firm sales. First, crime raises operational costs

(through extra security measures), lowering

competitiveness and ultimately lowering sales and in

extreme cases may result in firms shutting down

operations (Gaviria, 2002). Secondly, crime (through

misappropriated resources, vandalism etc) prevents

companies from enhancing productivity and this

affect sales growth. Finally crime may cause firms to

lose valuable human capital (through crime related

deaths or emigration to safer places) and this also

affects productivity and hence competitiveness. We

will also use an interaction variable (crime dummy

times security costs) to analyse the impact of crime on

sales given that the firm has invested on security. We

do this to ascertain whether investing on security

helps firms minimise or deter economic crime and

hence improve firm competitiveness.

3.1 Data

The World Bank’s Investment Climate Surveys (ICS)

on manufacturing and services sectors from South

Africa is the primary source of data used in this study.

The survey was done in 2007 and the total number of

establishments covered is 105713

. These firms were

also drawn from 14 International Standards Industrial

Classification (ISIC) industries in four cities namely

Johannesburg, Durban, Port Elizabeth and Cape

Town. The sectors covered in this study include

textile and garments, chemical and non metallic

products, construction and transport, machinery and

electronics, metals, rubber and plastics, as well as

food. The survey data on crime used in this study is

based on the following questions asked in the 2007

survey.

(i) In 2006 what percentage of the value of your

domestic shipments was lost while in transit due

to theft

(ii) In 2006, did the establishment pay for security?

If yes how much was spent as a percentage of

annual sales.

(iii) In 2006, did the establishment experience losses

as a result of theft, robbery, vandalism or arson.

If yes how much was lost as a percentage of

annual sales.

4 Descriptive Analysis Of Data

Using World Bank survey data and relating crime to

other firm characteristics like firm size, firm age and

ethnicity, we found that crime appear to be regressive

in nature in that losses due to theft and robbery are

relatively lower in large sized firms compared to

smaller ones (see table 5 appendix). It is about 1.3%

amongst large firms compared to 4.3% in small firms.

Firms complaining about crime are also relatively

more amongst smaller firms (34%) than larger firms

(32%). Probably this could be a result of the fact that

most large firms invest in security systems compared

to smaller firms. Thus statistics show that about 91%

of large firms pay for security compared to only 68%

of smaller firms. Whilst the highest losses from crime

expressed as a percentage of sales were about 10%

amongst large firms, they are about 30% amongst

smaller firms14

. The seriousness of business related

crime also extends to domestic shipments that are lost

due to theft. Thus about 2.7% is lost by large firms

compared to 4.3% in smaller firms. However, the

percentage of sales spent on security is higher

13 The data are collected through firm surveys that include a common set of questions for all countries surveyed. The sample is selected by a simple random or stratified random sampling method controlling for size sub sector, geographic distribution based on company registration records or manufacturing census information available from government. The sample size varies ranging from about 100 for small African economies like Lesotho to more than 1000 for big countries like India, China etc. 14 We use maximum and minimum values for this.

amongst small firms than larger firms. But the fact

that large firms’ sales are higher in absolute terms

than smaller firms means that they still spend more on

security systems and hence are able to minimize

criminal incidences.

By relating crime to ethnicity, statistics show

that there is no big difference between losses

experienced by most ethnic groups in the country

even though the Indian owned firms appear to have

incurred relatively huge losses compared to European

owned firms. Thus statistics also show that the

maximum loss that was experienced by an Indian

owned firm is about 40% compared to 10% amongst

African and other Asian owned firms. The same

situation is replicated again even when looking at

domestic shipments lost due to theft. They are also

relatively higher among Indian owned firms

compared to other ethnic groups. Probably this could

be a result of weak or inadequate security systems put

in place by Indian firms. This is because even though

there are many Indian firms paying for security, the

amount spent by these firms as a percentage of sales

(2.66) is lower than what are other big ethnic groups

(Africans, Europeans and Other) spend (3.14). Indian

firms are also far much smaller than in size compared

to Europeans and Other ethnic groups and therefore

affected by the regressivity of crime (see table 5 for

more). If there is a positive relationship between the

size of firms, amount of money spent on security

systems and the effectiveness of these systems, this

could then explain why Indians have experienced

more crime losses than other groups.

We also examined whether being old translate

into being more experienced in dealing with criminal

activities or not. Statistics show that a larger

proportion of older firms (more than 18 years, to

differentiate between old and young firms, we used

the mean age which we calculated to be 18 years) pay

for security and that these older firms experience

lesser losses than younger firms (less than 18 years).

This pattern is similar to that shown by the firm size

variable probably implying that smaller firms are also

relatively younger in age. Statistics on table 5 support

that small firms are relatively far much younger than

large firms.

To ascertain whether crime has any effect on

firm performance in the form of sales, we related sales

to losses incurred as a result of theft, robbery and

vandalism. The nature of the relationship is shown by

Fig 1 below. Thus it appears that there is a prima facie

negative relationship between these two variables.

However, this relationship holds only when looking at

all the other sample cities except Cape Town.

However, using a correlation matrix (table 7

appendix), the sales variable appears negatively

related to crime even though the relationship is not

significant.

Figure 1. Sales and Crime Relationship

Sales and Crime relationship

Johannesburg Capetown Port Elizabeth Durban

e losses (

f sale

sales crime level

Source: World Bank Investment Climate data

5 Results and Conclusions

After identifying a prima facie negative relationship

between firm sales and crime losses, the next step was

to see whether this can be confirmed by regression

results. We estimated using ordinary least squares,

country, city and sectoral level regressions.

Results at country level (see table 3 below) show

that variables like exporting, firm size and firm age

are consistent and robust determinants of firm

performance proxied using firm sales. These variables

are positive and significant with or without city and

sectoral dummies and even when using a Tobit

specification. Thus being large in size probably

through economies of scale improves firm

performance and this is also true for older firms. The

positive correlation between firm size and age suggest

that most large firms are older and therefore many

years of experience in producing a particular good

enables a firm to grow in size, generate economies of

scale as well as productivity effects that promote

better firm performance. Exporting (represented by a

dummy =1 if a firm exports and 0 otherwise) also has

a robust positive effect on performance suggesting

that more external markets are good for firm sales

growth.

The variables that are central to this study like

crime dummy and domestic shipments dummy are

also consistent in terms of their impact on firm

performance. The crime dummy is also consistently

negative and significant and robust to changes in

model and variable specification. Thus crimes

committed against firms in the form of theft,

vandalism arson etc have a negative effect on sales or

firm performance. The variable that captures domestic

shipments crime (proxied by domestic shipments

dummy) is negative but insignificant suggesting a

weak effect on firm performance. This is supported by

statistics on table 1 in that at country level, these

losses are an insignificant percentage of sales (0.83)

compared to other crime losses (2.39).

Table 3. Country level regressions

variables (1) OLS (2) OLS (3) OLS Tobit

Dependent variable

City dummies

Sect oral dummies No Yes Yes Yes

Export dummy

0.6755

(0.1189)***

0.5461

(0.1001)***

0.6577

(0.1099)***

0.4989

(0.1054)***

Crime dummy

-0.0465

(0.0231)**

-0.0326

(0.0121)*

-0.1876

(0.0227)***

-0.2952

(0.0211)***

Domestic shipments crime dummy

-0.0116

(0.0121)

-0.0156

(0.0168)

-0.0611

(0.0899)

-0.0337

(0.0897)

Firms size

1.9365

(0.03541)***

1.3209

(0.046)***

1.8765

(0.0469)***

1.9851

(0.0443)***

Firm age

0.1324

(0.0320)***

0.1898

(0.0657)***

0.1983

(0.0597)***

0.1889

(0.0330)***

Crime dummy * security costs

0.1778

(0.0321)***

0.1769

(0.0226)***

Domestic shipment dummy* security costs

Constant

No of observations

11.1086

(0.1296)***

10.2007

(0.3718)***

-0.0434

(0.0896)

11.6003

(0.348)***

0.0415

(0.0876)

13.5342

(0.2132)

***significant at 1%; ** significant at 5%; * significant at 10%: Standard errors in parenthesis

The use of the Tobit model here was to check for

robustness taking into account that sales values are a

censored variable (censored from below in that sales

values cannot be less than zero) and that ignoring this

may bias our estimates (Elbadawi et al 2007). The

pattern of significance of our variables appears not to

have been affected by this change in model

specification. The crime dummies are still negative

and domestic shipments dummy is still insignificant.

We also decided to include interaction variables that

capture the impact of crime on sales conditional on

the firm investing in security. Our aim is to find out

whether investing in security has an ameliorating

effect on sales by limiting criminal incidences against

firms. Results show that the variable has a positive

and significant effect on firm sales. This supports the

belief that security measures are very important in

minimizing the negative effects of crime on firm

performance and firms should therefore implement

and strengthen them. The situation is however

different when looking at domestic shipment crime

interaction dummy. When using OLS the sign is

negative but positive under the Tobit approach. This

suggests that security measures used to combat

domestic shipment crime have a weak effect on firm

sales. Since these types of losses are very small, very

little security resources are probably channeled by

firms towards these crimes resulting in them having

insignificant effect (These results might also be

affected by endogeneity as a result of the simultaneity

problem. It is possible that firms that are performing

well (high sales) invest more in security in as much as

investing more in security positively effect firm sales

or performance. However, coming up with

instruments to minimize this problem is difficult in a

cross sectional model like ours).

We also decided to assess whether the location

of the firm in terms of the city and sector in which it

operates from has any influence on firm performance

(see table 4 below). This is partly in response to what

we found under descriptive statistics that more firms

in Cape Town and Johannesburg and those in the

textile and garment sector identified crime as a major

problem in addition to having lost a relatively larger

amount to criminal activities (We also chose these

cities and sectors based on sample sizes. These are the

top two cities and sectors in terms of the number of

observations or with large sample size.). The pattern

of results is not significantly different from the one on

table 4 above except that crime related variables are

not significant in the metals sectors. Thus the impact

of crime on firm performance does not appear to

discriminate firms on the basis of location as found

under descriptive statistics above. The other

noticeable thing is that the domestic shipment

interaction variable is now consistently positive and

insignificant whilst the shipment dummy is only

negatively significant in Johannesburg. This could be

because losses made by firms in Johannesburg as a

result of domestic shipments crime are relatively

higher (see table 2 above). However sectoral level

results show that crime does not appear to have a

significant effect on firm performance. This is partly

corroborated by descriptive statistics in table 6,

appendix in that according to rankings, the metals

sectors is the 6th

sector that experienced high losses

due to theft, robbery and vandalism.

However, a negative relationship between crime

and firm performance exist in the metal sector even

though it appears weak.

Table 4. City and Sectoral level results using OLS

Variables

Johannesburg

Cape Town

Textile and

Garment

sector

Metal sector

Dependent variable

City dummies

Sectoral dummies Yes Yes No No

Export dummy

0.4336

(0.1235)***

0.4447

(0.2003)*

0.3775

(0.2339)

0.4689

(0.2335)

Crime dummy

-0.2442

(0.0356)***

-0.3879

(0.0897)***

-0.3997

(0.0886)***

-0.0398

(0.0587)

Domestic shipments crime dummy

-0.8914

(0.0567)**

-0.1467

(0.1760)

0.1144

(0.1231)

-0.0247

(0.3127)

Firms size

1.7965

(0.0853)***

1.4675

(0.1769)***

1.6189

(0.1315)***

1.8867

(0.1455)***

Firm age

0.1359

(0.0567)*

0.4489

(0.1254)***

0.3874

(0.1452)**

0.3568

(0.1443)**

Crime dummy * security paid

0.2897

(0.0352)***

0.2987

(0.0861)***

0.2723

(0.0339)***

-0.0657

(0.0782)

Domestic shipment dummy * security

Constant

No of observations

0.0987

(0.0756)

11.4003

(0.1165)***

2.8643

(4.8906)

13.6437

(0.5712)***

0.0789

(0.1123)

12.0779

(0.3349)***

0.1443

(0.1228)

11.8524

(0.3765)***

***significant at 1%; ** significant at 5%; * significant at 10%: Standard errors in parenthesis

5.1 Conclusions

The results in this study have shown that crime (theft,

robbery, vandalism, arson etc) has negative effects on

firm performance and this is a finding that does not

appear to discriminate in accordance to firms’

geographical location but however varies according to

sector. Results also suggest that investing in security

is important and can ameliorate the negative effect

that crime has on sales. Therefore firms should

strengthen their security measures and deterrent

punishment should be imposed on convicted criminals

by the courts or the affected firms so as to minimize

their negative effects on firm performance and general

economic growth in the country. However domestic

shipment crime though not significant at country level

appears to matter most to firms in Johannesburg.

Results suggest that the significance of this variable

depends on the size of shipment losses incurred by

firms in each region or city. Additionally, measures

should also be taken to help small sized firms in

containing crime since they appear to be the ones

mostly affected. Government or the business

community should encourage the development of

affordable and effective security systems to help the

growth of small businesses.

APPENDIX

Table 5. Crime and other firm characteristics

FIRM SIZE

Small Medium Large

ETHNICITY FIRM AGE

African Indian Asian European Other < 18yrs >18yrs

% of firms paying for security 68.3 83.3 91.3 61.6 64.9 61.1 82.1 76.9 66.4 80.3

Losses due to theft, robbery etc against the firm (% of sales)

Minimum

Maximum

4.35 4.00 3.17

0.10 0.10 0.10

20.0 40.0 20.0

Security costs (% of sales)

3.46 3.63 2.36

0.10 0.10 0.10

15.0 25.0 20.0

Domestic shipments lost due to theft (%)

Age of firms

Firm size

Firms complaining about crime as major obstacle

Firms complaining about corruption as major problem

5.79 7.14 3.69

0.10 0.10 0.10

40.0 70.0 50.0

19.2 5.50 31.9

163.1 53.9 195.9

38.6 35.1 35.8

40.4 26.3 27.6

Source: Author’s own calculations based on World Bank Investment Climate data

Table 6. Sectoral distribution of losses in the four cities

Textile

Garment

Chemical

Non metallic

Construction

Transport

Machinery

Electronics

Metals Rubber

Plastics

Other Food

% of firms paying for security 73.8 84.6 66.7 85.7 70.5 81.8 78.3 81.2

Losses due to theft, robbery etc against the firm (% of sales)

Minimum value

Maximum value

Security costs (% of sales) 2.15 2.66 0.30 3.35 3.61 3.38 3.63 3.91

Domestic shipments lost due to theft (%) 3.88 3.38 ---- 1.72 3.35 6.50 4.76 4.97

LOSSES DUE TO THEFT

Johannesburg

Cape Town

Port Elizabeth

Durban

% OF FIRMS PAYING FOR SECURITY

Johannesburg

Cape Town

Port Elizabeth

Durban

DOMESTIC SHIPMENT LOST DUE TO THEFT

Johannesburg

Cape Town

Port Elizabeth

Durban

Source: Author’s own calculations based on World Bank Investment Climate data

Table 7. Correlation matrix

| Sales Crime Security Crime2 Ethnicity Age Size Location

-------------+---------------------------------------------------------------------------

Sales | 1.0000

Crime | -0.0095 1.0000

| (0.7575)

Security | 0.1545* 0.2366* 1.0000

| (0.0000) (0.0000)

Crime2 | -0.0176 0.0892* 0.0477 1.0000

| (0.5676) (0.0037) (0.1210)

Ethnicity| 0.4448* -0.0194 0.0312 -0.0294 1.0000

| (0.0000) (0.5288) (0.3115) (0.3388)

Age | 0.0977* -0.0157 -0.0179 -0.0297 0.0397 1.0000

| (0.0015) (0.6096) (0.5605) (0.3345) (0.1976)

Size | 0.7734* -0.0128 0.0313 -0.0003 0.2702* 0.4447* 1.0000

| (0.0000) (0.6950) (0.3386) (0.9934) (0.0000) (0.0000)

Location | 0.0581 -0.0756* -0.2011* 0.1209* 0.0686* 0.0040 0.0153 1.0000

| (0.0592) (0.0140) (0.0000) (0.0001) (0.0258) (0.8966) (0.6400)

*significant at 5%; p- values in parenthesis.

Crime represents the proportion of sales lost due to theft, arson and vandalism;

Crime2 is a dummy representing those firms identifying crime to be a major problem.

Security is percentage of sales paid for firm security.

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Report No 26088

OWNERSHIP STRUCTURE AND DEBT POLICY OF TUNISIAN FIRMS

Hentati Fakher*, Bouri Abdelfettah**

Abstract

The relation between corporate governance and the financial decisions presents a rich subject but less pronounced in corporate finance. The purpose of this article is to study the impact of the ownership structure on the debt policy of the Tunisian companies. From the econometric tests applied to Tunisian data of panel, the results obtained corroborate the assumptions of the entrenchment theory. The ownership structure is unable to orient the management of the leaders towards the maximization of the shareholders' richness. The companies with concentrated property don't use the debt like mean to encourage the leader to act according to their interests. The remuneration system does not encourage the leaders to privilege the financing of the investments by debt. The presence of the financial institutions in the capital of the Tunisian companies does not influence the policy of financing of the company. They don't exert a particular role of control on the management of the leaders in place by the debt. Keywords: Ownership Concentration, Shareholding of the Leader, Financial Institutions, Debt Policy * Doctor and Teacher in finance at Economic Sciences and Management University of Sfax and member of laboratory of Corporate Finance and Financial Theory (COFFIT) E-mal: fakher.hentati@yahoo.fr ** Professor of Finance at Economic Sciences and Management University in Sfax, Tunisia and director of laboratory COFFIT E-mail: abdelfettah.bouri@fsegs.rnu.tn

1 Introduction

In the capitalist countries, various companies knew a

development in their strategies characterized, in

particular, by the diffusion of their shareholding and

the separation of their functions of property and

decision15

. Such a development led to examine about

the rationality of the strategic decisions made by the

leaders. The latter are in the centre of the decision-

making process and it is probable that their personal

strategies come to influence the performances of the

companies (Paquerot, 1997). The separation of the

functions of property and decision can create a

relation of agency who generates agency costs who

can influence the performance of the company

(Jensen and Meckling, 1976).

The study of the relation between the ownership

structure and the performance of the company is the

several theoretical debate object following problems

generated by such a separation. Indeed, the agency

theory provides that when the share of the rights of

ownership of the leader increases, it is encouraged to

allocate a significant effort with creative activities

such as the search for new profitable projects.

However, the entrenchment theory conceives that the

ownership structure constitutes a means to extend the

15 The function of decision corresponds to the function reserved for the leaders.

capacities of the leaders. The latter can express for

example by the abandonment of certain types of

profitable investments because of rigid controls to

which they are subjected. In addition, the neutrality

theory supports the idea that the ownership structure

does not have an influence on the performance of the

company. The presence of the heterogeneous factors

in the external environment of the company forces the

leaders to maximize the value of the shareholders.

The relation between the ownership structure

and the performance of the company was the subject

of an abundant literature since the thesis of Berle and

Means (1932). Nevertheless, the study of the relation

between the ownership structure and the debt policy

of the company were less pronounced (Florou and

Galarniotis, 2007). The principal objective of this

article is to study the impact of the ownership

structure on the debt policy of the Tunisian

companies.

The principal questions relating to this article are

as follows: Does the companies with concentrated

property count less, in their policy of financing, on the

debt? Is the debt policy of the company influenced by

the nature of the shareholder?

This paper is arranged as follows. After this

introduction, the second part provides the theoretical

framework for the study. The third part describes the

data and variables used in the empirical analyses. The

results of regression model are presented in the fourth

part. Finally, the paper discusses the conclusions

reached by the study and indicates directions for

future research.

2 Literature Review 2.1 The Ownership Structure as a Control Mode of the Leaders

Authors of the agency theory and those of the

government of company (Bethel and liebeskind, 1993;

Charreaux, 1997; Franks and Mayer, 1997; Ang, Stick

and Flax, 2001; Hiraki, Inoue, Ito, Kuroki, Masuda,

2003; Karathanassis and Drakos, 2004; Davies,

Hillier and McColgan, 2005) suppose that the

ownership structure constitutes part of the system of

corporate governance16

. It presents an effective

method of management control of the leaders. The

ownership concentration and the nature of

shareholders can answer the problem of incentive of

the controllers and contribute to the increase of the

performances of firm (Paquerot and Mtanios, 1999;

Lee, 2004).

The entrenchment theory, supported by Morck,

Shleifer and Vishny (1990), Paquerot and Mtanios ,

Alexandre and Paquerot, Fulghieri and Hodrick

(2005), stipulates that the leaders who have a solid

majority of the capital escape any control and can thus

manage the firm from a contrary of the maximization

of the value of the company. In this direction, the

leaders invest in credits specific to their know-how to

benefit from privileged information which makes it

possible to increase the job security, the remuneration

and the liberty of action to the detriment of the

shareholders (Coombes and Watson, 2000; Gompers,

Ishii and Metrick, 2003; Yermack, 2004). They do not

evaluate the investments compared to the created

richness, but compared to the advantages which they

will be able to withdraw for their entrenchment

strategy (Morck, Shleifer and Vishny, 1990; Dow and

Gorton, 1997; Subrahmanyam and Titman, 1999). In

addition, the neutrality theory thinks that the

ownership structure does not have an influence on the

performance of the company (Demsetz, 1983;

Demsetz and Lehn, 1985; Jensen and Warner,

1988; Agrawal and Knoeber, 1996; Himmelberg,

Habbond and Mitigated, 1999; Demsetz and

Villalonga, 2001). The pressures exerted by the

external environment of the company encourage the

16 Shleifer and Vishny (1997) define the corporate governance of the company like the whole of the mechanisms by which the contributors of capital guarantee the profitability of the action. Rajan and Zingales (2000) define the corporate governance as the whole of the mechanisms of allowance and exercise of the power. In the same direction, Rebrioux (2003) defines the corporate governance as the structuring and the exercise of the power in the organizations.

leaders to maximize the value of the company

(Raheja, 2005).

2.2 The Debt Policy of the Company:

Since Modigliani and Miller (1963), the debt was

emphasized in the policy of financing of the company.

These authors conclude that the tax advantage coming

from the character deductible from the interests leads

the companies to be involved in debt. The financial

literature attributes to the debt various functions.

Indeed, Ross (1977), who is at the origin of the signal

theory, regards the debt as a means of solving the

problems of the asymmetric information between the

better informed supposed leaders and the investors.

The level of debt constitutes a signal making it

possible to inform the investors of the real quality of

the investment opportunity (Ross, 1977). The debt can

be regarded as a means of pressure on the leaders

(Jensen, 1986). It can be also used to reduce the

asymmetric information ex- post between the

shareholders of a firm and its managers (Jensen and

Meckling, 1976). However, the financial literature

attributes to the debt harmful effects. In this prospect,

Altman (1984); Collongues (1977); Casta and Zerbib,

(1979); Malecot (1984); Gilson (1989, 1990) or

Wruck (1990) estimate that the excess of debt

constitutes a generator of bankruptcy costs, direct and

indirect costs17

. The In his article of 1984, Altman

conceives that the direct costs are related to the

process of rectification legal. He explains why the

bankruptcy generates indirect costs which are latter

involve a loss of confidence which results a loss of

customers before even the legal period of rectification

(Beaver, 1966; Altman, 1968).

The Pecking Order theory of capital structure

supposes, while being based on the assumption of

asymmetric information, that there is a classification

between the various modes of financing. Indeed,

Myers and Majluf (1984) think that the asymmetric

information generates phenomena of unfavourable

selection which affects the external request for

financing. To avoid undergoing this unfavourable

selection, the companies firstly finance their

investments by the self-financing. In the absence of

costs of failure, the leaders prefer the financial debt in

the long run at the expense of the emission of capital

to avoid revealing the information privileged at the

market. In the presence of costs of failure, the

company can be brought to emit capital to finance its

investments or to be freed of debts. The modeling of

Myers and Majluf (1984), was regarded as a play

intervening between the leaders who seek to

maximize the richness of the shareholders in place

17 In his article of 1984, Altman conceives that the direct costs are related to the process of rectification legal. He explains why the bankruptcy generates indirect costs which are costs of loss of credibility or loss of investment appropriateness.

and the contributors of capital, new shareholders or

creditors (Charreaux, 1992). The leaders act in favour

of the existing shareholders to the detriment of the

future shareholders (Narayanan, 1988). Consequently,

the financing of the company is ensured in priority, by

self-financing then by debt and finally by new issue of

capital. This hierarchy makes it possible to limit the

risks to be in situations of under investment, to limit

the distribution of dividends and to reduce the costs of

the capital by limiting the recourse to the loans

(Myers, 1984). Frank and Goyal (2003) tested the

relevance of the Pecking Order theory. Their

conclusions suggest that this theory "functions better"

within the firms characterized by a higher level of

entrenchment of their leaders. The order of financing

of these firms decides as follows: self-financing, debt

and finally stockholders' equity.

The classification of the Pecking Order theory is

the same one as that retained by the theory of the

cycle of life. The latter conceives that the dynamic

companies will have need for financing external to

finance their growth. For the introduction period, the

only source of financing available is the own capital

stocks. However, these firms are characterized by a

fast passage to the phase of growth. This phase is

generally financed by the commercial debts or of the

banking debts in the short term. These short- term

financings can generate risks of illiquidity also since

the very high growth rates.

In the model of Cornell and Shapiro (1987), the

objective of the leader is to maximize the value of the

firm. For the other partners (lenders, customers....),

the objective is to minimize the risks related to the

purchase or the financing of the specific investments.

The achievement of these two objectives supposes the

minimization of the costs of implied contracts. To

minimize the costs of these contracts, the firm may

find it beneficial not to exhaust its capacities of self-

financing and debt before the date at which it must

honour its implied contracts. Indeed, on this date, the

issue of shares can be very expensive. Thus, the

support hierarchy is: self-financing, increase in the

capital and finally debt.

In the framework of the agency theory, Fama

(1980) examined the structure of the whole of the

contracts which intervene in the operation of the firm.

He noted that the structures of financing are always

mixed whatever the organisational form, with a pre-

eminence of the debts. He insisted on the role of the

control of the banking in order to carry out the

objectives of the contracting agents. According to the

theory of Free Cash-flows, the recourse to the

financing by debt obliges the leader to manage the

firm in an effective way to avoid the bankruptcy in

order to face its engagements (Jensen, 1986 and Stulz,

1990). In revenge, Black and Schloes (1973), Galai

and Masulis (1976) think that the presence of the

debts limits the motivations of the shareholders and

the leaders. The debt constitutes a source of conflict

between these two partners giving rise to costs of

agency of debt.

While referring to the theory of the transaction

costs, Williamson (1981) analyzes the decision of

financing as a particular transaction where the degree

of specificity of the financed credit plays a central

part. The debt or the own capital stocks is not

regarded any more instruments financial but as

'governorship structure' of the particular transaction

(Ghertman and Quelin, 1995) which constitutes the

financing of an investment.

According to the theory of Conventions, the

objective consists in establishing conventions and

agreements making it possible to face uncertainty

inherent in the relation of financing in a way

considered to be acceptable and effective by the parts

concerned (Rivaud-Danset, 1995). Thus, by reference

to conventions of financing, the managers of company

prefer the self-financing rather than the loan. The

theory of the target ratio conceives that the companies

adjust their capitalization towards an optimal lever of

debt by emitting debts when their debt ratio is lower

than the target ratio and while being freed of debts

when it is higher to him (Hovakinian, Opler and

Titman, 2001). The deviations of the target ratio

following accumulations of benefit or losses are

compensated by the dual emissions of actions and

debts (Hovakinian, Hovakinian and Tehranian, 2004).

3 Data and methodology

3.1. Procedure

The sample for the present study consisted of

Tunisian firms listed on the Stock Exchange market.

These firms operate in various branches (industry,

business, tourism and transportation). The firms

belonging to the financial sector like the banks, the

insurances and the leasing companies were not

included in this sample. The statistics come from the

data stock exchange published by the financial market

over a period of seven years from 1999 until 2005.

3.2. Measures

The debt policy. According to the study of Zhang, He

and Chen (2008), the debt policy refers to the ratio of

total debt to total assets (TDAS).

• The ownership structure: According to the

agency theory, the ownership structure is

presented by the ownership concentration, the

shareholding of the leader and of the financial

institutions.

• The ownership concentration. The ownership

concentration constitutes a control means of the

leaders by the shareholders and contributes to

the increase in the performances of the firm

(Paquerot and Mtanios, 1999). According to

Godard (2001) and Shabou (2003), the level of

ownership concentration refers to the percentage

of the capital held by the first shareholder

(PCFS).

• The shareholding of the leaders: According to

the agency theory, the shareholding of the

leaders was regarded as a mean to reduce the

cost of control supported by the shareholders and

to encourage the leaders to contribute to the

creation of shareholders value (Jensen and

Meckling, 1976). According to Charreaux

(1987), the shareholding of the leaders refers to

the percentage of capital detained by the leaders.

This percentage is calculated by dividing the

number of shares detained by the leaders by total

number of shares of firm (NSDL).

• The shareholding of the financial institutions:

The financial institutions represent the best

shareholders having the resources necessary to

acquire important blocks of actions in the large

companies. They make it possible to solve

internal conflicts of interests in the firms

(Nekhili, 1994), to decrease the problems of

agency (Schwiete and Weigand, 1997) and to

influence the decisions taken by the leaders in

order to maximize the value of the company

(Lapointe, 2000; Yafeh and Yosha, 2003).

According to Patry and Poitevin (1995), the

shareholding financial institutions refer to the

percentage of the capital held by the financial

institutions. It measured by dividing the number

of shares held by the financial institutions to the

total number of the shares of firms (NSFI).

3.3 Regression model

The relationship between the ownership structure and

the debt policy was thus estimated using the following

regression model:

TDAS it = e + β1 × PCFSit + β2 × NSDLit + β3 ×

NSFIit + ɛit

in which:

TDAS it: The ratio of total debt to total assets for

firm i at time t; PCFSit: The percentage of the capital

held by the first shareholder for firm i at time t;

NSDL it: The number of shares detained by the

leaders dividing by total number of shares of firm i at

time t;

NSFI it: The number of shares held by the

financial institutions dividing by the total number of

the shares of firm i at time t;

e, β1, β2 and β3 constitute unknown parameter of

model; ɛ: the error term.

4 Results

4.1 Descriptive statistics

Descriptive statistics for the sample of firms are

reported in Table 1, Table 2, Table 3 and Table 4. In

fact, The Table 1 shows that the Tunisian companies

have an average level of concentration of about

37,74%. This average degree of concentration appears

weak compared to that of the French companies

which is 50% (This result comes from the study from

Broye and Schatt (2003) applied out of 402 French

companies with dimensions between 1986 and 2000.).

In Canada, Short and Keasey (1997) found that 60%

of the 500 larger companies have ownership

concentrated by only one shareholder. Moreover, the

principal known shareholders have the degree of

concentration between 0,66% and 83,75% of the

capital. In this context, the first five shareholders hold

on average more than 74% of the shares. However,

Demsetz and Lehn (1985) show, on a sample made up

of 511 American companies, that the five principal

shareholders hold on average 24,8%. Charreaux and

Pitol-belin (1985) found that the principal known

shareholders hold on average 52%. Fendjo (2006)

showed that the ownership in the Cameroonian

compagnies is strongly concentrated. The first five

shareholders are held with more than 50% of the

shares of 67% of the companies.

Table 1. Share of the capital of the first five shareholders

Variable Average Cumulated average Standard

deviation

Min Max

Share of the first shareholder 37,74 % 37,74 % 18,50 % 14 % 83,75 %

Share of the second shareholder 15,11 % 52,85 % 6,63 % 3 % 30,70 %

Share of the third shareholder 10,00 % 62,85 % 4,71 % 1,7 % 20,50 %

Share of the fourth shareholder 6,78 % 69,63 % 4,15 % 1 % 19,99 %

Share of the fifth shareholder 4,76 % 74,39 % 2,49 % 0,66 % 8,92 %

The Table 2 shows that the majority of the

Tunisian companies of the sample have a level of

ownership concentration lower than 50%. In this

framework, 70,4% of the sample companies have a

percentage of the capital held by the first shareholder

lower than 50%. On the other hand, 29,6% of

companies have a level of concentration exceeding

Table 2. Distribution of the companies' frequency

Concentration level Percentage of the companies 0 to 50% 70,4 %

More than 50% 29,6%

The Table 3 shows that the Tunisian leaders hold

less than 5% of the shares of 58% of the companies of

the sample. They hold a share ranging between 5%

and 25% of the capital of 25% of the companies. They

hold, also, more than 25 % of capital of 17% of the

companies of the sample. The average percentage of

capital represented by the leaders in these companies

is of 33,82%. This percentage is higher than that in

the French and American companies. According to

Charreaux and Pitol-belin (1985), it is to the

maximum of 20%. For the United States, the share of

the property which is held by the leaders and the

administrators is about 30% (Morck, Shleifer and

Vishny, 1988).

Table 3. Distribution of the sample according to the shareholding of the leaders

The proportion of shares held by the leaders Percentage of the companies

0 to 5% 58 % 5% to 25% 25 %

More than 25% 17 %

Moreover, the Table 4 shows that the companies

in which the participation of the financial institutions

is higher than 50% (HPFI) present 10,71% of the

sample companies. The financial institutions have

strong participation in the capital of these companies

exceeding 69%. The companies in which the

participation of the financial institutions is lower than

50% (LPFI) are about 89,29% of the companies.

These companies have a weak participation of the

financial institutions in their capital which is about

16,21%. In France, the search for Morin and

Rigamonti (2002) revealed that the financial

institutions hold the greatest proportion of capital in

many companies. In Great Britain, Berenheim (1994)

noted that 75% of the shares were held by such

institutions. In the United States, Demsetz and lehn

(1985), on a sample of 511 firms, find that the

percentage of shares held by the first five financial

institutions is 18,4%. Patry and Poitevin (1995) found

that the financial institutions held 53% of the shares

of firms in 1992.

Table 4. Distribution of the sample according to the participation of the financial institutions

Group Percentage of companies Average of participation Standard deviation of participation

HPFI 10,71% 69,7 % 13,14 % LPFI 89,29% 16,21 % 11,33 %

4.2 Regression results

The realization of the statistics of Fisher associated

with the test of constant homogeneity shows that the

regression model in Table 5 includes individual

effects. The probability of the test of Hausman is

higher than the conventional threshold, which implies

that this model represents a model of panel with

random individual effects, which is more appropriate

than the model of fixed effects. The coefficients of the

regression model can be estimated by the method of

generalized least squares (MCG). According to the

test of Breusch-Pagan, the homoscedasticity

assumption is not justified. The variance of residual

error of this model should not be constant. Moreover,

there is no autocorrelation of the individuals errors

because the value of Durbin- Watson (Dw =

1,6912409) is lower than (Dl=1,73).

Table 5. Regression model results

Variable Coefficients Test Z Constant 0.2087422 (3.70)*** PCFS -0.3778822 (-3.12)*** NSDL 0.0273701 (0.28)

NSFI 0.0617449 (0.46)

Wald chi2 Hausman Test Test of Breusch-Pagan Test of Durbin Watson (9.87)** (3.35) (42.43)*** 1.6912409

**represents being significant at the level of 5%.

***represents being significant at the level of 1%.

From the econometric tests applied to Tunisian

data of panel, the results obtained show that the

explanatory capacity of the regression model is, in

general, satisfactory (Prob > chi2 = 0.0197). The

ownership concentration has an incidence negative (-

0,377882) and statistically significant to the threshold

of 1% on the debt ratio. In this context, an increase in

1% of the capital held by the first shareholder will

involve a reduction in the debt ratio of 0.377882. This

result confirms the study of Bhojraj and Sengupta

(2003), Anderson, Mansi and Reeb (2003). Thus, the

Tunisian companies with ownership concentrated

count less on the debt policy to finance their

investments. They don't use the debt as mode of

financing to encourage the leader to act according to

their interests. The percentage of the capital held by

the leaders has an impact positive (0,0273701) but not

statistically significant on the debt ratio. This result

rejects the assumptions of Kim and Sorensen (1986),

Agrawal and Mandelker (1990), Smith and Watts

(1992), Mehran (1992) and Gaver (1993). The

shareholding of the leaders doesn't constitute an

incentive to carry out investments financed firstly by

debt. Such remuneration system doesn't represent an

efficient tool used by the

5 Conclusion

The objective of this study was to test the impact of

the ownership structure on the debt policy of the

Tunisian companies over the period 1999 - 2005. The

realization of statistics results shows that the Tunisian

companies have an average level of concentration.

The majority of these companies have a low level of

ownership concentration. The shareholding of the

leaders in the majority of the companies is weak.

However, the minority of these companies having a

strong participation of the financial institutions.

From the econometric tests applied to Tunisian

data of panel, the results obtained corroborate the

assumptions of the entrenchment theory. The

ownership structure is unable to orient the

management of the leaders towards the maximization

of the shareholders' richness. Firstly, the companies

with concentrated property don't use the debt like

mean to encourage the leader to act according to their

interests. Secondly, the companies which apply a

remuneration system by the formula of the

shareholding of the leaders in their capital don't

encourage the leaders to privilege the financing of the

investments by debt. They don't exert a particular role

of control on the management of the leaders in place

by the debt. Finally, the presence of the financial

institutions in the capital of the Tunisian companies

doesn't influence the decisions of financing of the

management of the firm in order to maximize the

shareholders' richness. Their presence doesn't improve

the efficient of control exerted on the management of

leaders. This inefficiency control can lead the leader

to realize the personal goals to the prejudice of

shareholders' richness.shareholders in order to

intensify their control on the management of the

leaders by debt. In addition, the percentage of the

capital held by the financial institutions has an effect

positive (0,0617449) but not statistically significant

on the debt ratio what rejects the empirical work of

Aoki (1991) and Nivoix (2004). The presence of the

financial institutions in the capital can't lead to

influence the management of the firm and to finance

its investments by a mode privileging the loans rater

than the own capital stocks. These shareholders don't

exert a particular role of control on the management

of the leaders in place by the debt.

Tunisia is a country that has companies which

their ownership is concentrated. These familial

companies have a small debt ratio; this can be

explained by the fear of the bankruptcy or the loss of

control of the company. The boards of directors apply

remuneration system for their leaders by the formula

of shareholding in order to act according to the

interest of shareholders. Such remuneration system

doesn't incite the leaders to create the value of

shareholders. The leaders seek to increase their own

wellbeing by other sources of remunerations like the

wages and others advantages to the detriment of the

richness of minority shareholders. The financial

institutions are not incited to realize the goals of the

companies and to reinforce their control on the leaders

by the debt policy. The asymmetric information

constructed by the leaders encourages them not to

exert their work correctly.

In general, this study leads us to wonder about the

solutions that permit to reinforce the efficiency of the

control of the Tunisian companies on the management

of their leaders. It is preferable to institute a board of

directors composed mainly of external administrators

and to implicate properly the financial institutions in

the corporate governance also since these investors

are regarded as the shareholders the more active and

the more apt than others to exert the control on the

managerial decisions and the pressure on the leaders

in order to oblige them to adopt the strategy of firm.

Several future research directions would add to

our understanding of the efficiency control of

Tunisian companies on the management of their

leaders. First, it is necessary to replicate this study in

other samples of firms not listed on the Stock

Exchange market. Second, it can examine the

influence of the other partners of the firm on the debt

policy. Finally, it is preferable to introduce others

variables of governance in order to know their

influence on the financial decisions like the board of

directors and the markets of external discipline.

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THE INTRA-INDUSTRY EFFECTS OF CHAPTER 11 FILINGS: EVIDENCE FROM ANALYSTS' EARNINGS FORECAST

REVISIONS

Gary L. Caton*, Jeffrey Donaldson**, Jeremy Goh***

Abstract

Shareholders suffer huge losses when firms they own file Chapter 11. Interestingly, even shareholders of rival companies experience statistically significant losses. We examine how the bad news associated with a bankruptcy filing is transferred to the filing firm's rivals. Using revisions in analysts' earnings forecasts as a proxy for changes in expected future cash flows, we find that after a bankruptcy filing the market revises downward its cash flow expectations for rivals. Regression analysis confirms a positive relation between changes in expected cash flow and stock market reactions. These findings are consistent with our hypothesis that bad news associated with bankruptcy filings are transferred to rivals through reductions in expected future cash flows. Keywords: Chapter 11, Sharegolders, Bankruptcy Filings, Rivals * Corresponding author, Montana State University, College of Business Bozeman, MT 59717-3040 Tel.: (406) 994-4421 E-mail: gary.caton@montana.edu ** College of Business University of Tampa 401 Kennedy Blvd. Tampa, FL 33606 Tel.: (813) 253-6221 x 3282 E-mail: jdonaldson@.ut.edu *** Singapore Management University, 50 Stamford Road Lee Kong Chian School of Business Singapore 178899 Tel.: + (65) 6828-0739 E-mail: jeremygoh@smu.edu.sg

Introduction

Previous studies reveal that the market discounts the

wealth of shareholders upon the announcement of a

bankruptcy filing. For instance, Bradley and

Rosenzweig (1992) report significant abnormal

returns of -24.34% for a five-day period surrounding

Chapter 11 filings. Lang and Stulz (1992) examine the

effect of bankruptcy filings on the rivals of filing

companies. They hypothesize that information

contained in announcements of bankruptcy filings

may have positive or negative implications for rivals

and coin the term competitive effect to describe the

former and contagion effect to describe the latter.

Specifically, the competitive effect occurs if the

bankruptcy indicates a weakness in the filing

company alone that can be exploited for the

competitive benefit of its rivals. Equity values of

rivals gaining this competitive benefit are expected to

react positively. On the other hand, the contagion

effect occurs if the bankruptcy filing indicates an

industry wide weakness that may spread like a

contagion to rivals because of their similar cash flow

characteristics. Equity values of rivals catching a

financial virus are expected to react negatively to

bankruptcy filings. Lang and Stulz's primary finding

is that bankruptcy announcements decrease the value

of a portfolio comprised of the equity of rival

companies by 1 percent on average, and conclude that

contagion effects dominate competitive effects for

rival companies.

Our primary focus is to examine the underlying

reason this negative valuation effect for announcing

companies is transferred to industry competitors. A

paper similar to ours in spirit is Ferris, Jayaraman, and

Makhija (1997) who separate rival companies into

two groups: those that file for bankruptcy themselves

over the subsequent three years, and those that do not.

Their premise is that at the original announcement,

the market makes a prediction of the likelihood of

future bankruptcy for the rival companies. The

authors then use the actual reported bankruptcies over

the subsequent three years as an indicator variable for

the market's prediction at the original Chapter 11

filing date. Those companies the market predicts will

fail (i.e., those that actually fail over the next three

years) are expected to suffer declines in value due to

the contagion effect, while those predicted to continue

operations (i.e., those that do not fail over the next

three years) are expected to gain in value due to the

competitive effect. Similar to Lang and Stulz, Ferris,

Jayaraman, and Makhija report a significant average

announcement effect of -0.56 percent for their full

sample over the three days surrounding the filing.

However, when they split the sample based on their

prediction criterion, the equity of companies that

subsequently file drop an average of -4.68 percent in

value, while the equity of those that do not

subsequently file drop - 0.49 percent. Since both

numbers are statistically significant, they conclude

that the contagion effect dominates the competitive

effect even for those companies predicted to remain

viable over the next three years.

Although the equity of both groups in the Ferris,

Jayaraman, and Makhija sample show statistically

significant declines in value, the magnitude of the

difference in average revaluations is consistent with

the idea that market expectations for future

bankruptcy affect current announcement period

returns. However, their proxy for market expectations,

i.e., whether the firm actually declares bankruptcy

over the subsequent three years or not, is not available

a priori. We hypothesize that rather than making

yes/no predictions of future bankruptcy for each rival,

market participants simply revise their estimates of

future cash flows. Unexpected decreases in expected

future cash flows due to the new information should

produce negative changes in firm values. Thus our

primary question is the following: Does a bankruptcy

filing by a firm affect the expected future cash flows

of industry rivals? We use changes in analysts'

earnings forecasts to indicate changes in the market's

expected future cash flows for these companies. If

earnings forecasts for rival companies are revised

after a bankruptcy filing then the equity values of

those companies would be expected to change as well.

Our results support our hypothesis. But first,

similar to Bradley and Rosenzweig (1992), we find

stock market reactions for our sample of 183

companies filing a bankruptcy petition that average -

28.83% for the three days surrounding the

announcement. In addition, we find results that

support both Lang and Stulz (1992) and Ferris,

Jayaraman, and Makhija (1997). For our portfolio

comprised of 3,250 rival companies representing 121

different industries we find significantly negative

stock price reactions that average -0.51 percent. Our

contribution, however, is an analysis of abnormal

earnings forecast revisions. We find these revisions to

be both negative and significant for rivals of failed

companies. This finding is consistent with our

hypothesis that the transfer of negative information

from filing companies to their rivals is due to a

decrease in expected future cash flows, a change in

expectation created by new information regarding the

entire industry provided by the bankruptcy

announcement of a single member therein. Finally, we

use regression analysis to formally test for a

significant relation between the market reactions and

earnings forecast revisions of individual rival

companies. The negative forecast revisions for rivals,

their respective market reactions, and our cross-

sectional regression results showing a positive and

significant relation between the two, are consistent

with our hypothesis that the contagion effect is

transmitted from filing companies to rivals through

revisions in rivals' future cash flows, revisions that

were made as a result of the original Chapter 11

filing.

Sample selection

We compiled our sample of companies filing for

bankruptcy primarily through a search of the

Lexis/Nexus files. Secondary sources include the

Wall Street Journal Index, and information obtained

from both Indepth Data Corporation and New

Generation Research Company. Our sample

companies filed for bankruptcy between October 1,

1979 (the date the Bankruptcy Reform Act was

implemented) and December 31, 1994. To be

included in the final sample, we require sufficient data

in the Center for Research in Security Prices (CRSP)

data files. The resulting sample of Chapter 11 filing

companies includes 183 companies operating in 121

different four-digit Standard Industrial Classification

(SIC) codes. Table 1 presents a time series of the

sample of filing companies and shows that the mid-

1980s was a time of few failures, while the rate of

firm failure steadily increased during the early 1990s.

The top half of table 2 presents descriptive statistics

for the filing companies. The mean and median

market values of equity of the 183 filing companies

are $65.8 million and $12.5 million, respectively, with

a standard deviation of $452.4 million. Apparently,

the market value of filing companies is relatively

small as might be expected of companies filing

bankruptcy.

An analysis of intra-industry effects of Chapter

11 filings requires, by definition, data from the filing

company's industry rivals. Following Lang and Stulz

(1992), we define a filing company's industry rivals as

all companies with the same four-digit SIC code. In

order to qualify for our sample of rivals a company

must have sufficient stock return data, but in addition,

it must have sufficient earnings forecast data in the

Institutional Brokers Estimation System (IBES)

earnings forecast database for the 25 months

surrounding the Chapter 11 filing. Previous studies

have shown that the IBES database can contain errors.

Following Ederington and Goh (1998), we eliminate a

firm from our sample if its earnings forecast revision

(defined below) is more than five standard deviations

from the overall mean over all firms in the IBES

database for any given month. After the initial round

of data eliminations, the standard deviation is

recalculated and again firms with observations outside

five standard deviations are eliminated. After

applying these various requirements our final sample

of rivals includes 3,250 rivals in those same 121

industries. The bottom half of table 2 reports

summary statistics for the rival companies indicating

that they are very similar in size to the filing

companies. Their mean and median market value of

equity is $60.45 million and $11.31 million,

respectively, with a standard deviation of $265.16,

about half that of the filing companies. In addition,

the mean and median number of rivals competing

with each filing company is 17.75 rivals and 6 rivals,

respectively, with a range from one rival in one of the

four-digit industries to 210 rivals in another industry.

Table 1. Distribution of bankruptcy filings by year

Year Number of filings

1980 6 1981 6 1982 16

1983 12

1984 3 1985 2

1986 0 1987 3

1988 3 1989 10

1990 12

1991 37 1992 26

1993 23 1994 24

Total 183 Filing firms are a sample of 183 companies that filed for Chapter 11 bankruptcy protection between October 1, 1979, and

December 31, 1994.

Stock Market Reaction

We compute standardized abnormal returns following

Patel (1976) as modified by Mikkelson and Partch

(1988). Day 0 is defined as the date the bankruptcy

petition is filed with the courts. The abnormal returns

are the difference between the actual return and an

expected return generated by the market model. We

estimate the parameters for the market model using

daily returns data from day t-251 to day t-505 (We

use this estimation period to prevent biased test

results since we look at the cumulative abnormal

returns in the pre-filing period from 250 days to 31

days prior to the filing.). Abnormal returns are

generated for both the filing companies and an

equally weighted portfolio of rival companies.

Finally, we compute a Z- statistic and use it to test for

statistical significance of standardized abnormal

returns and cumulative standard abnormal returns

(CAR).

Table 2. Summary statistics of firms filing Chapter 11 and their industry rivals

Filing Firms:

Mean market value of filing firms

Median market value of filing firms

Standard Deviation of market value of filing firms

$65.80 million

$12.46 million

$452.38 million

Rival Firms:

Mean market value of rival firms

Median market value of rival firms

Standard deviation of market value of rival firms

$60.45 million

$11.31 million

$265.16 million

Mean number of rivals per event

Median number of rivals per event

Minimum number of rivals per event

Maximum number of rivals per event

17.75 rivals

6 rivals

1 rivals

210 rivals

Filing firms are a sample of 183 companies that filed for Chapter 11 bankruptcy protection between October 1, 1979, and

December 31, 1994. Rival firms are the 3,250 companies whose four-digit primary Standard Industrial Classification code is

the same as that of the filing firms.

Table 3 reports the stock market reaction to a

Chapter 11 bankruptcy filing for both the filing

companies and their rivals. Consistent with earlier

studies, we observe a large and significant negative

stock market reaction to announcements of a

bankruptcy filing for the filing companies. The three-

day CAR (-1 to +1) for the full sample of 183 filing

companies is -28.83 percent with z = - 43.79.

Moreover, 78 percent of the abnormal returns over

this three-day period are negative, which is

significantly different from the null hypothesis of 50

percent. Clearly, as shown in previous studies, the

market views bankruptcy announcements as important

informational events for the filing companies.

Table 3. Effects of Chapter 11 filings on both the filing and rival firms' stock prices

Day AAR

z-statistic Percent

Positive

z-statistic AAR

z-statistic Percent

Positive

z-statistic

-10 -2.60 -8.04*** 39% -1.95* -0.03 -0.76 45% -0.57

-9 -1.80 -6.33*** 37% -2.38** -0.02 -0.86 43% -2.34**

-8 -1.20 -0.75 41% -1.29 -0.30 -3.25*** 42% -2 70***

-7 0.60 0.61 45% -0.43 -0.09 -1.11 46% 0.26

-6 -0.69 -2.45** 46% 0.03 -0.04 -1.08 43% -2.20**

-5 -1.23 -3.82*** 42% -1.12 0.09 1.43 48% 1.28

-4 -3.06 -7.84*** 34% -3.39*** -0.20 -0.54 46% 0.15

-3 -1.81 -5.68*** 41% -1.44 -0.10 -1.05 46% -0.07

-2 -2.71 -8.84*** 34% -3 14*** -0.31 -1.72* 44% -1.42

-1 -0.68 -0.55 40% -1.53 -0.11 -1.70* 46% 0.1

0 -13.38 -40.50*** 28% -4.65*** -0.05 -0.86 45% -0.46

1 -14.77 -35.24*** 33% -3.43*** -0.36 -3.41*** 45% -0.73

2 3.89 13.29*** 46% -0.13 0.10 0.05 45% -1.01

3 4.51 13.35*** 47% 0.2 -0.15 -0.87 44% -1.48

4 1.73 4.52*** 46% -0.12 0.03 -0.13 47% 0.54

5 0.88 0.5 48% 0.35 -0.02 -1.35 46% -0.15

6 3.34 7.88*** 53% 1.55 -0.29 -2.22** 47% 0.7

7 0.98 6.64*** 48% 0.5 0.05 1.59 44% -1.48

8 1.45 3.85*** 47% 0.27 -0.26 -2.00** 45% -0.46

9 0.64 2.50** 54% 1.79* -0.22 -1.72* 45% -0.74

10 -3.10 -7.73*** 41% -1.22 0.39 2.48** 48% 1.30

Cumulative

Returns

-31,-250 -15.30 -6.56*** 36% -2 75*** -4.83 -5.01*** 48% 1.36

-1,1 -28.83 -43.79*** 22% -6 11*** -0.51 -3.44*** 42% -3 21***

31,250 107.31 13.20*** 67% 4.78*** -7.32 -5.31*** 45% -0.54

*** Indicates significance at the 0.01 level.

** Indicates significance at the 0.05 level.

* Indicates significance at the 0.10 level.

We estimate average abnormal returns based on the market model around the announcement day (Day 0) of chapter 11

filings. The market model is estimated over the (-251,-505) period. The sample includes 183 firms filing for Chapter 11

protection from creditors between October 1, 1980, and December 31, 1994, and 3,250 rival firms.

The equally weighted portfolio of rival

companies has an average three-day CAR that equals

-0.51 percent with z = -3.34. In addition, 58 percent of

the abnormal returns over this period are negative,

which is significantly different from 50 percent.

These finding for the rival companies is similar to

both Lang and Stulz, who report a - 1.07 percent

reaction over the eleven days surrounding the filing,

and Ferris, Jayaraman, and Makhija, who report a -

0.56 percent reaction over the same three-day event

window as ours, both of which have different sample

periods. Due to their magnitude, these average

cumulative abnormal stock returns for rival

companies do not appear to be economically

significant in percentage terms, but as pointed out by

Ferris, Jayaraman, and Makhija, they are significant

in dollar terms. This is because the sum of the equity

value of the competitors is much larger than that of

the companies filing for bankruptcy. In fact, Ferris, et

al, report that for their sample the competitor portfolio

loses $3.32 of equity value on average for every

dollar of equity value lost by the bankrupt companies.

These event study findings indicate that

bankruptcy filings are bad news, on average, for both

the companies making the filing and their industry

rivals. We now turn our focus to determining how this

bad news is transmitted to the rivals hypothesizing

that the transfer of bad news is made through a

revision of the cash flow estimations of the rivals

upon the bankruptcy filing. The next section presents

our methodology for testing this hypothesis, and the

results of that test.

Abnormal Earnings Forecast Revisions

To judge whether or not the market reaction for rival

companies is due to changes in expected cash flow we

need a proxy for those expectations. Earnings analysts

help set the market's initial level of expected cash

flows with their initial forecasts of future earnings.

Similarly, revisions in analyst's forecasts help to reset

cash flow expectations to some new level. We use

reported earnings forecast revisions subsequent to a

bankruptcy filing as a proxy for changes in the

market's expectations of future cash flow from the

rival companies. Significant earnings revisions after a

filing are consistent with the hypothesis that bad news

for bankrupt companies is transferred to their rivals

through a change in the market's cash flow

expectations for those companies.

Following Brous (1992), we measure earnings

forecast revisions (FR) using the following equation:

FR i,t = [(F i,t – F i,t-1 )/ Pi] × 100 (1)

where Fi,t is the median analyst earnings

forecast in month t for the annual earnings per share

of firm i for the current fiscal year, and Pi is the stock

price for firm i six months prior to the bankruptcy

filing

Mean values of FR are reported in column two

of table 4 from six months before, through six months

after the filings, as well as cumulated forecast

revisions in the bottom two rows, while their t-

statistics are in column three. As shown there, large

and significant negative revisions in analysts' earnings

forecasts are observed in every month both prior to

and after Chapter 11 filings for rivals of filing

companies.

Table 4. Abnormal earnings forecast revisions for rival firms

Month FR T AFR t

-6 -0.245 -6.70*** -0.025 -0.79 -5 -0.318 -7 00*** -0.127 -2.72***

-4 -0.345 -7 27*** -0.149 -3.13***

-3 -0.398 -7.68*** -0.214 -4.09*** -2 -0.296 -5.80*** -0.025 -0.56

-1 -0.282 -7 27*** -0.035 -0.90 0 -0.286 -6.82*** -0.087 -2.19**

1 -0.232 -6.21*** 0.002 0.06

2 -0.197 -5.17*** 0.012 0.32 3 -0.285 -6.88*** -0.094 -2.22**

4 -0.241 -5.67*** -0.051 -1.27 5 -0.240 -4.93*** -0.040 -0.87

6 -0.176 -4.56*** 0.051 1.36

Cumulative Forecast Revisions

-6,-1 -1.884 -12.18*** -0.575 -4.89*** 0,5 -1.436 -11.03*** -0.218 -2.17**

For our sample of 3,250 rival companies, we define the forecast revision, FR for Month t as the mean of analysts' forecasts

reported in the IBES database in month t less the mean of analysts' forecast in month t-1, scaled by stock price at the end of

the month preceding the chapter 11 filing announcement. We define the adjusted forecast revision, AFR for month t as the

scaled forecast revision for month t less the expected forecast revision for month t. The t statistics test the hypothesis that the

mean analysts' earnings forecast revision is different from 0.

Unadjusted forecast revisions such as these,

however, are biased. O'Brien (1988) shows that

earnings forecasts systematically decrease month after

month until the actual earnings are announced by the

firm. This implies that forecasters are systematically

over optimistic when making their first earnings

forecast for a company, and that they never fully

correct for that over optimism. A different type of

bias in unadjusted forecast revisions is reported by

Brous (1992) who shows that the median monthly

earnings forecast revisions for a specific company

across all analysts covering that company tend to be

serially correlated. That is, if favorable new

information arrives that leads to an upward revision in

a company's average earnings forecast, for example,

that average will tend to continue to rise in future

months. Brous argues that this serial correlation is due

to the fact that analysts typically update their forecasts

for any specific company only every four to five

months. That is, in any given month only about 20

percent of forecasts are updated. To test our

hypothesis for intra-industry information transfer

effects of bankruptcy filings, we need a measure of

forecast revisions after correcting for these two

effects. This measure we call the abnormal earnings

forecast revision (AFR).

We follow the methodology of Caton and Goh

(2003), which is a modified version of that employed

by Ederington and Goh and Brous, to isolate surprise

forecast revisions. We start by randomly choosing

500 companies from the IBES database. Then, for

each company we randomly select a 25-month period

between January 1984 and December 1990. Finally,

we pool the resulting data and estimate the following

equation:

Fr i,t = -.093 + .085 FR i,t-1 + .085 FR i,t-2 + .081

FR i,t-3 + .072 FR i,t-4 + .058 FR i, t-5 +

.040 FR i, t-6 + u i,t

The negative intercept in this equation, -.093, is

consistent with the finding by O'Brien that absent new

information, analysts tend to reduce their forecasts

over time. For instance, for a firm with a P/E ratio of

20, the negative intercept implies an average revision

of -1.86 percent (20 x .093% ) every month. The

positive coefficients on the lagged forecast revisions

are consistent with Brouse's finding that revisions in

the median forecast tend to be followed by further

revisions of the same sign as more analysts update

their forecasts. For instance, the coefficients for the

FRi;t-i , for all i = 1-6, indicate that a doubling of the

median forecast one month tends to be followed by an

increase of about 8.5 percent the following month, 8.5

percent two months hence, 8.1 percent three months

later, and so on.

Using the parameters from equation 2 and each

firm's past values of FR, we calculate the expected

forecast revision, E(FRi,t), for each month t. We then

define the abnormal earnings forecast revision for

month t, AFRi,t, as the difference between the actual

revision in the consensus forecast in month t and its

expected forecast revision calculated as outlined

above. Specifically:

AFR i,t = FR i,t - E(FR i,t) (3)

Columns four and five of table 4 presents the

abnormal earnings forecast revisions for the rivals of

companies filing for bankruptcy. First note the

significant negative abnormal forecast revision of -

0.087 in month zero, the Chapter 11 filing month.

This is consistent with our hypothesis that Chapter 11

filing produces changes in the market's cash flow

expectaions for rivals which then lead to abnormal

equity returns. As mentioned above, Brouse reports

that because analysts cover more companies than they

can updated in any given month, that it may take up to

six months for news to be fully reflected in the

forecasts of all analysts' following a particular

compmany. For this reason we cumulate the abnormal

forecast revisions for the six months from the filing

month to month +5. The mean cumulative abnormal

forecast revision over this period is -0.218, which is

statistically significant below the 5 percent level. This

result is consistent with the result for the filing month

itself. That is, if earnings expectations do indeed

proxy for expected future cash flow, the sudden

decrease in expected cash flow resulting from a

Chapter 11 filing may lead to the negative abnormal

equity returns found by us, Lang and Stulz (1992),

and Ferris, Jayaraman, and Makhija (1997).

Cross-sectional regression

We formally test for a relation between abnormal

earnings forecast revisions and changes in market

values of equity using regression analysis.

Specifically, we regress the abnormal stock returns

cumulated over the three-day period surrounding the

bankruptcy filing on the abnormal forecast revisions

cumulated over the six-month period from month 0

through month 5. The six- month cumulation should

capture all the change in earnings expectations caused

by the filing. In addition, we control for other firm-

specific information that could affect earnings

forecast revisions. Hertzel and Jain (1991) and Hertzel

and Rees (1998) both indicate that because of the

serial correlation inherent in the IBES data, there is

potential for a great deal of contaminating information

since forecast revisions could reflect information

released either months prior to or after the bankruptcy

filing. In order to control for such firm-specific

information, we include two variables in the cross-

sectional regression models, the pre-announcement

cumulative abnormal return over the interval from

Day -250 to Day -31, and the post-announcement

cumulative abnormal return over the interval from

Day +31 to Day +250. These two variables should

capture any other firm-specific information that might

cause analysts to revise their earnings forecasts.

Results for the cross-sectional regression

analysis are presented in table 5 and suggest that the

stock market reaction is strongly related to abnormal

earnings forecast revisions. The regression coefficient

is positive and with a t-statistic of 3.34 is significant

below the 1 percent level. This is consistent with our

hypothesis that the negative stock market reaction

found by Lang and Stulz (1992), Ferris, Jayaraman,

and Makija (1997) , and shown in table 3 herein, may

be due to negative revisions in cash flow expectations.

That is, the average contagion effect is the result of an

industry-wide average reduction in cash flow

expectations that are a result of the Chapter 11 filing.

Table 5. Cross-sectional analysis of rival firms' cumulative abnormal forecast revisions on their cumulative

abnormal returns

Independent variables Coefficient t-statistic

Cumulative abnormal forecast revision 0.241 3.34***

Pre-announcement abnormal return 0.008 2.45**

Pre-announcement abnormal return 0.002 0.51

Conclusion

This paper provides evidence that the filing of a

bankruptcy petition reflects the release of new

information that affects the market values of rival

companies. As documented elsewhere, the

information contained in the filing comes as a surprise

to the market as evidenced by the negative stock price

reaction for rivals. We extend the analysis by looking

more deeply at how this negative information is

transferred from the filing company to its rivals. We

find significant negative abnormal earnings forecast

revisions for filing companies' industry rivals.

Furthermore, the results of a cross-sectional

regression analysis show a significant positive

relation between abnormal stock price reactions and

abnormal cumulative forecast revisions for rival

companies, thus formally confirming a positive

relation between the two. These findings are

consistent with our hypothesis that a Chapter 1 filing

produces a negative effect on the market's expected

future cash flows for rival companies that leads to

negative stock returns.

References

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case for chapter 11, Yale Law Journal, 101, 1043-

2. Brous, P.A., 1992, Common stock offerings and

earnings expectations: a test of the release of

unfavorable information, Journal of Finance 47, 1517-

3. Caton, G.L., and J. Goh, 2003, Are all rivals affected

equally by bond rating downgrades?, Review of

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4. Ederington, L.H. and J. Goh, 1998, Bond rating

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Journal of Financial and Quantitative Analysis 33, 569-

5. Ferris, S.P., N. Jayaraman, and A.K. Makhija, 1997,

The response of competitors to announcements of

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6. Hertzel, M. and P.C. Jain, 1991. Earnings and Risk

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