CEO Overconfidence and Distortions of Firms’ Investment: Some

CEO Overconfidence and Distortions of Firms’ Investment: Some
Empirical Evidence from China
WANG Xia, ZHANG Min
School of Business
Renmin University of China, P.R. China, 100872
，
Abstract: In this study, we argue that managerial overconfidence can account for corporate investment
distortions. Overconfident managers overestimate the returns to their investment projects, which induce
they to over-invest when firms have abundant funds. We test these predictions using a sample of
Chinese listed companies between 2003 and 2004. We identify CEOs as overconfident when they
purchase additional company stock despite their already high exposure to company risk. Based on their
characteristics and special institutional background in Chinese stock market, we find that overconfident
CEOs have a higher sensitivity of corporate investment to cash flow from equity financing than that of
free cash flow from operation. Overconfident managers over-invest when firms have abundant funds
from equity financing, but curtail investment when firms are short of cash flow from equity financing,
which is unique with prior researches where samples of west countries are used.
Key words:Over-investment, Overconfidence, Cash flow from equity financing , Free cash flow
1 Introduction
The association between investment and cash flow has been researched by an extensive literature.
Among these, two traditional explanations for investment distortions are the misalignment of managerial
and shareholders interests (Jensen and Meckling (1976); Jensen (1986)) and asymmetric information
between corporate insiders and the capital market (Myers and Majluf (1984)). Agency costs contribute
to the separation of ownership and control, exhibiting over-investment in which managers in firms with
free cash flow have strong incentive to waste any cash they have on hand on investment in negative
NPV projects (e.g., Jensen 1986; Stulz 1990). In the asymmetric information approach of Myers and
Majluf (1984), free cash flow is beneficial, because managers loyal to existing shareholders are assumed
to have information the market does not have. The managers themselves restrict external financing in
order to avoid diluting the (undervalued) shares of their company. In this case, cash flow increases
investment, but reduces the distortion.
In the recent years, some studies explore whether personal characteristics of CEOs lead to
distortions in corporate investment policies. Richard Roll(1986) suggested that managerial
overconfidence caused merge& acquisition ,which did not be tested by measuring economic decisions
and personal overconfidence simultaneously. Camerer and Danlovallo(1999) explored whether
overconfidence about relative ability is part of the explanation for excessive failure by creating
experimental entry games in which entrants' payoffs depend on their skill. Heaton (2002) established an
underinvestment-overinvestment tradeoff related to free cash flow without invoking asymmetric
information or rational agency costs. He first showed that common distortions in corporate investment
may be the result of managers overestimating the returns to their investment. Malmendier and Tate(2003)
expand on Heaton’s insight. They analyze the impact of CEO overconfidence on merges and
acquisitions. They argue that overconfident CEOs over-estimate their ability to generate returns in their
firm and in potential takeover targets. Thus, on the margin, they undertake merges that destroy value.
Overconfidence also implies that managers view their company as undervalued by outside investors.
Therefore, the impact of overconfidence is strongest when CEOs can finance mergers internally. Further,
Malmendier and Tate(2005) found that investment of overconfident CEOs is significantly more
responsive to cash flow, particularly in equity-dependent firms.
These overconfident stories build upon a prominent stylized fact from the social psychology
literature, the “better-than-average” effect. Psychological studies show that most people are
overconfident about their own relative abilities, and unreasonably optimistic about their futures. When
individuals assess their relative skill, they tend to overstate their acumen relative to the average (Langer
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(1975); Neil D. Weinstein, 1980; Alicke (1995)). Consistent with the experimental findings, managers
generally appear committed to the firm’s success (somehow defined), probably because their wealth,
professional reputation, and employability partially depend on it (e.g., Gilson, 1989).March and Shapira
(1987) indicates that managers underplay inherent uncertainty, believing that they have large amounts of
control over the firm’s performance.
Following Malmendier and Tate(2005)’s approach, we examine the extent of firm level
over-investment of cash flow and the managerial overconfidence in China. We use data of Chinese
listed firms because Chinese capital market is very young and has unique background, contrary to the
pecking order theory, of which the listed companies prefer to the cash flow financed from external
capital markets. The listed firms are wild about issuing additional shares through rights offered to their
existing shareholders or through seasoned equity offered to the new shareholders so far as they achieve
the guidelines issued by the CSRC to restrict rights issues after November 1993. This phenomenon is
called as “hungered symptom of equity financing” in Chinese capital market. In order to explore
whether managerial overconfidence account for corporate investment distortions, we expand on
Malmendier and Tate(2005)’s work to examine whether overconfident CEOs over-invest when they
have abundant funds from equity financing. Because of Chinese firms’ characteristic, we argue that
investment of overconfident CEOs is significantly more responsive to cash flow from equity financing,
rather than cash flow from operation.
The remainder of the paper is organized as follows. Section 2 lays out the hypotheses. Section 3
describes the sample selection and variable measurement. Section 4 provides empirical evidence that
overconfidence accounts for the overinvestment and increases the sensitivity of investment to cash flow.
Section 5 concludes.
2 Hypothesis Development
Cash flow forecasts are the most important inputs to project valuation and selection. Managers
should take projects that have positive net present cash flows. Overconfidence leads the managers’
forecasts to be biased. Available evidence is consistent with the managerial optimism prediction of
upwardly biased cash flow forecasts. Kaplan and Ruback (1995) study long run cash flow forecasts
made in connection with management buyouts and recapitalizations. They find statistically significant
upward bias of both operating income and operating margins. While they attribute some of this bias to
the fact that a recession began in 1990, a year included in part of the sample, similar evidence is
presented by Kaplan (1999) who studied the performance of a large sample of management buyout
firms not affected by the 1990 recession. Besides these, Malmendier and Tate (2003) find that
Overconfident CEOs over-estimate their ability to generate returns in their firm and in potential takeover
targets. Thus, on the margin, they undertake mergers that destroy value.
As predicted, overconfidence has the biggest effect in firms with the most cash and untapped debt
capacity. Overconfident CEOs systematically overestimate the return. The level of investment is not
disciplined by the capital market or corporate governance mechanisms because Chinese capital market
is a developing market and the corporate governance system of Chinese listed firms is very weak. Hence
the following hypothesis:
Hypothesis1: Overconfident CEOs are more likely to over-invest.
In a world of perfect capital markets there would be no association between firm level investing
activities and internally generated cash flows. If a firm needed additional cash to finance an investment
activity it would simply raise that cash from external capital markets. If the firm had excess cash beyond
that needed to fund available positive NPV projects it would distribute free cash flow to external
markets. Firms do not, however, operate in such a world. There are a variety of capital market frictions
that impede the ability of management to raise cash from external capital markets. In addition, there are
significant transaction costs associated with monitoring management to ensure that free cash flow is
indeed distributed to external capital markets. In equilibrium, these capital market frictions can serve as
a support for a positive association between firm investing activities and internally generated cash flow.
If firms were controlled by overconfident CEOs, they would be reluctant to issue new equity because
they perceive the stock of their company to be undervalued by the market. As a result, they curb their
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investment and the company investment policies are distorted. Prior researches, such as Heaton(2002),
Malmendler and Tate(2003;2005) all proved this. In china, listed companies have fewer channels to
finance from external capital market than firms in developed capital markets. On the surface, the
channels prescribed by the China Securities Regulatory Commission (CSRC hereafter) for Chinese
listed firms to finance from external capital market include issuing bonds, issuing convertible bonds,
seasoned offering and rights offering. However, due to the strict qualification requirements promulgated
by the CSRC, each year only a small number of listed firms with good performance can issue
successfully. On the other hand, weak corporate governance and lax enforcement mechanisms means
the management of listed firms have no pressures to pay cash dividends and have no incentive to use the
funds efficiently. The management of listed firms could not give up the opportunity of issuing new
equity even if they perceive the stock of their company to be undervalued by the market. So, we argue
that investment of overconfident CEOs is significantly more responsive to cash flow from equity
financing, rather than cash flow from operation. Hence the following hypothesis:
Hypothesis 2: overconfident CEOs are significantly more responsive to cash flow from equity
financing, rather than cash flow from operation.
3 Sample selection and variable measurement
Our sample includes all Chinese A-share companies which were listed prior to 2001, but banks and
financial institutions are excluded from the empirical analysis. Our final sample ends up with 895 listed
firms in the period of 2003 to 2004. Outside directors data are collected from the Genius Securities
Information System, a database prepared by Shenzhen GTI Financial Information Limited. Other data
are all obtained from CSMAR2004 Database Inquiry System prepared by the China Accounting and
Finance Research Center of Hong Kong Polytechnic University and Shenzhen GTI Financial
Information Limited.
To test the hypotheses, we use the following general regression specification:
Oinvesti = 0 + 1 Confi + 2 Xi’+ 3 Confi *Xi’ + 4Tobin’Q i + 5 Owpi
+ 6 Govi+ 7 Sizei + 8 Levi + Fixed effects+ i
Where Oinvest is defined as investment expenditure beyond that required to maintain assets in
place and to finance expected new investments in positive NPV projects. To measure this variable, we
follow Richardson (2006) to decompose total investment expenditure into two components: (i) required
investment expenditure to maintain assets in place, which defined as IMAINTENANCE and (ii) new
investment expenditure INEW,t, which can be decomposed into expected investment expenditure in new
positive NPV projects, I*NEW,t , and abnormal (or unexpected) investment, Iε NEW,t. INEW,t can be obtained
from the investment expectation model INEW,t = α + βVP t-1 +ΦZ t-1 + Iε NEW, t. ① The predicted value
ε
from this expectation model is I*NEW,t and the residual value from the expectation model is I NEW,t. The
residual value is our estimate of overinvestment.
Conf is the dummy variable of overconfidence of CEOs. Following Malmendler and Tate(2005),
we exploit the tendency of some CEOs to purchase additional company stock despite their already high
exposure to company risk. We consider the sub sample of CEOs who keep their position as CEO from
the period of 2002 to 2004 in our sample. We identify CEOs as overconfident if they were net buyers of
company equity during 2003 to 2004 in our sample, which is defined as 1, otherwise 0. The null
hypothesis1 is that 1, the coefficient on the overconfidence is equal to zero.
Xi ’ is the cash flow of company, includes FCF and NCFF. FCF is the cash flow from operating
activities after maintenance investment expenditure. It is calculated as cash from operations less
IMAINTENANCE. NCFF is the change of cash flow from equity financing activities.
β
β β
β
β
β
β
ε
β
β
β
① VP
is a measure of growth opportunities; we use Tobin’s Q to measure the growth opportunities. Z is a vector of
additional determinants of investment expenditure. This vector includes leverage, firm size, firm age, stock of cash,
past stock returns, prior firm level investment, annual fixed effects and industry fixed effects.
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Where relevant, we include Confi *Xi’, the interaction of cash flow and overconfidence. The null
hypothesis is that 3 is equal to zero when Xi ’ is defined as NCFF, the cash flow from equity financing
activities. We also predict that the estimated coefficient of 3 is insignificant when Xi ’ is defined as
FCF, the cash flow from operations.
Tobin’s Q is market value of assets over book value of assets. Owp is the fraction of company stock
owned by the management of the company at the beginning of the year. Gov is the number of the
outside directors. Size is the natural logarithm of assets at the beginning of the year. Lev is debt
ratio.Fixed effects includes two aspects. Ind is a vector of indicator variables to capture industry fixed
effects. There are 13 industry indicator variables (using China Securities Regulatory Commission 2001
groupings) in this regression. Year Indicators is a vector of indicator variables to capture annual fixed
effects.
The investment expenditure variable and all the cash flow variables are scaled by average total
assets.Table 1 reports descriptive details of all the variables. We analyze a full sample of 895 publicly
traded Chinese firms from the years 2002 to 2004. We identify CEOs as overconfident if they were net
buyers of company equity during 2003 to 2004 in our subsmple. There are 92 CEOs are defined as
overconfidence, which construct the subsmple.
From the Full Sample to the Subsmple, we can see that the mean and median of overinvestment is
increasing. It is 0.017 in the Subsample and is less than 0.001 in the Full Sample. Which primary
indicate that overconfident CEOs are more likely to over-invest. Like the overinvestment, the mean and
median of NCFF is also increasing, but that of FCF does not behave the same tendency. Even as the
hypotheses 2, overconfident CEOs are probably responsive to cash flow from equity financing, rather
than free cash flow.
β
β
Mean
Table 1
Descriptive Statistic of Variables
Full Sample
Subsample
Number of firms=895
Number of firm=92
Median
Max.
Min.
SD
Mean
Median
Max.
Min.
SD
Oinvest
0.000
-0.014
0.691
-0.321
0.083
0.017
0.005
0.253
-0.113
0.072
Conf
0.093
0.000
1.000
0.000
0.290
1.000
1.000
1.000
1.000
0.000
NCFF
0.004
0.000
0.220
-0.192
0.026
0.012
0.007
0.179
-0.042
0.027
FCF
-0.045
-0.039
0.740
-0.831
0.104
-0.043
-0.039
0.114
-0.642
0.084
Tobin'sQ
1.545
1.420
8.154
0.642
0.480
1.423
1.367
2.624
0.950
0.309
Owp
0.053
0.000
4.902
0.000
0.234
0.239
0.063
4.902
0.000
0.648
Gov
2.703
3.000
7.000
0.000
0.891
2.876
3.000
6.000
0.000
0.962
Variables
Observations
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Oinvest is defined as investment expenditure beyond that required to maintain assets in place and to finance
expected new investments in positive NPV projects and normalized by the average total assetat the beginning of the
year. Conf is the dummy variable of overconfidence of CEOs. FCF is the cash flow from operating activities after
maintenance investment expenditure. NCFF is the cash flow from equity financing activities. Tobin’s Q is market
value of assets over book value of assets. Owp is the fraction of company stock owned by the management of the
company at the beginning of the year. Gov is the number of the outside directors.
4 Empirical Result
Table 2 reports Pearson correlations for the variables used in the regression specification. About
the main test variables, the results of the correlations are consistent with our hypotheses. Oinvest is
significantly positively correlated with Conf, NCFF and FCF. As expected, Oinvest is significantly
positively correlated with Conf*NCFF but insignificantly correlated with Conf*FCF. however, for the
variables we made no predictions, Table 2 shows that Oinvest is insignificantly positively correlated
with Owp and Gov, and is insignificantly negatively with Tobin's Q.
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Oinvest
Oinvest
1
Conf
0.166***
NCFF
FCF
Conf*NCFF
Table 2 Pearson Correlations of Variables
Conf*
Conf*
Conf
NCFF
FCF
NCFF
FCF
Owp
1
***
0.372
0.222*
1
0.108**
0.026
-0.417***
***
*
0.357
Tobin'sQ
0.278
-0.328**
1
**
-0.427*
1
0.836
-0.333
-0.355
0.607*
-0.059
0.003
0.020
-0.092
0.043
-0.059
1
0.045
-0.047
0.065
0.015
-0.009
0.017
-0.069
1
Gov
0.057
0.086*
-0.004
0.040
0.001
*, **, *** indicates significance at the 10%, 5%, 1% level respectively.
0.009
-0.141
-0.108
Conf*FCF
-0.070
Tobin's Q
Owp
**
1
*
We run a set of eight baseline regressions to demonstrate the effects of CEOs overconfidence and
cash flow on investment: first with no additional controls, then including other dependent variables, and
finally including firm-fixed effects as well as controls for CEO stock ownership, firm size and corporate
governance. The results are presented in Table 3. Model 1 and Model 5 regressions confirm the stylized
facts of the investment–cash flow sensitivity literature, namely, cash flow (both free cash flow from
operating activities and cash flow from equity financing activities)has a large amount of explanatory
power for investment. Overconfident managers are more likely to over-invest than rational managers; all
the coefficients of the Conf (overconfidence indicator) are positive and highly significant. Thus, the
economically large and statistically significant effect of overconfidence on overinvestment is due mainly
to overconfident managers conducting more investment. This finding confirms Hypotheses 1.
Accounting to the model 7 and model 8, we find that the coefficient on the interaction of the
overconfidence indicator with free cash flow is negative but not significant. Using the NCFF as our
proxy for cash flow variable, all coefficients are positive and significant at the 1% level. So, we
conclude that CEOs who demonstrate a higher level of overconfidence than their peers in their personal
portfolio decisions also exhibit a higher sensitivity of corporate investment to cash flow from equity
financing. Hypotheses 2 are confirmed too. Among the control variables, when NCFF is the cash flow
variable, we find that Tobin’s Q has more impact on overinvestment. Besides this, corporate governance,
measured by outside directors on the board, significantly increase the level of overinvestment of the
company. All the control variables are insignificant in the model 8.
Next, we repeat the regressions of Table 3 with the data of Subsample1. CEOs who keep their
position as CEO from the years 2002 to 2004 in the full sample construct the subsumple1, which
includes 222 firm numbers. For the 222 firms, there are 92 firm’s CEOs who purchase additional the
company stocks despite their already high exposure to company risk are defined as overconfident CEOs;
the others who do not hold the company stocks or do not purchase additional the company stocks are
called as rational managers. Table 4 gives the results of estimating equation. As in Table 3, Conf
appears to positively impact on the overinvestment. The coefficient on the interaction of the Conf with
NCFF is positive (0.531 in the OLS specification with controls) and slightly significant. Also, as before,
the interaction of Conf with FCF is insignificantly associated with overinvestment.
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Table 3
Regression of Investment on Cash Flow
（Full Sample――895 number of firms）
Variables
NCFF
Conf
Conf*NCFF
NCFF as Cash flow variable
Model 1
Model 2
Model 3
1.138*** 0.684*** 3.386***
(15.934)
(19.508)
(9.344)
0.034*** 0.074***
(3.570)
(3.789)
2.211***
(4.085)
Model 4
0.656***
(15.857)
0.042***
(3.082)
0.691***
(5.031)
FCF
FCF as Cash flow variable
Model 1
Model 2
Model 3
Model 4
0.021***
(3.612)
0.017**
(2.354)
0.013*
(1.744)
0.075***
(4.295)
0.082***
(3.636)
0.087***
(3.852)
-0.099
(-0.837)
1790
0.01
1790
0.02
1790
0.02
0.093***
(3.713)
-0.108
(-0.953)
-0.004
(-0.868)
0.002
(0.243)
0.004
(1.523)
0.185
(1.501)
yes
yes
1790
0.02
Conf*FCF
Tobin's Q
Owp
Gov
Lev
Size
Fixed effects
Observations
Adjusted- R2
1790
0.13
1790
0.18
1790
0.22
-0.043***
(-7.218)
0.005
(0.322)
0.019***
(4.791)
0.034
(1.235)
yes
yes
1790
0.28
The dependent variable in the regressions is Oinvest. See earlier tables for definition of all variables.
T-statistics are reported in parentheses underneath coefficient estimates. *, **, *** indicates significance at the 10%,
5%, 1% level respectively.
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（Sample1――222 number of firms）
Table 4
Variables
NCFF
Regression of Investment on Cash Flow
NCFF as Cash flow variable
FCF as Cash flow variable
Model 1
Model 2
Model 3
Model 4
1.129***
(7.937)
2.869***
1.696***
0.707**
Conf
Model 1
Model 2
Model 3
Model 4
(20.769)
(3.648)
(2.427)
0.010***
0.074***
0.017***
0.021***
0.017**
0.015
(3.124)
(4.732)
(2.812)
(3.703)
(2.329)
(1.596)
2.871***
0.531*
(5.108)
(1.754)
0.057
0.101**
0.165***
0.164**
(1.457)
(2.510)
(3.852)
(2.048)
-0.177
-0.178
(-1.537)
(-1.267)
Conf*NCFF
FCF
Conf*FCF
Tobin'Q
Owp
-0.023
-0.007
(-1.223)
(-0.807)
0.008
0.003
(0.847)
(0.475)
-0.001
0.006
(-0.064)
(1.206)
Lev
0.011
0.235
(0.951)
(1.230)
Size
yes
yes
Gov
Fixed effects
Observations
yes
444
444
444
444
yes
444
444
444
444
0.66
0.05
0.61
0.003
0.04
0.04
0.04
Adjusted- R2 0.14
The dependent variable in the regressions is Oinvest. See earlier tables for definition of all variables.
T-statistics are reported in parentheses underneath coefficient estimates. *, **, *** indicates significance at the 10%,
5%, 1% level respectively.
5 Conclusion
The main goal of this paper is to establish the relation between managerial overconfidence and corporate
investment decisions. We explore the extent to which managerial overconfidence provides a satisfactory
explanation for the investment decisions of listed Chinese firms. Focusing on whether cash flow plays a relatively
more important role in investment decisions for overconfidence managers than for non- overconfidence managers,
we regress the overinvestment on the cash flow, the overconfidence measure, and the interaction of overconfidence
and the cash flow. We find that in China, overconfident managers are more likely to over-invest than rational
managers. Besides this, investment of overconfident CEOs is significantly more responsive to cash flow from
equity financing, rather than free cash flow from operation. Because of Chinese unique background, our result is
different from that of the researches where data of west countries are used. The evidence proposes that managerial
overconfidence plays a role in their investment decisions.
The overconfidence-based explanation for investment distortions has important implications for contracting
practices and organizational design. Specifically, most of Chinese listed firms are wild about equity financing but
make use of the cash excessively. Overconfidence also account for the abuse of cash from equity financing. As a
result, CSRC may need to employ alternative disciplinary measures to constrain overconfident CEOs. In addition,
the results confirm the need for independent and vigilant directors.
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The author can be contacted from e-mail: [email protected]
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