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DEBT EQUITY FINANCING CHOICE UNDER FINANCIAL CONSTRAINTS: DOES
CORPORATE SOCIAL RESPONSIBILITY MATTER?
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DEBT EQUITY FINANCING CHOICE UNDER FINANCIAL CONSTRAINTS:
DOES CORPORATE SOCIAL RESPONSIBILITY MATTER?
ABSTRACT
This study examines the role of corporate social responsibility (CSR) activities in a firm’s
debt and equity financing decisions and in the level of underpricing of secondary equity offerings
(SEO). We find that high CSR firms tend to use more debt financing and less equity financing than
low CSR firms. We also find that firms tend to follow the pecking order’s financing hierarchy
when they are financially constrained. Finally, we find that the high CSR firms that raise equity
capital experience a significantly lower level of SEO underpricing than low CSR firms.
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DEBT EQUITY FINANCING CHOICE UNDER FINANCIAL CONSTRAINTS:
DOES CORPORATE SOCIAL RESPONSIBILITY MATTER?
I. INTRODUCTION
A vast literature in both management and finance on corporate social responsibility
unanimously supports that CSR can have a positive impact on firm performance because firms can
better access to valuable resources as well as lager customer base. CSR also promotes a firm’s
reputation and branding equity, hence allowing for better marketing of products and services. CSR
help firms attract and retain higher quality employees. In the meta-study of 52 CSR and firm
performance by Orlitzky, Schmidt, & Rynes (2003), none investigates the association between
CSR and the pricing of equity offerings. Only recently, a few studies focus on the link between
the CSR and the cost of equity which examine the impact of firms’ CSR behavior on their implied
cost of capital based on the investors’ perceived risk of the firms. Dhaliwal, Li, Tsang, & Yang (
2011) investigate the impact of standalone voluntary disclosure of CSR issues on the cost of equity
and find that firms exploit the benefit of lower cost of capital by initiating the disclosures of their
CSR activities. They also find that firms are more likely time their equity offerings following their
initiations of CSR disclosures.
Using several approaches to estimate firms’ implied cost of equity based on perceived risk
of investors, El Ghoul, Guedhami, Kwok, & Mishra (2011) provide evidence that firms with better
CSR score are more likely experience lower discount rate, hence cheaper cost of equity. In
addition, they find that firms in “sin” industries such as fire arm, tobacco, nuclear power face
higher the implied cost of equity due to higher perceived risk. Goss & Roberts (2011), examining
the link between CSR and bank debt, find that firms with social responsibility concerns pay higher
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interest rate than firms that are more responsible. Using 3996 loans to US firms, they provide
evidence that firms with lower CSR score face higher loan spreads and shorter maturities.
Our study is related to, but differs from the work of El Ghoul et al., (2011) and Goss &
Roberts (2011). El Ghoul et al., (2011) mainly focus on the effects of CSR on the implied cost of
equity regarding the investors’ perceived risk of firms engaging social responsibility activities.
Although prior studies generally show the effects of CSR on the cost of equity and debt in terms
of higher implied cost of equity and higher interest rates, they do not quantify the effects of CSR
on the pricing of seasoned equity offerings. We contribute to the current literature by examining
the direct impact of CSR on firm’s debt-equity choice in financing decisions and firm value. More
specifically, we examine whether firms with high CSR scores can follow the pecking order in
raising external capital. In addition, we also examine the effects of CSR on the SEO underpricing
based on a decrease or increase of the perceived risks. Once a firm’s higher CSR is observed,
investor may react favorably to the firms’ new equity offerings. This suggest that the likelihood of
firm to issue new equity is positively associated with the CSR activities. Our main hypothesis is
that a higher level of corporate social responsibility is associated with the pecking order’s
hierarchy financing decisions for financially unconstrained firms and lower level of the
underpricing of seasoned equity offerings.
To our current knowledge, this is the first study that directly connects CSR with the pecking
order of financing decisions and SEO underpricing. The remainder of this paper is organized as
follows. Section 2, which follows this introductory section, provides related literature and
hypothesis development. Section 3 describes the sample construction and data sources, Section 4
provides descriptive statistics and empirical results. Finally, Section 5 concludes the paper.
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II. RELATED RESEARCH AND HYPOTHESIS DEVELOPMENT
The terms “corporate social responsibility” and “corporate social performance” have
become increasingly popular in the economics, finance and accounting literature over the past two
decades, (Cochran & Wood, 1984; El Ghoul et al., 2011 ; Wu & Shen, 2013; and Lins, Servaes, &
Tamayo, 2017)). Prior research suggests that corporate social responsibility (CSR) is value-
enhancing for shareholders by reducing agency costs due to enhancing stakeholder engagement,
and by lowering informational asymmetry due to higher transparency. Investing in CSR is
considered as an enabler of collective action and cooperation, leading to lower transaction costs
and more efficient allocation of resources (Lins et al., 2017).
Cochran & Wood, (1984) argue that CSR investments provide firms with better access to
valuable resources. Cheng, Ioannou, & Serafeim, (2014) show that high-CSR firms are more able
to access finance in capital markets. (Lins et al., 2017) find that firms build social capital and
stakeholder trust through CSR investments. The investments in CSR pay off because being
trustworthy are more valued, especially in unexpected low trust periods such as financial crises.
The extant literature provides evidence suggesting that high CSR firms are rewarded in both debt
and equity markets.
In debt markets, credit rating agencies tend to award higher debt ratings (Attig, El Ghoul,
Guedhami, & Suh, 2013; El Ghoul et al., 2011) and banks tend to offer lower loan interests (Goss
& Roberts, 2011) to high CSR firms. Shi and Sun (2015) show that CSR investments help to reduce
the number of bond covenants because better CSR performance can earn a firm good reputation
and increased transparency. Oikonomou, Brooks, & Pavelin (2014) investigate the impact of CSR
performance on the pricing of bond pricing and find that high CSR firms are rewarded in bond
markets through lower bond yields spreads.
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In equity markets, high CSR firms tend to have a lower implied cost of equity capital than
low CSR firms (El Ghoul et al., 2011). Examining the motives of the first-time CSR reporting
firms, Dhaliwal et al., (2011) argue and find that firms plan to voluntarily disclose their first CSR
reports to reduce the cost of equity capital before raising equity capital. Their findings indicate that
firms with a high cost of equity capital in the previous year tend to initiate their first CSR
disclosure, and that initiating firms with higher CSR performance experience a subsequent
reduction in the cost of equity capital.
It is worth to note that (Dhaliwal et al., 2011) only focus on the sample of firms that
initiating their first CSR disclosures. Little do we know about the role of CSR in equity market
after their first years of CSR disclosure. This gap naturally raises questions among researchers:
What is the role of CSR in a firm’s equity financing decision in the subsequent years?
In this study, we aim to examine the role of CSR in debt-equity choices of firms and the
impact of CSR on SEO underpricing when firms go raise capital in equity markets. Our study is
related to, but different from and complement to the work of Dhaliwal et al., (2011). First, while
Dhaliwal et al. (2011) focus on the first year of CSR disclosure, we examine the role of CSR in
both first years and subsequent years. Dhaliwal et al., (2011) examine the impact of the initiations
of the first CSR report on the implied cost of equity capital and the likelihood of issuing equity in
subsequent year. We examine the impact of CSR on actual market valuations of SEOs by
measuring SEOs underpricing.
Our first hypothesis predicts that high CSR firms are less likely to issue equity than low
CSR firms. The argument is based on the pecking order theory and the findings in prior research.
As discussed earlier, high CSR firms are rewarded in both debt and equity markets through lower
costs of debt and lower implied costs of equity. The pecking order theory (S. C. Myers & Majluf,
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1984) explains that due to adverse selection, firms prefer internal to external finance. When
external finance is necessary, firms prefer debt to equity because of lower information cost
associated with debt and equity. Compared to debt issuance, equity is more rarely issued (Frank &
Goyal, 2003). Since high CSR firms are rewarded in both debt and equity market, the alternative
and available options in debt markets would encourage high CSR firms to use debt financing but
to eschew equity financing. Our first hypothesis, stated in an alternative form, as follows:
H1A: High CSR firms are more likely to issue debt and less likely to issue equity than
low CSR firms.
If we find evidence supports our first hypothesis, then why would some high CSR firms
still need to issue equity? The pecking order theory predicts that firms need to issue equity when
their ability to use internal funds or debt financing is limited. Continuing in this line of argument,
we argue that one of the reasons for high CSR firms to issue equity is their financial constraint.
Financial constraints induce higher financing costs and thus, restricting financing options because
financial constrained firms are viewed as low quality borrowers. Goss & Roberts (2011) find that
in the context of the absence of security, low quality borrowers that engage more in CSR activities
face higher loan spreads and shorter maturities, but lenders are indifferent to the level of CSR
activities of high quality borrowers. We propose that when facing financial constraints, firms tend
to turn from debt financing to equity financing. We therefore propose the next hypothesis, H1B,
stated as bellow:
H1B: Financial constraint mitigates the impact of CSR on debt issuance and the
impact of CSR on equity issuance.
As discussed earlier, prior studies high CSR firms are rewarded through lower costs of debt
and implied costs of equity(Attig et al., 2013; El Ghoul et al., 2011; Oikonomou et al., 2014). If
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CSR investments are viewed as value-enhancing for shareholders by reducing agency costs, and
by lowering informational asymmetry, then higher CSR firms should receive lower SEO
underpricing. This logic suggests our H2 hypothesis:
H2: The SEOs of high CSR firms are underpriced significantly less and the SEOs of
low CSR firms.
III. DATA SAMPLE
Data for this study come from several sources. The seasoned equity offerings data comes
from the Thomson Financial SDC database. The social performance rating scores are retrieved
from the MSCI ESG KLD Statistics.1 The MSCI ESG KLD provides corporate social
responsibility (CSR) performance for about 650 companies that comprise the FTSE KLD 400
Social Index and S&P 500® with one record for each company the in early 1990s. MSCI ESG
KLD expanded its coverage universe to include the largest 1,000 U.S. companies by market
capitalization in 2001 and during 2003-2013 the MSCI ESG KLD extended its coverage to the
largest 3,000 U.S. companies by market capitalization. The MSCI ESG KLD provides social
performance rating scores based on proprietary research profiles of corporate environmental,
social, and governance (ESG) factors. The MSCI ESG KLD data covers approximately 80
indicators in seven major issue areas: community; corporate governance; diversity; employee
relations; environment; human rights; and product quality and safety. Each issue area has a number
of strength and concern items, where a binary measure indicates the presence or absence of that
particular strength or concern. We follow prior studies (Chatterji, Levine, & Toffel, 2009; Johnson
& Greening, 1999; Kim, Park, & Wier, 2012; Waddock & Graves, 1997) to construct a CSR score
1 Formerly KLD data were created by KLD Research and Analytics Inc., MSCI acquired KLD in 2010.
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based on five social rating categories which include community, diversity, employee relations,
environment, and product. We use the annual scores to construct a composite CSR score for every
year and each firm. Particularly, our CSR1 score is measured as total strength minus total concern
in MSCI ESG KLD’s above five rating categories. For our robustness analysis, we construct a
second measure (CSR2) in a similar vein but excluding corporate governance to disentangle the
effect of CSR and corporate governance. The CSR1 and CSR2 are equally weighted average of
five (four) above rating categories for the focal firm for every year in our panel dataset.
The share prices needed to calculate SEO underpricing and the financial characteristics for
regression analysis are from the Center for Research in Security Prices (CRSP) and Compustat
North America. As in our empirical analysis, the focus is on the effects of corporate social
responsibility performance on a firm’s debt-equity choices and the underpricing of seasoned equity
offerings (SEOs), we start with the sample of all U.S. common equity offerings which can be
matched the MSCI ESG KLD database to obtain CSR rating scores. Because the MSCI ESG KLD
began providing CUSIP in 1995 and covering firms from 1991-2013, we match the MSCI ESG
KLD’s CSR scores with 2,761 SEOs of 1,402 non-regulated firms during the period 1995-2015.
We can extend our analysis for SEOs until 2015 because we examine SEOs up to two years
following the ending of MSCI ESG KLD data. In our subsequent regression analyses of debt-
equity choices, after matching MSCI ESG KLD rating scores with the financial data from the
Compustat database, we obtain a sample of 1,866 firms with 20,894 firm-year observations during
the period 1995-2015. We exclude observations from regulated firms in our sample.
IV. EMPIRICAL RESULTS
Descriptive Statistics
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Table 1 presents the number of observations, mean, the first quartile, median, the third
quartile and standard deviation of each of variables in the sample. The mean and median for SEO
underpricing is 3.7 percent and 2.6 percent respectively. The average CSR1 (CSR2) score in the
sample is 0.067 (-0.136), and firms seem to perform slightly better on community, diversity,
employee relations, environment, human rights, and product quality and safety than on corporate
governance dimension.
[Insert Table 1 about here]
Table 2 shows the Pearson correlation matrix of a set of selected variables of interest.
Consistent with our expectation stated in the first hypothesis, high CSR firms tend to issue more
debt and less equity than low CSR firms. The correlation coefficient between CSR1 and
DEBT_ISSUED is positively significant (0.103, p-value <0.01). The correlation coefficient of
CSR1 and EQUITY_ISSUED is negatively significant (-0.362, p-value <0.01). The correlation
coefficient between CSR2 and DEBT_ISSUED and between CSR2 and EQUITY_ISSUED shows
consistent results.
[Insert Table 2 about here]
As shown in Columns 1 and 2 of Table 2, both CSR scores (CSR1 and CSR2) are
significantly and negatively correlated with SEOUNDERPRICE, KZINDEX and SAINDEX. This
preliminary univariate results suggest that high CSR firms tend to have lower SEO underpricing
(supporting our hypothesis H2) and are less financially constrained than low CSR firms. As shown
in the last two rows of Table 2, KZINDEX and SAINDEX are negatively significantly correlated
with DEBT_ISSUED and positively significantly correlated with EQUITY_ISSUED. The results
indicate that firms with high financial constraints tend to issue more equity and less debt than firms
with low financial constraints.
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The Effect of CSR on Debt Equity Choices and the Likelihood of Equity Issuance
In this section, we present initial evidence on the effect of corporate social performance on
debt/equity issuance decisions. To test H1A hypothesis, we examine whether a high rating of
social corporate performance in the previous year gives firms to follow the pecking order of capital
structure in meeting their financing needs. According to Myers (1984), due to adverse selection,
firms prefer internal to external finance. When outside funds are necessary, firms prefer debt to
equity because of lower information costs associated with debt issue. In the words of Myers (1984,
p. 585): ‘‘you will refuse to buy equity unless the firm has already exhausted its ‘‘debt capacity”—
that is, unless the firm has issued so much debt already that it would face substantial additional
costs in issuing more.”
In the empirical regression model (see Equation 1 below), our dependent variable is the net
debt (net equity) issued, (DEBT_ISSUED in Columns 1 and 2 and EQUITY_ISSUED in Columns
3 and 4), in the year following the year in which firms engage CSR activities.
Equation 1:
Net(Debt / Equity)Issuei,t +1 = 0 + 1CSRi,t + 2 MTBi,t + 5 DEFICITi,t + 4 LEVERAGEi,t
+ 5 ADJRETURNi,t + 6 PROFITi,t + 7CAPEX i,t + 8SIZEi,t + 9 NOISEt + i,t
We follow Bradshaw et al. (2006) to construct net debt and net equity issuance variables. Net debt
issue (DEBT_ISSUED) is the change in total long-term debt during the year. The net debt issue
represents net cash received from the issuance (and/or reduction) of debt. Net equity issue
(EQUITY_ISSUED) is the net amount of cash from issuing and repurchasing equities during the
year. Net equity issue represents net cash received from the sale (and/or purchase) of common
and preferred stock less cash dividend paid. To avoid missing too many observations, we set
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current debt to 0 if it is missing in the Compustat database. In addition to CSR scores, we include
a number of control variables in the regression. The control variables include the 24-month
cumulative market adjusted returns (ADJRETURN), market to book ratio (MTB), market leverage
(LEVERAGE), financing deficit (DEFICIT), profitability (PROFIT), firm size (SIZE), market
liquidity condition (NOISE), and capital expenditures (CAPEX).
We control FIRMSIZE in our regression because prior studies (e.g. Kurshev and Strebulaev, 2015)
provide evidence that firm size has been empirically found to be strongly and positively correlated
with capital structure. Firm size has also been consistently found that large firms in the U.S. tend
to have higher leverage ratios than small firms. We control for growth opportunities (measured as
market to book ratio, MTB) because firms are more likely to issue equity when their market values
are high, relative to book and past market values, and to repurchase equity when their market value
are low (Baker & Wurgler, 2002). We include profit (PROFIT) in the model because profitable
firms have lower amount of debt since they have more available cash which can be used as internal
sources of fund to meet firms’ financing needs. We also control for capital expenditure expenses
(CAPEX) and financing deficit (DEFICIT) because higher level of CAPEX and DEFICIT would
induce firms to issue more debt or equity to meet their financing needs. If firms maintain a target
debt ratio, the firm are expected to weight the benefit from tax relief against the increase
bankruptcy risk that comes with leverage. In that case, firms over time would gradually adjust their
capital structure toward their optimal leverage targets. So, we control debt ratio (LEVERAGE) in
our model. Finally, we include market noise (NOISE), to control overall market liquidity condition.
We use the (Hu, Pan, & Wang's, 2013) NOISE variable which captures episodes of liquidity crisis
of different origins across financial market. Our Appendix provides detailed information about
variable definitions.
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Table 3 provides regression results of the effect of CSR on the choices of debt and equity
issuance. Our main dependent variable is net debt issuance (DEBT_ISSUED in Columns 1 and 2)
and net equity issuance (EQUITY_ISSUED in Columns 3 and 4). As shown in Columns 1 and 2
of Table 3, we find a significantly positive coefficient of CSR1 (0.570, p-value < 0.01, Column 1)
and of CSR2 (0.494, p-value < 0.01, Column 2). This coefficient indicates that firms with higher
CSR scores in year t is positively related to higher debt issue in the following year (year t+1). In
contrast, the coefficients on CSR score in model 3 and 4 (Columns 3 and 4 of Table 3) when net
equity issuance is the dependent variable are significantly negative. The coefficient of CSR1 is
negative 0.203 (p-value <0.01) and the coefficient of CSR2 is negative 0.236 (p-value <0.01) in
Columns 3 and 4 of Table 3, respectively.
The results suggest that there is a negative association between high CSR ratings in year t
and the net equity issue in the following year (year t+1). This suggests that firms with high CSR
ratings are more likely to follow the pecking order of capital structure in their financing decisions.
The results provide evidence supporting our first hypothesis, H1A.
While the coefficients of MTB in specification 1 and 2 are positive and not significant, the
coefficient on MTB is negative and statistically significant in specification 3 and 4. This is
consistent with prior studies that firms are more likely to issue equity when their stock prices are
high relative to the book value (growth firms).
[Insert Table 3 about here]
In sum, Table 3 reveals that, holding other factors constant, firms with high CSR ratings
are more likely to issue debt and less likely to issue equity in their financing decisions. The findings
support our first hypothesis (H1A) that high CSR firms actively engaging CSR activities before
going to the capital markets in anticipation of obtaining cheaper external capital financing by
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following the pecking order theory of capital structure. In other words, high CSR ratings possibly
allow firms to obtain cheaper external capital by tapping debt markets first before turning to equity
markets.
CSR and the Likelihood of SEOs under Financial Constraints
As discussed previously, we predict that firms with high CSR performance are more likely
to issue debt and less likely to issue equity in financing decisions compared with those with low
CSR performance. In this section, we test our H1B by examining whether CSR performance can
mitigate financial constraints in making financing choices. We hypothesize that the effect of CSR
performance on debt equity choices is more pronounced in financially unconstrained firms and not
observed in financially constrained firms. Financially unconstrained firms may actively engage in
corporate social activities, as predicted by the pecking order of financing decisions. However,
corporate social activities only have a second order effect on the debt-equity choice in financing
decisions and the benefits of following the pecking order’s financing hierarchy manifest only
among financially unconstrained firms. We estimate the following logistic regression for equation
2 and OLS regression for equation 3 to empirically test our hypothesis.
Equation 2:
log L prob(SEOi,t +T ) / (1- prob(SEOi,t +T ))lJ = 0 + 1CSRi,t + 2 SIZEi,t + 3MTBi,t
+ 4 MKTLEVi,t + 5 DEFICITi,t + 6 ADJRETURNi,t + 7 PROFITi,t + 8CAPEX i,t (2)
+ 9 NOISEt + IndustryIndicators + i,t
Equation 3:
Net(Debt / Equity)Issuei.t+1 = 0 + 1CSRi,t + 2 FINCONSTRi,t + 3CSRi,t X FINCONSTRi,t
+ 4 MTBi,t + 5DEFICITi,t + 6 LEVERAGEi,t + 7 ADJRETURNi,t + 8 PROFITi,t
+ 9CAPEX i,t + 10SIZEi,t + 11NOISEt + i ,t
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Where t=1 and t=2 denotes one year or two years following the disclosure of CSR rating scores.
Following prior studies, we use the KZ index and the SA Index as measures of financial constraints
(see Appendix for full details of variable definitions) and subsequently classify firms into
financially constrained or unconstrained subsamples. A firm with high KZ-index or SA index is
financially more constrained. Specifically, we rank firms based on the KZ-index (SA index) in
ascending order each year. The firms ranked in the top 30% percentile are placed in the financially
constrained subsample and firms in the bottom 30% percentile are placed in the financially
unconstrained subsample.
The SEO is a dummy variable that equals one if a firm issue equity over the next two years
following the disclosure of CSR rating scores. Net debt issue (DEBT_ISSUED), and net equity
issue (EQUITY_ISSUED) are measured by the total dollar amount in millions U.S. dollars issued
annually 1 year following the disclosure of CSR rating scores. The variable of interest is corporate
social responsibility (CSR). We also include independent variables controlling for other potential
factors affecting the debt or equity issuance. Other control variables include the 24-month moving
cumulative market adjusted returns (ADJRETURN) ending in June 30 each year, market-to-book
(MTB), market leverage (LEVERAGE), financing deficit (DEFICIT), profitability, firm size
(SIZE), capital expenditures (CAPEX), and market liquidity (NOISE).
[Insert Table 4 about here] Table 4 presents results of logistic regressions accessing the weather financial constraints mitigate
the effects of CSR on the pecking order’s financing decisions. While the coefficients on CSR for
financially unconstrainted group are negative and significant (coeff. = - 0.062 and - 0.047, p –
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value = 0.012 and 0.034, respectively), the coefficients on CSR for financial constrained group are
positive and not statistically significant (coeff. = 0.008 and 0.028, p-value = 0.775 and 0.375,
respectively). The results indicate that firms with high CSR are less likely to issue equity when
seeking external financing. The effects of CSR on equity issuance is not pronounced in the group
of financially unconstrained firms. We extend our analysis by considering that financial constraints
may have the first order effect on the pecking order’s financing decisions. We use OLS regression
to examine the effects of financial constraints and the interactions between the CSR score and
financial constraints on the net amount of debt (equity).
[Insert Table 5 about here]
Table 5 presents the results of OLS net debt (equity) regressions on the firm’s CSR
activities. Colum 1 and 2 in Table 5 show the estimated association between DEBT_ISSUED and
CSR score, and the interaction effect of financial constrained dummy variable (FINSCONSTR)
with CSR score. The coefficients on CSR for DEBT_ISSUED as dependent variable are positive
and statistically significant (coeff. = 0.133 and 0.139 with p-value < 0.01): firms with higher SCR
score are more likely to issue debt. The coefficients on the interaction term are negative and
significant indicating that CSR score has a second order effects on debt financing choice. Columns
3 and 4 show the estimated coefficients on CSR and the interaction term between CSR and
financial constraint dummy variable (FINCONSTR). While coefficients on CSR are negative and
significant (coeff. = - 0.366 and - 0.349 with p-value < 0.01), the coefficients on the interaction
term are positive and significant (coeff. = 0.309 and 0.353 with p-value < 0.01). Taken together,
the results suggest that firms with high CSR scores are more likely to follow the pecking order’s
of financing decisions. However, the effects CSR score on the pecking order hierarchy financing
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decisions the second order only compared with the effects of financial constraints regarding the
debt-equity choice in financing decision.
CSR and Underpricing of SEOs
The significant underpricing of SEOs, i.e. the offer price is lower than the closing price on
the day prior to the offer date, is a well-known phenomenon [see, for example, (Corwin, 2003) and
(Mola & Loughran, 2004)]. In this section, we explore whether CSR help reduce the underpricing
if firms raise equity capital to satisfy their financing needs. In our second hypothesis, we
hypothesis that SEO firms with higher CSR are more likely to experience a lower degree of
underpricing through SEO episodes as these firms may exploit benefits from lower information
asymmetry due to a higher reputation in the financial markets. We test this hypothesis in the
following regression:
Equation 4:
SEOUNDERPRICINGi.t = 0 + 1CSRi,t + 2 PRECARi,t + 3BETAi,t
+ 4VOLATILITYi,t + 5 IPOUNDERPRICINGi,t + 6OFFERSIZEi,t
+ 7 RANKi,t + 8TICKi,t + 9 LNPRCi,t X TICKi,t + 10 NASDAQi,t + i,t
where the dependent variable is SEOUNDERPRICING (closing price on the offer day minus the
offer price, divided by the offer price). The main variable of interest is CSR. We expect that CSR
has a negative coefficient if our hypothesis is correct.
Also included in equation (4) is a set of control variables commonly used in the literature
of underpricing of equity offerings (e.g. Corwin, 2003). Specifically, PRECAR measures the pre-
offer price run-up. IPOUNDERPRICING measures the average underpricing (discount) across all
IPOs during the same month as the issue in question. VOLATILITY is a proxy for stock price
uncertainty. OFFERSIZE controls for the effect of price pressure. RANK is (Carter & Manaster,
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1990) underwriter reputation rankings. RANK controls for quality of underwriters2. BETA is a
firm’s beta estimated by the market model using 24-month stock and market returns before the
SEO. TICK is a dummy variable that equals one if the decimal portion of the closing price on the
day prior to the offer is less than $0.25, and zero otherwise. It reflects the effect of rounded prices
on SEO underpricing. NASDAQ is a dummy variable that equals one if the issuers are listed on
NASDAQ at the time of offer, and zero otherwise.
Table 6 Panel A reports the univariate test results for the subsamples of SEO firms where
Group 1 consists of firms with high CSR score in the year prior to a SEO and Group 2 consists of
those that have low CSR score. Panel A shows that the mean levels of SEO underpricing for groups
sorted by two CSR measures are significantly smaller for firms with higher CSR score than for
firms with high low CSR score. The means for high CSR1 group (CSR2 group) are 3.27 percent
(3.33 percent) while the means for low CSR1 group (CSR2 group) are 3.79 percent (3.82 percent),
respectively. The difference between two groups is statistically significant.
[Insert Table 6 here]
Table 6 Panel B shows that the coefficient on CSR from OLS regressions. The coefficients
on CSR are significantly negative both specifications using different CSR scores: -0.012 and -0.13
(p<=0.01). The results provide strong evidence for the hypothesis that issuers with high CSR
scores may be able to get more favorable offer prices and experience less severe underpricing or
value discounting. The signs of coefficients for other control variables are consistent with prior
studies.
2 Data on IPO_undepricing and underwriter’s rank are obtained from Jay Ritter’s website
https://site.warrington.ufl.edu/ritter/ipo-data/
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V. CONCLUSIONS
Investment in CSR brings benefits to firms by reducing information asymmetry, lowering
agency costs and serve as advertising. Prior research find that high CSR firms enjoy the benefits
in both debt and equity markets through a significantly lower cost of debt and lower implied cost
of equity. In this study, we aim to examine the role of CSR in corporate debt-equity financing
choices and the impact of CSR on SEO underpricing when firms choose to raise capital in equity
markets.
Using a U.S. sample of 1,866 firms with 20,894 firm-year observations during the period
1995-2015, we find that high CSR firms tend to use more debt financing and less equity financing
than low CSR firms. We also find evidence suggests that a firm’s decision to raise capital in equity
market is also determined by the level of financial constraints. And financial constraints also
influence the impact of CSR on a firm’s decisions to use debt or equity financing. Our findings
indicate that when a firm is financially constrained, the debt financing option is limited, and the
firm has to turn to equity market to raise capital.
Our predictions and findings are relied on and consistent with the pecking order theory.
The pecking order theory (S. Myers, 1984) explains that due to adverse selection, firms prefer
internal to external finance. When external finance is necessary, firms prefer debt to equity because
of lower information cost associated with debt and equity. Compared to debt issuance, equity is
more rarely issued (Frank & Goyal, 2003). Since high CSR firms are rewarded in both debt and
equity market, the alternative and available options in debt markets would encourage high CSR
firms to use debt financing but to eschew equity financing. The pecking order theory predicts that
firms need to issue equity when their ability to use internal funds or debt financing is limited.
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When firms actually have to raise capital in equity markets, high CSR firms receive
significantly lower SEO underpricing than low CSR firms. Our finding extends the extant literature
on the role of CSR in equity financing by showing a quantified benefit of CSR investment.
Overall, our study enhances our understanding of the role of CSR investment in firm’s
financing decision and the actual cost of equity financing. These results have important and
meaningful implications for companies, regulators, investors.
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Table 1 Descriptive Statistics
This table presents means, standard deviations, the first quartile, medians and the third quartiles of the variables used
in this study for a sample consists of 1,866 firms with 20,894 firm-year observations during the period 1995-2015.
We use the annual scores to construct a composite CSR score for every year and each firm. Particularly, our CSR1
score is measured as total strength minus total concern in MSCI ESG KLD’s five rating categories. We construct a
second measure (CSR2) in a similar vein but excluding corporate governance to disentangle the effect of CSR and
corporate governance. The CSR1 and CSR2 are equally weighted average of five (four) rating categories for the focal
firm for every year in our panel dataset. We follow Bradshaw et al. (2006) to construct net debt and net equity issuance
variables. Net debt issue (DEBT_ISSUED) is the change in total long-term debt during the year. The net debt issue
represents net cash received from the issuance (and/or reduction) of debt. Net equity issue (EQUITY_ISSUED) is the
net amount of cash from issuing and repurchasing equities during the year. Net equity issue represents net cash
received from the sale (and/or purchase) of common and preferred stock less cash dividend paid. SEOUNDERPRICE
is the ratio between the closing price on the offer day minus the offer price, divided by the offer price. KZINDEX is a
measure of financial constraint developed by Kaplan and Zingales (1997), it is the linear combination of five variables
from Kaplan and Zingales (1997): cash flow (CF), Tobin’s Q, debt, dividends, and cash holdings, all scaled by TA
except for Tobin’s Q. More financially constrained firms have a higher KZ index and vice versa. SAINDEX is a
measure of financial constraint developed by Hadlock and Pierce (2010), the index is a combination of asset size and
firm age. By construction, high SAINDEX implies more financially constrained. SIZE is firm size, measured as natural
logarithm of total assets. DEFICIT measures a firm’s financing demand, computed as the sum of common dividends
plus capital expenditures plus the change in net working capital minus cash flow, divided by total assets. ADJRET is
24-month cumulative market adjusted returns. MTB is market-to-book ratio, defined as total assets minus book equity
plus market equity, divided by total assets. PROFIT is profitability, defined as earnings before interest and taxes
divided by total assets. CAPEX is total capital expenditure measured as total capital expenditures divided by total
assets. LEVERAGE is market leverage measured as book debt divided by the result of total assets minus book equity
plus market equity. We follow Hu, Pan and Wang’s (2013) to measure market liquidity by using NOISE variable, this
variable capture different episodes of liquidity crisis of different origins across financial market. BETA is a firm beta,
computed from a regression of firms’ monthly raw returns on the monthly value-weighted market returns over the
rolling five-year window ending in the current fiscal year of the offer date. VOLATILITY is the standard deviation of
stock returns over the period of 30 trading days ending 10 days prior to the offer. IPOUNDERPRICE is the average
underpricing across all IPOs during the same month as the SEO, where the monthly underpricing estimates for IPOs
are obtained from Jay Ritter’s website. OFFERSIZE is Shares offered divided by the total number of shares
outstanding prior to the offer. RANK is underwriter ranking. We obtain underwriter ranking from Jay Ritter’s website.
Ritter refines Carter and Manaster’s (1990) ranking method to construct a new ranking database for major underwriters
and underwriters are ranked based on a 0-9 scale. TICK is a dummy variable taking the value 1 if the decimal portion
of the closing price on the day prior to the offer is less than $0.25, and zero otherwise. NASDAQ is a dummy variable
that takes the value of 1 if a firm’s stock is traded on NASDAQ and zero otherwise.
Variable Mean Std. 25% Median 75%
CSR1 0.067 2.026 - 1.000 0.000 1.000
CSR2 - 0.136 1.979 - 2.000 0.000 1.000
DEBT_ISSUED 57.958 251.742 - 15.630 0.000 52.103
EQUITY_ISSUED - 117.138 290.012 - 85.000 - 5.094 4.116
SEOUNDERPRICE 0.037 0.159 0.020 0.026 0.075
KZINDEX - 18.931 23.181 - 27.964 - 12.196 1.085
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SAINDEX - 3.872 0.684 -4.536 - 4.249 - 3.170
SIZE 6.708 1.794 5.188 6.571 8.132
DEFICIT 0.019 0.198 - 0.105 - 0.015 0.090
ADJRET - 1.904 0.560 - 2.292 - 1.993 - 1.645
MTB 1.971 1.238 1.071 1.427 2.422
PROFIT 0.093 0.097 0.025 0.090 0.158
CAPEX 0.033 0.040 0.003 0.018 0.044
LEVERAGE 0.405 0.286 0.138 0.358 0.655
NOISE 2.896 2.029 1.472 2.275 3.153
BETA 1.277 1.051 0.682 1.157 1.731
VOLATILITY 0.027 0.021 0.013 0.021 0.032
IPOUNDERPRICE 0.150 0.111 0.087 0.136 0.207
OFFERSIZE 0.123 0.110 0.058 0.094 0.154
RANK 8.059 1.275 8.001 8.501 9.001
TICK 0.275 0.447 0.000 0.000 1.000
NASDAQ 0.369 0.482 0.000 0.000 1.000
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Table 2: Pearson Correlation Matrix
This table reports Pearson pairwise correlation coefficients of the selected variables of interest. Two-tail p-values are reported in parentheses. Refer to Table 1 for
details about variable descriptions. *, **, and *** indicates the estimated coefficient is statistically significant at the 10 percent, 5 percent, and 1 percent levels,
respectively.
CSR1 CSR2 DEBT_ISSUED EQUITY_ISSUED SEOUNDERPRICE KZINDEX CSR2 0.949***
(< 0.01) DEBT_ISSUED 0.103*** 0.075***
(< 0.01) (< 0.01) EQUITY_ISSUED - 0.362*** - 0.277*** - 0.288***
(< 0.01) (< 0.01) (< 0.01) SEOUNDERPRICE -0.048 - 0.055*** -0.012 0.055
(0.218) (< 0.01) (0.776) (0.192) KZINDEX - 0.047*** - 0.057*** - 0.013 0.053*** 0.038
(< 0.01) (< 0.01) (0.292) (< 0.01) (0.473) SAINDEX - 0.178*** - 0.135*** - 0.042*** 0.247*** 0.0688 0.270***
(< 0.01) (< 0.01) (< 0.01) (< 0.01) (0.102) (< 0.01)
24
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Table 3: The Effect of CSR on Debt-Equity Choice This table presents the regression results of regressing firm’s corporate social responsibility score (CSR) and other
control variables on the net debt issue (Columns 1 and 2) and on the net equity issue (Columns 3 and 4) for a sample
of 20,894 firm-year observations between the period 1995-2015. Two-tail p-values are in parentheses. Refer to
Table 1 for details about variable descriptions. *, **, and *** indicates the estimated coefficient is statistically
significant at the 10 percent, 5 percent, and 1 percent levels, respectively.
Net(Debt / Equity)Issuei.t +1 = 0 + 1CSRi,t + 2 MTBi,t + 5 DEFICITi,t + 4 LEVERAGEi,t
+ 5 ADJRETURNi,t + 6 PROFITi,t + 7CAPEX i,t + 8 SIZEi,t + 9 NOISEt + i,t
Dependent Variable Net Debt Issue
Dependent Variable Net Equity Issue
CSR1 Measure
CSR2 Measure
CSR1 Measure
CSR2 Measure
(1) (2) (3) (4)
CSR 0.570***
(< 0.01) 0.494***
(< 0.01)
- 0.203***
(< 0.01)
- 0.236***
(< 0.01)
MTB 0.925 0.125 - 0.331*** - 0.318*** (0.710) (0.620) (< 0.01) (< 0.01)
DEFICIT 0.292*** 0.293*** 0.342** 0.351**
(< 0.01) (< 0.01) (0.050) (0.050)
LEVERAGE 0.247** 0.233** 0.553*** 0.493*** (0.050) (0.050) (< 0.01) (< 0.01)
ADJRETURN 0.108*** 0.944*** 0.439*** 0.419***
(< 0.01) (< 0.01) (< 0.01) (< 0.01)
PROFIT 0.227***
(< 0.01)
CAPEX 0.492
(0.390)
SIZE 0.265*** (< 0.01)
0.225***
(< 0.01)
0.423 (0.460)
0.276***
(< 0.01)
0.184
(0.590)
0.709***
(< 0.01)
- 0.918*** (< 0.01)
0.110
(0.750)
0.679***
(< 0.01)
- 0.938*** (< 0.01)
NOISE - 0.721*** - 0.719*** 0.123 0.126*** (< 0.01) (< 0.01) (0.160) (< 0.01)
Year Dummies
Industry Dummies
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Adjusted R2 16.10% 16.10% 39.70% 40.20%
N 20,894 20,894 20,894 20,894
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CSR1 CSR2 CSR1 CSR2 CSR1 CSR2
(1) (2) (3) (4) (5) (6)
CSR - in(1) and
(2) - 0.062**
- 0.047**
- 0.045
-0.015
0.008
0.028
(0.012) (0.034) (0.157) (0.605) (0.775) (0.375)
SIZE - - 0.059** - 0.064** - 0.166*** - 0.175*** - 0.111*** - 0.113***
(0.052) (0.033) (0.001) (<0.01) (0.001) (0.001)
MTB + 0.027 0.027 0.054 0.049 0.078*** 0.077***
(0.367 (0.363) (0.178) (0.216) (0.001) (0.001) MKTLEV 0.134 0.149 0.607* 0.619* -0.387 -0.389
(0.582) (0.541) (0.100) (0.094) (0.130) (0.128)
DEFICIT 0.050 0.046 1.962*** 1.956*** 0.566*** 0.565***
(0.798) (0.816) (< 0.01) (< 0.01) (0.007) (0.007)
ADJRETU RN
0.129***
(< 0.00)
0.132***
(< 0.00)
0.211***
(< 0.01)
0.216***
(< 0.01)
0.130***
(< 0.01)
0.131***
(< 0.01)
PROFIT 0.024 0.019 1.117 1.122 - 1.827*** - 1.829***
(0.953) (0.962) (0.120) (0.119) (<0.01) (< 0.01) CAPEX 3.046*** 3.056*** - 0.012 -0.011 - 4.215* - 4.263*
(< 0.001) (<0.001) (0.991) (0.993) (0.070) (0.067)
NOISE - 0.039* - 0.039* - 0.027 -0.027 0.017 0.016
(0.068) (0.068) (0.325) (0.324) (0.433) (0.443)
Industry
fixed
effects
Yes
Yes
Yes
Yes
Yes
Yes
Table 4: CSR and the Likelihood of SEOs under Financial Constraints This table presents the logistic analysis of the SEO as a function of firm’s corporate social responsibility score
(CSR) and other controlling variables for 3 subsamples partitioned by the level of financial constraints. Firms are in
the low, medium, or high financial constraint subsamples if they have an SAIndex in the top, middle or bottom
terciles of SAINDEX. Two-tail p-values are reported in parentheses. Refer to Table 1 for details about variable
descriptions. *, **, and *** indicates the estimated coefficient is statistically significant at the 10 percent, 5 percent,
and 1 percent levels, respectively.
log L prob(SEOi,t +T ) / (1- prob(SEOi,t +T ))lJ = 0 + 1CSRi,t + 2 SIZEi,t + 3MTBi,t
+ 4 MKTLEVi,t + 5 DEFICITi,t + 6 ADJRETURNi,t + 7 PROFITi,t + 8CAPEX i,t (1)
+ 9 NOISEt + IndustryIndicators + i,t
Expect-ed
Low
Financial Constraint
Medium
Financial
High
Financial
sign Constraint Constraint
- 2Log L 3,814.85 3,816.64 2,597.05 2,598.82 3,535.17 3,534.47
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Table 5: The Effect of CSR and Financial Constraint on Debt-Equity Choice This table presents the regression results when regressing firm’s corporate social responsibility score (CSR),
financial constraints (FINCONSTR), an interaction between CSR and FINCONSTR, and other controlling variables
on the net debt issue (Columns 1 and 2) and on the net equity issue (Columns 3 and 4) for a sample of 20,894 firm-
year observations for the period between 1995 and 2016. FINCONSTR is a dummy variable that takes the value of 1
if a firm’s SAIndex is in the top tercile and 0 if a firm’s SAIndex is in the bottom tercile of the sample. Two-tail p-
values are reported in parentheses. Refer to Table 1 for details about other variable descriptions. *, **, and ***
indicates the estimated coefficient is statistically significant at the 10 percent, 5 percent, and 1 percent levels,
respectively.
Net(Debt / Equity)Issuei.t = 0 + 1CSRi,t + 2 FINCONSTRi ,t + 3CSRi ,t X FINCONSTRi ,t
+ 4 MTBi ,t + 5DEFICITi ,t + 6 LEVERAGEi ,t + 7 ADJRETURNi ,t + 8 PROFITi ,t
+ 9CAPEX i,t + 10SIZEi,t + 11NOISEt + i,t
Dependent Variable Net Debt Issue
Dependent Variable Net Equity Issue
CSR1
Measure
CSR2
Measure
CSR1
Measure
CSR2
Measure
(1) (2) (1) (2)
CSR 0.133*** 0.139*** - 0.366*** - 0.349***
(< 0.01) (< 0.01) (< 0.01) (< 0.01)
FINSCONSTR - 0.013*** - 0.013*** 0.015*** 0.015***
(< 0.01) (< 0.01) (< 0.01) (< 0.01) CSR x FINSCONSTR - 0.126*** - 0.155*** 0.309*** 0.353***
(< 0.01) (< 0.01) (< 0.01) (< 0.01)
MTB - 0.040 - 0.037 - 0.218*** - 0.229***
(0.258) (0.294) (< 0.01) (< 0.01)
DEFICIT 0.209*** 0.209*** 0.372* 0.354*
(< 0.01) (< 0.01) (0.084) (0.102)
LEVERAGE - 0.222 - 0.243 0.012*** 0.118***
(0.17)** (0.139)** (< 0.01) (< 0.01)
ADJRETURN 0.051 0.041 0.343*** 0.375***
(0.375) (0.477) (< 0.01) (< 0.01)
PROFIT 0.122** 0.117** 0.117*** 0.131***
(0.018) (0.023) (0.014) (0.006) CAPEX 0.438*** 0.434*** 0.455*** 0.470***
(< 0.01) (< 0.01) (< 0.01) (< 0.01) SIZE 0.312*** 0.333*** - 0.104*** - 0.111***
(< 0.01) (< 0.01) (< 0.01) < 0.01)
NOISE - 0.036*** - 0.036*** - 0.012 - 0.012
(0.009) (0.010) (0.366) (0.377)
Year Dummies Yes Yes Yes Yes Industry Dummies
Adjusted R2
Yes 7.80%
Yes 7.80%
Yes 46.14%
Yes 45.5%
N 20,894 20,894 20,894 20,894
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Table 6: CSR and SEO Underpricing Panel A of this table presents univariate results of comparing the levels of SEO underpricing of high CSR firms
and low CSR firms. Panel B of this table presents the regression results when regressing firm’s corporate social
responsibility score (CSR) and other controlling variables on SEO underpricing levels (SEOUNDERPRICE). Two-
tail p-values are reported in parentheses. Refer to Table 1 for details about variable descriptions. *, **, and ***
indicates the estimated coefficient is statistically significant at the 10 percent, 5 percent, and 1 percent levels,
respectively.
SEOUNDERPRICEi.t = 0 + 1CSRi,t + 2 PRECARi,t + 3BETAi,t
+ 4VOLATILITYi,t + 5 IPOUNDERPRICEi,t + 6OFFERSIZEi,t
+ 7 RANKi,t + 8TICKi,t + 9 LNPRCi,t X TICKi,t + 10 NASDAQi,t + i,t
Panel A: Univariate Analysis CSR1 Measure CSR2 Measure
Group 1 (Low CSR Score) 0.0379 0.0382
Group 2 (High CSR Score)
Difference (Group 1-Group 2)
0.0327
0.0052***
0.0334
0.0048***
t-value 3.11 2.78
Panel B: Regression Analysis - Dependent Variable (SEOUNDERPRICE)
CSR1 Measure CSR2 Measure Expected sign
(1) (2)
CSR - - 0.012*** - 0.013*** (< 0.01) (< 0.01) PRECAR + 0.006** 0.006***
(0.05) (< 0.01) BETA + 0.002 *** 0.002 ***
(< 0.01) (< 0.01) VOLATILITY + 0.536 *** 0.534 ***
(< 0.01) (< 0.01) IPO UNDERPRICE + 0.018 ** 0.019 **
(0.03) (0.028) OFFER SIZE - 0.015 *** 0.016 ***
(<0.01) (< 0.01) RANK - -0.00 *** -0.004 ***
(<0.01) (< 0.01) TICK + 0.027 *** 0.028 ***
(< 0.01) (< 0.01) LNPRC*TICK - - 0.010 *** - 0.012 ***
(< 0.01) (< 0.01) NASDAQ + 0.008 *** 0.008 ***
(0.001) (0.001) Year Dummies Yes Yes Industry fixed effects Yes Yes Adjusted R2 16.1% 16.1% N 2,761 2,761
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Appendix: Variable Definitions
CSR1 CSR1 score is measured as total strength minus total concern in MSCI
ESG KLD’s five rating categories
CSR2 CSR2 is constructed similarly to CSR1 but excluding corporate
governance to disentangle the effect of CSR and corporate governance.
The CSR1 and CSR2 are equally weighted average of five (four) rating
categories for the focal firm for every year in our panel dataset.
DEBT_ISSUED Net debt issue is the change in total long-term debt during the year. The
net debt issue represents net cash received from the issuance (and/or
reduction) of debt.
EQUITY_ISSUED Net equity issue is the net amount of cash from issuing and repurchasing
equities during the year. Net equity issue represents net cash received
from the sale (and/or purchase) of common and preferred stock less cash
dividend paid.
SEOUNDERPRICE The ratio between the closing price on the offer day minus the offer price,
divided by the offer price
KZINDEX A measure of financial constraint developed by Kaplan and Zingales
(1997), it is the linear combination of five variables from Kaplan and
Zingales (1997): cash flow (CF), Tobin’s Q, debt, dividends, and cash
holdings, all scaled by TA except for Tobin’s Q. More financially
constrained firms have a higher KZ index and vice versa.
SAINDEX A measure of financial constraint developed by Hadlock and Pierce
(2010), the index is a combination of asset size and firm age. By
construction, high SAINDEX implies more financially constrained.
SIZE Firm size, measured as natural logarithm of total assets.
DEFICIT A firm’s financing demand, computed as the sum of common dividends
plus capital expenditures plus the change in net working capital minus
cash flow, divided by total assets
ADJRET Adjusted returns, computed as 24-month cumulative market adjusted
returns.
MTB Market-to-book ratio, defined as total assets minus book equity plus
market equity, divided by total assets.
PROFIT Profitability, defined as earnings before interest and taxes divided by total
assets.
CAPEX Total capital expenditure measured as total capital expenditures divided
by total assets
LEVERAGE Market leverage measured as book debt divided by the result of total
assets minus book equity plus market equity
NOISE Market liquidity, a measure developed by Hu, Pan and Wang (2013) to
capture different episodes of liquidity crisis of different origins across
financial market.
BETA Firm beta, computed from a regression of firms’ monthly raw returns on
the monthly value-weighted market returns over the rolling five-year
window ending in the current fiscal year of the offer date.
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VOLATILITY The standard deviation of stock returns over the period of 30 trading days
ending 10 days prior to the offer
IPOUNDERPRICE The average underpricing across all IPOs during the same month as the
SEO, where the monthly underpricing estimates for IPOs are obtained
from Jay Ritter’s website
OFFERSIZE Shares offered divided by the total number of shares outstanding prior to
the offer
RANK Underwriter ranking, we obtain underwriter ranking from Jay Ritter’s
website. Ritter refines Carter and Manaster’s (1990) ranking method to
construct a new ranking database for major underwriters and underwriters
are ranked based on a 0-9 scale.
TICK A dummy variable taking the value 1 if the decimal portion of the closing
price on the day prior to the offer is less than $0.25, and zero otherwise
NASDAQ A dummy variable that takes the value of 1 if a firm’s stock is traded on
NASDAQ and zero otherwise