281 earning performance. We need to control for the selection biases so that we construct a new
control group of non-VC-backed firms using the propensity score matching Croce et al., 2013; Rosenbaum and Rubin, 1983. The aim is to find the non-VC-backed firms that have the most
similar probability of receiving VC for each VC-backed firm. Following the notation in Lee and Wahal 2004, we define 1 as VC-backed and 0 as non-VC-
backed. Hence Y and Y separately denote the daily return of non-VC-backed IPO and VC- backed IPO. Our intention is the impact of VCs on IPOs, which is Y − Y . Since one firm is
either to be funded or not be funded, Y − Y is unobtainable. Thus we estimate the average treatment effect ATT of VCs, which is as follows.
E[Y − Y |VC = , X] = E[Y |VC = , X] − E[Y |VC = , X] X is denoted as industry features that are related to the selection procedure. E[Y |VC = , X]
defines the average daily return for VC-backed IPOs but the E[Y |VC = , X] is unobtainable. From the conditional independence assumption, the traditional way is to apply
[Y |VC = , X
] = [Y |VC = ，X
] The conditional independence assumption Rubin, 1977 is firms vary in target factor
�
regardless whether realizations of
�
is the same or not. If the above assumption stands, the ATT is as follows,
E[Y |VC = , X] − E[Y |VC = , X]. Unfortunately, venture fund is not invested randomly but is an endogenous choice. It means the
existence of bias, which is �
= E[Y |VC = , X] − E[Y |VC = , X] To eliminate the bias, propose the propensity score method PSM is proposed by Rosenbaum
and Rubin 1983 to match the treated and control groups. A probit model is estimated for the endogenous selection variable Y=1 for venture fund and Y=0 otherwise with a set of X
variables including firm age, education of founders, numbers of employees, total assets, gross sales and industry dummies. The firms’ conditional possibility to obtain VC fund is employed as
the propensity score and VC-funded IPO is matched with the non-VC-funded IPO with the nearest propensity score. As PSM we used in STATA is a one-to-one matching technique, the
limitation is it drops potentially valuable sample.
282
3.2 Hypothesis Testing
As suggested by Alavi et al. 2008, the initial return is used to measure the underpricing. This paper uses the market adjusted initial return, which is measured by adjusting the market return to
the raw initial return. We use the return earned on the first trading day on the Shanghai Securities exchange to calculate raw initial return and the market return is denoted by the Shanghai
Composite Index Stock code: 000001.
H1 is
H : IR VC = IR NON − VC UP =
P − P P
Where: UP = Raw underpricing.
P = Offer price. P = Closing price on the first trading day.
R
m
= I − I
I Where:
R
m
= Market return. I = Open market index of the offering day.
I = Closing market index of the offering day. Market-adjusted initial return denotes the difference between raw underpricing and market
return: UP
mk
= UP − R
m
Ta le : Varia le defi itio s a d easure e t
Variables Definition and measurement
Dependent variable
IR Initial Return Difference between market return
and raw underpricing
Independent variables
IPO features VCDUM
VC dummy 1 for VC-backed, 0 otherwise LPROCEEDS
Log of offering size in aspects of amount raised in the IPO
IPRICE Issue price
DAY Number of days between offering and listing
LNUM Log of the number of issued shares
PERCENT Proportion of non-negotiable shares
Firm specific
variables LASSET
Log of total assets LSALES
Log of gross sales AGE
Year span of firm’s establishment date and the IPO
283
H2 predicts the following IPO characteristics and firm specific variables significantly influence
the underpricing level of the IPOs backed by VCs. H2 explores the value-added effect of VC. To test the features of VC-funded IPOs and the alternations in the IPO underpricing, OLS
estimations would be used and the basic model is as follows: IR
i,t
= + X
,i,t
+ X
,i,t
+ ε
i,t
Where: IR
i,t
=performance of the � th firm at time period‘t’ = the overall constant in the model
X
,i,t
= firm specific variables of � th firm X
,i,t
= IPO characteristics of � th firm ε
i,t
= error term Based on existing literature, the initial return is the dependent variable and we divide the
independent variables into IPO features and firm particular variables. IPO features contain the number of days between offering and listing, log of the number of shares being issued, log of
gross issue proceeds capital raised during the IPO, the proportion of the non-negotiable shares, a dummy variable of VC funded, issue price and VC age. Firm specific variables are log of total
assets, log of gross sales. The VC age is defined as the time interval between the year of the establishment and the IPO Wang et al., 2003.
Based on Chen et al. 2004, we use DAY, LNUM and PERCENT to explain underpricing that is caused by section difference. DAY denotes the days form offering to listing. Different from
developed markets where only a short time exists between the offering and the listing, the lasting days normally takes more two months in China. As a result of the information asymmetry, longer
dates between the offering and the listing reflect higher risk for investors to obtain the payback, so that a larger underpricing is expected by investors Su and Fleisher, 1999. Thus, a positive
relationship between DAY and underpricing is proposed. This paper defines LNUM as the number of issued shares at the IPO. Shleifer 1986 states that
the shares’ demand curve in an individual company is not perfectly elastic. When there are more shares being issued, investors do not need to buy the shares urgently on the first day of trading so
that initial returns will be lower. Thus, a negative relationship between LNUM and underpricing is predicted.
PERCENT represents the percentage of non-negotiable shares. When the legal or state institutions hold a large percent of shares, this may be regarded as a signal of operational
inefficiency and bureaucratic control. Hence, most investors may be unwilling to pay a higher price. Mok and Hui 1998 indicate that the IPO return is negatively associated with the
proportion of institution-owned shares. However, Su and Fleisher 1999 claim that the IPO underpricing is positively related to the proportion of government state. We still conjecture that
PERCENT is negatively related to the underpricing.
H3 estimates the influence of VC’s participant on the market performance of the IPO. By
verifying whether PE ratio of VC-funded IPO is greater than or equal to non-VC-funded ones, test is performed:
H : PE VC = PE NON − VC
H4 assumed that excess return of VC-treated IPOs is the same as excess return of non-VC-
treated IPOs. It tests if VCs will affect the market performance of the VC-treated listed firms. The aftermarket return is defined as buy-and-hold market return for a particular time interval,
which is calculated as the closing price after the IPO minus the closing price of the first day of
