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Frontiers of Entrepreneurship Research
Volume 33 | Issue 2
CHAPTER II. VENTURE CAPITAL
Article 2
6-8-2013
PRIVATE EQUITY FUND PERFORMANCE
SIGNALS AND THE LIKELIHOOD OF
FOLLOW-ON FUNDRAISING
Tom Vanacker
University of Gent, Belgium, [email protected]
Mirjam Knockaert
University of Gent, Belgium and University of Oslo, Norway
Sophie Manigart
University of Gent and Vlerick Leuven Gent Management School, Belgium
Recommended Citation
Vanacker, Tom; Knockaert, Mirjam; and Manigart, Sophie (2013) "PRIVATE EQUITY FUND PERFORMANCE SIGNALS AND
THE LIKELIHOOD OF FOLLOW-ON FUNDRAISING," Frontiers of Entrepreneurship Research: Vol. 33: Iss. 2, Article 2.
Available at: http://digitalknowledge.babson.edu/fer/vol33/iss2/2
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Vanacker et al.: PRIVATE EQUITY FUND PERFORMANCE SIGNALS
F RO N T I E R S O F E N T R E P R E N E U R S H I P R E S E A RC H 2 0 1 3
PRIVATE EQUITY FUND PERFORMANCE SIGNALS AND
THE LIKELIHOOD OF FOLLOW-ON FUNDRAISING

Tom Vanacker, University of Gent, Belgium
Mirjam Knockaert, University of Gent, Belgium and University of Oslo, Norway
Sophie Manigart, University of Gent and Vlerick Leuven Gent Management School, Belgium
Abstract
Drawing upon signaling theory and the attention-based view of the firm, we study if signal receivers attend differently to different types of signals when they interact with different firms or operate
under different market conditions. Our theorizing and empirical analysis is situated in the context
of the follow-on fundraising activities by private equity managers managing a first fund. Using
a sample of 238 private equity partnerships, we find that overall performance of the first private
equity fund and its two components, namely realized performance and unrealized performance,
positively influence the likelihood of raising a follow-on fund. Nevertheless, the impact of realized
performance on fundraising is less important for funds investing in early stage companies (early
stage funds) as compared to funds investing in mature companies (late stage funds). Moreover,
realized performance is a more important signal to fund investors in hot equity markets than in
cold equity markets.
Introduction
Traditionally, signaling theory has focused on the deliberate communication of positive
information signals from the perspective of the signaler in an effort to convey firm quality
and thereby ease resource mobilization from outside stakeholders (Gera, 2009). Signaling has
acquired a prominent position in the management literature, including strategic management,
entrepreneurship and human resource management. The strategic management literature, for
instance, has mainly focused on how firms signal quality to investors and other stakeholders,
the entrepreneurship literature has studied the role of board, top management team, investor
and founder characteristics for signaling, and the human resource management literature has
examined signaling during the recruitment process (see Connelly et al. (2011) for an excellent
overview of the literature).
Although scholars have previously argued that the environment in which firms signal may
influence the attention of receivers towards these signals (Gulati and Higgens, 2003), the empirical
evidence on the impact of the signaling environment is rather mixed. While some scholars
found evidence on the impact of the signaling environment on different aspects, including the
observability of the signal (Carter, 2006) and receiver attention (Gulati and Higgens, 2003), other
scholars have found limited evidence of the role of the signaling environment on the effectiveness
of signals (Lester et al., 2006). More importantly, next to our limited understanding of the role
of the signaling environment, we lack insight into how signals may have different consequences
for different firms in specific situations (Connelly et al., 2011). In this study, we address these
shortcomings by studying how different signals may have different consequences when receivers
interact with different firms and operate in different environments.
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Our theoretical and empirical analysis is situated in the context of follow-on fundraising
activities by private equity (PE) managers managing a first PE fund (Wright and Robbie, 1998).
PE managers typically engage in new fundraising activities some three years after raising their
first fund (Rider and Swaminathan, 2012; Sahlman, 1990). At the time of new fundraising
activities, however, the majority of investments of the first-time fund are often unrealized, causing
significant information asymmetries between PE managers and capital providers. It has been
well acknowledged that, in situations with high levels of information asymmetries, signaling is
important (Balboa and Marti, 2007). Therefore, PE fund managers routinely report their realized
and unrealized returns to their capital providers (Cumming and Walz, 2010). In this study, we
focus on whether and how these different performance signals—which may entail both positive
and negative information towards prospective capital providers—influence the likelihood that
PE firms managing a first-time fund raise a follow-on fund. Further, we study to which extent the
impact of different performance signals is contingent on the type of firm (early versus late stage
funds) and environment (hot versus cold equity markets). For this purpose, we use a worldwide
sample of 238 PE firms managing a first-time fund of which 85 raised a follow-on fund. For
each first-time fund we have access to, amongst others, its overall performance, split in realized
performance and unrealized performance.
The present study makes a number of theoretical contributions. First, our study contributes to
the signaling literature. Signaling models have often distinguished between high-quality and lowquality firms, where high-quality firms will communicate positive information signals to outside
stakeholders (Connelly et al., 2011). However, firms reside on a quality continuum and not on a
dichotomy, and may also communicate negative information signals to outside stakeholders. By
studying two continuous signals, namely realized and unrealized performance (which may convey
both positive and negative information), we are able to provide more fine-grained insights on
the impact of signals. We further contribute to signaling theory by increasing our understanding
of the role of receiver attention on the effectiveness of signaling. Whereas most scholars have
focused on the perspective of the signaler, our paper responds to a call for more research to take
the perspective of the receiver (Gera, 2009). At the same time, our research contributes to an
under researched aspect of signaling theory, namely the signaling environment (Connelly et al.,
2011). We contribute to the discussion on the role of the signaling environment, that has provided
convincing conceptual arguments, but that has failed to provide convincing empirical evidence so
far. We further show that not only the signaling environment in which firms operate influences
signal interpretation by signal receivers (see for instance Gulati and Higgins, 2003), but that signal
receivers also look differently at the performance signals communicated by different firms.
Second, this study contributes to the PE literature. Our theoretical contribution lies in
advancing a signaling theory of PE firm fundraising. Previous studies have shown the importance
of performance signals for subsequent fundraising by PE managers (e.g., Cumming et al., 2005;
Gompers and Lerner, 1998; Kaplan and Schoar, 2005). In this study, however, we provide a more
contextualized understanding of the role of performance signals on subsequent fundraising. We
do so by arguing and showing that performance is not a homogeneous construct and that both
realized performance signals and unrealized performance signals of first-time funds influence
the likelihood of raising follow-on funds. More significantly, the value of realized performance is
contingent upon the context and situation in which prospective capital providers operate, making
realized performance signals more important for late stage first-time funds and first-time funds
that raise follow-on financing during hot equity markets.
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Finally, we contribute to a dearth of research on the functioning of first-time PE funds (e.g.,
Zarutskie, 2010). Raising follow-on funds is a critical activity for PE firms managing a first PE fund
and many are eventually unsuccessful in this activity (Rider and Swaminathan, 2012). We study
the impact of performance signals of first-time funds on the probability of raising a follow-on
fund. Signals are argued to be particularly relevant for these PE firms, which are confronted with
large information asymmetries between the PE firm’s management and potential investors.
The remainder of the paper is structured as follows. First, we briefly describe the private equity
setting in which we situate our study. Second, we develop our theoretical framework. Third, we
outline the methods, including the sample, variables and econometric approach used. Fourth,
we present the main research findings. Finally, we conclude by discussing our results from both a
theoretical and a practical perspective.
The Research Context: Private Equity Fundraising
PE investors are specialized financial intermediaries, which usually invest in illiquid assets, that
is, privately held companies (Cumming and Walz, 2010). Two types of PE investors are frequently
distinguished, namely venture capital (VC) and buyout investors (Wright and Robbie, 1998). VC
refers to equity or equity-linked investments made for the launch, early growth or expansion
of young companies. Buyout refers to investments in more mature companies with established
business plans to acquire equity stakes from existing shareholders such as families or corporates.
PE firms are typically organized as limited liability partnerships whereby PE managers act as
general partners managing PE funds and the capital providers (including institutional investors,
such as banks, insurance companies, and pension funds, but also governments, sovereign wealth
funds, corporations, family offices and private individuals) serve as limited partners of the PE
funds (Sahlman, 1990). The economic life of most funds is set at around 10 years, although
provisions are often included to extend the life of the funds by two years (Sahlman, 1990). Each
fund moves through various stages. During the investment period stage, usually the first four years
after establishing a fund, the investment portfolio is formed. During this investment period stage,
PE firms may also provide value-adding services to their portfolio companies. During the fund
maturity stage, some three to seven years after establishing a fund, follow-on financing rounds
are provided to the portfolio companies in order to further support their growth. Finally, in the
harvest or liquidation stage, generally from five years after establishing a fund to the end of a fund’s
life, fund managers are focused on exiting their investments thereby turning their illiquid stakes in
privately held companies into realized returns.
Given the limited economic life of many PE funds, however, PE firm managers (general
partners) need to raise new funds from limited partners on a regular basis to continue their
activities (Balboa and Martí, 2007). PE managers often engage in fundraising activities to establish
a new fund some three years after the start of their previous fund (Rider and Swaminathan, 2012;
Sahlman, 1990). Nevertheless, a large percentage of PE firms only raise one fund and eventually
“exit” the market or experience mortality (Rider and Swaminathan, 2012). This is not surprising
as the relationship between PE managers and capital providers is characterized by significant
information asymmetries (Sahlman, 1990), especially for first-time funds where fund managers
often need to raise follow-on funds before exiting their investments from the first fund. In such
a context characterized by significant information asymmetry, signaling by PE managers may
alleviate some of the difficulties they experience when raising a follow-on fund.
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Theoretical Framework
Signaling theory is useful in describing behavior when two parties have access to different
information (Connelly et al., 2011). In such situations, the sender of the signal must choose
whether and how to signal information, whereas the receiver must choose how to interpret the
signal. Typically, signalers are insiders who obtain information which outsiders could find useful
(Connelly et al., 2011). Further, for signaling to take place, the signaler should benefit from some
action from the receiver that the receiver would otherwise not have done; or: the signal should
cause selection of the signaler in favor of alternatives. There are two major characteristics of
efficacious signals. The first is signal observability, referring to the extent to which outsiders are
able to observe signals. The second characteristic is signal cost, indicating that some signalers are
in a better position than others to absorb the associated costs of generating signals (Spence, 1973).
PE follow-on fund raising is an interesting context to study the impact of signals. The
relationship between PE managers and prospective capital providers is characterized by significant
information asymmetry (Sahlman, 1990; Balboa and Marti, 2007). PE managers are likely to
possess superior information on the quality of the funds they manage compared to prospective
capital providers. This may lead to adverse selection among other problems. Adverse selection
pertains to the risk that capital providers invest in low-quality PE funds which have been presented
to them as high-quality projects. This may be especially the case for follow-on funds of first-time
funds which typically lack a track record of successful investments, because PE managers typically
engage in new fundraising activities well before the outcome of the majority of investments in
first-time funds become visible (Sahlman, 1990). Indeed, as Gompers (1996) indicate, more
established funds will not need to signal as investors have evaluated their performance over many
years and believe in their ability (or not). In such a situation, signaling may be especially valuable
to create a separating equilibrium where prospective capital providers are able to distinguish highquality from low-quality PE firms.
There is significant evidence that the overall performance of PE funds will signal fund quality
to prospective capital providers which subsequently increases the likelihood of PE managers of
these better performing funds to raise follow-on funds. Gompers and Lerner (1998) demonstrate
how the value of equity held by a PE firm in companies brought public increases the likelihood
of raising a follow-on fund. More recently, Cumming et al. (2005) provide direct evidence that
pension funds commit a greater amount of capital to Australian VC firms that achieve superior
performance in terms of internal rates of return (IRRs) of previously managed funds. Kaplan and
Schoar (2005) provide further evidence that capital flows into PE firms are positively related to
past performance. While there is no research looking into the impact of performance as a signal
to future fund providers in the case of first-time funds, we expect that the previously established
relationship between fund performance and follow-on fund raising likelihood will also hold for
first-time funds. This is because potential investors in these follow-on funds are confronted with
large information asymmetries, even more so than in later follow-on fund raising when a fund
reputation has been established. Further, signalers may benefit from giving performance signals,
which are observable through their reporting and which are costly to obtain. We therefore present
the following base hypothesis:
Hypothesis 1: Higher overall performance of first-time funds will increase the likelihood of
raising a follow-on fund.
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Importantly, previous research linking PE fund performance to follow-on fund raising has
assumed that performance is a homogeneous construct. Nevertheless, first-time funds may be
particular cases as only part of the overall return will be realized at the time of engaging in new
fundraising activities, while another part will represent returns on unrealized exits. While the
measurement of returns on investments that have been exited is straightforward, matters are far
more complicated for reporting returns on unrealized investments, since this reporting hinges on
the valuations of privately held companies determined by the PE managers themselves (Cumming
and Walz, 2010). The particular situation of first-time fund follow-on fundraising in a PE context
allows us to examine the value of two distinct signals related to PE firm quality, namely realized
performance and unrealized performance.
First, PE managers may signal fund quality through the realized performance of their firsttime funds, which represents the investment return exits realized by PE managers on investments
by way of initial public offerings, acquisitions, or other forms of exit (Wright and Robbie, 1998).
Realized performance may act as an efficacious signal, as this performance is observable through
the PE firm’s reporting and is difficult to obtain. It is indeed difficult for PE managers to realize
a successful exit and generate a significant return upon an investment. Specifically, Puri and
Zarutskie (2012) show that after the length of a typical venture capital investment, almost 40
percent of U.S. venture capital-backed companies fail. Second, realized performance of first-time
funds at fundraising will be correlated with the quality of PE funds’ investments although not
perfectly, since PE managers typically engage in fundraising well before the end of the economic
life of the first-time fund (Gompers, 1996). Hence, PE managers might not have had enough time
to realize an exit on their most promising investments by the time they need to raise new funds.
The reported return on unrealized investments (or unrealized performance) is likely to be
particularly important for first-time funds given the gap between the time when PE managers
start raising a follow-on fund and the end of the economic life of the first-time fund. However,
the evaluation of the unrealized performance of PE funds is more subject to the discretion of
PE fund managers. Cumming and Walz (2010), for instance, convincingly showed that there are
systematic biases in PE managers’ valuations of private portfolio companies that are not yet sold.
Specifically, Cumming and Walz (2010) find that these biases depend on the accounting and legal
environment in a country and on proxies for the degree of information asymmetry between
institutional investors and PE managers. This might turn the value of unrealized performance
signals less valuable to potential investors.
However, we argue that unrealized performance signals will still be used by prospective capital
providers although they are partially subject to the discretion of PE managers. This is because,
in the case of first time funds, the limited availability of realized performance will trigger both
signalers and receivers to provide or look for other types of signals, even though they may not be
that objective. We argue that, while realized performance will be a useful signal in our context, also
unrealized performance will be an important signal for potential investors. This is because, after
considering realized performance, which at the time of follow-on fund raising only represents a
very partial picture on the quality of the fund, considerable information asymmetries continue
to exist. Information on unrealized performance may help overcome the disadvantages of such
information asymmetries, and may help PE managers of first-time funds to signal their quality
beyond realized performance.
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Unrealized performance is traditionally reported to limited partners during the fund raising
process and is therefore observable. Moreover, although there might be systematic biases, valuation
committees in PE firms comprised of PE managers and outsiders and certification by external
auditors, should be able to dampen the concern that low quality funds present themselves as high
quality funds (Bygrave et al., 1989). Hence, given that unrealized performance is likely to capture
the majority of value that will have been created by first-time funds at the time of fundraising and
that several mechanisms are at work which makes it difficult and costly for low quality funds to
present them as high quality funds with high unrealized performance, unrealized performance is
expected to serve as a valuable signal for prospective capital providers.
Overall, we argue that both realized performance and unrealized performance might serve as
valuable signals that influence the decision making of prospective capital providers. Therefore,
Hypothesis 2a: Higher realized performance of first-time funds will increase the likelihood of
raising a follow-on fund.
Hypothesis 2b: Higher unrealized performance of first-time funds will increase the likelihood
of raising a follow-on fund.
The above hypotheses assume that both reported realized and unrealized performance
function as signals to potential investors when managers of first-time PE funds raise subsequent
funds. Signal receivers, however, are likely to put more or less attention on particular signals when
they observe signals from different firms or operate under different conditions. This is in line with
the basic premises of the attention-based view of the firm. Attention is defined as “the noticing,
encoding, interpreting and focusing of time and effort by organizational decision-makers.”
(Ocasio, 1997: 189). Central to the attention-based view is the notion of selective attention. The
principle of selective attention indicates that “decision makers will be selective in the issues and
answers they attend to at any one time, and what decision-makers do depends on what issues and
answers they focus their attention on” (Ocasio, 1997: 190). By consequence, selective attention
facilitates perception and action towards what is being considered, and away from others. Indeed,
as Hoffman and Ocasio (2001) point out, not all events are attended equally. “Selective attention
to events is driven by salience (Fiske and Taylor, 1991) and salience is shaped by how individuals,
organizations, and industries enact events in the external environment (Hoffman and Ocasio,
2001).” Gulati and Higgins (2003) showed that these ideas may be extended towards the context
of investment decisions by capital providers operating in hot versus cold public equity markets.
We argue that prospective capital providers are less likely to focus on the realized performance
signals of early stage first-time funds as compared to late stage first time funds. Rider and
Swaminathan (2012) show that the vast majority of PE firms raise a fund within three years of
their last fund closing. Especially for first-time VC funds, which focus on early stage investments,
there might not be sufficient time for PE managers to realize successful exits. While there is
evidence that young VC firms bring their portfolio companies public prematurely to establish a
reputation, Gompers (1996) shows that companies are typically around 4.5 years old when they
are prematurely brought public. Hence, there might simply not be enough time for VC managers
to push for a successful exit and demonstrate some level of realized performance before followon fundraising starts. More importantly, even if VC managers are able to demonstrate realized
performance, this might not necessarily produce an optimal outcome for existing capital providers
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(which are likely to contribute financing for subsequent funds as well). Gompers (1996) shows
that more money is left on the table through higher underpricing when young VC firms try to
establish a reputation. For first-time late stage funds, however, which focus on investments in more
mature companies, it might be relatively more straightforward to demonstrate a successful exit
with less pressure to push for premature exits. Late stage investments are often exited more quickly
as compared to early stage investments (Giot and Schwienbacher, 2007). Overall, prospective
capital providers might attach more attention to realized performance for late stage PE funds as
opposed to early stage PE funds. Therefore,
Hypothesis 3: Higher realized performance will have a stronger influence on the likelihood of
raising a follow-on fund for late stage funds compared to early stage funds
We further argue that next to the characteristics of PE funds, the context will influence the
signaling value of realized performance. Specifically, we distinguish between hot and cold equity
markets. Specifically, prospective investors are more likely to focus on realized performance
during hot equity markets as opposed to cold equity markets. During hot equity markets, PE
fund managers should have ample opportunities to exit their portfolio companies by taking their
portfolio companies public, which has been recognized to be the most important and profitable
way for PE funds to exit an investment (Gompers and Lerner, 2004). Public equity markets are
receptive for new equity offerings often at interesting terms. Moreover, private markets represent
another important exit route, for instance, through mergers and acquisitions (Cumming and
Macintosh, 2003). Valuations in these private markets often follow conditions in public equity
markets (Cumming and Walz, 2010). Hence, during hot equity markets, the time might be
particularly ripe for PE fund managers to demonstrate their abilities and exit their portfolio
companies. During hot equity markets, prospective capital providers are hence particularly likely
to direct their attention towards realized performance signals by first-time PE funds as they are
aware of the ample possibilities to realized successful exits in such a context. During cold markets,
however, the exit options might be limited, even for PE managers of high quality funds. Moreover,
it might be a more lucrative strategy to wait and exit promising portfolio companies when exit
markets become more receptive. This implies that prospective capital providers are less likely to
pay attention to realized performance signals during cold equity markets. Therefore, following the
basic premise of the attention based view, indicating that what indicators (in our case: signals)
decision makers will focus their attention on is highly depending on the context, we argue that, in
hot equity markets, potential investors will to a large extent focus their attention towards realized
performance signals. Subsequently, realized performance will have a larger impact on follow-on
fund raising likelihood in such a context. We offer the following hypothesis:
Hypothesis 4: Higher realized performance will have a stronger influence on the likelihood of
raising a follow-on fund in hot equity markets compared to cold equity markets.
Method
Data
The data for this study was obtained from Preqin. Preqin provides information on the PE, real
estate, hedge funds and infrastructure asset classes, which encompasses the following areas that
are critical for our study, namely funds, fundraising and performance. The Preqin PE database
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covers performance returns for over 5,800 PE funds. Preqin claims it is “the world’s most extensive
and transparent database of private equity and venture capital fund performance. In terms of
aggregate value, this [database] represents around 70% of all capital ever raised.”
For the purpose of this study, we selected all first-time funds from the Preqin database, totaling
865 firms at the end of December 2010. Of these firms 343 (39.65%) raised a follow-on fund
and 522 (60.35%) did not raise a follow-on fund. We eliminated those first-time funds for which
essential data such as performance measures and fund size was lacking. This resulted in a final
sample of 238 first-time funds, where 85 funds (35.71%) raised a follow-on fund and 153 funds
(64.29%) did not raise a follow-on fund.
Measures
Dependent variable. The dependent variable Likelihood of raising a follow-on fund is a dummy
variable equaling one if a PE firm managing a first-time fund raises a follow-on fund and zero otherwise.
Independent variables. The key independent variables are correlates of fund performance.
Specifically, we use three performance measures for each first-time fund. These measures
are overall performance (a multiple) defined as distributions plus unrealized value. Realized
performance defined as distributions received to date as a percentage of called capital. Unrealized
performance defined as valuation of unrealized investments as percentage of called capital. We take
the natural logarithm of these performance measures which has the advantage that it functions as
a normalizing transformation and decreases the probability that extreme observations will affect
the findings. Performance is measured in the year before fundraising. For those PE firms which do
not raise a follow-on fund, we measure performance three years after the vintage year of the firsttime fund. This corresponds with a stylized fact in the PE industry: PE investors typically engage
in fundraising activities to establish a new PE fund some three years after the start of their previous
fund (Rider and Swaminathan, 2012; Sahlman, 1990).
Contingency variables. We test to which extent realized and unrealized performance are more
or less valuable signals depending on contingency factors such as early versus late stage markets
and hot versus cold equity markets. First, we construct a number of fund stage dummies for PE
firms which are respectively focusing on early stage deals or late stage deals. Early stage PE firms
include venture capital funds and early stage funds, whereas late stage PE firms include buyout
funds and late stage funds.
We use the yearly S&P500 return to measure the market conditions in which a fund was raised.
The S&P500 return is highly correlated with the return on the MSCI (Morgan Stanley Capital
International) World index (0.9856; p < 0.001). We define hot equity markets as those where yearly
returns are above the median (8%) and cold markets as those where returns are below the median.
As such, we follow Gompers et al. (2008), studying determinants of the likelihood that a VC firm
will invest in a portfolio company, and employing a number of measures related to IPO activity to
assess public market signals.
Control variables. We control for macro-economic evolutions and PE fund characteristics. For
macro-economic evolutions, we include the ratio of private equity raised on GDP. This allows us
to control for the cyclical nature of fundraising in private equity markets (Gompers and Lerner,
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2001). Specifically, we calculated the ratio of private equity raised to GDP for the US economy. We
use statistics for the US because the bulk of PE firms in our sample are located in the US. Moreover,
private equity markets in other regions around the world have typically followed the evolution of
fundraising in the US market. For PE firm characteristics, we control for fund size, location and
industry focus. Fund size is calculated as the natural logarithm of capital under management of
the first-time fund. We control for PE firm location to control for differences in the development of
PE markets for different regions around the globe. We make a distinction between firms located in
the US, Europe and rest of the world. We use firms located in the US as the base category. We also
control for firm industry focus as PE investors might specialize in investments within particular
industries or have a more generalist investment strategy.
Econometric Approach
Our dependent variable is dichotomous and hence we use logistic regression models. An
assumption in traditional logistic regression models is that observations are independent of each
other. Nevertheless, funds with the same vintage year might share particular characteristics. To
deal with such potential clustering in our data, we use the “cluster” option in Stata and report
robust standard errors for each regression coefficient. To test hypotheses 3 and 4, we split the full
sample into respectively early stage versus late stage funds and hot versus cold equity markets.
We consciously opt not to interact realized performance and unrealized performance with a
fund stage variable or equity market index in a full-sample analysis. Unlike linear models, the
coefficient of interaction terms in nonlinear models does not represent the marginal effect of the
interaction, and its statistical significance cannot be tested using a t-test and may even be of an
opposite sign (Hoetker, 2007). Our approach is consistent with previous research confronted with
a similar challenge (e.g., Dushnitsky and Shaver, 2009). We use seemingly unrelated estimation,
or the “Suest” command in Stata, to compare coefficients between the different logistic regression
models (Weesie, 1999).
Results
Descriptive Statistics and Correlations
Table I reports descriptive statistics for the overall sample of first-time PE funds, and the
subsamples of early stage PE funds, late stage PE funds, PE funds which engage in fundraising
during hot equity markets and PE funds which engage in fundraising during cold equity markets.
Table II reports the correlations between the dependent and independent variables. There is no
indication that multicollinearity may unduly influence our results.
Main Results
The results of the logit regressions estimating the likelihood of raising a follow-on fund are
reported in Table III. In the first model, we focus on the impact of overall performance of firsttime funds on the likelihood of raising a follow-on fund. In the second model, we split up overall
performance and focus on the impact of realized performance and unrealized performance of
first-time funds on the likelihood of raising a follow-on fund. In the third model, we report the
impact of realized performance and unrealized performance of first-time funds on the likelihood
of raising a follow-on fund for respectively early stage funds (Model 3A) and late stage funds
(Model 3B). In the fourth and final model, we report the impact of realized performance and
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unrealized performance of first-time funds on the likelihood of raising a follow-on fund during
respectively hot equity markets (Model 4A) and cold equity markets (Model 4B).
Hypothesis 1 stated that higher performance of first-time funds would increase the likelihood
of raising a follow-on fund. Model 1 shows a positive relationship between the overall performance
of first-time funds (β = 2.31; p < 0.01) and the likelihood of raising a follow-on fund. This provides
support for Hypothesis 1: higher overall performance signals PE firm quality which increases the
likelihood of first-time funds to raise a follow-on fund.
Hypothesis 2 stated that (a) higher realized performance and (b) higher unrealized
performance of first-time funds would increase the likelihood of raising a follow-on fund. Model
2 shows that first-time funds with higher realized performance have a higher likelihood of raising
a follow-on fund (β = 0.22; p < 0.001). First-time funds with higher unrealized performance also
have a higher likelihood of raising a follow-on fund (β = 1.06; p < 0.01). Overall, this provides
support for Hypothesis 2a and 2b: both higher realized performance and unrealized performance
signals PE firm quality which increases the likelihood of first-time funds to raise a follow-on fund.
Hypothesis 3 stated that higher realized performance of first-time funds would have a stronger
influence on the likelihood of raising a follow-on fund for late stage funds compared to early stage
funds. Model 3A reports the findings for early stage funds. We fail to find a significant impact
of realized performance of first-time, early stage funds on the likelihood of raising a follow-on
fund. Unrealized performance has a positive impact on the likelihood of raising a follow-on fund
for first-time, early stage funds (β = 1.90; p < 0.05). Model 3B reports the findings for late stage
funds. We find a positive impact of both realized performance (β = 0.51; p < 0.001) and unrealized
performance (β = 1.46; p < 0.10) of first-time, late stage funds on the likelihood of raising a followon fund. Providing additional supporting evidence for Hypothesis 3, the coefficient of realized
performance is significantly larger for first-time, late stage funds compared to first-time, early
stage funds (p < 0.05). The coefficient for unrealized performance is not significantly different
between first-time early stage and late stage funds.
Hypothesis 4 stated that higher realized performance of first-time funds would have a stronger
influence on the likelihood of raising a follow-on fund in hot relative to cold equity markets.
During hot equity markets, the likelihood of raising a follow-on fund increases significantly when
first-time funds report higher realized performance (β = 0.53; p < 0.001) and higher unrealized
performance (β = 1.82; p < 0.05). During cold equity markets, we fail to find a significant impact
of realized performance of first-time funds on the likelihood of raising a follow-on fund. We do
find a positive impact of unrealized performance by first-time funds on the likelihood of raising a
follow-on fund during cold equity markets (β = 1.30; p < 0.05). Providing additional supporting
evidence for hypothesis 4, the coefficient of realized performance of first-time funds is significantly
larger during hot relative to cold equity markets (p < 0.05).
Discussion and Conclusion
This study aimed at contributing to our limited understanding of the effectiveness of signaling
for different firms operating in different environments. Specifically, we assessed how different
performance signals affected follow-on fund raising likelihood in the case of first-time PE funds,
hereby considering different types of performance for different firms (early versus late stage funds)
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Vanacker et al.: PRIVATE EQUITY FUND PERFORMANCE SIGNALS
F RO N T I E R S O F E N T R E P R E N E U R S H I P R E S E A RC H 2 0 1 3
and different contexts (hot versus cold equity markets). Our findings indicate that, while overall
performance, realized performance and unrealized performance function as effective signals,
positively influencing follow-on fundraising likelihood, the strength of these signals is contingent
on a number of factors. Specifically, we found that the impact of realized performance is larger
in case of late stage follow-on fundraising and in hot equity markets. We attribute this to the
selective attention of potential investors, who direct their attention to a larger extent to realized
performance in cases such performance can be expected to be optimally realized after a relative
short lifespan of the fund (typically 3 years). This is to a larger extent the case for late stage funds
and funds raising follow-on funds during hot equity markets.
The aforementioned results provide interesting insights to both signaling and private equity
literature, amongst others. It may however be argued that, in our analysis, performance is just
a mediator between PE firm human capital or reputation and the likelihood of raising followon funds. Indeed, Zarutskie (2010) shows that the human capital of a VC management team
managing a first-time VC fund is an important driver of VC fund performance. She further
shows that PE managers with more task-specific human capital in managing a start-up and more
industry-specific human capital in consulting increase the likelihood of raising a follow-on fund.
Our results might hence be attributed to unobserved difference in the quality of first-time PE
funds. Nevertheless, we control for the size of first-time PE funds, which is likely to capture some
inherent quality differences between first-time funds. More importantly, we show that first-time
PE funds with higher performance do not simply have a higher likelihood of raising follow-on
funds. Indeed, we do not find evidence that first time early stage funds with a higher realized
performance have a higher likelihood of raising follow-on funds, nor do we find that evidence that
first-time funds with higher realized performance have a higher likelihood of raising follow-on
funds in cold equity markets. As such, it is not likely that our findings can be entirely attributed to
such mediation effect.
Our findings have implications for academia and practitioners. For academia, our research
has important implications to the signaling and private equity literatures. By linking signaling
theory to the attention-based view, we provide an insight into which mechanisms explain the
effectiveness of signals. Specifically, we show that it is less effective to send signals which are not
found very credible or which are not in line with the signal receiver’s expectations, which is the case
for realized performance signaled by early stage funds or in cold equity markets. In such situations
and contexts, the signal receiver’s attention is largely focused on unrealized performance signals.
Further, our research context allowed to study performance signals in a continuum, while previous
research has, often limited by available measures, dichotomized these firms in high-quality and
low-quality firms. In sum, our research contributes to the signaling literature by studying gaps
related to the continuum of signals, while taking into account the signaling environment and
taking the perspective of the receiver, while extant research has focused on the perspective of the
signaler (Connelly et al., 2011). We further make an important contribution to the private equity
literature. While previous studies have highlighted the importance of performance for follow-on
fund raising, we confirm these findings in the context of first-time funds, while our findings indicate
that performance is not a homogeneous construct, and that unrealized and realized performance
is attended to by signal receivers differently, and contingent on situational and contextual factors.
For practitioners, including general and limited partners of private equity funds, our findings
provide interesting insights into which signals are more effective in which situations. Specifically,
our research shows that realized performance signals are more effective in hot equity markets and
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when late stage funds raise follow-on funding. In such situations, it may be more effective for
general partners to focus on optimizing realized performance signals instead of using unrealized
performance signals. Along the same lines, limited partners may benefit from understanding how
their peers value different performance signals in different situations.
CONTACT: Tom Vanacker; [email protected]; (T): +32 9 264 79 60; Faculty of Economics
and Business Administration, Tweekerkenstraat 2, 9000 Gent, Belgium.
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Table I. Descriptive statistics
Overall sample
Early stage
Late stage
Hot markets
N = 238
N = 80
N = 116
N = 149
Cold markets
N = 89
Mean
S.D.
Mean
S.D.
Mean
S.D.
Mean
S.D.
Mean
S.D.
Does first-time fund raise a follow-on fund?
0.36
0.48
0.31
0.47
0.34
0.47
0.29
0.45
0.47
0.50
Overall performance
0.73
0.20
0.64
0.23
0.76
0.19
0.70
0.19
0.77
0.23
Realized performance
1.93
1.71
1.16
1.51
2.28
1.61
1.80
1.63
2.17
1.81
Unrealized performance
4.39
0.55
4.28
0.72
4.46
0.44
4.37
0.49
4.41
0.64
S&P500
6.28
17.07
6.62
17.11
7.11
16.96
16.41
6.26
-10.67
15.95
Buyout fund
0.39
0.49
0.00
0.00
0.80
0.40
0.41
0.49
0.36
0.48
Early stage fund
0.15
0.35
0.44
0.50
0.00
0.00
0.13
0.33
0.18
0.39
Late stage fund
0.10
0.30
0.00
0.00
0.20
0.40
0.11
0.32
0.07
0.25
Venture capital fund
0.19
0.39
0.56
0.50
0.00
0.00
0.20
0.40
0.17
0.38
Other
0.18
0.38
0.00
0.00
0.00
0.00
0.15
0.36
0.22
0.42
Private equity raised on GDP
0.81
0.49
0.88
0.53
0.72
0.45
0.56
0.34
1.22
0.40
Fund size
5.41
1.21
4.65
0.97
5.83
1.08
5.40
1.20
5.42
1.24
Fund location US
0.74
0.44
0.78
0.42
0.68
0.47
0.72
0.45
0.78
0.42
Fund location Europe
0.17
0.37
0.14
0.35
0.21
0.41
0.18
0.39
0.15
0.36
Fund location Rest of World
0.09
0.28
0.09
0.28
0.11
0.32
0.09
0.29
0.08
0.27
Business and industrial products/services
0.47
0.50
0.43
0.50
0.53
0.50
0.49
0.50
0.44
0.50
Consumer products/services and retail
0.28
0.45
0.13
0.33
0.41
0.49
0.34
0.47
0.19
0.40
Energy and environment
0.16
0.37
0.11
0.32
0.20
0.40
0.17
0.37
0.15
0.36
Financial services
0.17
0.37
0.05
0.22
0.26
0.44
0.16
0.37
0.18
0.39
Information and communication technology
0.34
0.47
0.45
0.50
0.29
0.46
0.32
0.47
0.37
0.49
Life sciences
0.37
0.48
0.49
0.50
0.33
0.47
0.36
0.48
0.39
0.49
Other industries
0.28
0.45
0.08
0.27
0.32
0.47
0.28
0.45
0.28
0.45
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Table II. Correlation matrix
1
1 Does first-time fund raise a follow-on fund?
2
3
4
5
6
7
8
9
10
11
1.00
2 Overall performance
0.26
1.00
3 Realized performance
0.16
0.49
1.00
4 Unrealized performance
0.18
0.60
-0.14
1.00
5 S&P500
-0.13 -0.05 -0.07
0.03
1.00
6 Buyout fund
0.00
0.09
0.00
7 Early stage fund
-0.01 -0.23 -0.17 -0.17 -0.05 -0.33
8 Late stage fund
-0.07 -0.02 -0.03
0.06
0.08
-0.26 -0.14
9 Venture capital fund
-0.07 -0.13 -0.24 -0.02
0.06
-0.39 -0.20 -0.16
10 Other
0.14
0.14
0.14
0.01
-0.08 -0.37 -0.19 -0.15 -0.22
1.00
11 Private equity raised on GDP
0.30
0.26
0.13
0.10
-0.48 -0.11
0.11
0.03
0.08
1.00
12 Fund size
0.20
0.17
0.15
0.10
-0.03
-0.27 -0.05 -0.29
0.10
-0.08
0.17
0.22
1.00
0.38
1.00
1.00
-0.11
1.00
Note. All correlations with absolute value greater than 0.12 are significant at p < 0.05. Fund location and fund industry
focus controls are not reported. Variables 1, 6, 7, 8, 9 and 10 are dummy variables, hence their correlations should be
interpreted with care.
Table III. Logit estimation of the probability of raising a follow-on fund
Model 1
(Full sample)
Model 2
(Full sample)
Model 3A
(Early stage)
Model 3B
(Late stage)
Model 4A
(Hot market)
Realised performance
0.22 *** (0.06)
-0.22
0.51 *** (0.12)
0.53 *** (0.12)
0.11
Unrealized performance
1.06 ** (0.33)
1.46 †
(0.87)
1.82 *
(0.75)
1.30 * (0.57)
0.01
(0.03)
Overall performance
Model 4B
(Cold market)
2.31 ** (0.69)
(0.25)
1.90 * (0.87)
-0.03
(0.02)
(0.13)
S&P500
0.00
(0.02)
0.00
(0.02)
Early stage fund
0.26
(0.64)
0.39
(0.63)
0.54
(0.94)
1.59
(1.20)
Late stage fund
0.25
(0.77)
0.25
(0.79)
1.74 *
(0.78)
-1.56
(1.69)
Venture capital fund
0.03
(0.46)
0.19
(0.43)
-1.66 ** (0.58)
Other fund
0.65
(0.56)
0.77
(0.57)
(0.75)
0.70
(0.72)
Private equity on GDP
1.25
(0.85)
1.28
(0.87)
1.80
(1.38)
1.00
(1.18)
4.44 *** (0.99)
-1.52
(1.07)
Fundsize
0.46 ** (0.17)
0.47 *
(0.19)
0.59 * (0.26)
0.20
(0.16)
0.48 *
-0.55
(0.53)
-0.77
(0.80)
Fund location Europe
-0.67 †
(0.35)
-0.67 †
(0.37)
Fund location Rest of World -0.80
(0.59)
-0.74
(0.58)
Business products/services
0.31
(0.30)
0.35
(0.31)
Consumer and retail
1.19
2.39 * (1.04)
-0.31
(1.08)
(omitted)
0.68
(0.58)
0.38
(0.37)
-0.47
(0.21)
0.85 ** (0.28)
(0.88)
-0.79 † (0.46)
(omitted)
1.80 * (0.88)
0.22
(0.51)
1.29 * (0.52)
1.50 *
0.22
(0.32)
0.26
(0.33)
1.31
(1.37)
0.56 †
(0.34)
(0.58)
-2.18 * (0.91)
Energy and environment
-0.19
(0.46)
-0.23
(0.48)
-1.17
(1.17)
0.29
(0.46)
-0.45
(0.80)
-0.10
(1.12)
Financial services
-0.54
(0.59)
-0.63
(0.61)
-0.74
(0.76)
-2.52 †
(1.48)
1.81
(1.21)
ICT
0.10
(0.44)
0.16
(0.47)
1.11
(0.82)
0.18
(0.70)
1.24 *
(0.51)
-1.03
(0.81)
Life sciences
0.80 *
(0.34)
0.79 *
(0.34)
1.43 ** (0.53)
0.07
(0.48)
1.25 *
(0.50)
0.69
(0.72)
(omitted)
0.12
(0.50)
(0.75)
0.54
(0.85)
-14.64 ** (4.36)
-10.78 **
(3.97)
Other industries
-0.22
Constant
-6.34 *** (1.56)
Pseudo R-squared
0.19
Chi-square 58.39 ***
(0.39)
-0.19
(0.40)
-9.96 *** (2.20)
0.20
61.75 ***
(omitted)
0.34
28.81 **
0.18
27.08 *
-0.79
-16.47 *** (3.82)
0.43
73.25 ***
-10.22 ** (3.46)
0.28
34.84 **
Note. Robust standard errors clustered by vintage year are reported in parentheses. *** p < 0.001; ** p < 0.01; * p < 0.05 and
† p < 0.10 (conservative two-tailed tests).
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