Venture Capital in Europe

and the Financing of Innovative Companies

Laura Bottazzi∗

Universita Bocconi, IGIER, and CEPR

and

Marco Da Rin

Universita di Torino and IGIER

July 2001

Abstract

Venture capital is considered to be the most appropriate form of financing for innovativefirms in high-tech sectors. Venture capital has greatly developed over the last threedecades in the United States, but much less so in Europe, where policy makers are strivingto help channel more funds into this form of financial intermediation. We provide thefirst assessment of venture capital in Europe. We document its development in the 1990s,also providing a conceptual framework for this analysis. Comparing the evolution andstructure of European and American venture capital, we find the wedge between thesetwo industries to be large and growing. We then look at the involvement of venturecapital with some of Europe’s most innovative and successful companies: Those listed onEurope’s ’new’ stock markets. Venture capital is effective in helping these firms overcomecredit constraints, and thus to be born in the first place. Using a unique, hand collecteddata set from the listing prospectuses and annual reports of these companies, we then findEuropean venture capital to have a limited effect on their ability to raise funds, grow, andcreate jobs. We conclude that public support of the European venture capital industryshould look at both its growth and at its maturation.

Forthcoming, Economic Policy, v.34, 229-69, April 2002.

∗We thank Erik Berglof, Jean-Bernard Chatelain, Jan van Ours, Henri Pages, Guido Tabellini, and partic-ipants to the Economic Policy 33rd Panel Meeting for valuable comments. Detailed suggestions by RichardBaldwin (the editor) helped us improve the quality of the paper. Veronica Guerrieri, Giuseppe Maraffino,Gaia Narciso, and Battista Severgnini provided excellent research assistance. We also thank all the companieswhich provided us with data and prospectuses. Financial support from Fondation Banque de France and fromUniversita Bocconi (Ricerca di Base) is gratefully acknowledged. All errors remain our own.

1 Introduction

The ability to encourage and sustain technological innovation is one of the main sources of

economic growth. In the last decade, the increasingly rapid pace of innovation induced by en-

trepreneurial firms has substantially contributed to the strong competitiveness and protracted

growth of the US economy. Several studies have documented the ability of US venture capi-

talists to select promising companies, provide adequate financing, and spur innovative firms

to behave aggressively and emerge as market leaders (see Hellmann (2000) for an overview).

A wide consensus among economists, business leaders, and policy-makers exists that a vibrant

venture capital industry is a cornerstone of America’s leadership in the commercialization of

technological innovation, and that the lack of venture capital hinders European firms from

competing on an equal footing (European Commission (1994)).

Several official documents of European governments and institutions suggest bolstering

venture capital and revamping the regulation of stock markets as remedies to Europe’s eco-

nomic slugginesh and dismal unemployment. For instance, the European Commission’s 1998

Risk Capital: A Key to Job Creation in the European Union Communication states as its

main message that ‘[d]eveloping risk capital in the European Union, leading towards the

development of pan-European risk capital markets is essential for major job creation in the

EU’ (European Commission (1998) p.1). As the title of the Communication indicates, the

creation of a pan-European equity market for innovative companies was identified by the

Communication as a crucial step not only for providing risk capital to companies, but also

for the creation of a substantial number of new jobs.

More recently, the ’Final Report of the Committee of Wise Men on the Regulation of

European Securities Markets,’ ’urges governments and the European institutions to pay par-

ticular attention to ensuring that there is an appropriate environment for the development

of the supply of risk capital for growing small and medium sized companies, given the cru-

cial importance of this sector for job creation’ (Committee of Wise Men (2001) p.10). The

Committee goes on to argue that ’[t]oday there is still an inadequate supply of risk capital

in the EU with venture capital only one fifth of US per capita levels. However, if the Euro-

pean Union’s financial markets can integrate (...) European venture capital financing will be

encouraged from the bottom up’ (p.78).

Other official documents and reports identify the immaturity of Europe’s venture capital

industry and the hostility of its stock exchanges towards young firms as powerful obstacles to

the growth of European entrepreneurial firms (see for instance Bank of England (2000)). In

1

turn, entrepreneurial firms are viewed as major contributors to economic growth and to the

creation of new jobs (see German Federal Ministry of Economic and Technology (1999a,b)),

and venture capital as an important tool for job creation, technological innovation, export

growth, and regional development (European Investment Bank (2001)). There is a growing

perception that Europe’s growth problems may be caused not as much by rigidities in labour

markets, as by weakensses in capital markets, and in particular in the access to risk capital.

These documents raise important policy issues. In particular, it is crucial to understand

how policy can actually contribute to the growth of a dynamic venture capital industry in

Europe. European official documents, but also industry reports like the White Paper of the

European Venture Capital Association (EVCA (1998)), tend to focus on the supply of funds

and on the creation of favorable structural conditions for entrepreneurship. However, it is far

from evident which policy measures would be most appropriate to nurture venture capital in

Europe. Here the lack of rigorous investigation is felt most.

In this paper we provide a contribution in this direction by developing the first systematic

analysis (to the best of our knowledge) of venture capital in Europe. To get around the dearth

of firm-level data on European venture capital, we exploit the unique opportunity offered by

the opening in 1997 of Euro.nm, the alliance of Europe’s ’new’ stock markets for innovative

companies in high-growth industries–along the lines of America’s Nasdaq. Euro.nm brought

under its wings the ’new’ markets of Amsterdam, Brussels, Frankfurt, Paris, and (since June

1999) Milan. Euro.nm ceased to exist as an alliance in December 2000, but its five members

have continued to operate independently. Over its life span, Euro.nm has allowed nearly 600

companies to list and raise over 40 billion euros of equity capital.

We collect a unique data set from issuing prospectuses and annual reports of more than

500 Euro.nm listed companies. These data provide an excellent opportunity to study the

effects of venture capital on Europe’s innovative companies, given the wealth of information

which they are required to disclose in order to go public. We focus on three key issues. First,

we develop a conceptual framework for appraising the role of venture capital in the financing

of innovative companies. Second, we document the development of venture capital in Europe,

compare it to that of US venture capital, and assess the extent and determinants of venture

financing to companies listed on Euro.nm. Third, we study the effect of venture capital on

the ability of these companies to raise funds, grow, and create jobs.

The evidence we provide is useful in assessing the extent to which European venture capital

helps create and nurture innovative companies. We challenge several common beliefs on the

role of venture capital in Europe, and question its ability to make a difference for economic

2

growth and job creation. In particular, we argue that venture-backed companies do not grow

and create jobs faster than non venture-backed companies. Whether this is due to a lack of

’stars’ among European firms or to the immaturity of European venture capital is not possible

to tell apart, but several pieces of evidence make the latter possibility more than likely. We

also have good news. We find that venture capital does help European innovative companies

by providing them with financing crucial for their creation and development. This also means

that an increasing number of (venture-backed) companies benefits from the possibility to go

public on Euro.nm, with a positive effect on the growth of Europe’s ’new’ stock markets.

Since venture capitalists benefit, in turn, of the possibility to exit their investments through

a listing on a stock market, this may have triggered a self-reinforcing virtuous circle.

These findings provide support for the European Commission’s stated policy of promot-

ing European venture capital. The major action of Commission in this respect has been

transformation of the European Investment Fund (EIF) into a major investor in venture cap-

ital funds. Our findings suggest that the ’quality’ of European venture capital should be as

urgent a concern for the EIF as its sheer ’quantity,’ so as to advance both the size and the

maturation of the industry.

The rest of the paper is organised as follows: Section 2 provides a primer on venture

capital based on the extant economics literature and on the available empirical evidence.

Section 3 develops a statistical portrait of the European venture capital industry, comparing

it to its American counterpart and assessing its involvement in financing Euro.nm listed

companies. Section 4 evaluates the role of European venture capital in the companies it

finances. Section 5 concludes. A Data Appendix contains a detailed description of our data

collection, and a Web Appendix provides additional tables and material.

2 Venture capital and the creation of innovative companies

2.1 History, definitions and jargon

In 1946 Georges Doriot, a professor at Harvard University, created American Research and

Development (ARD) together with Karl Compton, president of the Massachusetts Institute of

Technology, Merrill Griswold, chairman of Massachusetts Investors Trusts, and Ralph Flan-

ders, president of the Federal Reserve Bank of Boston. ARD was created to raise funds

from wealthy individuals and college endowments and invest them in entrepreneurial start-

ups in technology-based manufacturing: Modern venture capital was born. Half a century

3

later venture capital has become the form of financial intermediation most closely associated

with dynamic entrepreneurial start-ups, especially–though not exclusively–in high-tech in-

dustries like biotechnologies, computer hardware and software, information technology (IT),

e-commerce, medical equipment, and telecommunications.1 Many of today’s most dynamic

and successful corporations received venture capital at the initial stages of their lives: Ama-

zon, Apple, Cisco, e-Bay, Genentech, Genetic Systems, Intel, Microsoft, Netscape, and Sun

Microsystem, to name just a few. As a result, venture capital has developed into an impor-

tant, established form of financial intermediation (see Gompers and Lerner (2001)).

The maturation was not smooth, though (see Gompers (1994)). Until the 1980s, ven-

ture capital firms were in large part publicly funded Small Business Investment Companies

(SBICs). While SBICs trained many venture capitalists and helped the industry reach a

critical mass by channeling large sums to start-ups, their ability to perform was limited by

bureaucratic constraints, lack of professional expertise, and a faulty design of capital structure

and incentives (Lerner (1994a)). Their investment record was in fact mixed, and spurred a

fall in investor confidence and in committed funds around the late 1980s. Also, many venture

firms, including ARD, were organized as closed-end funds, but this attracted retail investors

with short-term horizons, whose needs clashed with the long-term returns of venture capital.

Only in the late 1980s were SBICs and closed-end funds superseded by the limited partner-

ship as the dominant organizational form of American venture capital firms. Another major

contribution to the adoption of a more efficient organizational form was the clarification, in

1979, of the Employment Retirement Income Stabilization Act, which allowed pension funds

to invest in venture capital. This resulted in a staggering increase of funds invested, and in

a faster professionalization of the industry.

Until the early 1990s, venture capital remained essentially an American phenomenon.

Its success in supporting dynamic companies which create jobs and wealth brought many

governments to look for ways to nurture a national venture capital industry. At the same

time, the high returns enjoyed by US venture capital firms induced venture capitalists to

become active also in other countries. Venture capital is by now a sizeable industry also in

Europe and Asia.

While no standard definition of venture capital exists, there is wide consensus that it

corresponds to the professional financing of young, unlisted dynamic ventures through equity

or equity-like instruments like convertible securities. Unlike wealthy individuals who occa-

1Dynamic firms in traditional services, like Federal Express, Staples, or Starbucks, also received a sizeableshare of venture finance.

4

sionally invest in start-ups (’business angels’), venture capitalists are professional investors,

organised in small limited partnerships, who raise funds from wealthy individuals and in-

stitutional investors and invest on their behalf. They specialise in financing young firms

which typically have not yet produced any sales, but which have high growth and earnings

potential–many investees are ’start-ups’ which come into life through venture financing.

Box 1 provides an explanation of some common terms of the venture capital jargon.

2.2 Financing an innovative company: The alternatives

2.2.1 How to start a start-up

Why do innovative companies in high-tech industries get financed primarily by venture capi-

talists? To set the stage for our empirical investigation, it is useful to consider what we know

about this question, and therefore what one would expect to find from companies backed by

a venture capitalist.

Consider the hypothetical case of a brilliant academic engineer who has just discovered

in his lab a technology to produce a new type of circuit for mobile phones. He believes his

product would make an important breakthrough by opening a market for three-dimensional

messaging. He thinks he could get rich and famous by creating a start-up which could hope-

fully go public. However, the industrial implementation of his product requires an investment

in the order of three million euros. This sum far exceeds his personal wealth and that of his

family and friends. He asks his bank for a loan, but is told that the bank does not lend to

start-ups–unless enough collateral is pledged to cover the full value of the loan. The same

disappointing answer comes from several other banks he then contacts.

2.2.2 Why banks won’t do

Why do banks typically refrain from investing in start-ups? The reason is that they are

not a suitable financier for this type of projects. Banks specialize in raising deposits from

the public, lending these sums to businesses, and earning an interest margin in the process.

The high liquidity of deposits requires that loans be made only to businesses likely to repay

within a relatively short period and with high probability. Banks also rely heavily on a firm’s

tangible assets for collateral, but the assets of entrepreneurial start-ups are in large part

intangible, like marketing knowledge or technology. In other words, the very nature of banks

makes them suitable to lend to firms in established industries, with reasonably predictable

cash flows.

5

Box 1: The jargon of venture capital

Start-up: a new company which is created by an entrepreneur in a high-tech industry,

often with the goal of going public within a few years.

Limited partnership: the typical form of organization of a venture capital firm. Its

’general partners’ (venture capitalists) manage the firm and assume full liability,

while ’limited partners’ (investors) provide funds and assume no liability beyond

the contributed capital.

Captive: a venture capital firm which is owned by an industrial company or a finan-

cial intermediary. Captives are common in Europe, whereas in the US ’independent’

venture firms, which raise money from institutional investors, are the norm.

Convertible securities: equity-like financial instruments which offer venture capi-

talists strong protection in case of liquidation, while ensuring participation in the

upside should the project succeed.

Vesting: a legal term which indicates the process by which a person comes into

possession of corporate stock. It usually applies to entrepreneurs or employees whose

right of possession over their stocks is contractually deferred until a certain date or

until certain targets are met.

’Exit’ : the mode of exit from an investment. Venture capitalists typically exit their

investee companies through an IPO, a trade sale, or by writing-off (liquidating) a

non-performing company.

Initial Public Offering (IPO): the offering of corporate stock to the public through

which a company ’goes public’. It is the most sought after way of cashing in their

investment by venture capitalists and entrepreneurs, since it allows the highest val-

uation.

Trade sale: sale of a start-up to another company, typically a large competitor. It is

a common way for venture capitalists to liquidate their investment when a company

is not growing enough for an IPO or the stock market is experiencing a downturn.

Write-off: the disaster scenario. When a funded company fails, the venture capital

writes off the investment from its assets. Most venture investments end up as write-

offs.6

A start-up, on the contrary, is an utterly risky business: Most start-ups go bust but are

extremely profitable if eventually successful. Another reason for banks’ reluctance to finance

start-ups is their being heavily regulated intermediaries which face severe limits to holding

equity.

2.2.3 Some possible alternatives...

What other options could our engineer consider? The embryonic form of his project rules

out direct access to capital markets, which is feasible only for firms with a proven business

model, a solid organization, and a clear earning potential. Moreover, the capital needed by a

start-up (three million euros in our example) is far below the minimal threshold for an Initial

Public Offering (IPO). Government grants are also unsuited for such a project, since they

are typically targeted at very small firms, and often require a proven track record which no

high-tech start-up may provide (see Gordon (1998) and Lerner (1999)).

Four practicable options remain: convincing a ’business angel’ or a financial company to

invest in the start-up, finding an established industrial company interested in supporting the

project (a ’corporate venture capitalist’), or going for a venture capitalist.

A business angel is a wealthy individual who invests directly in a private company (see

Benjamin and Sandles (1998) and Prowse (1998)). In some countries associations or groups of

business angels provide some legal and organizational support, but these individuals largely

invest based on personal relationships. In some cases they also provided expert knowledge of

an industry, since many of them are (or have been) executives.

A financial company is a holding company which invests in industrial companies. Finan-

cial companies rarely invest in start-ups. They prefer more mature firms which are close to

going public, to which they often provide ’bridge financing’ to strengthen a company’s equity

base in the wake of the IPO.

A corporate venture capitalist is an industrial company which invests in start-ups directly

or through a dedicated subsidiary–such as Innovacom, the venture capital arm of France

Telecom. Established companies invest in new ventures in order to keep up with technological

developments and acquire a foothold on possible breakthrough. In other words, they invest

for financial but also strategic reasons (see Hellmann (2001)). Corporate venture capitalists

bring to new ventures not only money but also knowledge of the market and organizational

strength (see Gompers and Lerner (2000)).

7

2.2.4 ... and their drawbacks

Our engineer ponders over these possibilities. He discards business angels, since they are

a good source of funds, but only for smaller start-ups. Moreover, business angels lack the

financial power which is needed at later stages–and he would rather not risk being stranded

once his business starts rolling. Corporate venture capitalists have their drawbacks, too.

Sometimes, especially in Europe, they are bureaucratic and slow, while start-ups need speed

and thrust to succeed. Also, a start-up which threatens to ’cannibalise’ a major source of

revenue of its corporate venture capitalist may end up being delayed or even stopped. In fact,

start-ups backed by a corporate venture capitalist have been found to choose a less aggressive

strategy than those financed by independent venture capitalists (Zahra (1996). Our investor

believes his project to be highly innovative, and therefore wants to avoid the risk of being

put on hold by a corporate venture capitalist. His scant experience in business suggests

that a professional venture capitalist, with his extensive business contacts and experience in

mentoring start-ups, may be a better solution. These gains of being financed by a venture

capital seem to outweigh its costs, which consist of a constant scrutiny of all decisions, of the

risk of losing control if performance is unsatisfactory, and of the large amount of equity the

venture capitalist takes in exchange for his money and support. Our engineer decides to seek

support from a venture capitalist. What should he expect?

2.3 A conceptual framework for venture capital

2.3.1 The soft side of venture capital

Systematic accounts of the operations of US venture capital firms are provided by Barry et al.

(1990), Sahlman (1990), and more recently by Kaplan and Stromberg (2000). These studies

show that venture capital constitutes a special form of financial intermediation, with contrac-

tual arrangements substantially different from debt contracts. The nature and complexity

of these arrangements suggest that the financial ’hard’ side of the capital contribution is

complemented by a non-financial ’soft’ side consisting of mentoring and monitoring. Venture

capitalists are often thought of as providing firms with expert advice together with stringent

incentives to perform. Venture capitalists’ expertise and network of contacts with potential

suppliers and customers allow entrepreneurs to focus on what they are best at–technical de-

velopment. Their industry knowledge is precious for honing strategies. They concentrate on

start-up firms located nearby, and use their knowledge of industries and markets to evaluate

and mentor entrepreneurs. Indeed, most venture capitalists have higher degrees, and a tech-

8

nical, not economic or financial, background. Venture capitalists also provide ’reputational

capital’ by allowing firms to boast being venture-backed so as to lure top-fly executives or

to obtain new contracts. But venture capitalists are also demanding investors, who retain

the right to remove the entrepreneur from his post of chief executive officer should she fail to

meet any agreed upon milestone. The combination of these ’soft’ sticks and carrots is widely

seen to provide venture-backed start-ups with an advantage over others firms, since it should

increase the chances of survival, and help start-ups attract further funding as they expand.

The narrative literature on venture capital documents extensively these ’soft’ aspects of

venture capital. For instance, Gorman and Sahlman (1989) find that the lack of business

experience of many entrepreneurs makes mentoring from expert venture capitalists crucial to

their chances of success. Survey evidence from four countries collected by Sapienza, Manigart,

and Vermeir (1996) shows that venture capitalists see themselves as mentors and advisors.

Sapienza (1992) also finds that the involvement of venture capitalists increase with the degree

of innovation pursued by a firm. Rosenstein et al. (1993) find that entrepreneurs who are

financed by leading venture capitalists regard these as the most useful board members.

More formal studies of how venture capital works in the US corroborate this anedoctal

findings. For instance, venture capitalists do not provide full financing upfront, but disburse

money in installments at different stages of a firm’s development. contingent on the achieve-

ment of milestones such as the construction of a prototype, a certain amount of sales, or the

hiring of key management figures. Financing at different stages is found to take different roles

(see Box 2) and to allow venture capitalists to gather information over time, thus keeping the

option of abandoning firms whose hopes of success have dwindled (Gompers (1995)). Venture

capitalists are also found to closely oversee investee firms, and to be active board members

who step in and take control when times get difficult (Lerner (1995)).

Some recent analyses of the influence of venture capital on corporate strategy and per-

formance provide even tighter evidence that non-financial aspects are crucial to define the

activity of venture capital. Venture-backed firms are found to be faster in developing their

products and in bringing them to the market (Hellmann and Puri (2000))–an important ad-

vantage in technology markets, where timing is essential to achieve market leadership. This

implies that venture capitalists provide dynamic companies with money but also with support

and monitoring of their management. Venture-backed companies are in fact found to pursue

more radical and ambitious product or process innovations than other companies (Hellmann

and Puri (2000)). Venture capitalists also play an important role in the professionalization of

the firms they invest in, for example by helping them hire experienced financial and marketing

9

executives and by firing under-performing chief executive officers (Hellmann and Puri (2002)).

Very importantly, venture-backed companies produce more, and more valuable, patents than

non venture-backed firms (Kortum and Lerner (2000)).2 Venture capitalists also shield com-

panies from the need to rush to markets, thus prematurely disclosing strategic information

to competitors. They also allow firms to go public only when market conditions are most

favorable (Lerner (1994a)).

Box 2: The stages and roles of venture capital financing

Seed finance: Small investment, in the order of a few hundred thousand euros at

most, which allows an entrepreneur to verify whether his project is feasible and eco-

nomically attractive. At this stage the venture capitalist helps explore the viability

of a project.

Start-up finance: Investment aimed at making a firm operational by attracting the

necessary employees and executives, developing a prototype and/or implementing

marketing tests. At this stage the venture capitalist may become involved in the

organization of the company. His contribution to shaping corporate strategy is felt

most heavily at this stage.

Expansion finance: Investment aimed at reaching the scale of industrial production,

upgrading the production facilities and attracting further employees. At this stage

the venture capitalist may help find additional financing and help the company

contact clients and suppliers. As the company grows and needs revenue, he may

also help recruit marketing and other non-technical executives.

Later stage finance: Investment aimed at helping the firm grow fast enough to be-

come a market leader and unleash its earning potential and to make it ready for a

trade sale or for listing on a stock exchange. At this stage the venture capitalist

may help set the stage for either a trade sale or an Initial Public Offering.

2Venture capitalists also play an important role in the process of going public. Their experience helpscompanies choose the most favorable time for their IPOs (Lerner (1994a)) and experience lower underpricing(Megginson and Weiss (1991)). Venture-backed companies which went public in the US in the 1970s and 1980sare also found to perform better than non venture-backed companies over five years spells (Brav and Gompers(1997)).

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2.3.2 Venture capital as a package of services

Why should the ’hard’ and ’soft’ sides of venture capital coexist under the same roof? In

’standard’ economic conditions straight debt contracts provide the optimal form of financing

(Gale and Hellwig (1985)), so that the separation of financing and mentoring would also be

optimal. However, technological start-ups are not ’standard’ borrowers. A start-up relies on

the talent and skills of its founder, who knows more about its technical aspects than anybody

else. This makes it particularly difficult to evaluate her performance, and requires of the

financier a technical and not purely financial expertise. Moreover, running a laboratory

requires more freedom than operating a factory, so that an entrepreneur can more easily

appropriate funds than a manager in an established firm. Finally, entrepreneurs can use

privy information, like the status of technical tests, to pursue strategies which conflict with

the interest of investors–like rushing to market to gain a reputation of first-comer at the cost

of long-term profitability. Moreover, the very nature of entrepreneurship prevents start-ups

and financiers to write ’complete’ contracts which specify all conceivable future contingencies

(Hart and Moore (1998)). The right to control future strategic decisions is in fact even more

important in determining success for start-ups than for mature firms.

These characteristics of start-ups provide good economic reasons for the coexistence of

the ’hard’ and ’soft’ sides of venture capital. Financial economists have produced several

justifications for why the optimal contract between entrepreneur and venture capitalist should

be different from debt. Optimal financing should not arrive all upfront but should be ’staged,’

coming once new milestones have been met, in order to reveal information on the venture as

it arises (Admati and Pfleiderer (1994) and Bergemann and Hege (1998)). Financing of start-

ups should also take the form of convertible securities in order to induce the entrepreneur

to behave efficiently (Cornelli and Yosha (1998), Repullo and Suarez (1999)), and to allow

financiers to take control of the venture if the entrepreneurs under-performs (Berglof (1994).

A key aspects of these models is that, unlike in standard financial contracting, both the

entrepreneur’s effort and the venture capitalist’s mentoring and monitoring are not verifiable

by a court, and therefore cannot be contracted upon. A start-up therefore creates a situation

where both sides have special skills to contribute for which they experience a problem of moral

hazard. This situation is fundamentally different from that of a bank loan, and in the context

of start-up finance a standard debt contract simply does not work. A formalization of these

results can be found in Casamatta (2000), who focuses on the complementary role of the hard

and soft sides of venture capital, and in Hellmann (1998), who shows that the expertise of

11

a venture capitalist in replacing an under-performing entrepreneur as CEO of his company

is a necessary ingredient for convertible securities to entail an optimal allocation of control

rights.

3 Venture capital in Europe: A statistical portrait

3.1 Venture capital in Europe and the US: A comparison

The first step in assessing the contribution of European venture capital to the creation of

innovative companies requires a quantitative look at the state and structure of the European

venture capital industry and at its evolution over time. Since the US venture capital industry

is the most mature and developed, we use it as the term of comparison for European venture

capital.

We base our analysis on the aggregate statistics published by the European Private Equity

and Venture Capital Association (EVCA) for Europe and by the National Venture Capital

Association (NVCA). These data come from extensive surveys of venture capital firms in

both economies. For Europe, EVCA distributes each year a survey to venture capital firms

irrespective of their EVCA membership status in cooperation with PricewaterhouseCoopers.

For 2000, the last available year, the number of respondents was 949, corresponding to a

70% response rate. The yearly statistics published by NVCA are based on the commercial

database VentureXpert by Venture Economics, a division of Thomson Financial Securities,

which contains data on over 5,000 American venture capital firms.

Tables 1 through 6 and Figures 1 and 2 report our elaborations on these aggregate data

for 1991-2000. There is much that one can learn from these data. Figure 1 shows the amount

of funds raised by venture capital firms, and Table 1 provides a break-down of the sources of

finance. The explosion in venture capital activity during the 1990s is apparent, but has been

uneven. In the US, the amount of funds raised increased by a factor of 80.

Figure 1 about here

In Europe, only by a factor of twelve. What is intriguing is that the level of funding

in Europe increased mostly after the opening of Euro.nm in 1997, which paved the way for

the listing of high-tech start-ups. Whether this coincidence conceals a causal link or reflects

broader changes cannot be told apart based on simple inspection of these figures, but it

suggests a challenging research topic. Figure 1 also shows a widening gap in the amount of

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funds raised in the two economies (which we express in dollars for sake of comparability). The

figure also shows that growth has been smoother in the US, whereas Europe has experienced

several ups and downs.

Venture capitalists finance their activity by raising ’funds’ from institutional investors like

pension funds, insurance companies, or endowments. Each ’fund’ is invested in a number of

firms with a five to ten years horizon. Once a ’fund’ is ended, its cash proceedings, which

come from IPOs and trade sales, are distributed to investors together with any remaining

equity holdings. Table 1 uncovers a substantial difference in the structure of venture capital

funding across the Atlantic. Institutional investors (mainly pension funds) are by far the

largest contributor in the US, accounting for nearly two thirds of all funds, as compared to

less then one third in Europe. The stability of the share of institutional investing in the US is

also worth pointing out as a sign of maturity of that market. European venture capital is in-

stead dominated by funding from financial institutions (mainly banks), which still remain the

largest source of funding. Funds controlled by a financial or corporate entity (’captive’ funds)

are in fact more common this side of the Atlantic, where the share of corporate investment

has doubled in the second half of the 1990s.3 The table also highlights the lower reliance of

American venture firms on ’other’ sources (individual investors and realized capital gains),

another sign of the maturity of that market. Government funding is virtually inexistent in the

US, where publicly-funded Small Business Investment Companies are not considered venture

firms, and it is low in Europe. These profound differences in funding patterns largely reflects

the different structure of capital markets in the two economies. Europe is still dominated

by banks, which control a large part of the mutual funds industry. Since also the nascent

pension fund industry is likely to be controlled by banks, we should expect these differences

to persist, and to influence the behaviour of venture capital firms.

3The drop in the share of corporate funding in the US in 2000 is partly due to the shift from corporatefunds to ’in-house’ corporate investing, which does not get recorded in NVCA statistics.

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Table 1. Venture capital: Sources of finance

Europe

Institutional Investors Corporations Financial Government Other

(%) (%) (%) (%) (%)

1991 15 5 48 2 30

1992 13 6 45 9 27

1993 16 5 40 6 33

1994 20 9 41 3 27

1995 29 5 36 3 27

1996 34 3 35 2 26

1997 26 11 42 2 19

1998 24 10 37 5 24

1999 23 10 43 5 19

2000 31 10 32 5 22

United States

Institutional Investors Corporations Financial Government Other

(%) (%) (%) (%) (%)

1991 76 5 6 - 13

1992 67 4 17 - 12

1993 73 8 12 - 7

1994 69 9 10 - 12

1995 59 5 20 - 16

1996 70 20 3 - 7

1997 56 25 6 - 13

1998 66 12 10 - 12

1999 61 14 16 - 9

2000 61 4 23 - 12

Notes: Institutional investors includes endowments and pension funds, corporations include invest-ments by corporations (including corporate venture capital through dedicated funds), financial insti-tutions includes banks, insurance companies, and funds raised from capital markets, other includesindividuals and realized capital gains. European data in millions of euros (ECUs before 1999) and USdata in millions of dollars.

Source: Authors’ calculations on EVCA and NVCA data.

14

Taken at face value, the aggregate funding data shown in Figure 1 would suggest that in

the second half of the decade Europe has seen an impressive growth in the amount of funds

raised, which increased nearly twelve-fold between 1995 and 2000 after remaining stagnant

in the first half of the decade. Unfortunately, this is not the case. Figure 2 and Table 2 tell

us why. The problem is that aggregate data for funding comprise two very different types

of data. They include funds raised for venture capital, but also funds raised by firms which

specialize in management buy-outs (MBOs). These are financing operations which enable

management to acquire (’buy out’) an existing business from its original owners. MBOs

typically involve established companies in mature industries, and are therefore quite distinct

to venture capital, which is directed to new ventures.4

Figure 2 about here

That the resulting bias is serious is shown by Figure 2, which plots the amount of funds

invested each year. Aggregate data on investments separate between funds which go into

venture capital proper and into MBOs.5 Once we compare the amount of funds raised with

that of funds invested into venture capital proper, we see that the performance of Europe

is less thrilling than suggested by Figure 1: The growth of funds invested in venture capital

between 1995 and 2000 has been near six-fold, a mere fourth of that experienced in the US. A

similar results holds if we look at the whole decade, since its early years saw sluggish growth

in both economies. Despite the rise of venture capital activity, the gap between Europe and

the US has actually widened, and at an increasing pace.

Table 2 reveals that European venture capital invests an increasing share of its funds

at ’early stage,’ which are those where its contribution is expected to be most significant,

though the monetary amount invested in early stage in Europe is about a fifth of what is

invested in the United States. In Europe, the share of early stage financing has more than

doubled between 1997 and 2000, and since 1999 it has been greater than in the US. Again,

though one is intrigued by the coincidence of the opening of Euro.nm and the increase in this

riskier type of investments, a causal can only be conjectured at this stage. In both countries

the majority of funds goes to expansion investments. These go to companies which have

4EVCA started separating the amount of funds raised for these two purposes only in 1999.5It should be noticed that the amount of funds raised and invested each year may diverge, since venture

capital firms invest the money they raise over a three to five year time span. Therefore they may accumulateresources when good investment opportunities are scarce, and invest more when good projects abound. Forinstance, US venture capital firms raised 29.1 billion dollars in 1998, but invested only 19.2 of them, whereasin 2000 they invested about 8 billions more than they raised.

15

survived the perilous early years and have shown good success prospects. As for funding, the

higher variability of investment patterns in Europe can be taken as a sign of immaturity of

the industry, which still has to find a stable structure.

Table 2. Venture capital investments, by stage

Europe

Total of which in VC (Early stage %) (Expansion %) (Later stage %)

1991 6,381 3,429 10 80 10

1992 6,354 3,828 10 76 14

1993 4,639 2,794 8 78 14

1994 6,635 3,707 10 75 14

1995 7,370 3,952 11 77 12

1996 8,389 4,652 12 71 18

1997 8,992 5,388 15 70 15

1998 15,662 7,636 23 62 15

1999 25,628 12,623 27 64 9

2000 33,177 19,516 32 63 5

United States

Total of which in VC (Early stage %) (Expansion %) (Later stage %)

1991 2,464 2,257 32 47 21

1992 5,059 3,759 25 43 32

1993 4,919 4,560 40 36 24

1994 5,263 3,723 35 32 33

1995 5,471 4,810 40 38 22

1996 11,211 9,676 38 37 25

1997 17,213 14,931 26 47 27

1998 21,981 19,190 30 46 24

1999 59,372 54,111 24 53 23

2000 103,494 100,622 24 56 20

Notes: Data are in millions of current dollars. Early stage includes seed and start-up financing.

Source: Authors’ calculations on EVCA and NVCA data.

The gap between Europe and the US is also evident from Table 3, which compares the

amount invested in venture capital as a percentage of GDP in the US, in Europe, and in some

16

of its national economies. Two facts stand out. First, Europe invests a smaller share of its

GDP into venture capital than the US, a difference which widened in 2000, reflecting the boom

in venture capital investment on the western side of the Atlantic. The second striking fact

is the large and persistent variability of venture capital intensity across European countries.

One also notices that a higher venture capital intensity does not necessarily corresponds to a

higher number of stock market listings. Countries like Sweden, Belgium or the Netherlands,

with a high venture capital intensity, have very few companies listed on Euro.nm. One likely

explanation is that many venture-backed companies from these countries list in the US on

Nasdaq, or in their national ’traditional’ stock markets. For instance, 25 Dutch companies

are listed on Nasdaq, 9 of which did so since 1997. One intriguing fact is that the opening

of Euro.nm seems to have spurred also venture capital intensity at national level, albeit

with some delay. Indeed, intensity increased more than sixfold in Germany since 1997, and

nearly doubled in France since 1996, the year the Nouveau Marche opened. Not all countries

experienced such an upsurge, though. Venture intensity in Italy and Belgium, for instance,

has languished.

Table 3. Venture capital investments as a percentage of GDP

US Europe UK Germany France Sweden Italy Belgium Nether. Spain

1990 0.05 0.01 0.11 0.04 0.06 0.02 0.02 0.04 0.07 0.02

1991 0.04 0.01 0.09 0.04 0.07 0.01 0.04 0.03 0.07 0.04

1992 0.06 0.01 0.08 0.03 0.06 0.01 0.04 0.08 0.06 0.03

1993 0.07 0.01 0.07 0.03 0.06 0.01 0.02 0.05 0.06 0.03

1994 0.05 0.04 0.09 0.03 0.06 0.05 0.02 0.05 0.09 0.02

1995 0.06 0.04 0.09 0.03 0.04 0.02 0.03 0.05 0.12 0.03

1996 0.12 0.05 0.09 0.03 0.06 0.11 0.04 0.05 0.13 0.04

1997 0.18 0.06 0.11 0.05 0.10 0.04 0.04 0.08 0.19 0.05

1998 0.21 0.09 0.16 0.07 0.07 0.06 0.06 0.10 0.24 0.05

1999 0.58 0.14 0.21 0.13 0.13 0.20 0.06 0.27 0.34 0.10

2000 0.78 0.17 0.38 0.30 0.10 0.21 0.07 0.10 0.80 0.08

Notes: Venture capital spending from EVCA and NVCA data. National GDP data from the Inter-national Financial Statistics of the IMF, GDP for Europe (EU-15) and for the US from the MonthlyBulletin of the OECD.

Source: Authors’ calculations on EVCA and NVCA data.

17

Table 4 provides data on the sectoral distribution of venture capital investments.6 While

differences in sectoral classifications make it difficult to closely compare EU and US patterns,

some facts stand out. Most notably, manufacturing–which includes consumer and industrial

products–plays a major role in Europe, but only a marginal role in the US. While this is

partly due to the inclusion of MBOs in the European data, its lower propensity to high-tech

investments is confirmed by the relevance of investments in agriculture and finance (’other’ in

the table). The evolution of investment patterns is also telling. Europe is much less dynamic,

and the relevance of investment in more advanced sectors has only begun in 1999. The US,

instead, shows a more flexible investment attitude. For instance, the share of money put into

biomedical companies has shrunk the last few years, which have seen a boom of computer

investments, which include Internet-related companies.

6Unfortunately data for Europe are inclusive of investments in MBOs, since a sectoral breakdown for ventureinvestments is not published by EVCA. This may be one reason behind the predominance of investment intraditional sectors in Europe.

18

Table 4. Venture capital investment destination, by sector

Europe

Telecom Computer Manufacturing Biomed Electronics Other

% % % % % %

1991 2 6 56 6 3 27

1992 4 4 58 5 3 26

1993 1 6 59 6 4 24

1994 2 4 61 5 4 24

1995 5 7 56 8 4 20

1996 4 5 52 6 4 29

1997 6 7 51 7 5 24

1998 9 9 46 7 3 26

1999 12 11 50 7 2 18

2000 14 13 43 10 4 16

United States

Telecom Computer Manufacturing Biomed Electronics Other

% % % % % %

1991 12 19 13 25 17 14

1992 21 12 8 22 10 27

1993 21 30 8 21 7 13

1994 17 18 9 23 10 23

1995 18 21 12 22 12 15

1996 15 27 9 20 7 22

1997 16 30 8 27 8 11

1998 16 36 8 17 11 12

1999 17 56 6 7 6 8

2000 17 58 7 6 8 4

Notes: European data in millions of euros (ECUs before 1999) and US data in millions of dollars.Biomed includes biotechnologies, medical technology and healthcare; Computer includes online and In-ternet start-ups; Manufacturing includes industrial products, consumer products, energy; Electronicsincludes computer hardware and semiconductors. Other includes agriculture and financial services.

Source: Authors’ calculations on EVCA and NVCA data.

19

Table 5 shows another interesting difference between the structure of venture capital

investments in the two economies. While Europe invests much less in venture capital than

the United States, it supports a much larger number of companies, nearly twice as many.

This means that the average amount invested per company is much smaller in Europe, where

money is spread very thinly across companies.

Table 5. Venture capital backed companies

US companies EU Investments EU companies

1991 1,088 5,615 n.a.

1992 1,294 5,088 n.a.

1993 1,150 4,422 n.a.

1994 1,191 4,459 n.a.

1995 1,325 3,891 n.a.

1996 2,002 4,081 n.a.

1997 2,697 5,044 3.967

1998 3,149 6,062 5,083

1999 3,969 9,470 7,335

2000 5,412 12,958 9,574

Notes: Data are counts of exits.

Source: Authors’ calculations on EVCA and NVCA data.

An interesting way of looking at the evolution of the venture capital industry is also to

consider the number of venture capital firms. A problem in this respect is that no standard

definition or registry of venture capital exists. Therefore—unlike banks or brokers—one must

resort to a subjective criterion to identify venture capitalists. What we did was to consider a

venture capital firm as such if it belongs to EVCA, whose directories since 1990 are available.7

Based on this definition, Table 6 provides some interesting insights in the dynamics of the

venture capital industry. The numerosity of venture firms confirms that Europe still has some

way to go before boasting a venture capital industry as thick as in the US.

The number of venture capital firms in Europe remains nearly half than in the US. It

also interesting to notice that the high growth of the American industry has started at least

7Despite contacting the major national venture capital associations, we could not obtain their pre-1999directories.

20

in 1995, together with the growth wave in funding and investment. In Europe, instead,

the number of venture capital firms almost doubled over just three years, raising again the

question of what role the opening of Euro.nm might have played in this. Indeed, the five

countries where a ‘new’ stock market opened accounted for almost half of the total growth

in the number of EVCA members since 1997. Also the numerosity of venture capital firms

is much greater in those countries with an active stock market for innovative firms. Italy is

the only exception, with a small and less dynamic venture capital industry. Taken together

with the difference in organizational structure (Jeng and Wells (2000)), funding sources and

investment behavior, these numbers offer a picture of deep differences in the venture capital

industries of the US and Europe. What might that mean for the financing of innovative

companies is the object of the rest of this article.

Table 6. Venture capital firms, EU and US

US EU UK Germany France Sweden Italy Belgium Spain Netherlands

1991 389 163 42 11 30 1 10 12 5 21

1992 397 161 38 15 29 2 12 11 6 20

1993 401 159 40 13 29 3 11 12 7 19

1994 400 162 42 15 27 5 11 14 8 17

1995 425 169 40 18 32 5 11 13 8 16

1996 460 176 42 20 31 4 13 13 8 18

1997 507 184 52 27 32 5 12 16 8 19

1998 547 210 61 36 33 7 12 17 10 25

1999 620 331 79 51 48 11 16 23 14 32

2000 693 424 90 75 59 22 19 30 17 33

Notes: Venture capital firms members of EVCA and NVCA.

Source: Authors’ calculations on EVCA and NVCA data.

21

3.2 Venture capital in the winner’s circle: venture-backed companies on

Europe’s ’new’ stock markets

Aggregate data provide an intriguing picture, but they raise more questions than they can

answer. One is left with the impression that European venture capital has substantially

developed over the last decade, but that it has also lost ground to the US industry in its

ability to fund innovative start-ups. Aggregate data cannot tell us much about how effective

European venture capital has become in nurturing fast-growing companies. Has the growth

in the size of the industry corresponded to a growth in its ability to support the creation

of innovative companies, or not? The only way to obtain a convincing answer is to turn to

firm-level data.

Here we face serious obstacles. While in the US commercial companies like VentureOne

and Venture Economics have been gathering comprehensive and reliable data on venture

partnerships and venture-backed firms since the 1970s, in Europe systematic data collection

of this sort has begun only very recently. Therefore we cannot yet rely on adequate data for

in-depth empirical inquiries.

A number of studies conducted for industry associations portrait venture capital as con-

ducive to job creation and to the growth of technologically oriented firms. Venture-backed

firms are found to grow faster, create more jobs, and export more than established firms. For

instance, between 1993 and 1997, British venture-backed companies increased employment

by an yearly 24%, and sales by an yearly 40%. By comparison, employment at the hun-

dred largest British listed companies grew by 7%, and sales by 15% (BVCA (1999)). On a

European scale, between 1991 and 1995, employment at venture-backed companies grew by

an yearly 15% and sales by an yearly 35%, as compared to 2% and 14% for the 500 largest

European listed firms (EVCA (1996)).

Suggestive as they are, these studies are based on a few ’stylized facts’ which are still

to be rigorously tested.8 At least two problems make their findings unconvincing. First,

they suffer from severe survivorship bias, since they only look at successful start-ups without

considering the much large number of those which failed. A correct comparison should look

at both winners and losers, taking into account that small and medium enterprises (SMEs)

suffer from a high mortality rate (OECD(1998)). The contribution of SMEs to economic

growth or net job creation is in fact far from obviously positive, and has been recently

8Stimulating case studies on the difficult gestation of European venture capital in the 1980s and 1990s areprovided by Becker and Hellmann (2000) and by Freeman (1998).

22

challenged in a series of studies (see Audretsch and Thurik (1999)). Second, these studies

compare venture-backed firms with large firms, which are, by their nature, less dynamic

(Davis, Haltiwanger and Schuh (1996)). A correct comparison should instead pit venture-

backed against non-venture-backed start-ups. These studies, therefore, are unable to separate

the effects of venture capital financing from those of being a (naturally fast-growing) start-

up, and risk to capture effects due to a spurious correlation between being a start-up and

receiving venture capital. In other words, it could very well be that the purported vitality

of European venture-backed firms is due to factors other than venture capital. A deeper

analysis is therefore warranted, and our paper provides a first attempt in this direction.

We do so by looking at the involvement of venture capital with companies which listed

on Euro.nm between 1997 and 2000. Looking only at companies which make it to the stock

market has the obvious limitation of disregarding what happens to those which are still

private, or choose to remain so. However, in our case this limitation should not be too much

of a concern. Start-ups which go public are arguably among the most successful ones, since

the pecuniary and reputational rewards for founders and financiers are highest in this case.

Founders can get a much higher valuation with a flotation than with an acquisition or a

private placement. The ability to bring companies public is one of the key abilities venture

capitalists boast about with institutional investors, since IPOs are the most lucrative exit

from a venture investment, on average four or five times more profitable than acquisitions

(Gompers and Lerner (1997)). Since venture capitalists are profit-seeking organizations we

would expect them to bring as many of their portfolio companies public as possible, and since

they crucially rely on reputation for their business, we would also expect them to select the

most promising firms as investees. Therefore we might over-estimate the impact of venture

capital on corporate growth by looking only at listed companies, a possibility we will return

to in the interpretation of the data.

An advantage of looking at Euro.nm listed companies is that they belong to a small

number of high-tech industries, are of fairly similar age, and come from a small number of

countries. This makes them a relatively homogeneous group of ’venturable’ companies where

we naturally find a reliable control sample, avoiding sample design problems. Focusing on

Euro.nm listed companies also gives the advantage of obtaining detailed information thanks

to the tight disclosure requirements of Euro.nm, which makes companies disclose information

not only for the years starting with the IPO, but also for the three pre-IPO years. Such

breadth and depth of information can not be attained for private firms.

23

3.2.1 Euro.nm: Europe’s ’new’ stock markets

Euro.nm was created in the spring of 1997 as an alliance of the newly born ’new stock

markets’ of the stock exchanges of Amsterdam (Nieuwe Markt), Brussels (Euro.nm Brussels),

Frankfurt (Neuer Markt), and Paris (Nouveau Marche, which had opened in March 1996). In

June 1999, Milan’s Nuovo Mercato completed the ranks of the alliance. The stated purpose of

Euro.nm was to attract dynamic, innovative companies with high growth potential by offering

them suitable admission and trading rules, along the lines of what Nasdaq does in the US

(Euro.nm (1999)). Euro.nm offered admission criteria and listing requirements appropriate

for young companies with bright prospects but no established track record, willing to accept

tight disclosure rules in order to attract investors (see Box 3).

Box 3: Euro.nm admission and listing criteria

• Shareholder equity (pre-IPO): at least 1.5 million euros

• Age: at least three years (waiveable)

• IPO volume: at least 5 million euros and 100,000 shares. At least half of theIPO volume must come from a capital increase

• IPO prospectus according to international standards

• Lock-up: existing shareholders must lock-up their holdings for at least 12months after the IPO (6 months on the Neuer Markt)

• Free float: at least 20% of the nominal capital must be floated

• Only ordinary shares with no restrictions to negotiability can be floated

• At least one sponsor (an investment bank regulated by the stock exchange)must be designated by the firm to coordinate the listing process

• Timely release of annual and quarterly reports and of price sensitive informa-tion

The listing rules of Euro.nm were less restrictive than those in use for ’traditional’ ex-

changes, and thus more appropriate for dynamic new ventures. However, listing on Euro.nm

was more demanding than listing on a traditional exchange in terms of disclosure require-

24

ments. The Neuer Markt, which adopted the strictest rules, required prospectuses and an-

nual reports to be published also in English, acceptance of the German Takeover Code, and

compliance with international accounting standards (IAS or US-GAAP). Euro.nm closed in

December 2000 after the merger of the Paris, Amsterdam, and Brussels stock exchanges into

Euronext, but its constituent markets have continued their activity independently. In Bot-

tazzi and Da Rin (2001) we analyse the evolution of Euro.nm and provide an assessment of

its contribution to the financing of European innovative firms. Tables 7 and 8 provide an

overview of the structure and evolution of Euro.nm in terms of total number of listings and

funds raised.

Table 7. Euro.nm summary statistics

Nouveau Neuer Nieuwe Euro.NM Nuovo

Euro.nm Marche Markt Markt Brussels Mercato

Number of IPOs 567 165 333 15 15 39

(of which in the data set) (511) (157) (306) (6) (6) (36)

Total capital raised 41,618 7,986 26,673 470 225 4,633

Capital raised at IPO 29.4 10.1 38.2 5.7 8.1 44.0

Notes: The number of IPOs includes 16 financial companies which we exclude from our data set.Capital raised in millions of euros. Capital raised at IPO: median values.

Source: Authors’ calculations.

More than half of the IPOs occurred on the Neuer Markt, almost a third on the Nouveau

Marche, while the Nuovo Mercato attracted almost as many companies as the Neuer Markt

in its first eighteen months. Our sample closely replicates the market composition of the

population, apart for the two smaller markets–which are under-represented. Notice that the

Neuer Markt accounts for a larger share of capital raised than of listed companies. Therefore,

the (median) amount of capital raised at IPO is far larger on the Neuer Markt than elsewhere.9

Table 8 summarises the evolution of IPOs on Euro.nm. It is worth noticing that IPOs on

the Belgian and Dutch markets has tapered off with time, and that the Neuer Markt shows a

robust and uninterrupted growth pattern, unlike the uneven growth of the Nouveau Marche.

9The large amount of capital raised on the Nuovo Mercato is due to a small number of very large telecomcompanies.

25

Table 8. Number of IPOs on Euro.nm

Nouveau Neuer Nieuwe Euro.NM Nuovo

Euro.nm Marche Markt Markt Brussels Mercato

1996 18 18 — — — —

1997 44 20 17 5 2 —

1998 103 43 46 8 6 —

1999 182 32 138 1 5 6

2000 220 52 132 1 2 33

Total 567 165 333 15 15 39

Source: Authors’ calculations.

3.2.2 The data set

We develop a unique, hand collected data set with information from the listing prospectuses

and annual reports of companies which went public on Euro.nm since its inception to Decem-

ber 2000. We obtained the listing prospectuses and annual reports in several ways. Whenever

possible, we downloaded electronic copies from the company (or stock exchange) web site.

For prospectuses which were not electronically available, which was often the case for earlier

years, we contacted the issuing company by phone, fax, or e-mail. In some cases we photo-

copied the documents at the relevant stock exchange. Overall, we collected 527 prospectuses

out of 567 IPOs which took place in the sample period, or 92% of the total. We also collected

1,790 annual reports, about 94% of the total.

Listing prospectuses are valuable for studying the role of venture capital in innovative

companies because they contain detailed information on the financial and business situation

of the company. Such information is not confined to the IPO year, but extends back in

time, up to the three previous years. We use prospectuses and annual reports also to derive

quantitative information on several financial and business variables. For each company we

collect all the available data for pre-IPO years from the issuing prospectus, which usually

contains data for the preceding three years. We also collect data for all the available post-IPO

years from annual reports. Each company in the data set is assigned to a sector through a

procedure we describe in the Data Appendix, which also contains a detailed description of the

data collection process and a list of the variables we use in this study and of their definition.

Our final data set, which does not include sixteen companies in financial services, consists of

26

511 companies.10

Finally, we collect data about financing from venture capitalists and their involvement

with these companies. We put particular care in extracting relevant information from our

sources. This turned out to be an extremely time-consuming task which required careful

search of each single prospectus and cross-checks with several other sources.11 The process of

identification of venture capitalist was made particularly difficult by the fact that, unlike for

banks, no standard identification criterion is available. We were able to collect data on the

extent of ownership and on the timing of venture capital financing, while the exact amount of

funding generally remains undisclosed. The details on the construction of the venture capital

data set can be found in the Data Appendix.

3.2.3 Venture-backed companies on Euro.nm

The first question one wants to ask is what was the actual involvement of venture capital

with companies listed on Euro.nm. The answer is that venture-backed companies constitute

a substantial part of Europe’s new public companies: The first two rows of Table 9 show

that nearly 40% of the listed companies were backed by at least one venture capitalist.

This proportion is higher for companies listed on the Nouveau Marche than for those listed

elsewhere. The proportion of listed companies which receive venture finance has doubled

since the opening of Euro.nm, a trend which is most noticeable in Germany, a fact we will

return to. Notice also that no company listed in Amsterdam or Brussels was backed by a

venture capitalist. This is at odds with the numbers in Table 3, where these two countries

were shown to have a relatively high venture capital intensity. One possible explanation is

the long tradition of listing on Nasdaq of Dutch companies (Blass and Yafeh (2000)), which

might be helped by venture capitalists to go through a more expensive listing in the more

established American market. Ease of access to Nasdaq could also explain the overall dismal

performance of the Nieuwe Markt. More difficult to explain is instead the lack of venture-

backed companies on Euro.nm Belgium, and a Parisian dominance cannot be invoked: only

one Belgian companies is found on the Nouveau Marche.

10Companies in the financial services sector are not considered because their financial structure, fundingrequirements and strategic behavior differ substantially from those of industrial and (non-financial) servicescompanies.11We are grateful to our research assistants for the enthusiasm they put in this demanding and tedious job.

27

Table 9. Venture capital and Euro.nm listed companies

Nouveau Neuer Nieuwe Euro.NM Nuovo

Euro.nm Marche Markt Markt Brussels Mercato

Without VC 292 68 186 6 6 26

With VC 219 89 120 0 0 10

VC before Euro.nm 67 27 34 0 0 6

VC after Euro.nm 130 41 86 0 0 3

(VC entry date unknown) 22 21 0 0 0 1

Notes: With (without) VC identify companies which received (did not receive) venture capital fi-nancing. Before (after) Euro.nm identifies companies which received venture capital financing before(after) the opening of the ’new market’ they list on. The last row lists companies for which we couldnot ascertain the date of venture capital financing.

Source: Authors’ calculations.

3.2.4 Venture capital and Euro.nm listed companies

We then want to know the extent to which European venture capital has been involved with

listed companies. Table 10 documents that the involvement of European venture capitalists

with Euro.nm has been substantial. We look at the number of venture capital firms financing

companies listed on Euro.nm. In the second column we list the number of venture capitalists

firms, and in the third those which also finance at least one listed company. The first row

shows the total number of EVCA members, plus the members of the French, German, or

Italian venture capital associations which are not also EVCA members. The other three rows

show the number of national association members, which includes both EVCA members and

members of the national association only. These constitute the largest sets of professional

venture capitalists we could identify at the European or national level. Nearly one third of

the ’core’ group of European venture capital firm was involved with companies which listed

on Euro.nm. This represents a substantial involvement, given that about 70% of Europe’s

venture capital firms have been members of EVCA since less than three years and therefore

may not have had enough time to take investee companies to the stock market. The lower

proportion recorded at the national level is due to the fact that a small number of venture

capitalists with international reach (often US or UK based) finance a very large number of

companies. These are European but not French, German, or Italian association members.

28

Table WA-2 in the Web Appendix shows that the sectoral composition of venture capital

investments is very close to the sectoral structure of Euro.nm, except for a slightly lower

involvement with Media & Entertainment and a higher involvement with Biomed.

Table 10. Venture capital firms and Euro.nm

Venture capital of which:

firms financing a listed company

European 601 172

German 152 42

French 153 40

Italian 73 6

Notes: European venture capital firms are members of the European Venture Capital Association(EVCA) and of national venture capital associations. German, French and Italian venture capitalfirms are members of the respective national venture capital associations (and possibly also of EVCA).

Source: Authors’ calculations.

Figure 3 examines the distribution of venture capital investments. It plots the number of

venture capital firms which finance 1, 2-4, 5-9, or more than ten listed companies. Only 24

venture capitalists (out of 172) finance more than five companies, and only eight more than

ten. This reflects the fact that many European venture capital firms are still very young,

and have not had the time to get many companies public. Information in the Web Appendix

shows that it is the larger venture capitalist with an international presence who tend to

support the largest number of listed companies.

Figure 3 about here

Figure 4 looks at the other side of the coin, namely the number of venture capital investors

by company. It shows that syndication of venture investments is not very common in Europe,

unlike in the US (Lerner (1994b)): More than half of the 219 venture-backed companies only

had one venture capitalist.

Figure 4 about here

Another way to look at the involvement of venture capitalists with listed companies is to

look at their equity holdings, which we examine in Table 11. While fairly volatile, holdings

are far from negligible. Moreover, these numbers are likely to under-estimate the involvement

29

of venture capital, since in many case ’bridge financing’ from specialised intermediaries is used

in the wake of the IPO to increase the equity base. Venture capitalists often sell part of their

stakes at this stage, but we are not able to see these transactions. The table also show that

at the time of going public, venture capitalists sell only about 40% of their holdings, and

remain involved with the company after it has gone public. As a comparison, Barry et al.

(1990) find that US venture capital firms had a higher average pre-IPO equity stake (32%)

and sold about a third of it. European venture capital thus seem to have lower shareholdings.

Table 11. Equity holdings by venture capital firms

Pre-IPO Post-IPO

Mean St.Dev. Min Max Mean St.Dev. Min Max

Neuer Markt 10 17 0 100 6 9 0 43

Nouveau Marche 14 18 0 85 8 12 0 53

Nuovo Mercato 7 14 0 46 4 9 0 32

Source: Authors’ calculations.

Our last piece of information comes from Table 12, which lists the nationality of venture

capital firms and investee companies. Reported numbers are counts of investments by venture

capital firms (row) in a certain country (column). One would expect venture capitalist to

invest in firms geographically close to them, given their need for constant interaction with

their investees. Several studies based on US data document the fact that venture capitalists

tend to invest in the proximity of their headquarters (Lerner (1995)). The table confirms that

this is the case for our sample, as the vast majority of investments is made within a venture

capitalist’s own national borders, as one can see by looking at the diagonal in the table. The

only seeming exception is represented by venture capital firms with an international reach,

and American venture capitalists which invest in Europe. But this impression is deceptive,

since both categories possess local offices in several countries.

30

Table 12. Venture capital and investee companies, by nationality

Investee companies

Venture Capitalists Germany France Italy Israel US Others

Germany 134 3 0 0 2 1

France 2 139 1 0 1 0

Italy 0 0 10 0 0 0

Israel 2 4 0 5 0 0

US 11 9 1 0 2 1

International 44 32 2 0 1 1

UK 5 9 2 0 0 0

Others 5 1 0 1 0 5

Notes: Others includes venture capitalists from Austria (5 investments), Denmark (1), Ireland (1),Netherlands (8), South Korea (1), Switzerland (5).

Source: Authors’ calculations.

3.2.5 Which companies are venture-backed?

Before proceeding to the analysis of the effects of venture capital we want to know which

characteristics of a firm are associated with receiving venture capital financing. Theory

predicts venture capital to be associated with young, innovative companies that, being at

an early stage of development, are characterised by low profitability and a small amount of

sales.12 We have seen in Table 2 that European venture capitalists have been increasing their

early stages investment. Therefore we expect our findings to conform to the predictions of

the theory.

We estimate a probit regression in which the dependent variable is a dummy variable

that takes value one if a company has obtained venture capital financing. The independent

variables are measured before the arrival of the first venture capitalist (’preVC’).13

Unfortunately we cannot use in this analysis all the companies in the data set, since

there are some missing observations, and since 30 companies, i.e. 14% of the venture-backed

12We are not aware of any statistical study of the determinants of venture financing for the US, except forHellmann and Puri (2000), who look at a sample of venture-backed start-ups and find that those which pursuemore radical innovations are more likely to attract venture capital.13For non venture-backed firms, we use the average of the pre-IPO values. We also experimented with

alternative measures, such as measuring variables in the years before the average date of entry of venturecapital in venture-backed companies, but we found no substantial difference in the results. Hence we stick tothe simpler pre-IPO measure.

31

companies in our sample, have received venture capital funding before they started reporting

accounting information. Still, this leaves us with 359 companies.

Table 13 reports the probit regression results. We find that sales negatively affect the

probability of obtaining venture capital financing, while leverage has a positive effect, al-

though it is not statistically significant. We control for sectors of activity, but these are

found to have no effect.

Table 13. Probit regression–dependent variable venture capital

Independent Marginal increase Coefficient z-statistic

Variables in probability

Sales(preVC) - 0.003 -0.01 *** -2.651

Leverage(preVC) 0.117 0.34 1.482

Constant -0.45 -1.131

Number of obs. 349

Log likelihood -184.82

Waldχ2(7) 19.74

P-value 0.006

Notes: ‘preVC’ denotes variables measured before the arrival of a venture capitalist. Significance

levels are indicated by * (10%), ** (5%), and *** (1%). Huber-White corrected standard errors are

used to obtain robust estimates.

Our findings are consistent with a view of venture capital getting involved with firms

which are still at a very initial stage of development and are therefore not yet able to sell: A

marginal increase in sales decreases the likelihood of receiving venture financing by 0.3%, an

economically small but statistically highly significant result. The positive effect of leverage is

consistent with a view of venture capital as an important source of financing. In other words,

the ’hard’ side of venture capital goes well along its ’soft’ side.

Alternative (unreported) specifications have considered the level of debt, its maturity, the

amount of assets and a national market effect as possible determinants of venture financing.14

We have done so to check if companies whose debt is mostly short-term might be more credit

14The national effect is measured through dummies which take value one for companies listed in France,Belgium, Italy, and the Netherlands. As in all other regressions, the latter three never turn out to be significant,also due the low number of observations.

32

constrained and might therefore look more aggressively for venture financing. A dummy that

takes care of the national effect was also used to capture the higher proportion of French

venture-backed companies. All these variables turn out to be statistically insignificant, and

in all specifications the quality of the fit worsens.

We also expect venture capital to be involved with more highly innovative companies. To

check for this prediction we control for the natural proxy for innovativeness, R&D intensity,

measured as the ratio of R&D to assets.15 This reduces the number of observations to 101,

since few companies disclose R&D expenditure. The reported R&D figures are however reli-

able, since they are voluntarily disclosed in the IPO prospectuses as a signal of the company’s

quality and are not a legally required item of the accounts. All the tables with the results of

our statistical analysis where we control for R&D can be found in the Web Appendix. We find

that a higher R&D intensity makes a company less likely to receive venture capital financing

(see Table WA-4 in the Web Appendix), but the result is not statistically significant. The

amount of sales remains the driving force behind obtaining venture financing, and industry

controls are all significant.16

3.3 The impact of Euro.nm on venture capital

We conclude our statistical portrait of venture capital in Europe by taking a dynamic view of

its involvement with the ’new’ stock markets. A close inspection of the listing data reveals in

fact that something is changing in the involvement of venture capital with listed companies.

We have seen in Table 6 that venture firms are growing fast in Europe. This is good news, for

at least two reasons. One is that numerosity is a sign of maturity. The second is that a large

part of Europe’s venture capitalist are what the jargon defines ’captives,’ i.e. subsidiaries of

industrial companies or financial institutions (typically banks). Captives are not the most

aggressive among venture capitalists (Hellmann, Lindsey and Puri (1999)). An important

change seems however to be taking place, with a new breed of US-style, independent, venture

capital firms entering the market and possibly changing the way venture capital operates in

Europe.

Table 9 above shows a suggestive piece of information in this respect. Of the 197 venture-

15Our results do not vary if we control for R&D expenditure.16The finding that R&D has a negative (albeit statistically weak) effect is only apparently at odds with the

theory, however, since we are measuring variables before the arrival of the venture capitalist. The result is infact consistent with venture capital selecting companies at an early stage of development, when R&D intensityis still low. However, one could conceivably think of alternative interpretations, for example that companieswhose R&D intensity is higher are less credit constrained and therefore less likely to look for venture financing.

33

backed firms in our sample for which we could identify the entry date of a venture capitalist,

two thirds received venture financing after the opening of Euro.nm. Interestingly, this pro-

portion is higher in Germany, whose Neuer Markt is considered the most dynamic of the

’new’ markets. Table 14 provides further evidence that Euro.nm may really be having an

effect on the European venture capital industry. Here we define a start-up as venture-backed

(’VC-backed’) if it receives venture finances within six months from its foundation. These

are arguably the companies where a venture capitalist has most chances to use its ’soft’ side:

It is much easier to affect strategy and management in a new firm than in a five years old

one. There are 50 VC-backed start-ups, which we divide into those which were born before

the opening of Euro.nm (pre-Euro.nm, 20 companies) and those which were born after it

(post-Euro.nm, 30 companies). The number of VC-backed start-ups clearly increases after

the opening of Euro.nm. We take this evidence as a suggestive indication of the positive ef-

fect of Euro.nm on venture capital. We also notice differences across markets, as the positive

effect seems to be much stronger in France than in Germany or Italy. No venture-backed

companies are listed in Amsterdam and Brussels.

Table 14. Cohorts of venture-backed companies

Born VC-backed

Total pre-Euro.nm post-Euro.nm

Neuer Markt 120 31 16 15

Nouveau Marche 89 18 3 15

Nuovo Mercato 10 1 1 0

Source: Authors’ calculations.

Table 15 further refines this evidence. We count all venture-backed start-ups and partition

them by the year of listing on Euro.nm. The relative figures can be read in the second column

of the table. Then, in the third column, we count those venture-backed companies which were

also born such. This way we can measure how many companies were created with the help of

a venture capitalist. Several things are worth noticing. First, the number of venture-backed

start-ups, whether born such or not, increases over time. In particular, the number of born

venture-backed start-ups more than doubles each year. Moreover, the proportion of venture-

backed companies which are born such doubles in 2000. Our data set also shows that six of

the 28 companies which were born venture-backed in 2000 had a ’young’ venture capitalist,

34

i.e. one which had become a member of EVCA at most two years earlier. Between 1996 and

1999 only two such cases had occurred. Overall, these figures suggest a picture of increasing

involvement of European venture capitalists with companies which have the potential to list,

and an increasing importance of venture capitalists in the creation of innovative start-ups.

Table 15. Euro.nm and new venture-backed companies

VC-backed born VC-backed

1996 7 1

1997 12 3

1998 35 6

1999 72 12

2000 93 28

Total 219 50

Source: Authors’ calculations.

There are good reasons to greet this evidence with optimism and hope. Several studies

have recently analyzed the relationship between venture capital and stock markets. Black

and Gilson (1998), for instance, offer a conceptual framework for analyzing the interplay

between venture capital and capital markets, while Michelacci and Suarez (2000) develop

an elegant formalization of the link between business creation and equity markets. Both

studies emphasise the complementary role of stock exchanges and venture capital. In this

view, venture capital and stock exchanges are more than simple sources of finance. Ven-

ture capital contributes effective oversight of new ventures, selecting and supporting valiant

entrepreneurs and promising new ventures. Such support facilitates the growth of these ven-

tures and accelerates their arrival to equity markets. In turn, active and liquid stock markets

make IPOs affordable for companies and attractive for investors, creating a complementarity

similar to that modeled by Pagano (1993). The American experience with Nasdaq, which was

created in 1971 to provide an equity market for high-tech companies, is certainly suggestive

in this respect. Over the 1990s about 6,500 companies listed on Nasdaq, the American stock

exchange focussed on high-technology industries which in December 2000 listed over 6,000

companies with a capitalization above five billion dollars. Many of these companies had been

backed by venture capital, among them successful ones such as Amazon, Cisco Systems, Dell

Computers, Intel, Microsoft, and Yahoo!. The evidence we provide in this paper will show

that for Europe this road is still very long, but we are probably moving in the right direction.

35

4 Venture capital and the financing of European innovative

companies

We now turn to the core of our analysis. Our goal is to provide a rigorous assessment of

whether European venture capital helps select and nurture the most dynamic innovative

companies, so as to provide guidance for informed policy. In Section 2.3 we have seen that

venture capital is expected to provide valuable support to investee companies, and that it is

indeed found to do so in the US. Does European venture capital also provide the companies it

finances with ’hard’ and ’soft’ support able to make them the ’superstars’ among innovators?

4.1 Null and Alternative Hypotheses

We start by setting forth our conjectures on the effects of venture capital financing on the

following key aspects of corporate evolution:

• The timing of the listing decision. This decision is a crucial one in the life of an

innovative company. Going public helps future growth and financially rewards financiers

and founders. Our first null hypothesis is that venture capital does not play any role

on the process of going public, i.e. that venture capital neither speeds up nor slows

down the IPO process. There are at least two alternative hypotheses. The first is that

venture capitalists speed up the decision to go public. This would be the case if venture

capitalists invested to reap a capital gain and therefore push for a quick IPO to cash in

and turn to new ventures, or if they enabled companies to mature faster. NVCA (1988)

indeed claims that, between 1992 and 1996, US venture-backed companies were 70%

more likely to become listed than other start-ups. Alternatively, venture capital might

lengthen time-to-listing (TTL) because it invests in younger firms and waits for them to

mature. In this case a venture capitalist, by ensuring adequate financing, would bring

a company public only when its potential has been fully brought out, or when the cycle

in the IPO market may ensure a high valuation of the company.

• The amount of funds raised at IPO. The amount of capital raised is important to deter-mine the amount of resources a growth-oriented company can rely on for its investments.

Our second null hypothesis is that venture capital does not affect the amount raised at

IPO. There are at least two alternative hypotheses. First, ’certification’ from a venture

capitalist may reassure investors even when financial results do not still reflect the full

potential of the company. In this case venture capital would increase the amount raised,

36

which would also be the case were venture capitalists patient enough to wait for a ’hot’

IPO market. But if venture capital ’pushed’ firms to the market, its eagerness to exit

quickly could be detrimental for the amount of funds raised, both because investors

would be suspicious of venture-backed companies and because the IPO might happen

during a ’cold’ market.

• The post-IPO corporate growth, measured by sales and employees. Our third null hy-

pothesis postulates that the post-IPO growth of a listed company is ’venture capital

neutral,’ i.e. that is there is no relation between the post-IPO growth and the presence

of a venture capitalist. Venture capitalists might indeed be attracted by the innovative-

ness of a firms, which could be unrelated to employment or sales. We take the IPO as a

turning point in the life of these companies, because it provides them with the financial

resources necessary to fully unfold their business potential. Again we have some plau-

sible alternative hypotheses. The first alternative is that venture capital favors sales

and employment growth through its ability to connect the firm with potential clients

and suppliers and to attract addition funding. NVCA (1998) claims that US venture-

backed companies created jobs at a 55% faster pace than other start-ups between 1992

and 1996, and Brav and Gompers (1997) find them to yield higher stock returns in the

five years after listing. If that were indeed the case we would have a very nice piece

of evidence to support the presumption of a positive macroeconomic effect of venture

capital. An opposite alternative would see venture capital as detrimental to growth if

its main goal is to realize a ’quick and dirty’ capital gain at IPO and then leave the

company to its own fate.

4.2 Evidence on the timing of the IPO

In this section we test the effect of venture capital on a crucial strategic decisions of Euro.nm

listed companies: When to go public. To explore this issue we compute a variable, time-to-

listing (TTL), defined as the amount of time elapsed from a company’s foundation to the date

of its IPO. For companies born before the creation of Euro.nm we must take into account

that they could not access stock markets until Euro.nm was open. For these companies, that

represent 80% of our sample, we compute TTL as the difference between the calendar date at

which a company went public and the date at which the ’new’ market it lists on was created,

a date which differs across countries. The model we test can be written as:

TTL = f(leverage, ROA, age, venture capital)

37

where we measure financial variables at IPO and control for country and sector of activity.

We use a parsimonious semi-parametric model for the analysis of the timing of that decision,

i.e. a Cox proportional hazard model (see Kiefer (1988)), which we can write as:

h(t) = h0(t) expnβ0Xo

where h(t) is the hazard rate that measures the risk of the event ’go public’ happening at

every instant, which depends on some independent variables Xi, while h0(t), the ’baseline’

hazard function, measures the risk of going public were all Xi equal to zero.

The Cox proportional hazard model has the notable advantage of not imposing any re-

striction on the baseline hazard rate h0(t) in providing estimates of the coefficients β, since

we are interested in estimating the hazard ratio. Let us define the ’risk set’ Ri as the set of

firms which may decide to go public at time ti. The hazard ratio is the probability that firm

i goes public at time ti, conditional on the same firm being in the risk set at ti:

expnβ0Xi

oP

j∈Riexp {β0Xj}

If all firms were the same, the hazard ratio would be equal to the number of firms gone public

in an interval of time divided by the number of firms who were at risk of going public in the

same period. Firms, however, are not the same. They differ with respect to the explanatory

variables Xi which affect the probability of going public. If a unit increase of an independent

variable affects the hazard ratio by increasing its value above one, we infer that the effect of

the variable is to increase the probability, or risk, of the event ’go public’ on Euro.nm.

Table 16 reports the hazard ratio estimates, which are obtained using robust standard

errors. We look at the effect of venture capital, controlling for the return on asset (ROA) and

for leverage, both measured at IPO, for sectors of activity, and for country dummies. As in

the other regressions, we also try a different specification which uses the venture capitalists’

shareholdings size as a measure of their influence. Since in all cases we find no significant

difference in the results obtained, we report the simpler dummy specification. Finally, we

control for age at IPO since this variable might introduce a bias as firms differs in their

stage of maturity at the time of the creation of Euro.nm. In other words, older firm may be

readier for going public than newborns. We take care of this possibility by controlling for the

age of the firms at the creation of the ’new markets’ through a variable which interacts the

company’s age with the calendar year of its listing.

38

Venture capital turns out to have little effect on TTL: The hazard ratio is 1.05, meaning

that venture capital increases TTL, but it is not significant. Also ROA and leverage do not

significantly affect TTL. The age of the company at the creation of the ’new markets’ is instead

always statistically significant, but it leaves the hazard ratio virtually unchanged. Companies

listed on the Nouveau Marche have a TTL which is about 60% longer than elsewhere. Finally,

companies in all sectors of activity, except the traditional one, have a hazard ratio which is

close to 0.3 and highly significant.

Table 16. Cox regression–dependent variable time—to—listing

Independent variables Hazard ratio t-statistic

Venture capital 1.05 0.61

Leverage(atIPO) 0.89 -0.48

ROA(atIPO) 1.00 0.18

France 0.36 *** -8.71

Age*97 1.00 *** 7.32

Age*98 1.01 *** 8.24

Age*99 1.00 * 1.60

Age*100 0.99 *** -6.37

Number of obs. 488

Log likelihood -2,460.57

Waldχ2(13) 233.67

P-value 0.00

Notes: All variables are measured at IPO. Age times year is the age of the company interacted with

a dummy for year of listing. Significance levels are indicated by * (10%), ** (5%), and *** (1%).

Huber-White corrected standard errors are used to obtain robust estimates.

When we control for R&D expenditure as a way to focus on the most innovative companies

in our sample, we confirm these results, except that now venture financing increases TTL,

albeit still without statistical significance, casting some doubts on the robustness of our

previous estimates (see Table WA-5 in the Web Appendix).

4.3 Evidence on the amount of funds raised

We know that an important role of venture capital is the provision of financing. Does this also

imply that venture-backed companies are able to raise more money from the public markets?

39

To answer this question we collect information on the amount of funds that companies raise

at IPO and we try to understand whether venture capital influences it.

Table 17 reports the results from our regression, which employs robust standard errors.

Given the high variability of our data we choose an estimation method that performs an initial

screening and eliminates gross outliers and performs the regression iteratively, weighting the

observations by absolute residuals.17

The dependent variable is the amount of funds raised. Given the high variation in firm

size, which arguably influences how much capital a company can raise, we normalise it by

dividing it by assets (measured at IPO). We use assets and not sales because the latter would

be a poor measure of the size of these innovative companies, which still need time and money

to invest to fully express their commercial potential. Sales, instead, may be a good measure

of the extent to which an innovative company has matured. We then use sales (divided by

assets) as a regressor, along with the presence of a venture capitalist, the return on asset

(ROA), leverage, and age, all measured at the time of the IPO. As in the previous regressions

we control for country and sectoral effects.

Table 17. Robust regression–dependent variable amount of funds raised

over assets

Independent variables Coefficient t-statistic

Venture capital 0.633 *** 2.411

Sales/Assets 0.096 *** 3.465

Leverage(atIPO) 1.399 * 1.787

ROA(atIPO) 1.627 *** 32.389

Age -0.004 *** -3.650

France -1.799 *** -6.104

Constant 2.984 *** 3.714

Number of obs. 470

F (11, 458) 144.61

P-value 0.000

Notes: All variables measured at IPO. Significance levels are indicated by * (10%), ** (5%), and ***

(1%). Huber-White corrected standard errors are used to obtain robust estimates.

17The method is based on Cook’s D.

40

The results are interesting. Companies that have higher sales (over assets), and therefore

are probably more mature, are able to raise a higher amount at IPO: An increase of 10%

of sales (over assets) brings an additional 1% increase in the amount raised (over assets).

A similar result holds for companies whose ROA and leverage are higher: A 10% increase

in either of these ratios carries an increase of 16% and 14%, respectively, in the amount of

funds raised (over assets). Companies listed on the Nouveau Marche are characterized by

a markedly lower ability to raise funds–they raise about 180% less than other companies.

Older companies also raise less capital, but only marginally so. Venture capital has a positive

and significant role: venture-backed companies raise on average 60% more than the others, a

result we will come back to. Sectors of activity are found to play no role.

When we control for the R&D intensity some of the above results change (see Table WA-6

in the Web Appendix). Sales (over assets) become only marginally significant and lose much

of their economic impact. Venture capital also becomes statistically insignificant, while the

negative effect of age and of France persists. Overall, these results refuse our null hypotheses

that venture capital has no influence on the dimension of the IPO, a results that is consistent

with the idea that the ’hard’ side of venture capital is very important.

4.4 Evidence on corporate growth

We now examine how venture capital affects corporate growth. A first piece of evidence comes

from a systematic comparison of how venture-backed and non venture-backed companies

behave. Table 18 reports the results of two tests.

A Wilcoxon test looks at the difference in the medians of several variables pre- and post-

IPO, where pre- and post-IPO are defined as the periods of (up to) three years before and

after the IPO. We run this test for both venture-backed and non venture-backed companies. A

Kruskal-Wallis sign-rank test looks instead at whether the medians of several variables differ

in statistically significant manner between venture-backed and non venture-backed compa-

nies, within the pre- and the post-IPO periods. Table WA-3 in the Web Appendix reports

descriptive statistics for all reported variables, so as to facilitate comparisons of ’pre’ and

’post’ values. Bold figures in Table 18 show, those median values which differ significantly

across time and within the venture-backed and not venture-backed groups of companies. Un-

derlined figures show instead, within the pre- and post-IPO periods, those median values

which are statistically significantly different between the two types of company.

Let’s concentrate first on how variables differ across time. Here we find that virtually all

41

variables vary significantly, with the only notable exception of profitability for venture-backed

companies. This results confirms that listed companies do invest and grow substantially after

the IPO, and that this does represent a turning point of their evolution.

Things become more varied when we look at differences between venture-backed and

non venture-backed companies. Before the IPO venture and non venture-backed companies

do not differ systematically. We find statistically significant differences in three variables:

profitability and sales, both of which are lower for venture-backed companies, and R&D

intensity, which is instead higher (as one would expect from our probit estimate). After

the IPO, non venture capital firms become significantly bigger in terms of assets, debt and

equity, although both types of companies show the same level of leverage. We also find a

systematic difference between venture-backed and non venture-backed companies in terms of

sales (which we interpret as a sign of maturity), employees, capital expenditure, intangible

assets–venture capital being linked to lower values.

42

Table 18. Venture capital and corporate growth

Pre-IPO Post-IPO

Assets no VC 7.1 59.3

VC 6.2 42.8

Debt no VC 4.7 18.1

VC 3.5 11.5

Equity no VC 1.2 35.6

VC 0.9 24.5

EBITDA no VC 0.8 3.2

VC 0.2 0.4

Leverage no VC 0.8 0.3

VC 0.8 0.3

ROA no VC 0.11 0.07

VC 0.05 0.01

Sales no VC 9.3 36.4

VC 5.6 22.9

Employees no VC 77 210

VC 54 170

Capex no VC 0.6 7.0

VC 0.4 4.9

Foreign sales (%) no VC 0.01 0.00

VC 0.03 0.01

Intangible assets no VC 0.2 8.0

VC 0.2 4.0

R&D no VC 0.8 3.3

VC 0.8 3.4

R&D intensity no VC 0.1 0.05

VC 0.2 0.06

Notes: For each variable we report the average of its median values for the (up to) three years before

(Pre-IPO) or after (Post-IPO) the IPO. In the upper row we report the medians for non venture-backed

companies (no VC), in the lower row those for venture-backed companies (VC). Bold values indicate

a statistically significant (at 5% confidence level) difference of medians across time. Underlined values

indicated statistically significant (at 5% confidence level) differences between venture-backed and non

venture-backed companies. Source: Authors’ calculations.

43

Although the analysis of Table 18 is suggestive, it can not be considered conclusive. We

need to control for other characteristics of the firms in order to ascertain the true impact

of venture capital financing on corporate growth. We thus turn to a more formal analysis,

where we look at the effect of venture backing on the growth of employment and sales after

the IPO.

The model we have in mind is very simple: the capacity of an innovative firm to grow is a

positive function of its ability to invest, which can be financed either from revenues or from

external finance (debt or equity). Age, an indicator of the stage of corporate development,

is also relevant since we expect younger companies to grow faster. We therefore estimate the

following model:

employment (sales) growth = f(ROA, leverage, age, foreign sales, venture capital)

and we control for country and sector of activity. As before, we adopt an estimation method

which eliminates gross outliers and employs robust standard errors. Notice that we add a new

dummy, whose value is one when a company declares in the IPO prospectus its willingness to

expand the market for its products outside of the domestic domain. We believe the willingness

to export to be a characteristics of more dynamic companies, since expanding beyond one’s

natural realm requires the ability to sell truly innovative products and services.

In Table 19 we report our results. The dependent variable is the growth of employment

in the period of (up to) three years after the IPO. Note that the dimension of our data set

decreases both because not all companies report employment data and because we cannot

compute post-IPO employment growth for companies which went public in 2000. We are

then left with 270 observations.

The results confirm our intuition. Relatively older companies and those whose return

on asset (ROA) and leverage are higher, increase their employment most. Leverage, in

particular, is not only statistically but also economically significant: A 1% increase in leverage

means a company creates 121 jobs in the post-IPO period. Companies listed on the Nouveau

Marche experience a decrease of 51 units in employment, while the foreign sales dummy has

a statistically insignificant effect. Venture capital plays no role, as it implies a slight decrease

in employment, which is however statistically insignificant.18 Sectors of activity are also not

significant.

18In alternative, unreported, specifications we control for capital expenditure, the level of debt (relative toasset) and its maturity, but this worsens the statistical significance of individual variables and of the regression.

44

Table 19. Robust regression–dependent variable employment growth

Independent variable Coefficient t-statistic

Venture capital -8.93 -0.548

ROA(atIPO) 16.56 *** 2.375

Leverage(atIPO) 121.48 *** 2.623

Foreign sales 10.58 0.695

Age 0.10 * 1.836

France -51.47 *** -2.602

Constant 50.35 1.055

Number of obs. 270

F (11, 258) 3.90

P-value 0.000

Notes: All independent variables measured at the time of the IPO. Significance levels are indicated

by * (10%), ** (5%), and *** (1%). Huber-White corrected standard errors are used to obtain robust

estimates.

We then control for R&D expenditure (at IPO), as reported in Table WA-7 in the Web

Appendix, where our sample almost halves. To avoid an issue of simultaneity and of reverse

causality we control for R&D at IPO. Since R&D expenditure includes expenditure for labor

in R&D it is highly plausible that the latter variable is significant in explaining employment

growth. In fact this turns out to be the case: one million euros of additioinal R&D expenditure

creates an additional 11 jobs. Leverage and the France dummy remain significant and retain

(even increase) their size and sign, while ROA becomes insignificant. Interestingly, the foreign

sales dummy now becomes statistically significant, and negative: for companies with high

R&D expenditure the willingness to expand abroad is detrimental for employment growth.

Again, venture capital does not seems to be relevant and retains its negative effect on job

creation.

We finally turn to the post-IPO sales growth. Table 20 reports our estimates, which

are based on a sample of 316 companies. The results do not differ much from those for

employment growth. Older companies with a high ROA and leverage experience a higher

increase in sales: A 1% increase in ROA results in almost 8 millions of additional post-

IPO sales, and a similar increase in leverage creates 13 million euros of sales, albeit with

scant statistical significance. The new result is that the intention to expand their product

45

market in foreign countries does contribute to sales: Export-oriente companies enjoy almost

7 million euros more of revenue than purely domestic players. French companies significantly

grow less also in terms of sales: Their post-IPO turnover is almost 10 million euros lower

than elsewhere. Venture capital financing remains ineffective: Venture-backed companies sell

almost 5 less millions than others, but the result is marginally statistically significant. Sectors

of activity continue to hold no effect.

Table 20. Robust regression–dependent variable sales growth

Independent variables Coefficient t-statistic

Venture capital -4.68 -1.542

ROA(atIPO) 7.73 *** 5.603

Leverage(atIPO) 13.19 1.508

Foreign sales 6.80 ** 2.302

Age 0.03 *** 2.676

France -10.05 *** -2.768

Constant 7.69 0.870

Number of obs. 316

F (11, 304) 6.63

P-value 0.000

Notes: All independent variables measured at the time of the IPO. Significance levels are indicated

by * (10%), ** (5%), and *** (1%). Huber-White corrected standard errors are used to obtain robust

estimates.

Controlling for R&D expenditure undertaken at IPO, we reduce the sample to 143 com-

panies. Table WA-8 in the Web Appendix shows that R&D expenditure turns out to be

relevant again: R&D performing companies enjoy 2 million euros of sales more than non per-

forming ones. Age and leverage retain their positive effect on sales, while ROA and France

become insignificant. The intriguing result is that venture capital does finally play a role:

Venture-backed companies decrease their sales by almost 8 million euros after IPO.

Before turning to an overall interpretation of these results and of their meaning for the role

of European venture capital, we need to tackle some limitations of our analysis. Our results

could indeed suffer from two possible selection biases, on both observable and unobservable

variables. We thus turn to some robustness checks.

46

4.5 Robustness checks

In the previous sections we have tried to evaluate the impact of venture capital financing on

the companies listed on Euro.nm. The ’evaluation problem’, as it is known in the econometric

literature, is the problem of correctly measuring the effect of a ’cure’–such as a policy reform

or a training program–on some variables (see Blundell and Costas Dias (2000)). The problem

in evaluating a cure is that both observable and unobservable variables may be present, which

might bias the estimates if not properly accounted for.

In our case the correct approach to assess the effect of venture capital (the ’cure’) should

look at certain companies and compare their reaction when they do and when they do not

receive venture financing. Unfortunately this is not possible as our companies are either

venture-backed or non venture-backed, and receiving venture capital is not a random event.

The issue is then how to construct the right counterfactual.

In the impossibility of obtaining experimental data, different methods of evaluation have

been adopted by researchers. We consider two different methodologies. One approach is

known as the matching method, and mainly addresses the issue of bias due to incorrect

control for observable variables. The second approach is known as the difference in differences

method, and it is particularly useful in removing unobservable individual effects and common

macro effects. We thus re-evaluate the effect of venture capital assessing whether our previous

estimates are subject to these biases.

4.5.1 The ’matching’ method

What we have tried to measure in our analysis is the effect of being venture-backed on sales

and employment growth, on the amount raised at IPO, and on the time-to-listing. Denote

any of these variables with Y . The analysis then entails measuring the average effect (τ) of

venture capital on venture-backed companies:

τ = E(Y ivc/i V C)−E(Y i

nvc/iεV C) (1)

where the first element on the right hand side measures the expected value of vetnure capital

on variable Y conditional on company i being venture-backed, while the second term measures

the expected value of the same variable, were company i without venture capital. The problem

is that this last term is not observable: It is impossible to see the characteristics of venture-

backed companies in the absence of venture capital. In other words we lack a proper control

sample. Being backed by venture capital is in fact not random, as we have observed when

47

we have estimated the probability of receiving venture financing. As a consequence, the

assignment process to venture capital might be determined by (observable) variables (Xi)

that potentially affect the outcome Y as well. If that effect turned out to be important, our

previous estimates might be biased and our conclusions flawed.

To exploit the information we get about Y from non venture-backed companies, that act as

our control sample, we assume that, conditional on Xi, the value of Y (time to listing (TTL),

amount raised at IPO, sales or employment growth) and the fact of being venture-backed are

independent. Under this assumption equation (1) can be re-written as:19

τ = E(Y ivc/i V C,Xi)−E(Y i

nvc/iεNV C,Xi) (2)

We can now estimate equation (2) non parametrically. In order to correctly measure the

effect of venture capital we need to estimate the two terms on the right hand side of equation

(2), matching each venture-backed company with a non venture-backed company with the

same characteristics Xi. In other words, we need to find a way to compare observations with

similar Xi. Only in this case the different behavior of the two companies can be correctly

attributed solely to the presence of venture capital.

When Xi is high dimensional the estimation strategy may become unfeasible. Still, one

can resort to matching companies not on the values of Xi but on a function of Xi. We do this

through the ’propensity score’ method, which we illustrate in detail in the Web Appendix. We

then proceed to estimate the average effect of being venture-backed, taking into account that

by using the matching method we reduce the bias due to specification error but possibly at

the cost of losing efficiency. In other words we could obtain estimates with a lower statistical

significance.

Table 21 reports the estimates obtained with this method for our four variables. The

estimated values of τ provide measures of the effect of venture capital different from those we

obtained in the previous sections. Venture capital is now found to slightly (but statistically

significantly) increase TTL. As regards the average effect of venture capital on the amount

raised at IPO the matching method suggests a negative effect, casting some doubts on the

positive effect of venture capital which we found in Table 17. However, this method confirms

our finding of a negative effect of venture financing on the post-IPO growth of sales and

employment. The standard errors of amount raised, employment and sales growth (but not

that ot TTL) in fact become considerably larger, but, as we observed, this is not surprising

19This assumption is known in the literature as ’conditional independence.’

48

for this type of estimates.

Overall, we conclude that the inference from our regression analysis may not be robust

to possible specification biases with respect to observable variables in the case of TTL and

amount raised. In the case of sales and employment growth, instead, we find reasons to

remain confident on the robustness of our findings.

Table 21. Nonparametric stratification estimates: Average effect of venture

capital

τ t-ratio

Time-to-listing 0.42 *** 5.276

Amount raised (over assets) -10.19 0.639

Employment growth -21.478 0.434

Sales growth -36.678 0.513

Notes: Significance levels are indicated by * (10%), ** (5%), and *** (1%).

4.5.2 The ’difference in differences’ method

Another popular method of evaluation is called ’difference in differences’ (DID), and is helpful

in addressing possible evaluation biases due to the effects of unobservable variables which

could be driving the difference in behavior of the two groups we are trying to compare,

venture-backed and non venture-backed companies. The name of the DID estimator comes

indeed from the fact that it compares the difference in the average behavior before and after

the IPO for the eligible group (venture-backed companies) with the behavior before and

after the IPO of the control group (non venture-backed companies). Notice that we compare

behaviour around the IPO since we need to pin down the effect of venture capital (the ’cure’)

on how treated and untreated companies react to a common external shock (the IPO).

We can apply the DID estimator only in the case of employment and sales growth, since

time-to-listing and amount raised only occur at IPO. We indicate the estimator with θDID,

which measures the growth of venture-backed in excess to that of non venture-backed com-

panies. Abstracting from any regressor besides venture capital indicator, we write:

θDID = (YV Ct1 − Y V C

t0 )− (Y NV Ct1 − Y NV C

t0 ) (3)

49

where Y V C and Y NV C are the mean values of the variables for the venture-backed and the

non venture-backed companies, respectively, and ta0 and t1 represent the pre- and post-IPO

periods.

Under the assumptions of common time effects across groups and of no composition

changes within each group, θDID measures the average effect of the IPO by removing the

unobservable individual effects and common macro effects. In fact, by differentiating the mean

value of Y inside the brackets we eliminate the common individual effect without affecting

the common time effect, which can be eliminated by differentiating the two brackets.

Table 22 shows the results of the DID estimator for the post-IPO growth in employment

and sales for the two groups of companies. Our estimated effects confirm the sign of the

coefficient of our previous estimates, as well as that of the stratification estimator, although

both their value and their significance is now higher. There are two possible weaknesses of

the DID estimator. One is due to the lack of control for unobservable (temporary) individual

specific components that might influence the behavior of the two groups. The DID estimator

might then over-estimate the effect of the cure. This is a possible an explanation of the

higher values in Table 22 than in Table 21. A second weakness of the DID estimator is

that the assumption of common macro effect across companies. If the two groups have some

characteristics which distinguish them and make them react differently to the common shock,

we may get inconsistent estimates.

Table 22. Difference in differences estimates: Average effect of venture

capital

θ t-statistic

Employment growth -106.38 * -1.84

Sales growth -127.18 -1.08

Notes: Significance levels are indicated by * (10%), ** (5%), and *** (1%).

4.6 Venture capital in Europe: An assessment

We are now able to provide an initial assessment of the role of venture capital in Europe, and

of its ability to contribute to economic growth and job creation. We should consider several

elements in turn.

First, we have seen that European venture capital has grown substantially over the last

few years. The amount of money invested in innovative companies and the number of venture

50

capital firms have increased fast. Wide differences remain across national economies, and the

gap with the United States is far from closing, but the European venture capital industry is

certainly expanding fast. This is hardly surprising, since the industry appears to be highly

profitable: The internal rate of return for three year old investments was in 2000 a hefty

29.2%, and that for ten year old ones a remarkable 15.6%, according to the European Venture

Capital Association (EVCA (2001)).

Second, we have documented that the involvement of venture capital with companies

listed on Europe’s ’new’ stock markets has become substantial, and might have started a

virtuous circle whereby easier exit through an IPO encourages venture investments, which

in turn nurture companies which can soon list and support the growth of stock markets.

Intriguingly, we have seen that the number of venture-backed listed companies which were

born with the financing of a venture capitalist increases year after year, as does its proportion

over all venture-backed firms.

Third, we have focused on the effect of venture capital on some of Europe’s most successful

innovative firms, those which made it to list on one of the ’new’ markets. Here we can apply

a more formal statistical analysis and sharpen our arguments. On the basis of the theoretical

literature, and of empirical studies of US venture-backed firms, we have explored the effect

of venture capital on the timing of the listing of investee companies, and on their ability to

raise funds at IPO, to generate revenue, and to create jobs. Venture capital appears to yield

uncertain influence on the timing of IPOs. We also find that it helps companies raise more

capital at IPO, but this result does not seem robust to possible biases in the analysis. From

this we conclude that the ability of venture capital to ease credit constraints in Europe is

very important but still confined to the earlier stages of a firm’s life, when financing may be

crucial for its very coming into existence. In fact, the number of venture-backed companies

has more than doubled after the opening of Euro.nm, reaching almost 10,000. It is suggestive

to compare this result with what Hellmann and Puri (2000) find for a sample of Silicon Valley

firms. They argue that that the role of venture capital in front of less radically innovative

companies is precisely the provision of funds at early stages, rather than speeding up their

maturation.

We also find that venture-backed companies do not generate more sales or create more

new jobs than others. On the contrary, when we restrict our sample to the more innovative

companies, those which perform R&D, the venture-backed ones appear to increase their sales

less than the others. Robustness checks to detect possible biases in our analysis confirm that

these findings are indeed robust, and that venture-backed companies are not the ’superstars’

51

among those listed on Europe’s ’new’ stock markets–at least in terms of sales and employ-

ment growth. While we cannot eliminate all reasonable doubts on the possibility of selection

biases, the empirical evidence we uncover does support the idea that venture-backed listed

companies are not systematically different from non venture-backed companies, and that they

do not grow faster, either before or after the IPO.

We interpret this finding as suggesting that the role of venture capital in Europe is

somewhat different than in the United States. The provision of early stage financing, which

has grown very fast in the past three years, seems to be crucial to allow innovative start-ups

to overcome credit constraints, which are arguably tighter in the old continent. Whether the

lack of a systematic association with the most successful innovative companies is due to the

immaturity of European venture capital or to a lack of ’superstars’ among European firms

we cannot say at this stage.20

A sensible objection to our interpretation is that the unselective high valuation of compa-

nies listed on Euro.nm might have masked the true value of being venture-backed. This is a

fortunate time to look at this possibility, since stock valuation on Europe’s ’new’ stock markets

have fallen sharply since mid 2000. One may conjecture that the true value of venture-backed

companies would only show up once the market becomes more selective. While a thorough

analysis of the determinants of valuation goes well beyond the scope of this paper, we can

provide some telling information.

Figure 5 plots a simple (unweighted) stock price index of all the companies in our sample,

which we divide into venture-backed and non venture-backed ones. One can readily see that

there has been no systematic under-valuation of venture-backed companies, and that the

behaviour of the two indices is quite similar.21 Since our data go through June 2001, we

consider it unlikely that extremely high valuations of high-tech companies in the late 1990s

may have obscured the true value of being venture financed. On the contrary, this pattern

appears at first sight in contrast to the results of Brav and Gompers (1997), who find that

in the five years after going public venture-backed companies growth outperform similar

non-venture-backed companies.

20One should also consider that venture capital firms are (successful, it seems) profit-driven organizations,not public bodies. Hence, one may expect them to contribute to corporate growth and job creation onlyinasmuch as this make them richer.21Moreover, the standard deviation of the index of venture-backed companies is about one and a half times

that of non venture-backed companies, i.e. the former are more volatile, suggesting more uncertainty on partof investors. A rank-sign test accepts the hypothesis of equality of the medians of the two series, but not ofthe variances.

52

Figure 5 about here

Another possible objection to our interpretation is that main role of venture capital is

to bring companies up to the levels required for listing, thus helping those which would

not be able to qualify for an IPO without external help. In this case, the value of venture

capital would result in high growth of investee companies after its arrival but before the IPO.

Unfortunately, the nature of our data set prevents us to test directly for this possibility, since

for the companies in our sample the time between the arrival of the venture capitalist and

the IPO is too short to allow any statistical analysis.22 However, indirect evidence suggests

that this conjecture may not hold to a closer scrutiny. First, the listing requirements of

Euro.nm do not constitute a tight barrier, and are in fact far from binding for most of the

companies which go public on Euro.nm. Second, the financial structure of listed companies

varies widely, so that not even ’de facto’ minimum standards seem to characterize these IPOs

(Bottazzi and Da Rin (2001). Finally, we find that firms which receive venture capital are

characterised by a low level of sales (see Table 13), but also that the sales and earnings of

venture-backed companies remain lower than those of non venture-backed firms in the three

years before IPO (see Table 18). This would not be the case if the main task of venture

capital were to bring investee companies to pass a hurdle or to reach the same performance

of more aggressive competitors.

While the nature of our data clearly makes it difficult to distill truly conclusive results,

ours is clearly a piooneering attempt and we have to make do with available data. For

instance, we cannot obvserve the instrinsic quality of investee companies, nor the actual be-

haviour of venture capitalits to assess if some of them may be more effective than others in

nurturing innovative businesses. Still, we believe that we have constructed a solid interpre-

tation of what venture capital is presently doing in Europe, and that this hard evidence may

contribute to more informed policy decisions.

5 Conclusion

Venture capital is growing fast in Europe, and its influence on European entrepreneurial

firms is increasingly important. Without financing from venture capital many of today’s

most dynamic start-ups could have never come into existence, and a non negligible number

of the companies which list on Europe’s ’new’ stock markets would probably never have made

22The median time between the arrival of a venture capital and the IPO is only 16 months.

53

it. Venture capital is therefore understandably high on the policy agenda, both at EU and

national levels. The presumption is that venture-backed firms are particularly dynamic, and

able to create jobs and wealth. An effort to create suitable conditions for the development of

this form of financial intermediation then seems warranted.

We provide the first attempt at a rigorous assessment of this policy stance. We ask

ourselves what role does venture capital really play in Europe. We find that the industry is

expanding fast, but that the sums invested are growing less than in the US. Since venture

capital plays a crucial role for the creation of innovative start-ups in a continent where capital

markets are particularly unsupportive of non established businesses, the public concern for

fostering the supply of funds to industry appears justified. However, studies for the US

also suggest that it is probably the demand, rather than the supply of venture funds to be

constraining the rise of the industry (see Gompers and Lerner (1998)). We then look beyond

the supply side to the ability of European venture capital to deliver more than pure financing.

Our results show that in Europe venture capital is not systematically associated with

particularly dynamic companies, whether we look at sales growth, at new employment, or at

stock market performance. The limitations of our data make us stop short of a final answer,

but they resonate well with an increasing body of evidence that European venture capital lacks

more more human than financial resources. For instance, recent case studies show that in the

1990s German venture capital suffered from a lack of qualified, experienced professionals (see

Becker and Hellmann (2000)). In an insightful survey study, Freeman (1998) finds that lack

of human resources is cited by respondents–insiders to the industry–as a major problem

for the maturation of the German venture capital industry. We mentioned the relative stock

market under-perfomance of venture-backed companies in Europe, as compared to the United

States, which might be another indication of an immature industry.

This interpretation, while still tentative, would also be consistent with the need to learn

its ropes by this still very young industry. After all, American venture capital matured over a

much longer period, which was not always a bed of roses. Other facts point to this direction.

For instance, in 2000 the number of investee companies per venture firm in Europe was three

times as large in Europe as in the United States (23 to 8). Since effective nurturing requires

an intense and close relationship with investee companies, beyond a certain threshold the

quality of the ’soft’ side of venture capital might well fall. To us, these facts and the evidence

we uncovered suggest that creating the conditions for a more mature venture capital industry

should be a high priority for European and national policy-makers.

54

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Data Appendix

We collect our information from all available issuing prospectuses and annual Reports

or Euro.nm listed companies. Data are codified for all available years prior to the IPO

(from prospectus information, which typically contains information for the three years before

listing), as well as for all available years after the IPO (from subsequent annual reports).

Some companies choose to end their fiscal years in a month different from December. In

these cases if the company’s fiscal year ends between January and June we consider it as

ending the previous December, otherwise we consider it ending the following December. For

the year 2000 in the few cases where the annual report was not yet issued at the time of

writing, we rely on end-year official announcements of results.

Since 1999 most information is reported in euros. For earlier years we use monthly

averages of the exchange rate between the ECU and national currencies to obtain an euro-

equivalent. For subsequent years we use euro conversion rates.

Financial and business variables

We codify several financial variables: assets, debt, equity, and Ebitda (earnings before

interest, taxes, depreciation and amortization), from which we compute leverage (debt divided

by debt plus equity) and ROA (return over assets, computed as Ebitda over assets). Ebitda

is a common measure of a firm’s profitability which does not depend on its financial policy

and tax regime.

We computed the amount of capital raised at IPO as the issue price times the number

of shares sold at IPO, except those sold by existing shareholders, but including the amount

of greenshoe actually used. The amount of shares issued under the greenshoe over-allotment

option is taken from the web site of the stock exchange for the German and Italian markets,

and for the French market until the end of 1999. For French IPOs in 2000 we contacted

directly issuing companies.

We take from the prospectus and annual reports information about a company’s business

and strategy. We codify the following variables: Sales (total revenue from sales of goods and

services), Employees (at year end), Capex (capital expenditure), Foreign sales share (share

of foreign sales over total sales), Intangible assets (the stock of goodwill, patents, software

and advertising), and R&D (current expenditure in research and development. From these

data we can compute R&D intensity (R&D over Sales). Patents would be a natural measure

of a firm’s innovation strategy. Unfortunately, the nature of the data makes it difficult to use

them sensibly since patent applications take about 18 months to be released by the European

Patent Office, so we are only starting to get patent data for the post-IPO period.

Sectoral attributions

Each company in the data set is assigned to a sector. The procedure we use is based

on the sectoral attribution of Datastream, which are derived from the classification of the

Financial Times. We use the following seven sectors: BIOMED, FINSER, ITSIS (comprising

Internet, IT services, and software), MEDIA & ENTERNAINEMENT, TECHNOLOGY,

TELECOMMUNICATIONS, and TRADITIONAL (products and services).

We also employ an alternative sectoral classification, following the sectoral attributions

introduced in May 2000 by the Neuer Markt, and we obtain very similar results as the one we

report in the main text. The Neuer Markt assigns each company to the sector which generates

the largest share of its earnings. For companies listed in markets other than the Neuer Markt

we attribute sectors by looking at the business description contained in the issuing prospec-

tus, and we augment the Neuer Markt classification with two further sectors: Manufacturing

(other than high-tech products) and (traditional) Services. The nine resulting sectors are:

Biomed (which includes biotechnology—pharmaceutical products and services based on appli-

cations of genetics—and medtech-medical goods and health care services), Financial services

(banking, insurance and brokerage, usually provided through the internet), Industrial Ser-

vices (innovative services for industrial firms), ITSIS (infrastructure for the internet, internet

services, IT services, internet, software), Manufacturing (goods other than high-tech), Media

and entertainment, Services (marketing services, wholesale and retail distribution, business

consulting, logistic services), Technology (high-tech products and services), and Telecom.

Venture capital data

In order to identify venture capital financing we could not rely on a simple procedure. A

venture capital firm is not a bank, which can be readily identified as such. Since no license

or professional registry exist, one must resort to a number of ’identifying conditions.’ For

each company we proceeded to identify from the listing prospectus the venture capitalists

which provided financing, starting from a pool of more than 300 ’candidates,’ i.e. financiers

which were not founders, nor individuals, friends and families, or strategic partners (i.e. other

companies). For each company we used the information about its ownership structure at the

time of the IPO, which lists all its shareholders and details their holdings before and after the

IPO. This helped us identify which venture capitalist have been involved with the company,

and the extent of their shareholdings. A potential limitation of relying on data at IPO is

that a venture capital might have already exited the company. This turns out to be a rare

event, since the venture capital can profit much more by remaining until IPO. Moreover,

the US experience shows that when a venture capital sells before IPO, it usually sells to

another venture capitalist, in which case the presence of a venture capitalist at IPO would

still show up. Direct inspection of the history section of all prospectuses revealed that a

venture capitalist exited before IPO only in a couple of cases.

The process of identification of venture capitalist consisted of several steps. First, We

identified venture capitalists by using the directories of the European Venture Capital Asso-

ciation and the directories of the British, Belgian, Dutch, French, German, Italian, Israeli,

and US national venture capital associations. The venture capitalists members of one of

these association form our ‘tier 1,’ or core, group of venture capitalists, and they total 123.

We then proceed to using other sources in order to identify venture capitalists which are

not members of an association. Using online directories of venture capitalist (mainly at re-

gional level), web sites, IPO prospectuses, and press sources we check if each ’candidate’ is

defined as an ’actual’ venture capitalist. These ’self declared’ venture capitalists form our

’tier 2’ group, which comprises 75 more venture capitalists. Overall, our sample reveals that

198 venture capitalists were involved with companies listed on Euro.nm. Ten of these were

national branches of international venture capital groups, like 3i group, the British private

equity and venture capital firm. We report the results we obtain using the broader definition

of venture capitalist (i.e. those falling in either tiers), as our results do not change if we

restrict the definition to the core.

For each venture capitalist we measure from the prospectus the share of equity held at

IPO and the amount which is sold at that time. Finally, we then looked at information about

the date of entry of venture capitalists, i.e. the date at which they first contributed funds to

the company. If more venture capitalist are involved with a company, we use as date of entry

that of the first of them which got involved with the company. The entry date could often

be identified from the company’s own history description. In all the other cases we directly

contacted the company. Overall, we could assign the entry date in 90% of the cases.

Price data

We take our price data from Datastream. We collect price data for all the companies in

our data set, excluding the sixteen ones in the financial services sector. We use daily closing

prices, which are corrected for stock splits and changes in nominal value of the underlying

stocks.

Definitions of the variables

The following is a list of definitions for all the variables we use.

AGEIPO is the age of a company at the date of its IPO. To determine a company’s date

of birth we employ the earliest evidence of business activity in the listing prospectus, which

need not coincide with the date of incorporation. In fact, several companies were born as

partnerships or limited companies before incorporating.

TIME-TO-LISTING (TTL) is the time elapsed from a company’s foundation to its IPO. For

companies born before the opening of the Euro.nm market in which they list, TTL is the

time elapsed from the opening of the Euro.nm market and their IPO. Two companies which

went public in the same month but which are listed in two different markets may then have

two different TTL, since different markets opened at different times.

VC is a dummy variable that takes the value 1 if a company has received venture capital

financing, and 0 otherwise.

AMOUNT measures the capital raised at IPO. It equals the issue price times the number of

shares sold at IPO (except those sold by existing shareholders, but including the greenshoe).

BIOMED, FINSER, ITSIS (comprising Internet, IT services, and software), MEDIA & EN-

TERNAINEMENT, TECHNOLOGY, TELECOMMUNICATIONS, and TRADITIONAL (prod-

ucts and services), are dummy variables which take the value 1 if the company operates in

that industry and 0 otherwise.

We use the following financial variables:

ASSETS is current total asset.

DEBT is the sum of commercial and financial debt.

EQUITY is total shareholders’ equity.

EBITDA is earning before interest, taxes, depreciation and amortization.

DEBT-TO-EQUITY is DEBT divided by EQUITY.

LEVERAGE is DEBT divided by DEBT plus EQUITY.

ROA is EBITDA over ASSETS.

We use the following variables which reflect a company’s business situation and strategic

choices:

SALES is total revenue from sales of goods and services.

EMPLOYEES is the total number of employees at year end.

CAPEX is capital expenditure, i.e. investment in tangible and intangible fixed assets.

FOREIGN SALES SHARE is the share of foreign sales over total sales.

INTANGIBLE ASSETS equals the capitalized amount of goodwill, patents, software and

advertising.

R&D is current expenditure in research and development.

R&D INTENSITY is R&D over ASSETS.

Web AppendixContents

This Appendix we provide additional information to that provided by the main text.

Part 1 provides two additional descriptive tables about venture capital investments in Eu-

rope. Part 2 provides four additional regressions, which we comment in the main text, where

we control for R&D or R&D intensity. Part 3 provides additional explanations on the econo-

metric techniques used to perform our robustness checks.

Part 1: Additional descriptive statistics

Table WA-1. Frequency of venture capital investment

Venture capitalist Nationality Number of investees

3i Group INT(UK) 27

Apax Partner INT(UK) 12

Galileo Partners F 12

Gold-Zack AG D 12

Technologie-Beteiligungsgesellschaft D 12

ABN Amro Ventures INT(NL) 10

BNP Developpement F 10

Financiere Natexis F 10

Atlas Ventures INT(US) 9

Group de Rothschild INT(F) 8

Soffinova Partners F 8

TBG-Technologie-Beteiligungsges. D 8

Banexi Ventures Partners F 7

Dassault Developpement F 7

CDC Innovation F 6

Sofimac Partners F 6

Techno Venture Management Gmbh D 6

Commerz Beteilugungsgesellschaft D 5

Concord Effekten AG D 5

DEWB-Deutsche Effekten und Wech.-B. D 5

IKB Beteiligungsgesellschaft D 5

Venture Capitalist Nationality Number of investees

Knorr Capital Partner AG D 5

TechnoStart GmbH D 5

Vertex Management LTD INT(SIN) 5

AXA F 4

Bank Austria A 4

Banque de Vizille (Group CIC) F 4

HSBC Private Equity INT(UK) 4

IRDI de Midi F 4

Schroeder INT(UK) 4

Thompson Clive & Partners INT(UK) 4

Alpinvest F 3

BUWB Bayerische D 3

CEA Capital Partner GmbH & Co. Beteiligungs KG D 3

Europ@web (Groupe Arnault) F 3

TFG Venture Capital AG D 3

UCA Unternehmer Consult AG D 3

Financiere Vecteur F 3

LBB Beteiligungsgesellschaft D 3

Paribas F 3

Partcom SA (group CDC) F 3

Private Equity Partners I 3

Sal. Oppenheim jr. & Cie. D 2

S-UBG AG D 2

Advent International INT(US) 2

Alta Berkeley US 2

Apollo Invest F 2

BayBG Bayerische D 2

BB-Kapitalbeteiligungsges. D 2

bmp AG D 2

BW-Venture Capital D 2

DG-Private Equity D 2

Epicea SA F 2

IBB Beteiligungsgesellschaft D 2

Venture Capitalist Nationality Number of investees

Initiative and finance F 2

KB Partners, LLC US 2

Mivtah Shamir IL 2

Pechel Industries F 2

Pino Venture Partners I 2

Saarlandische Kapitalbeteiligungsges. D 2

SNBV Partecipations F 2

Sogginove (groupe Societe Generale) F 2

Sopromec F 2

TechnoStart GmbH D 2

Transconnect GmbH D 2

Value Management & Research D 2

Ventech F 2

Venture-Capital Baden-Wuerttenberg D 2

WeHaCo Kapitalbeteiligungs GmbH D 2

West-LB D 2

Other venture capitalists with one investment 122

Notes: INT stands for ’international,’ i.e. a venture capitalist with active offices in more than threecountries. In brackets the nationality of the headquarters.

Source: Authors’ calculations.

Table WA-2. Venture capital, sectoral specialization

Euro.NM VC-backed

% %

Biomed 8 12

Traditional (manufacturing and services) 4 3

ITSIS (IT Services, Internet, Software) 57 53

Media & Entertainment 10 8

Technology 16 17

Telecommunications 5 7

Source: Authors’ calculations.

Table WA-3. Corporate growth: descriptive statistics

Pre-IPO

Mean Median Min Max S.D. Obs.

Assets 113 7 0 44,823 2,082 463

Debt 28 4 0 7,967 370 462

Equity 72 1.3 0 28,213 1,383 416

EBITDA 5.8 0.5 -18.1 1,679 79 456

Leverage 0.7 0.8 0 1 0.2 414

ROA 0.1 0.1 -6.1 5.1 0.7 455

Sales 52 7.5 0 12,344 576 463

Employees 141 68 0 1,538 216 413

Capex 1.8 0.6 -2.8 37 4 342

Foreign sales (%) 0.2 0 0 1 0.3 282

Intangible assets 2.6 0.2 0 30.8 8.6 372

R&D 2 0.8 0 17.4 3 156

R&D intensity 0.8 0.1 0 20 1.7 158

Post-IPO

Assets 195 53.1 0.2 13,187 1,013 355

Debt 64.2 14.9 0.2 5,194 302 354

Equity 123 33.5 0 7,959 616 350

EBITDA -17.1 1.8 -7,035 338.9 379 352

Leverage 0.4 0.3 0 1 0.2 349

ROA 5.1 0.04 -140 1.853 99.5 349

Sales 121 30 0 18,287 967 360

Employees 399 194 10 3,210 553 332

Capex 37.7 6.3 -96 3,860 235 293

Foreign sales share (%) 0.2 0.1 0 1 10.3 147

Intangible assets 39.5 6 0 2249 162 299

R&D 13.8 3.3 0 731 65.6 152

R&D intensity 0.4 0.1 0 32 2.6 152

Notes: For ease of comparability, we drop 34 companies with negative equity values in the pre-

IPO period, and three companies with negative values in the post-IPO period. Source: Authors’

calculations.

Part 2: Statistical analysis, controlling for R&D

In the tables ’preVC’ indicates variables which are measured before the arrival of the venturecapitalist, while ’atIPO’ indicates variables which are measured at the time of the IPO.Significance levels are indicated by * (10%), ** (5%), and *** (1%). Huber-White correctedstandard errors are used to obtain robust estimates.

Table WA-4. Probit regression–dependent variable venture capital

Independent Marginal increase Coefficient z-statistic

Variables in probability

R&D intensity(preVC) -0.05 -0.15 -0.736

Sales(preVC) -0.006 -0.02 * -1.816

Leverage(preVC) 0.221 0.75 1.522

Constant -3.04 *** -4.688

Number of obs. 101

Log likelihood -54.02

Waldχ2(7) 8.7

P-Value 0.001

Table WA-5. Cox regression–dependent variable time—to-listing

Independent variables Hazard ratio t-statistic

R&D(atIPO) 1.00 *** 7.01

Venture capital 0.83 -1.22

Leverage(atIPO) 1.07 0.17

ROA(atIPO) 1.00 -1.30

France 0.34 *** -5.56

Age*97 1.01 *** 7.29

Age*98 1.01 *** 6.31

Age*99 1.00 * 1.70

Age*100 1.00 *** -3.13

Number of obs. 186

Log likelihood -752.98

Waldχ2(14) 194

P-value 0.00

TableWA-6. Robust regression–dependent variable amount of funds raised

over assets

Independent variables Coefficient t-statistic

R&D intensity(atIPO) -0.005 -0.424

Sales/Assets 0.065 1.574

Venture capital 0.49 1.241

Leverage(atIPO) 2.717 ** 2.327

ROA(atIPO) -1.184 *** -3.416

Age -0.005 *** -2.510

France -1.883 *** -4.165

Constant 3.642 ** 2.010

Number of obs. 180

F (12, 167) 4.07

P-value 0.000

Table WA-7. Robust regression–dependent variable employment growth

Independent variable Coefficient t-statistic

R&D(atIPO) 11.59 *** 4.037

Venture capital -27.94 -1.134

ROA(atIPO) -7.82 -0.256

Leverage(atIPO) 185.51 *** 2.948

Foreign sales -46.11 * -1.829

Age 0.03 0.811

France -69.68 *** -2.548

Constant 77.12 1.204

Number of obs. 117

F (11, 105) -4.43

P-value 0.000

Table WA-8. Robust regression–dependent variable sales growth

Independent variables Coefficient t-statistic

R&D(atIPO) 2.04 *** 5.041

Venture capital -7.90 *** -2.435

ROA(atIPO) -3.90 * -1.366

Leverage(atIPO) 18.10 ** 2.015

Foreign sales -1.22 -0.343

Age 0.03 ** 2.351

France -1.10 -0.301

Constant 9.54 1.263

Number of obs. 143

F (11, 131) 5.31

P-Value 0.000

Part 3: The stratification estimator

Here we discuss the implementation of the stratified estimation method we use in our

robustness checks. When the dimensionality of the vector Xi becomes unwieldy, one pos-

sibility is to make use of the ’propensity score’ method, i.e. to estimate the probability

(p(Xi)) of obtaining venture capital conditional on observables Xi. Observations with the

same propensity score will then have the same distribution of the full vector of observables

Xi. This methodology entails a two step strategy: We first estimate the propensity score,

and subsequently the conditional average of the variable venture capital.

In order to estimate the average effect of venture capital we need first to estimate the

propensity score for each observation of our sample. We use a probability model where we

introduce the following covariates (Xi), which we measure at IPO: return on assets (ROA),

sales, the dummy for foreign sales,, and controls for country and sector of activity.

Then, following Dehejia and Wahba (1998) we stratify the estimated propensity scores

for venture-backed and non venture-backed firms into five blocks (’bins’) of equal score range

(0-0.2,..,0.4-0.6). Ideally we would like to have the same frequency of venture-backed and non

venture-backed firms in each bin. We check whether we succeed in balancing the covariates

within each stratum by testing for the equality of the first and second moments of covariates

within each stratum. If there are no differences we accept that specification. Otherwise we

split the block and test again. Six observations for venture-backed companies are discarded

since their propensity scores were lower than the minimum value of the propensity scores

associated to non venture-backed companies.

The stratification estimator is then nothing more than a weighted average of the differ-

ence in means for the variable Y, across the discrete bins produced by the propensity score

estimation:

τ =1

N

XbNV Cb (

XiεV Cb

1

NV Cb

Y V Ci −

XiεNV Cb

1

NNV Cb

Y NV Ci )

where VCb and NVCb are the sets of VC backed and non VC backed observations in each bin

and NV Cb ,NNV C

b the corresponding numeber of observations. The relative variance can also

be computed as:

V ar(τ) =1

NV C

"V ar(Y V C

i ) +Xb

NV Cb

NV C

NV Cb

NNV Cb

V ar(Y NV Ci )

#