The effect of Capital Venture Investments on tech start-up efficiency in the Benelux

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PIETER DUIJS STUDENT NUMBER 10266607 UNIVERSITY OF AMSTERDAM FACULTY OF ECONOMICS AND BUSINESS SUPERVISOR: MARK DIJKSTRA

The Effect of Capital Venture Investments on Tech Start-up

Efficiency in the Benelux

29th of June 2016

Abstract: This paper presents an empirical study of the effect of venture capital investment on efficiency. A panel data regression of 43 tech start-ups based in the Benelux is performed over the period of 2000-2015 to test what the effect of venture capital investments is on the efficiency. The results show a significant negative influence of 327300 euros of the years after capital investment. When separating the years after investment, only the first years showed a negative significance of 309800 euros. The following years however, showed a decrease of negative influence on efficiency. From this decreasing negative effect, an average growth of 3% of efficiency can be concluded.

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1.1. INTRODUCTION

Currently 83,5% of start-up capital is financed by private financing or bank loans. With the rise of many tech start-ups, the banks’ valuation methods are having trouble to value these companies and with this, they are unable to minimize the risk of the start-ups’ loan default. (Bertoni, Croce & D’Adda, 2010). Therefore, banks are not as willing to provide loans as they used to be to new companies, and especially to tech companies. Banks lack expertise and knowledge to invest in young and high-risk companies (Wang & Zhou, 2002). As a solution to this problem, entrepreneurs will have to find new ways to fund their businesses. Start-ups are looking for venture capital firms to provide their needed financial resources, and involvement in their activities by revenue sharing in exchange for equity. These venture capital firms provide the financial resources needed, next to that they provide a network, monitoring and experience. These additional resources can’t be provided by the classic funds providers (Gompers, 1995). Since there are different ways of funding, and the new trend towards capital venture is rising, current literature is questioning what the effect of this way of funding is on company performance.

Hellmann & Puri (2002) state that the use of owner funds and funds from friends, family and fools will have a positive effect on efficiency due to a higher growth in value added across time. Stearns, Carter, Reynolds and Williams (1995) state that venture capital backed start-ups increases the number of employees with 151% on average in the first year to prepare for future growth, which has a negative effect on company efficiency.

According to Levenson & Willard (2000) start-ups are insufficiently prepared to efficiently use the invested resources. When in this stage the capital investment firm does invest, even though the company isn’t ready for this investment, the investment will be necessary for funding the preparation of growth. This way in the first years the effect of assets and sales growth will be minimum. Since efficiency is affected by assets, this will have a negative effect on efficiency (Levenson & Willard, 2000).

According to Lofstrom, Scherr, Sugrue & Ward (1993) it appears that the capital venture backed companies have an average 26% higher growth of sales in the first 4 years. These higher sales will benefit the assets growth; which leads to a positive effect on efficiency.

Venture capital firms exchange their financial resources for a percentage of equity (Faulklender and Petersen, 2004). Due to this investment, assets will rise and efficiency will increase since the acquired cash/asset will be an asset with no payback obligation.

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As a results of these doubts about the effect of venture capital investment on company efficiency, the following research question is constructed; “What is the effect of capital venture investment on the efficiency of tech start-ups based in the Benelux?”

This thesis will focus on the funding effect on company efficiency. With the efficiency measured in total assets divided by the number of employees. To answer the research question, a panel data regression is performed to test this effect.

This thesis will focus the regression on tech start-ups based in the Benelux (Belgium, Netherlands and Luxembourg). The choice for tech companies based in the Benelux is coming from the fact that in these countries, compared to countries as the UK and US, capital venture investment is not the main form of start-up investment (Manigart & Struyf, 1997). The results present negative numbers concerning company efficiency. The total effect of venture capital investment showed a significant effect of 327300 euros. When separating the years after investments, the first year that venture capital firm invested in the start-ups, showed a significant negative effect on company efficiency. The following years show negative coefficients as well. However, the negative effect of venture capital investment decreases after the first year. The decreasing negative effect can be concluded as an average 3% growth of efficiency in the first 5 years after investment.

The conclusion from these results, is that the presence of capital investment firms in tech start-ups has a negative effect on tech start-ups in the Benelux in total, however when separating the years after investment the results are dissimilar. This thesis will be constructed in the following way: in section 2 the different capital seeds will be explained and the pros and cons regarding these different ways of funding will be contradicted. Section 3 will provide the research model used, section 3 will consist of an explanation of the data used in this research, section 5 will provide the research results and section 6 will be the research conclusion.

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2.0. LITERATURE REVIEW

2.1. Venture capital firms

Start-ups are in need of funding, especially in their growth stage1. This need is fulfilled by loans or investments. A part of the total investments comes from capital venture firms. They differ from the classic way of bank loans or FFF-investments (friends, family, fools). The FFF-investments are, together with financing out of ‘your own pocket’, the most frequently used form of financing to start with the business of the start-up. However, these forms of financing are in 73,7% of start-up financing cases, not enough to provide enough financial resources for the growth stage of the company (Scherr, Sugrue & Ward, 1993).

The entrepreneur has to make a choice between an external investment or a loan. With a loan, the lender provides the financial resources in exchange for a contractual agreement to repay the loan. Bank loans are still frequently used; the numbers are declining as main financial resource method for start-ups. Banks are unable to rely on their valuation models with the current trend of tech companies. Therefore, start-ups are due to high information asymmetry and the failing valuation systems of banks, they are unable to access traditional financing sources such as loans (Faulklender and Petersen, 2004). Therefore, new forms of investments are emerging. One of these new forms of investments is venture capital.

Venture capital firms are investment vehicles. The financial resources of these companies come from bank capital, pension funds, financial institutions and external investors (Keuschnigg & Nielsen, 2004). Compared to banks, venture capital firms’ information asymmetries are lower. Capital venture firms invest heavily in their own management to get a better understanding from the market the start-up is in, invest in models to evaluate these start-ups and providing a network of external resources. (Davila, Foster & Gupta, 2003).

The venture capital firm was introduced in 1946 when Georges Doriot created American Research and Development. Together with the president of the Federal Reserve Bank and others, American Research and Development raised funds from wealthy individuals to invest them in entrepreneurial start-ups in technology-based manufacturing (Botazzi & da

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Rin, 2002).

According to Bergemann and Hege (1998) venture capital investors cash out of only 20% or less of the invested companies. Most of this cashing out, 67%, is done by IPO’s. These cashing out capital venture firms tend to do later stage investments. Wang & Zhou (2004), who performed a research among 636 tech start-ups worldwide of the time-span 2000-2003, show that across Europe, the returns of staged investment capital venture firms is 33% higher than single investment capital venture investment firms.

Stearns, Carter, Reynolds & Williams (1995), which performed a research of start-ups founded between 1979 and 1985 in the states of Minnesota and Pennsylvania, the business that will seek for these capital venture firm investments are companies that are not expecting positive returns in the first years, since they have to invest market penetration and future growth.

According Levenson & Willard (2000), who surveyed a nationally representative sample of small businesses (500 employees or fewer) in the United States in 1988-89, only 23% of start-ups is able to fund the company with a bank loan, since banks only provide these loans to companies with positive cash flows. The second type of companies, are the tech companies that have to make high investment in research and development. Sufficient financial resources are needed for the funding of R&D. Therefore, these business with their high amount of start-up costs will not make any positive cash flows in the first years. Next to that, they are unable to go public since they are too small to access these markets (Levenson & Willard, 2000).

Furthermore, start-ups lack experience, expertise and possibly a network (A. Davila et al., 2003). These intangible assets can be provided by the right capital investment firms as well, since capital investment firms are a collaboration of people who possess these assets. They contribute to the management of the start-up and will effect, when used in the right ways, efficiency in a positive way (Keuschnigg & Nielsen, 2004).

2.2. Pros and Cons

Keuschnigg & Nielsen (2004), state that in the US, venture capital is one of the common used, 34%, resource for start-up funding. This is in contrast to the European start-up market where there is even an aversion to these companies in Europe.

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According to Bettignies & Brander (2007) from 2005 until 2006 venture capital firms funded only 10% of start-ups in Europe. The involvement in management activities of start-ups is one of the factors that withholds European entrepreneurs from engaging with capital venture firms. Since Manigart & Struyf (1997) state that entrepreneurs fear of losing their independence.

Hellmann & Puri (2002), who performed a research among 170 Silicon Valley based start-up in the time-span 1991-2001, state that the use of owner funds or funds from family, friends and fools in really small companies is profitable for start-ups New ventures that use more own funds, more interim personnel, more subsidy finance and decrease the days of sales outstanding, also exhibit 13.5% higher growth in value added in the first years compared to venture capital financing. This will have a positive effect on company efficiency since the number of employees will not increase significant and assets will increase.

According to Stearns, Carter, Reynolds and Williams (1995) the number of employees experience an average increase of 151% during the first year of capital investment. The engagement of the capital venture firm obligates the management of the company to invest the available resources in R&D and in the future growth preparation. The significant growth in number of employees is part of this preparation for future growth. This will therefore decrease the efficiency ratio2 compared to the first year significantly, since entrepreneurs start with interns and try to save as much possible on human resources in the first year (Stearns, Carter, Reynolds & Williams, 1995).

Levenson & Willard (2000) state that the start-up factors as management skills, clarity of the business opportunity, the business model, the route to market and the governance arrangements are not ready for investment. This means that they are insufficiently defined or prepared to efficiently use the invested resources. When in this stage the capital investment firm does invest, even though the company is not ready for this investment, the investment will be necessary for funding the preparation of growth. This way in the first years the effect of assets and sales growth will be minimum. Since efficiency is affected by assets, this will have a negative effect on efficiency (Levenson & Willard, 2000).

Banks lack experience and methods to value the tech companies (Wang & Zhou, 2002). The financial resources then have to come from capital venture firms. According to

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Lofstrom, Scherr, Sugrue & Ward (1993) it appears, moreover, that the capital venture backed companies have an average 26% higher growth of sales in the first 4 years. These higher sales will benefit the assets growth; which leads to a positive effect on efficiency.

Venture capital firms exchange their financial resources for a percentage of equity (Faulklender and Petersen, 2004). Due to this investment, assets will rise, this has a positive effect on efficiency since the acquired cash/asset will be an asset with no payback obligation. Davila et al. (2003) concluded a significant effect of venture capital investment presence on growth of assets. According to Davila et al. (2003) this effect comes from the staged financing of capital venture firms. The results indicate an average 17% increase of growth pace when start-ups receive their first stage of following stage funds. This increase leads to a positive effect on efficiency since the growth pace of assets increases. A well-known term that capital venture firms contribute to the start-ups is monitoring.

2.2. Monitoring

Venture capital firms receive a stake in the firm in exchange for their capital investment, they will have the right, just like other investors, to influence decisions regarding company activities. According to Gompers (1995), who performed a research of a random sample of 794 firms that received venture capital financing between January 1961 and July 1992, they have more control over potential moral hazards3 this way.

Engaging with stakeholders will bring a completely new view into the company and will benefit efficiency; if the founders would like to invest in a project that is profitable for them on a private level they might continue the project, even if this project might not be profitable for the company. Venture capitalists will prevent these projects and will only engage in projects which will be for the sake of the company (Bertoni, Croce & D’Adda, 2010). Prevention of these projects will have a positive effect on efficiency since the investments done by the start-up will be focussed on investments that are profitable for the company. All tough the venture capitalists will engage in the management team; the probability of moral hazards will never be zero. Therefore, they invest in stages to prevent persuasive moral hazards and will always maintain the option to quit (Bertoni, Croce &

3_{When one party knows that it is protected against the risk when involving in a risky event and the other party}

will incur the cost. Moral hazard arises when both parties have incomplete information about each other. In this case the founding start-up management might have incomplete information about future investments and therefore potential dangers of these investment.

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D’Adda, 2010). Staged financing allows capital venture firms to monitor projects, if these projects might turn out to be non-profitable the capital venture firm can decide not to perform any future investments. This staged financing helps capital venture firms limit their losses in projects that seemed profitable in the beginning, but not-profitable in the years after the first investment. With non-staged financing, the complete investment is performed in advance and therefore in case of non-profitable projects, these investments are seen as sunk costs (Bertoni, Croce & D’Adda, 2010). The higher the risk in the project, the higher the value this option has to venture capitalists. This option to quit is similar to debt, in that it limits potential financial losses (Wang & Zhou, 2002). Concluding, the project monitoring of venture capital firms and their expertise and knowledge will lead to more profitable projects and limited moral hazards. Therefore, according to Gompers (1995), the effect of monitoring on efficiency will be positive.

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3.0. RESEARCH METHOD

3.1. Regression

This study attempts to examine the effect of venture capital injections on efficiency of Benelux based tech start-ups. To examine the effect on efficiency the following panel data regressions are formed and tested:

𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑖𝑖𝑖𝑖 = 𝐶𝐶𝐶𝐶𝐸𝐸𝐶𝐶𝐶𝐶𝐶𝐶𝐸𝐸𝐶𝐶𝑖𝑖+ 𝛽𝛽1∗ 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐸𝐸𝐸𝐸𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖+ 𝛽𝛽2∗ 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐸𝐸𝐸𝐸𝐶𝐶𝐸𝐸𝐸𝐸𝐶𝐶𝐶𝐶𝐸𝐸𝑖𝑖𝑖𝑖 + 𝛽𝛽3 ∗ 𝐶𝐶𝐶𝐶𝐸𝐸𝑎𝑎𝑎𝑎𝐸𝐸𝑎𝑎𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖+ 𝛽𝛽4∗ 𝐶𝐶𝐶𝐶𝐸𝐸𝑎𝑎𝑎𝑎𝐸𝐸𝑎𝑎𝐶𝐶𝐸𝐸𝐸𝐸𝐶𝐶𝐶𝐶𝐸𝐸𝑖𝑖𝑖𝑖+ 𝛽𝛽6∗ AgeOfFirmVC𝑖𝑖𝑖𝑖 + 𝛽𝛽7 ∗ AgeOfFirmBInj 𝑖𝑖𝑖𝑖 + 𝛽𝛽8∗ FinancialCentreDummy + 𝜀𝜀𝑖𝑖𝑖𝑖

Where i and t refer respectively to the company observed and to the year at which it is observed.

3.2. Dependent variable

The dependent variable efficiency that is used in both the regressions consists of the following:

𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝑖𝑖𝑖𝑖 = _{𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝑁𝐸𝐸𝐶𝐶 𝐶𝐶𝐸𝐸 𝐸𝐸𝑁𝑁𝐶𝐶𝑇𝑇𝐶𝐶𝐸𝐸𝐸𝐸𝐸𝐸𝐶𝐶}𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑇𝑇 𝐶𝐶𝐶𝐶𝐶𝐶𝐸𝐸𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖 𝑖𝑖𝑖𝑖

According to Chemmaunur, Krishan & Nandy (2011) company financials are hard to find or inaccurate. Number of employees and total assets tend to be accurate. Therefore, this ratio efficiency is chosen to test on the most accurate numbers.

3.3. Other variables

The explanatory variable CapVenToT is the dummy variable that consists of the first years after a capital investment. This varies per company from 2 years until 6 years. In the second regression that is performed this dummy is separated into the initial investment years, the 5 years after the investment separated and the variable for more than 5 years after the investment. CapVenBefore is the dummy variable that contains the first years before the

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venture capital investment, varying from 1 to 3 years

The variables BankInjTot is the dummy variable that consists of the year of investment and the first years after the bank capital injection. In the second regression that is performed this dummy is separated into the initial investment years, the 5 years after the investment separated and the variable for more than 5 years after the injection. BankInjBefore is the dummy variable that contains the first years before the venture capital investment, varying from 1 to 3 years.

The dummy variable NoCapitalInj for no injection is added to the regression to control for firms that received no external bank or venture funding. This variable is however left out to prevent the effect of over qualification.

The AgeOfFirmVC is added to control for the age of the firm since the capital venture investment. AgeOfFirmBiInj is added to control for the age of the firm since the bank capital injection. Stearns, Carter, Reynolds & Williams (1995) state that the older the start-up, the better the start-ups are prepared for future growth and investments.

The FinancialCentreDummy consists of the fact whether the start-ups are based in financial centres. According to Gompers (1994) the effect of being based in a financial centre will be positive since the better availability of capital and human resources.

3.4. Assumptions

Before performing the panel data regression, assumptions have to be made:

Linearity has to be assumed; the model is linear in parameters constant, 𝛽𝛽, and error term 𝜀𝜀. Independence has to be assumed; the dependent variable, parameters and other variables have to be independent and identically distributed. The observations are independent across companies but not necessarily across time. This guaranteed by random sampling of companies.

Strict exogeneity is another assumption that has to be made; E[uit|Xi , zi , ci ]= 0 which means that the mean is independent. The error term is assumed to be uncorrelated with the explanatory variable of all past, current and future time periods of the same company (Baltagi, Song & Koh, 2003)

Since the regression is a panel data with random effect since variation across start-ups is assumed to be random and uncorrelated with the variables of other start-ups, extra assumptions regarding the random effects have to be made. The company specific effect is a

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random variable that is uncorrelated with the explanatory variables of all, past and current years of the same company (Baltagi, Song & Koh, 2003)

4.0. DATA AND RESEARCH METHOD

4.1. Data

The Thomson One database is used to find start-ups that are founded after 2000 are selected to form a recent view of this study. Only tech start-ups based in the Benelux are selected that are capital venture backed, bank funded or received no capital injections. In the end there are 43 tech start-ups used in this study, with a distribution of 18 capital venture backed, 15 bank funded and 8 with no capital injections with a total of 372 observations.

Company financials are collected to form the final formation of the dataset. This data comes from the WRDS database. The WRDS data consist of the end of year financial reports. All the possible years are used with starting year 2000 until 2015.

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4.2. Descriptive data

Table 1 shows the descriptive statistics of the used dataset. The table shows the mean, standard deviation per form of the used capital investment and the totals.

Table 1: Descriptive statistics

Graph displays the average efficiency per year. From the graph there can be seen that the venture capital backed company efficiency decrease strongly in the first year compared to bank capital or no injection.

Graph 1: Efficiency averages per year

VC Bank Other Total

Mean Std.Dev Mean Std.Dev Mean Std.Dev Mean Std.Dev Efficiency € 38.524,14 € 1.292.920,41 € 46.156,81 € 240.505,75 € 32.651,23 € 121.451,36 € 106.262,47 € 569.652,59 Total assets € 748.228,59 € 4.708.602,65 € 452.225,45 € 2.464.256,43 € 281.264,89 € 1.256.123,11 € 160.350,39 € 949.110,85 number of employees 32,06 56,88 10,22 19,20 9,31 25,25 27,96 40,96

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5.0. RESULTS

5.1. Total effect of capital investments

To test whether capital venture effects have a significant on company efficiency, the first panel data regression is performed.

Efficiency Efficiency Efficiency Efficiency Efficiency

CapVenTot -16,92* _(10.21) -19,54* _(11.21) -26,06** _(12.54) -27,56* _(15.44) -32.73* _(15.74) CapVenBefore _(12.84)-7,30 _(13.76)-13,02 _(13.80)-12,79 -11,87 (13.74) BankInjTot _(15.68)-16,9 _(24.25)-23,89 -33,13 (25.47) BankInjBefore _(32.78)-18,06 _(33.28)-19,89 -17,34 (33.13) Ageoffirmsincecv _(3.33)0,70 _(3.85)1,00 Agesincebankinj _(6.98)2,47 _(6.94)2,55 Financialcentredummy 24,60 (11.18) Constant 22,12*** _(6.15) 24,80*** _(7.68) 31,31*** _(9.52) 31,17*** _(95.51) 24,63** _(9.72) R-squared 0,0074 0,0082 0,0119 0,0123 0,106 N 372 372 372 372 372

Table 2: Results first panel data regression. Significance levels: 10%=* 5%=** 1%=***

The first panel data regression shows a significant negative effect of capital venture effect on efficiency. With the assumed significance levels, the total years after the capital venture firm investment show a significant negative effect. Stearns, Carter, Reynolds & Williams (1995) argue that the number of employees make a relative high increase when venture capital is invested. Companies in their growth stage of their lifecycle, are investing in their preparation of future growth and R&D. The growth of employment will be the foundation of this preparation.

Additional to this, is the fact that start-ups are founded by a small group of people. When for example a start-up is founded by 2 entrepreneurs, they will make a 100% increase of their employees when hiring two more people. Assets however, never increase with the same percentage in the same time as the number of employees in the short run. Therefore, in

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the growth stage, the number of employees shows a much higher relative growth than the growth of assets. (Stearns, Carter, Reynolds & Williams,1995).

5.2. Capital investment effects per year

Burkart, Gromb and Panunzi (1997) state that during the growth stage of start-ups, the efficiency tends to change significant due to since the fast relative growth of employees and, if successful, the high relative growth of sales and assets. Therefore, the capital venture and banking injection needs to be explained for the years during and after the investment to test the effect of venture capital on the years after the initial capital injection. Dummy variables for the years during and after are used instead of the total capital injections dummy. This regression provides the following results:

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Table 3: Results first panel data regression. Significance levels: 10%=* 5%=** 1%=***

According to the results of the second regression, efficiency is only significant negatively affected by capital investment in the actual funding year. This is in line with the conclusions of Stearns, Carter, Reynolds and Williams (1995) since they state that the relatively high increase of employees is relatively much higher than the growth of assets in start-ups in the first year. The investments values invested in the start-ups used in this dataset, are relatively small to medium ,compared to bigger companies.

According to Levenson & Willard (2000) the effect venture capital venture investment on assets and sales growth will be minimum in the first years. This is based on the fact that these companies are still in the growth stage and will use these investments to prepare their company for future growth and invest in R&D. The negative coefficients of

Efficiency 1 2 3 4 5 -13.22 -13.13 -20.67 -25.79 -30.98 (17.31) (17.59) (18.33) (19.27) (19.59) 0.38 7.15 -11.41 -13.23 (11.91) (12.91) (13.90) (13.93) -18.69 -23.52 -28.99 (18.42) (19.27) (25.52) -18.01 -21.39 -26.98 (20.44) (21.22) (26.22) -17.96 -21.01 -26.33 (23.23) (24.05) (28.13) -17.03 -20.55 -25.97 (28.64) (29.39) (31.95) -16.99 -20.51 -25.58 (31.18) (31.91) (33.47) -16.38 -19.28 -24.85 (39.76) (40.47) (41.55) -17.39 -14.61 (33.40) (33.93) -9.07 -10.73 (23.32) (32.56) -19.29 -25.21 (29.13) (35.03) -17.49 -22.31 (33.17) (37.76) -18.49 -24.54 (35.49) (39.16) -18.74 -28.48 (40.17) (44.20) 8.00 20.53 (49.17) (72.81) 37.61 -27.85 (68.80) (41.55) 0.15 (50.16) 0.03 (78.16) 22.05 (11.23) 17.21*** 17.11** 24.65*** 29.78*** 24.70** (5.16) (5.96) (7.70) (9.48) (9.79) R-squared 0.0016 0.0016 0.0082 0.0133 0.0239 N 372 372 372 372 372 BankInj5p AgeOfFirmSinceVC FinancialcentreDummy Constant CapVenYbefore CapVenY1 CapVenY2 CapVenY3 CapVenY4 CapVenY5 CapVenY5p BankInjBefore BankInj0 AgeOfFirmSinceBankinj BankInj1 BankInj2 BankInj3 BankInj4 BankInj5 CapVenY0

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efficiency are therefore in line with the conclusions of Levenson & Willard (2000).

However, panel data compares the efficiency per year with the first year of the company. Even though the capital venture coefficients have a negative effect on efficiency, the negative influence of the coefficients is decreasing after the first year of investment. The negative influence of the coefficients is shown in graph 1. The graph shows that in the first year the negative influence compared to the first year decreased with 327000 euro’s. In the fifth year the efficiency decreased with 255800 euros. From these results, a positive increase of efficiency can be concluded after the first year. This is in line with the findings of Stearns, Carter, Reynolds and Williams (1995), since they state that the average of 151% increase of number of employees in the first year has a negative influence on the efficiency.

Graph 2: negative coefficients of capital venture firms on efficiency

6.0. CONCLUSION

Using a sample of 43 tech start-ups based in the BeNeLux over the period 2000-2015, this thesis examines the effect of capital venture investment on company efficiency with a panel data regression. The results provided an answer to the research question “What is the effect of capital venture investment on the efficiency of tech start-ups based in the Benelux?”.

Based on the results, it can be concluded that venture capital investments do show negative influence on company efficiency. The total effect of capital investment showed a negative significant effect on the efficiency of the start-ups.

When testing the years of capital investment separately, only the first year of investment showed a negative significant effect. The following years even showed a growth

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pattern since the negative influence of these coefficients was decreasing by year.

According to Wang & Zhou (2002) capital venture firms invest in stages. Since in this thesis only first-time investments are used, further research should test the possible influence of staged financing. The influence of the height of the investment leaves room open for further research as well. Since the height of the investment is not taken into account in this thesis.

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7.0. LITERATURE

- Alperovych, Y. et al. 2015. How does governmental versus private venture capital backing affect firm’s efficiency?. Journal of Business Venturing 30, 508 –525

- Bergemann, Dirk & Hege, Ulrich (1998), Venture capital financing, moral hazard and learning, journal of banking &finance, Volume 22, Issues 6–8, August 1998, Pages 703–735

- Bertoni, F., Croce, A., & D’Adda, A., (2010) Venture capital investments and patenting activity of high-tech start-ups: a micro- econometric firm-level analysis. Vol. 12, venture capital, No. 4, October, 307–326

- Bettignies,J., & Brander, A., Financing entrepreneurship: Bank finance versus venture capital, Journal of Business Venturing, Volume 22, Issue 6, November 2007, Pages 808-832, ISSN 0883-9026,

- Bottazzi, L., & Da Rin, M., Venture Capital in Europe and the Financing of Innovative Companies. Economic Policy, Vol. 17, pp. 229-269, 2002.

- Davila, A., Foster, G., & Gupta, M., (2003), Venture capital financing and the growth of startup firms, Journal of Business Venturing, 18, issue 6, p. 689-708

- Faulkender, M., & Petersen, M., (2004), Does the source of capital affect capital structure?, CSIO working paper, No. 0054

- Gompers, P., (1995), Optimal investment, monitoring and the staging of venture capital. The Journal of Finance Vol. 50, No. 5 (Dec., 1995), pp. 1461-1489

- Hellmann, T. and Puri, M. (2002), Venture Capital and the Professionalization of Start-Up Firms: Empirical Evidence. The Journal of Finance, 57: 169–197.

- Hölmstrom, Bengt. "Moral Hazard and Observability." The Bell Journal of Economics 10.1 (1979): 74-91. Web.

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- Keuschnigg, C. & Nielsen, S., (2004), Start-ups venture capitalists, and the capital gains tax. Journal of Public Economics. 88, 1011–1042.

- Levenson, R. & Willard, K., (2000), Do Firms Get the Financing They Want? Measuring Credit Rationing Experienced by Small Business in the U.S. issue 2, p. 83-94.

- Manigart, Sophie and Struyf, Carol, (1997), Financing High Technology Startups in Belgium: An Explorative Study, Small Business Economics, 9, issue 2, p. 125-35.

- Moore, J., (1994), a theory of debt based on the inalienability of human capital, national bureau of economic research, no 3906

- Rahim, H. & Bakar, S., (2014), The impact of financial resources management on SME performance, International journal of humanities and social science, vol 4 no 9

- Reynolds, P., Williams, M., Stearns, T. & Carter, N., (1995). New Firm Survival: Industry, Strategy, and Location, Journal of Business Venturing, Vol. 10, Issue 1, p. 23-42 1995.

- Scherr, F., Sugrue, T., & Ward, J., (1993) Financing the Small FirmStart-Up: Determinants of Debt Use, Journal of Small Business Finance: Vol. 3: Iss. 1, pp. 17-36.

- Thrift, N., & Andrew Leyshon, A., A phantom state? The de-traditionalization of money, the international financial system and international financial centres, Political Geography, Volume 13, Issue 4, 1994, Pages 299-327, ISSN 0962-6298.

- Wang, S. & Zhou, H, (2004), staged financing in venture captal:more hazard and risks, journal of corporate finance, 10, issue 1, p. 131-155.

The effect of Capital Venture Investments on tech start-up efficiency in the Benelux