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Determinants and effects of Venture Capital and Private Equity ...

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described in section 4.1. Finally, Year includes the years when the deal took place <strong>and</strong> controls<br />

for specific common <strong>effects</strong>.<br />

4.3.2 The econometric set‐up for the <strong>effects</strong><br />

In this section we present the procedure adopted to analyze the performance – in terms <strong>of</strong><br />

various balance sheet indicators – <strong>of</strong> backed firms relative to the companies that did not<br />

receive this form <strong>of</strong> financing.<br />

For the main accounting <strong>and</strong> financial variables (denoted yi,t) we estimate the following<br />

fixed‐effect regression:<br />

yi,t = α +β1Deal0 + β2Deal13 + ut + dt + εi,t<br />

Where Deal0 is a dummy variable which takes value 1 in the year <strong>of</strong> the deal. It should be<br />

pointed out that if the firm is financed more than once in our sample period, the dummy takes<br />

value 1 more than once, specifically in the year <strong>of</strong> each operation. Deal 13 is a dummy equal to<br />

1 in the three years after the deals, which is considered the average holding period for the<br />

industry.<br />

Regarding the estimation method, there is a discussion as to whether the individual <strong>effects</strong><br />

should be treated as fixed or r<strong>and</strong>om variables. However, this is not an important distinction<br />

because we can always treat the individual <strong>effects</strong> as r<strong>and</strong>om variables without loss in<br />

generality (Wooldrige 2002). However, it is really important to determine whether or not these<br />

individual <strong>effects</strong> are correlated with the variables observed. To test for the existence <strong>of</strong> this<br />

correlation, the Hausman test (1978) is usually used. If this test does not reject the null<br />

hypothesis that the individual <strong>effects</strong> are not correlated with the explanatory variables, the<br />

most suitable estimation would then be the r<strong>and</strong>om‐<strong>effects</strong> model <strong>and</strong> the best estimator<br />

would be Balestra‐Nerlove’s (1966) generalised least squares estimator. If, on the contrary, the<br />

null hypothesis is rejected, the within groups ordinary least square estimator would then be the<br />

most suitable one. More intuitively, implementing a fixed effect regression allows us to control<br />

for firm‐specific characteristics that are time‐invariant but that could be correlated with the<br />

deals, such as industry or managerial quality.<br />

5. Methodology <strong>and</strong> data<br />

5.1 Methodology<br />

The key objective <strong>of</strong> the research is to outline a general framework for the investment deals<br />

realized by VCs <strong>and</strong> PE firms with respect to Italian SMEs. Being this our aim, foreigner investors<br />

operating in Italy are also included.<br />

- 19 -<br />

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