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

debt 8 . A negative sign, in particular coupled with an increase of debt, would give clear evidence
of better conditions applied to backed firms, in turns allowing for the presence of the
certification effect.
4.3 The econometric set‐up
In order to test the hypothesis outlined we rely on econometric techniques applicable to
panel data, allowing us: (1) to control for unobservable individual heterogeneity; (2) to use a
large amount of information, including many companies and several years for each company,
thus increasing the degrees of freedom and reducing colinearity between the explanatory
variables; (3) to analyse the evolution over time of the variables in a group of companies.
A logarithmic transformation has been applied to most of the variables. Applying this
procedure we obtain beneficial effects such as: steadying the variance, reducing multiplicative
effects into additive ones and normalizing the distributions. Since the transformation it is not
feasible when there are null and negative values we first add 100 to each value and then
calculate their logarithms. In particular, this was the case for variables obtained as variation
between two subsequent periods such as Growth, Capex and ROE.
4.3.1 Econometric set‐up for the determinants
In this section we present a multivariate analysis to test Hypothesis 1 which will allow us to
quantify the importance of the different determinants for the financing through Venture
Capitalists and Private Equity funds.
Based on the theoretical predictions on the variables that should affect the likelihood of an
external funding, we estimate various versions of the following probit model:
Pr(Backedi,t=1)= F(β1Agei, t‐1 + β2Sizei,t‐1 + β3Size 2 i,t‐1 + β4Intangibles i,t‐1 + β5Ebitdai,t‐1 +
β6ROEi,t‐1 + β7Leveragei,t‐1 + β8High‐Techi,t‐1 +β 9Capexi,t‐1 +
β10Growthi,t‐1 + β11Short Debti.t‐1 + κiArea +ηiYear)
The multivariate Probit model uses Backed as a discrete variable representing a choice from a
set of mutually exclusive choices: it equals 1 when firms are backed, 0 otherwise. Yet to be
described are controls Area and Year. The former focuses on geographical characteristics that
may be involved in the investment decision. The firms are divided into three groups according
to the location of their registered offices: north, centre and south are the different macro‐
regions identified. This strategy joins the procedure for the selection of the control group
8
The cost of debt calculated in this way will underestimate the real one since the scaling variables (total debt)
include items that are not interest bearing.
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