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

5.3 The determinants of venture capital financing
Table 4 presents the results obtained estimating equation (1). In column (a) attention is
confined to the variables with the coefficients from β1 to β8 (controlling for geographical area
and time dummies). This is done in order to maximize the number of observations on which
estimation is performed; in fact, employing variables such as Capex and Growth would imply a
loss of observations given that they are calculated over year t‐1.
Consistently with the theories of asymmetric information, the signs of Size and Age turn out
to be negative; the existence of a non‐linear relation between the probability of receiving
external capital and size also emerges. In the same direction goes the positive sign and the
statistical significance of the variable Intangibles. Forthcoming considerations will conclude on
the intuition by which banks are more keen on granting credit to firms with higher liquidation
value of assets. In terms of profitability Ebitda appears to be an important determinant; we can
anticipate here that its sign and its magnitude will be constant in all the different specifications
of the model. Provided that Ebitda is a measure widely used in the financial industry for the
assessment of the value of a company, e.g. the “multiples approach”, thus, this result can be
considered coherent with the state of art in use. Conversely, investors seem not to rely much
on the figures for ROE and see other variables as important factors for predicting the future
performances of a firm. Looking at the negative sign we can assume that the internal finance is
not sufficient and is curbing firm’s investment decisions, hence its growth opportunities. In this
way, we would strengthen the theory of Carpenter and Petersen (2002a). Finally, the negative
sign of Leverage backs the intuition that predicts a higher demand for venture capital finance
by firms which encounter more difficulties in accessing debt financing.
We check the robustness of these results in various ways. We re‐estimated specification (a)
using different lags of the variables. In particular, if the variables are entered with a lag of one
year (results not reported), the basic results are confirmed, with the exception of Size and
Leverage which become not significant.
Column (b) of the table reports the results obtained estimating the richer model for the
whole set of variables reported in equation (1). In particular we introduce Capex and Growth to
measure the expansion of the firm and Short Debt to capture the access to credit. Results
confirm that firms that are younger, smaller and have a higher share of intangibles assets in
their balance sheet are more likely to be financed. Leverage is still significant though at 10% of
significance, the dummy High‐Tech and Roe are still not significant. As regards the adding
variables of specification (b), we find contrasting evidence between the two determinants
chosen to proxy for firm expansion: while Capex is positive and not significant, Growth is
positive but significant. On this basis it is possible to argue that the firms that have as their
most valuable asset their knowledge are more likely to be financed by venture capitalists.
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