Table A3

Regression results, robustness tests on subsamples excluding the most frequent country and the sectors

RegressorModel 1Model 2Model 3Model 4Model 5Model 6
Excl. UK firmsExcl. Internet and Software, Mobile
famDum0.203**  −0.186  
(0.088)  (0.144)  
cumulFamNbr 0.122**0.094 −0.0980.076
 (0.049)(0.070) (0.099)(0.368)
Complexity measures
inventorsNbr  0.000  −0.062
  (0.046)  (0.119)
techScope  −0.139  0.216
  (0.089)  (0.247)
bwdPatCitNbr  −0.014**  −0.010
  (0.006)  (0.024)
bwdPubCitsPerc  −0.160  −0.537
  (0.409)  (1.053)
Quality measures
assigneesNbr  0.194**  0.749*
  (0.089)  (0.431)
geoScope  0.036  0.169
  (0.030)  (0.139)
weiFwdCitsNbr  0.205***  −0.104
  (0.065)  (0.183)
Controls
pastFinAmt0.008***0.007***0.010***0.012***0.012***0.065***
(0.003)(0.003)(0.002)(0.004)(0.004)(0.024)
firmAgeAtDeal0.0050.004−0.0160.0080.009−0.040
(0.014)(0.014)(0.020)(0.032)(0.032)(0.080)
Time, sector, geo dummiesYesYesYesYesYesYes
Round dummiesYesYesYesYesYesYes
Constant−10.893−11.18841.544−161.386**−161.972**−74.889
(33.803)(33.818)(44.588)(69.581)(70.428)(246.990)
Observations1,2861,28645827627661
R-squared0.5020.5030.4520.6340.6330.691
Adjusted R-squared0.4910.4920.4120.6060.6050.513

Note(s): The dependent variable is the logarithm of the financed amount. Robust standard errors are shown in parentheses. Models 1 to 3 analyze the subsample that exclude the most frequent country (United Kingdom). Models 4 to 6 focus on the sub-sample of low appropriability sectors and exclude the two most frequent sectors (“Internet”, “Software and Mobile”). The significance levels are represented by ∗∗∗ as 1%, ∗∗ as 5%, and ∗ as 10%

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