Table 19

Diff-in-diff robustness check: effect of equity and contractual agreements with banks on FinTechs' Size, implemented as an alternative measure of website traffic. Estimations for the time window (−4, 4)

Time intervals−4 to 0−4 to 1−4 to 2−4 to 3−4 to 4
Panel A – Dependent variable: size
Post*Bank_Equity0.338***0.291***0.300***0.320***0.315***
(0.109)(0.108)(0.108)(0.112)(0.114)
Post*Age−0.102***−0.094***−0.094***−0.100***−0.102***
(0.020)(0.022)(0.021)(0.022)(0.023)
Firm fixed effectsYesYesYesYesYes
Year fixed effectsYesYesYesYesYes
N° observations257326378416442
R20.0970.0900.0940.0920.081
F-stat9.268***11.833***14.922***16.602***15.469***
Panel B – Dependent variable: size
Post*Bank_Partner0.1500.1640.2040.2070.228
(0.106)(0.129)(0.140)(0.141)(0.145)
Post*Age−0.036**−0.040**−0.042**−0.044**−0.046**
(0.018)(0.018)(0.019)(0.020)(0.021)
Firm fixed effectsYesYesYesYesYes
Year fixed effectsYesYesYesYesYes
N° observations367447502534558
R20.0280.0330.0370.0350.037
F-stat3.711**5.735***7.502***7.642***8.397***

Note(s): The coefficient of the interactions Post*Bank_Equity and Post*Bank_Partner (β3) measures, respectively, the effect of equity agreements and contractual with banks on the Size of treated FinTech firms compared to control units and can only be estimated when considering also post-treatment periods. All the specifications include firm fixed effects, time fixed effects and the interaction Post*Age. The columns show the results of separate panel regressions for each time interval, with the dummy Post equal to 1 in the years when we want to evaluate the effect of strategic alliances with banks and 0 in pre-treatment period (−4, −1). Standard errors are clustered at firm level. Significance levels: *, **, *** for 10%, 5% and 1%, respectively

Source(s): Table was created by the authors

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