Table 16

Robustness check: controlling for the year of establishment (cohort) of contractual agreements

Time intervals−4 to 0−4 to 1−4 to 2−4 to 3−4 to 4
Panel A – Dependent variable: G_Trends
Post*Bank_Partner0.1510.1870.2840.2590.277***
(0.146)(0.130)(0.175)(0.158)(0.176)
Post*Age−0.040−0.054−0.065−0.063−0.066
(0.036)(0.038)(0.042)(0.042)(0.042)
Post*Year_Partner_AgrYesYesYesYesYes
Firm fixed effectsYesYesYesYesYes
Year fixed effectsYesYesYesYesYes
N° observations257326378416442
R20.0450.0510.0610.0580.050
F-stat1.2901.963**2.767***2.800***2.554***
Panel B – Dependent variable: G_Trends_Growth
Post*Bank_Partner0.0020.0130.0590.0170.016
(0.035)(0.042)(0.059)(0.091)(0.125)
Post*Age−0.012−0.019−0.023−0.018−0.017
(0.012)(0.013)(0.016)(0.015)(0.016)
Post*Year_Partner_AgrYesYesYesYesYes
Firm fixed effectsYesYesYesYesYes
Year fixed effectsYesYesYesYesYes
N° observations257326378416442
R20.0110.0270.0410.0310.035
F-stat0.3001.0011.809*1.4651.745*

Note(s): Robustness check controlling for the year of establishment of contractual agreements through the interaction Post*Cohort_Partner_Agr, where Cohort_Partner_Agr is a factor variable indicating the year of establishment of contractual agreements. The coefficient of the interaction Post*Bank_Partner (β3) measures the effect of contractual agreements with banks on the website traffic 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 to −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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