Table 9 Diff-in-diff baseline results:...

Table 9

Diff-in-diff baseline results: effect of contractual agreements with banks on FinTechs' website traffic (Model 2b) for different time intervals

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_Partner	0.054	0.125	0.228	0.210	0.232
Post*Bank_Partner	(0.099)	(0.124)	(0.175)	(0.149)	(0.155)
Post*Age	−0.034	−0.051	−0.062	−0.063	−0.065
Post*Age	(0.036)	(0.037)	(0.041)	(0.041)	(0.041)
Firm fixed effects	Yes	Yes	Yes	Yes	Yes
Year fixed effects	Yes	Yes	Yes	Yes	Yes
N° observations	367	447	502	534	558
R2	0.011	0.024	0.036	0.028	0.025
F-stat	1.138	3.596**	6.348***	5.294***	5.144***
Treated pre-treatment average (*): 11.671
Control pre-treatment average (*): 4.080
Panel B – Dependent variable: G_Trends_Growth
Post*Bank_Partner	−0.004	0.015	0.062	0.031	0.038
Post*Bank_Partner	(0.027)	(0.042)	(0.075)	(0.091)	(0.123)
Post*Age	−0.011	−0.018	−0.023	−0.023	−0.024
Post*Age	(0.010)	(0.012)	(0.015)	(0.014)	(0.015)
Firm fixed effects	Yes	Yes	Yes	Yes	Yes
Year fixed effects	Yes	Yes	Yes	Yes	Yes
N° observations	367	447	502	534	558
R2	0.007	0.023	0.026	0.006	0.004
F-stat	0.954	2.788*	4.589**	1.048	0.819
Treated pre-treatment average (*): 2.974
Control pre-treatment average (*): 1.888

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_Partner	0.054	0.125	0.228	0.210	0.232
Post*Bank_Partner	(0.099)	(0.124)	(0.175)	(0.149)	(0.155)
Post*Age	−0.034	−0.051	−0.062	−0.063	−0.065
Post*Age	(0.036)	(0.037)	(0.041)	(0.041)	(0.041)
Firm fixed effects	Yes	Yes	Yes	Yes	Yes
Year fixed effects	Yes	Yes	Yes	Yes	Yes
N° observations	367	447	502	534	558
R2	0.011	0.024	0.036	0.028	0.025
F-stat	1.138	3.596**	6.348***	5.294***	5.144***
Treated pre-treatment average (*): 11.671
Control pre-treatment average (*): 4.080
Panel B – Dependent variable: G_Trends_Growth
Post*Bank_Partner	−0.004	0.015	0.062	0.031	0.038
Post*Bank_Partner	(0.027)	(0.042)	(0.075)	(0.091)	(0.123)
Post*Age	−0.011	−0.018	−0.023	−0.023	−0.024
Post*Age	(0.010)	(0.012)	(0.015)	(0.014)	(0.015)
Firm fixed effects	Yes	Yes	Yes	Yes	Yes
Year fixed effects	Yes	Yes	Yes	Yes	Yes
N° observations	367	447	502	534	558
R2	0.007	0.023	0.026	0.006	0.004
F-stat	0.954	2.788*	4.589**	1.048	0.819
Treated pre-treatment average (*): 2.974
Control pre-treatment average (*): 1.888

Note(s): 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

(*) Pre-treatment average of the dependent variable for treated and control FinTech firms

Source(s): Table was created by the authors

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