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Table 15 Alternative estimation method: GMM

From: Entrepreneurial, institutional and financial strategies for FinTech profitability

Variables

Profitable

ROA

Size

11.15***

3.432***

 

(3.296)

(1.298)

Asset structure

1.001***

0.0307**

 

(0.220)

(0.0144)

Liquidity

− 0.000132

− 8.27e−06

 

(0.000461)

(1.44e−05)

Solvency

0.00131***

0.000437***

 

(0.000432)

(0.000106)

Leverage

0.000108***

− 1.37e−07*

 

(3.91e−05)

(8.24e−08)

Efficiency

0.000398

0.000497***

 

(0.00134)

(0.000168)

Entrepreneur

− 1.244***

− 0.0309

 

(0.348)

(0.0256)

Number of partner founders

− 0.438***

− 0.0136*

 

(0.160)

(0.00789)

Single entrepreneur

0.172**

− 0.0177

 

(0.0831)

(0.0168)

Mobile app

0.302**

− 0.0203

 

(0.136)

(0.0148)

Digital tracking

0.00699***

− 0.000226

 

(0.00257)

(0.000244)

Digitally tracked regionally

− 0.0583

− 0.0233**

 

(0.167)

(0.0103)

Funding

− 0.316

− 0.0108

 

(0.205)

(0.0125)

Public subsidy

0.213

0.0208

 

(0.160)

(0.0159)

FinTech accelerator

0.509***

0.0270

 

(0.194)

(0.0331)

Bank investor

− 0.845

− 0.0305

 

(1.029)

(0.0255)

Tech cluster

− 0.461***

− 0.0253***

 

(0.147)

(0.00767)

Time trend

0.0247

− 0.000697

 

(0.0340)

(0.00179)

Observations

706

706

Number of FinTech

170

170

Year

Yes

Yes

Clustered standard errors

FinTech

FinTech

Hansen test

0.197

0.345

  1. Column 1 and 2 presents the coefficients and the clustered standard errors for the GMM estimation of FinTech profitability. In Column 1, the dependent variable is a binary variable that takes the value 1 if the FinTech company is profitable (return on assets is positive). In Column 2, the dependent variable is the FinTech return on assets. All variables are defined in Table 2. Standard errors are clustered at the FinTech-level. A constant term (not reported) is included in all regressions. *, **, *** Coefficients are statistically significant different than zero at least at 10%, 5%, and 1% levels