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Table 10 Provincial-level analysis: fintech and financial access. Criterion (\({FD}_{(A)}\))

From: Fintech, regtech, and financial development: evidence from China

Variables

Model A

Model B

FE

IV-2SLS

FE

IV-2SLS

Fintechj,t-1

0.129***

(0.004)

0.219***

(0.000)

0.137**

(0.020)

0.704***

(0.005)

Finregj,t-1

  

0.034

(0.202)

0.219***

(0.009)

Fintechj,t-1 × Finregj,t-1

  

-0.001

(0.790)

-0.050**

(0.022)

\(G\) DPgrj,t-1

− 0.003

(0.772)

0.014

(0.109)

0.0003

(0.978)

0.023*

(0.084)

TOPj,t-1

− 0.757***

(0.000)

− 0.651***

(0.000)

− 0.683***

(0.000)

− 0.883***

(0.000)

INDj,t-1

0.0002

(0.979)

− 0.003

(0.381)

− 0.003

(0.691)

− 0.016**

(0.030)

Urbj,t-1

0.068***

(0.000)

0.050***

(0.000)

0.065***

(0.000)

0.0517***

(0.000)

City FE

    

Year FE

    

Observations

248

248

248

248

F Statistic

131.40***

295.37***

105.42***

147.63***

R2

0.887

0.873

0.891

0.819

  1. P values are shown in parentheses. Clustered standard errors at the provincial level are reported. R-square (within) is reported for FE and centered for IV-2SLS
  2. ***, **, and *, significance at the 1%, 5%, and 10% levels, respectively