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Table 7 Impact of Dodd-Frank Act on aggregate alternative P2P lending

From: Regulatory constraint and small business lending: do innovative peer-to-peer lenders have an advantage?

 

(1)

(2)

(3)

 

P2PSBL

P2PSBL

P2PSBL

Treated*DFA

0.674***

0.678***

0.863***

 

(30.179)

(29.373)

(24.741)

Population

0.016

0.027*

0.027*

 

(1.379)

(1.901)

(1.961)

Income

− 0.385***

− 0.470***

− 0.456***

 

(− 5.265)

(− 5.660)

(− 5.515)

Unemployment

0.028***

0.043***

0.043***

 

(5.068)

(6.743)

(6.770)

C3

− 0.003

− 0.004

− 0.004

 

(− 1.324)

(− 1.454)

(− 1.225)

HHI

0.160**

0.166**

0.151*

 

(2.316)

(2.044)

(1.849)

BRNUM

0.006

0.005

0.007

 

(0.423)

(0.278)

(0.381)

DebtoIncome

0.046**

0.067***

0.070***

 

(2.591)

(3.051)

(3.218)

Domdep

0.011***

0.013***

0.013***

 

(2.996)

(3.089)

(3.105)

County FE

 

Yes

Yes

Year FE

  

Yes

Obs

3555

3555

3555

Adj. R2

0.189

0.175

0.191

  1. Table 7 shows the difference-in-differences estimation results in Eq. (3). The dependant variable P2PSBL is the small business loan origination volume of alternative lenders in counties. The variable Treated takes on the value 1 for the treated counties where there is a bank with $10 billion assets or over and affected by Dodd-Frank Act and there is low competition according to the C3 and HHI, which are in the top 75th. If the county has a bank asset below $10 billion exempts from the Dodd-Frank Act and there is high competition in the bottom 25th, it is defined as a control county and takes the value of 0. Counties other than the 75th and 25th percentile are not included in the model. DFA is the treatment dummy that takes the one from July 2010 onwards and zero prior to that date. Standard errors are clustered at the county level and shown in parentheses. Statistical significance at the 10%, 5% and 1% levels is denoted by*,** and ***, respectively.t-statistics are presented in parentheses