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Financial Innovation

Table 10 Regression results from a probit model identifying the factors that influence borrowing from formal sources

From: Financial decision-making behaviors of Ethnic Tibetan Households based on mental accounting

Variable

Coeff.

Marginal effects

Credit village

0.056

0.018

 

(0.312)

(0.100)

Temple

− 0.005

− 0.002

 

(0.120)

(0.038)

Telecom

0.857

0.275

 

(0.590)

(0.185)

Certificate

0.804***

0.258***

 

(0.287)

(0.082)

Poverty

0.584***

0.187***

 

(0.212)

(0.064)

Religion

− 0.397***

− 0.127***

 

(0.110)

(0.032)

Association

1.188*

0.381*

 

(0.613)

(0.195)

Str income

− 0.200

− 0.064

 

(0.357)

(0.115)

Dowry

0.054**

0.017**

 

(0.022)

(0.007)

Age

− 0.009

− 0.003

 

(0.009)

(0.003)

Gender

− 0.471**

− 0.151**

 

(0.233)

(0.075)

Married

0.147

0.047

 

(0.161)

(0.051)

Health

0.103

0.033

 

(0.104)

(0.033)

Edu

− 0.011

− 0.004

 

(0.079)

(0.025)

  1. Probit estimates (log-likelihood =  − 152.00, Wald chi2 = 49.93, and prob. > chi2 = 0.00). The dependent variable is the availability of bank loans (1—acquired, 0—not acquired). It's worth noting that among the independent variables, str income means the proportion of agricultural income in total household income. Standard errors in parentheses are obtained by village clustering
  2. *, ** and *** represent significant at 10%, 5% and 1% level, respectively
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