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Table 11 Regression results from a probit model identifying the factors that influence borrowing from informal sources

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

Variable

Coeff.

Marginal effects

Credit village

− 0.353

− 0.116

 

(0.320)

(0.102)

Temple

0.333**

0.110**

 

(0.163)

(0.052)

Telecom

1.937**

0.639**

 

(0.984)

(0.308)

Certificate

− 0.721**

− 0.238***

 

(0.299)

(0.092)

Poverty

− 0.253

− 0.083

 

(0.243)

(0.078)

Religion

− 0.013

− 0.004

 

(0.113)

(0.038)

Association

− 0.242

− 0.080

 

(0.541)

(0.178)

Str income

− 0.130

− 0.043

 

(0.421)

(0.138)

Dowry

− 0.032

− 0.011*

 

(0.020)

(0.006)

Age

− 0.024***

− 0.008***

 

(0.007)

(0.002)

Gender

0.451*

0.149**

 

(0.237)

(0.075)

Married

0.023

0.008

 

(0.165)

(0.054)

Health

0.066

0.022

 

(0.111)

(0.037)

Edu

− 0.180*

− 0.059*

 

(0.095)

(0.031)

  1. Probit estimates (log-likelihood =  − 152.75, Wald \({\chi }^{2}\) = 59.03, and prob. > \({\chi }^{2}\)  = 0.00). The dependent variable is whether a household borrowed from informal sources (1 = borrowed, 0 = did not borrow). 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. The two columns to the right stand for probit regressions coefficients and marginal effects, respectively
  2. *, ** and *** represent significant at 10%, 5% and 1% level, respectively