# **<u>Table 9 mechanism</u>**

|Approached HHs|(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|Panel A: OLS|Illiquid<br>dummy|Log (1+<br>Illiquid<br>asset)|Illiquid<br>asset / total<br>asset|Informal<br>dummy|Social_exp|Cooperation|
|Credit_cons|-0.053<sup>***</sup><br>(0.009)|-0.602<sup>***</sup><br>(0.105)|-0.038<sup>***</sup><br>(0.008)|0.327<sup>***</sup><br>(0.013)|0.001<sup>***</sup><br>(0.000)|0.052<sup>***</sup><br>(0.011)|
|county dummy|Yes|Yes|Yes|Yes|Yes|Yes|
|Other controls|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|16433|16330|15907|16433|15618|16433|
|R-sq<br>|0.106|0.114|0.115|0.214|0.103|0.0890|
|Panel B: 2SLS (2<sup>nd</sup>stage)|||||||
|Credit_cons|-0.685<sup>***</sup>|-7.755<sup>***</sup>|-0.588<sup>***</sup>|1.635<sup>***</sup>|0.010<sup>**</sup>|0.808<sup>***</sup>|
||(0.261)|(2.857)|(0.224)|(0.368)|(0.005)|(0.309)|
|County dummy|Yes|Yes|Yes|Yes|Yes|Yes|
|Ivs. Mills<br>|Yes|Yes|Yes|Yes|Yes|Yes|
|Other controls|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|15298|15210|14836|15298|14594|15298|
|Weak IV F. stat|14.10|13.55|13.57|14.10|13.01|14.10|
|Over Ident.(Hansen J)|0.888|0.713|1.387|0.169|4.112|0.0180|
|Hansen J. p-value|0.346|0.398|0.239|0.681|0.0426|0.893|

Note: This table discuss the potential mechanism of credit constraint and fraud victimization, we employ urban households that are approached by fraudsters as our sample. Two alternative mechanisms are discussed, personal discount rate and social network expansion. Column (1) – (3) discuss the potential mechanism from the perspective of discount rate, the explained variables are possession of illiquid account dummy, amount of illiquid account and the ratio of illiquid to proxy discount rate, respectively. In column (4), we use a dummy variable ( _informal dummy_ ) to indicate whether households have borrow money from informal source. The explained variable for column (5) is social activity intensity ( _Social_exp_ ), which is defined as the ratio of household expenditure in commute and telephone services over total consumption. In column (6), we use a dummy variable ( _Cooperation_ ) to indicate whether the households behave cooperatively during the interview. We estimate the models using OLS in panel A, while 2SLS in panel B. _Credit_cons_ is a dummy variable indicating whether household is credit constrained. _Lincome_ is the logarithm of the total sum of household income, which consists of labor income, business income, agriculture income, investment income, transfer income and other income. _Schooling_ is the years of schooling for the household head. _Illness_ is a dummy variable to indicate if the household head suffers from at least one chronic disease, such as hypertension, hyperlipidemia, diabetes, stroke, heart disease, mental issue, Alzheimer's disease, and Parkinson. _Alone_ is a dummy variable to indicate whether the household head lives alone. And _Male_ equals to 1 if respondent is male.. In panel B, we additional control inverse mills ratio to rule out potential selection bias issue, we also reported weak IV test statistics (F statistics) and over identification test statistics (Hansen J statistics and corresponding P-value). County fixed effects are controlled for in all specifications. Robust standard errors are clustered at city level and reported in parenthesis<sup>*</sup> _p_ < 0.1,<sup>**</sup> _p_ < 0.05,<sup>***</sup> _p_ < 0.01.

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