expenditure in commuting and telephone services over total household expenditure. Informal dummy is an indicator for using informal credit. Cooperation is a dummy variable and equals to 1 if households were very compliant during the interview. **<u>Table 4: Credit Constraint and Fraud Victimization: OLS results</u>**

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
||Al<br>|l HHs<br>dummy ofbei<br>|Approa<br>ngfraud vic<br>|ched HHs<br>tim<br>|All<br>|HHs<br>lnVicti<br>|Approa<br>m_loss<br>|ched HHs<br>|
|Credit_cons|0.017<sup>***</sup><br>(0.004)|0.017<sup>***</sup><br>(0.004)|0.024<sup>***</sup><br>(0.006)|0.023<sup>***</sup><br>(0.006)|0.137<sup>***</sup><br>(0.030)|0.136<sup>***</sup><br>(0.030)|0.191<sup>***</sup><br>(0.046)|0.186<sup>***</sup><br>(0.045)|
|Lincome||-0.001||-0.004<sup>*</sup>||0.003||-0.013|
|||(0.001)||(0.002)||(0.009)||(0.015)|
|Head age||-0.002<sup>***</sup>||-0.003<sup>***</sup>||-0.013<sup>**</sup>||-0.024<sup>***</sup>|
|||(0.001)||(0.001)||(0.005)||(0.008)|
|Head age sq.||1.9*10<sup>-5**</sup>||3.5*10<sup>-5***</sup>||1.4*10<sup>-4 **</sup>||2.5*10<sup>-4 ***</sup>|
|||(6*10<sup>-6</sup>)||(1*10<sup>-5</sup>)||(4.9*10<sup>-5</sup>)||(7.4*10<sup>-5</sup>)|
|Illness||0.006<sup>**</sup>||0.006||0.056<sup>**</sup>||0.060<sup>*</sup>|
|||(0.003)||(0.005)||(0.022)||(0.033)|
|Alone||0.006||0.014||0.040||0.091|
|||(0.007)||(0.011)||(0.056)||(0.085)|
|Male||-0.003||-0.004||-0.027||-0.037|
|||(0.003)||(0.004)||(0.023)||(0.033)|
|Schooling||0.000||-0.001||0.002||-0.006|
|||(0.000)||(0.001)||(0.003)||(0.005)|
|Constant|0.035<sup>***</sup>|0.081<sup>***</sup>|0.053<sup>***</sup>|0.174<sup>***</sup>|0.253<sup>***</sup>|0.483<sup>***</sup>|0.383<sup>***</sup>|1.090<sup>***</sup>|
||(0.001)|(0.021)|(0.001)|(0.033)|(0.005)|(0.164)|(0.007)|(0.252)|
|County D.|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Obs.|25635|24472|17087|16433|25635|24472|17087|16433|
|R2|0.0188|0.0206|0.0333|0.0378|0.0189|0.0208|0.0319|0.0357|

Note: This table presents the baseline relationship of credit constraints and fraud victimization using OLS, and the sample of all urban households is used. The dependent variable for columns (1) to (4) is being a fraud victim; the dependent variable for columns (5) to (8) is the total amount of economic loss subject to fraud scheme. Full sample containing all households is used in columns (1), (2), (5) and (6). As households are approached by fraudsters before victimization and approached households may have distinct characteristics, we further restrict our sample to approached households in columns (3), (4), (7), and (8). County fixed effects are controlled for in all specifications. _Credit_cons_ is a dummy variable indicating whether household is credit constrained. Being credit constrained is defined as unable to borrow money for any of the following reasons: (a) need loan, but rejected by bank or other credit institutions; (b) unable to obtain sufficient loan from bank or other credit institutions; (c) didn’t apply for loan because no collateral/complex paperwork/outstanding loan/maybe rejected. _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. Robust standard errors are in parenthesis, and are clustered at city level.<sup>*</sup> _p_ < 0.1,<sup>**</sup> _p_ < 0.05,<sup>***</sup> _p_ < 0.01.

35