**Table 2. Summary statistics**

|**Household head characteristics**|E-households|Non-e-households|Difference|
|---|---|---|---|
|Age of HH head|41.020|51.450|-10.291***|
|If HH head is male|0.947|0.922|0.024|
|If HH head is married|0.905|0.910|-0.003|
|HH head’s highest education is...||||
|less than primary|0.060|0.189|-0.129***|
|primary school completed|0.150|0.271|-0.121***|
|middle school completed|0.361|0.323|0.038|
|high school completed|0.082|0.024|0.058***|
|vocational school completed|0.164|0.136|0.028|
|college completed|0.133|0.037|0.096***|
|university completed|0.051|0.019|0.031***|
|Health of HH head is...||||
|healthy|0.969|0.895|0.074***|
|sick but can work|0.015|0.052|-0.036***|
|sick and cannot work|0.015|0.053|-0.038***|
|Hukou status of HH head is...||||
|registered in current village|0.591|0.751|-0.160***|
|same county different village|0.064|0.055|0.009|
|same province different county|0.075|0.057|0.019|
|different province|0.270|0.137|0.132***|
|If HH head worked in urban areas before|0.469|0.380|0.090***|
|If HH head learned about e-commerce while in urban areas|0.265|0.066|0.199***|
|If HH head is self-employed|0.485|0.176|0.308***|
|Risk preference index (ranges 0-1; 0 means most risk-loving<br>and 1 means most risk-averse)|0.300|0.390|-0.095***|
|**Household characteristics**||||
|Household size|3.810|3.530|0.280***|
|Agricultural land (_Mu_)|2.690|2.640|0.062|
|Share of HH members age 15~35|0.503|0.290|0.212***|
|Share of HH members age 36~49|0.161|0.220|-0.059***|
|Share of HH members age 50~69|0.139|0.268|-0.130***|
|Number of observations<br>Note: Risk preference of the household head is constructed fr|453<br>om the answers t|620<br>o hypothetical survey q|1073<br>uestions that ask|

Note: Risk preference of the household head is constructed from the answers to hypothetical survey questions that ask people to choose between receiving an amount of cash for certainty versus playing a game with uncertainty. The seven survey questions are formulated as the following: “Would you like to receive X yuan for certainty or receiving 2000 yuan with 50% possibility and zero yuan with 50% possibility?” Value X takes values 400, 600, 800, 1000, 1200, 1400, and 1600. We construct a binary variable for each of these seven questions, which takes value one if the answer is to receive with certainty, and zero if the answer is to play the game. We calculate a proxy of risk premium from each question. For example, when X is 400, and the person would like to receive 400 yuan with certainty. This means that the person would like to pay at least 600 yuan to avoid playing the game with uncertainty, which further means that the risk premium in this case is at least 600 yuan. We then add up all positive and negative “risk premiums” from the seven questions and normalize it to a range from 0 to 1, with 0 being the most risk-loving and 1 being the most risk-averse. * p-value <0.1 ** p-value<0.05 *** p-value<0.01

# **3. Research methodology**

This section presents the methodology to examine the role of e-commerce participation in household income growth and the distributional aspects of the benefits of e-commerce participation. The descriptive statistics show the average income per capita of e-commerce households is higher than that of non-e-commerce households. Empirically, we aim to answer two questions: 1) Are more-wealthy/better-endowed households more likely to participate in e-commerce than less wealthy households? and 2) Do more-wealthy/better-endowed households benefit more from e- commerce participation in absolute and relative terms?

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