**Table 1. Share of migration in an average village and a Taobao Village**

|**Percentage**|**of migrants**|**in all rural vil**|**lages**<br>|**Percentage of**|**migrants in T**|**aobao Villages**||
|---|---|---|---|---|---|---|---|
|**All**<br>**migrants**|**Different**<br>**village**<br>**same**<br>**county**|**Different**<br>**county same**<br>**province**|**Different**<br>**province**|**All migrants**|**Different**<br>**village same**<br>**county**|**Different**<br>**county same**<br>**province**|**Different**<br>**province**|
|5.3%|1.7%|1.4%|2.2%|29.0%|4.7%|4.7%|19.6%|

Note: Social registration ( _hukou_ ) information for all rural villages is derived from module 1-1c and 1-4c of China Population Census in 2010. Migrants are defined as individuals who live in this village but are registered outside of the village.

# **_2.3 Characteristics of e-households and non-e-households in Taobao Villages_**

E-commerce participation is not random. E-households and non-e-households differ in many dimensions. Table 2 shows the descriptive statistics for these two household types in the Taobao Villages. Comparing the characteristics of household heads, e-households are significantly younger than non-e-households with an average difference of about 10 years. E-household heads are better educated than those of the non-e-households. Specifically, non-e-household heads are about 12 percent more likely to have completed primary or junior high school education compared to e- household heads, but 6 percent, 10 percent, and 3 percent less likely to complete senior high school, college, and university education, respectively. E-household heads are healthier and less likely to be unable to work due to sickness. E-households are 16 percent less likely to be locally registered than non-e-households, but 13 percent more likely to come from another province. This observation confirms the finding on the village level illustrated in Table 1 that people tend to migrate to Taobao Villages to engage in e-commerce. E-household heads are 9 percent more likely to have working experience in urban areas and 31 percent more likely to have self-employed experiences than non-ehousehold heads. Among those who have urban experiences, e-household heads are 20 percent more likely to have learned about e-commerce than non-e-household heads. Measured by a constructed risk preference index,<sup>9</sup> e-household heads are significantly less risk-averse than non-e-households.

In terms of household characteristics, e-households have slightly more members than none-households and have younger age composition. Land ownership of the two household types is not significantly different, potentially because agricultural land is not essential capital for e- commerce business.

> 9 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 follows: “Would you like to receive X yuan for certainty or receiving 2,000 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.

9