Experimental Design

The aim of the experiment is to back out each group of workers’ preference pa- rameters for wage and non-monetary aspects of jobs. We restrict the geographical coverage to the labor market of one location – Shandong Province of China. This is because the wage distribution differ greatly across provinces depending on the economic development level of the province. Workers at different locations, there- fore, have very different expectations for wage and working conditions offered. If we were to cover a national representative sample, a more dispersed distribution of wage levels will need to be included in the choice experiment, which will increase the mental task of the respondents. It is therefore optimal to restrict the sampling to one local labor market. We chose Shandong because it is a middle-level province in terms of economic development. It is also a relatively large labor market that attracts a large number of migrant workers from all over the country.

The hypothetical jobs are constructed to best reflect the reality of contempo- rary labor market in Shandong. Each sampled worker responds to 4 hypothetical choice scenarios where in each scenario he has to consider the trade-off between the wage and attributes of two listed alternatives and choose his preferred one or opt out. This also allows us to estimate the willingness to accept (WTA) distribu- tion of each group for undesirable job characteristics, namely, how much a worker needs to be compensated to accept a job with undesirable working conditions. Each respondent also fills out a questionnaire that collects basic demographic in- formation after he completes the choice task. We combine information gathered from the questionnaire and the choice experiment to examine if within group het-

erogeneity in WTA can be explained by personal characteristics such as gender, age, education, and family income.

Constructing Attributes and Attribute Levels

The first step of designing this choice experiment is to decide what job attributes should be included in the portfolio and the range of variation of each attribute (the levels). Attributes included in the experiments should capture what choice makers deem relevant and important whereas the levels of attributes should reflect the reality and at the same time include a wide range of variation so that substitution patterns can be identified. To achieve these goals, we extract attributes and their distributions from both public data and a pilot survey we conducted in August 2016. The public data was extracted from the 2015 National Beural of Statistics Report3_{. We summarize job characteristics that are deemed important in the past}

literature by industry. We further implemented a pilot survey where we interviewed 30 migrant and urban workers in Shandong to collect information on their wage, working hours, and working conditions. Distributions of attributes are summarized in Figure 2.9. We observe that wage ranges roughly from 2000 RMB to 4500 RMB per month, and sectors with more disamenities (for example construction) offer relatively higher wages. Working hours range from 9 to 11 hours a day and 6-7 days a week. Although more than two-third of our surveyed migrants reported to have signed contract with their employers, less than half of them are enrolled in social insurance programs and more than half of them face danger.

3_{Source: Pilot survey in Shandong Province by authors, August 2016; Report on Chinese} Migrant Workers 2015, National Bureau of Statistics of PRC

Figure 2.9: Attributes and Levels from Public Data and Survey

Note that the public data from National Bureau of Statistics of China uses a nation-wide sample, which may not accurately reflect wage levels in Shandong Province. We therefore conducted two focus group interviews one with migrant workers and the other with urban residents in Shandong – where we presented participants with the attribute levels and asked them if these are realistic and if they would like to add any other attributes that they deem important when they search for jobs. Almost all participants suggested that wage be adjusted upward. We therefore set 4 wage levels ranging from 3000 to 6000 RMB per month, which covers both the average wage range of migrants and urban workers. Some migrants suggested location whether the job is in large or small cities would matter. We therefore added location as an additional attribute and provided 3 levels – First- line cities, Second-line cities, Counties for migrants and First-line cities, Second-line cities, Third-line cities for urban workers (it is unrealistic for urban residents to go work in counties). The final construct of attributes and attributes levels are presented in Figure 2.10.

Generating Choice Profiles

We use JMP to generate a Bayesian D-Optimal experimental design according to Sandor and Wedel (2001). This design criterion seeks to minimize the determinant of the variance-covariance matrix of the parameter estimators. Sandor and Wedel (2001) showed that the D-optimal designs generally outperform the linear design where prior parameter vector is set to be zero with zero prior variance (Huber and Zwerina 1996).

In our design, each respondent is presented with 4 choice scenarios where each choice scenario provides 2 alternative jobs that are presented as bundles of job attributes from Figure 2.10. Since it is widely acknowledged in choice modeling literature that “respondents often find it difficult to trade off prospective goods when every attribute of the offering changes in each comparison, especially in studies involving many attributes” (Kessels et al. 2011), we keep 3 attributes constant and vary 4 attributes at a time in each scenario. We have 16 choice scenarios in total that are divided into 4 versions of surveys. Each respondent is randomly assigned 1 version.

Each scenario begins with the following statement (in Chinese): “Imagine that you are currently not employed and you are actively looking for jobs. If these are the only two jobs you are offered and all other aspects that are not included in the table are identical across alternatives, which one will you choose?” Our prior mean parameters are set assuming that unattractive levels of an attribute can be compensated for by attractive levels of another attribute. To take into account the possibility that the above compensatory decision making assumption can be violated, we provide an opt-out option in each choice scenario where respondents can reject both alternatives and choose to stay unemployed for 6 months and

keep looking for other jobs. Figure 2.11 shows a sample choice scenario that a respondent is presented with.

Figure 2.11: A Sample Choice Scenario

The choice experiment is followed by a questionnaire where we collect infor- mation on the respondents’ demographic characteristics (gender, age, education, experience, etc.) as well as information on their current jobs (occupation, wage, hours, working conditions, access to contract and social insurance).

Experiment Implementation

Prior to the formal implementation of our experiment, we implemented two rounds of pilot experiment. The first round took place in December 2016 at Shandong University of Finance and Economics where 81 undergraduate and graduate stu- dents from 4-5 majors participated. The purpose was to test if the experiment instructions and the presentation is clear and easy to understand. The second round of piloting took place in February 2017, where we interviewed 50 migrant workers that returned to their hometown during Chinese New Year and 30 urban workers with low-medium level of education and non-elite jobs so that the migrant

and urban samples are comparable. We also asked respondents for their feedback on the clarity and length of the survey and adjusted the format accordingly.

The formal experiment was implemented in July 2017 in Shandong Province in China in two stages. In Stage 1, we randomly sampled incoming passengers at the train station at Jinan City, a transportation hub where migrant workers come in for jobs and urban residents return home from either work or vacation. In Stage 2, we interviewed workers at construction sites, grocery stores and office buildings in Jinan City to obtain a balanced sample of blue-collar and white-collar workers. Since we do not know the hukou status (rural vs urban) a priori, the proportion of migrant and urban workers is not half-half – 142 migrant workers and 83 urban workers completed the choice experiment and the questionnaire. The demographic characteristics of the migrant sample and the urban sample are summarized in Table 2.1. The percentage of female, age, and number of kids are roughly balanced across samples. However, urban workers do have higher level of education and higher marriage rate compared to migrant workers.

Table 2.1: Summary Statistics for Migrant and Urban Samples Migrant Urban Difference

Female 50% 60.20% -10.20% Age 35.718 36.699 -0.98 Year of Education 11.93 14.41 -2.480*** Marriage 0.697 0.855 -0.158*** Number of Kids 0.923 0.964 -0.041 Number of Observations 142 83

The experiment was conducted face-to-face on a one-on-one basis. The experi- menter starts with introducing the purpose of the survey and asking the respondent if he or she would willingly participate. After the respondent agrees, the experi-

menter reads the experiment instructions on the questionnaire to the respondent (see Appendix). Each respondent is randomly assigned one version of the ques- tionnaire that contains 4 choice scenarios. He or she is given 1 minute for each choice scenario to choose between the 2 alternative jobs or choose to opt out. In order to make sure the respondent understands the task and is paying attention, the experiment randomly pick one choice scenario and ask the respondent why he or she chose one alternative job over the other. After the choice experiment por- tion is finished, each respondent proceeds to fill out a short questionnaire on their demographics and current job situation. The whole process takes 8-10 minutes. Each respondent is thanked with a small gift equivalent to 8-10 RMB.