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Finding a job in urban China: A comparative analysis of migrants and natives

connections of family and friends, personal recommendations and employment with fami-
ly businesses. The 2008 Shanghai Health and Migration Study asked respondents only for
their current job or position. Among 33 respondents who had multiple answers for job
search channels, 14 used both hierarchy and market methods, 8 used network and market
methods, and 1 used all three channels. I excluded these individuals due to their small
number. The resulting sample of individuals includes 540 local Shanghai residents and 334
rural-to-urban migrants.
In addition to migrant status, the other independent variable, job search period, is the
period during which a respondent was looking for his or her current or last job. I used in-
formation of respondents’ self-reported job duration (in years) to calculate when he or she
found the job, then coded the year according to four categories: before 1990, between
1990 and 1999; between 2000 and 2004, and 2005 and after (until 2008 when the data was
collected). I suspect that individuals’ job search behavior may have been different de-
pending on the period of time when they were looking for a job. The 1980s began the
reform era and the rural-to-urban migration; the 1990s saw rural migration take off and the
labor market expanded; the early 2000s corresponded with the booming economy; and the
later 2000s witnessed labor shortage in urban areas.
In the analysis, I controlled a set of socio-demographic and job-related variables, in-
cluding age, gender, education, and "private sector." Education is measured on a four-level
scale, from low to high: elementary school and below, middle school, high school and
professional school, college and above. Private sector is a dummy variable with value of 1
if a respondent’s workplace is privately-owned (such as private enterprises, foreign enter-
prises, or family businesses), and 0 if the workplace is in state sector, such as a govern-
ment institution, or state-owned or local government-owned enterprise.
4.3 Statistical Analyses

T tests, chi-square tests, and multinomial logistic regression models were used to examine
questions regarding job search channels and migrant status, testing the hypotheses. In mul-
tinomial logistic regression models, several sequential models were performed by adjust-
ing for different sets of covariates that noted in the above section. It turned out that the
results of these models were more or less the same compared to the full model that in-
cluded all covariates. Therefore, only the results from the full model were presented in the
text.

5. Results

Table 1 presents descriptive statistics for our sample. Similar to what past research has
found, migrants in our sample were on average more than 6 years younger and less edu-
cated than the Shanghai natives. It is also not surprising to find that migrants in our sample
were concentrated in the private sector while the majority of urban natives worked in the
state sector. Most migrants secured their current or last jobs relatively recently (31.8%
between 2000 and 2004, and 50.82% during 2005 and after), while a significant proportion
of urban natives had had their current or last jobs since the 1980s (21.5%) and 1990s
(19.47%). For our sample, compared to Shanghai urban natives, rural migrants relied more
on market (27.85 % versus 17.9% for urban natives) and network (55.37 % versus 28.4%
for urban natives) methods, and relied less on hierarchy (16.78% versus 53.7% for urban
natives) in finding employment.
Table 2 presents odds ratios of migrant status for job search channels using multinomial
logistic regression. Three sets of results are shown, each using a different base category of

International Journal of Population Studies | 2015, Volume 1, Issue 1 100