The Settlement of Rural Migrants in Urban China—Some of China’s
Migrants Are Not “Floating” Anymore
Rachel Connelly
Economics Department
Bowdoin College
Brunswick ME 04011 USA
connelly@bowdoin.edu
Kenneth Roberts
Economics Department
Southwestern University
Georgetown TX 78626 USA
robertsk@southwestern.edu
Zhenzhen Zheng
Chinese Academy of Social Science
Beijing PRC
zhengzz@cass.org.cn
March 2010
The Settlement of Migrants in Urban China—Some of China’s
Migrants Are Not “Floating” Anymore
1: Introduction
The sweeping economic and social changes affecting China are compressing into
a few decades the transition from a predominately rural agricultural society to an urban
society based in manufacturing and services. The pioneers in this transition have been
the millions of Chinese migrant workers who have left their rural villages to work in the
cities. These labor migrants form the vast majority of what the Chinese call the “floating
population” (liudong renkou), the official term for all of the people who are away from
their place of permanent household registration.1 At first, most of these labor migrants
were men who planned to return home after a few years, but women now comprise nearly
half of all rural migrants. Recent evidence shows that not only are more women
migrating, but they are going after marriage, often with their husbands and children. As
migrants increasingly migrate as families, they are more likely to settle in their urban
destinations.
The goal of this paper is to investigate the issue of permanent settlement in
Chinese urban areas. In a major review of international labor migration, which scholars
argue provides the best model for understanding rural to urban labor migration in China
(Cai, 2001; Fan, 2004; Roberts, 2000) , Sassen (1999: 142) found an important similarity
over time and space was “the formation of permanent settlements for a variable share of
migrants … even when there are high return rates and even when a country’s policies
seek to prevent permanent settlement.” In this paper, we consider which factors
1
This term has a long and meaningful etymological history, one that is suggestive of the importance of
place and belonging in Chinese society. The character liu, which means to flow, when combined with min
or people, came to mean drifters or refugees. When combined with mang, which in traditional times meant
to be forced to leave one’s land, the word liumang becomes “hooligan.” Thus, the term floating population
in Chinese evokes the idea of the outsider, the unsettled (Chen, 1998).
determine settlement, and what types of people are most likely to settle in the Chinese
context. To accomplish this goal, our study uses the 2000 Chinese Census, the 2005
One-percent Population Survey, and the 2001 Chinese Urban Labor Survey (CULS).
The 2001 CULS data collection effort, which focused on five large cities and specifically
targeted migrants in a separate sampling frame, yielded 500 migrant interviews in each
city and included dimensions of settlement beyond length of stay. We argue that self
employment, coresidence with family members, remittances, and current hukou status are
all aspects of the settlement process, in addition to length of stay. We explore each of
these aspects in this initial portrait of the new settlement of the Chinese rural migrants in
urban areas.
The next section explores theoretical approaches to the issue of settlement and
Section 3 applies those theories to factors affecting settlement in China. Section 4
provides a statistical portrait of the interrelationship among the various aspect of
settlement, followed in Section 5 by a multivariate approach to three of the identified
aspects of settlement. Section 6 concludes the paper.
2: The Role of Settlement in Migration Theory
2.A: Neoclassical Theory and Return Migration
The focus of migration theory has been on the causes and consequences of
movement from one place to another, so it is only natural that standard migration theory
has assumed permanent migration as the norm and return migration as the anomaly. Yet
close examination of any migration process shows a very large proportion of migrants do
return to their place of origin, whether they are legal immigrants to the United States or
guest workers to European countries (Dustmann, 1996).
2
Neoclassical economics views migration and return as rational decisions that
weigh the costs and benefits of staying in the destination versus returning to the origin.
In situations where a significant wage gap between sending and receiving areas persists
over time, a simple application of neoclassical theory can only view returnees as failures,
unable to reap the benefits available to them in the destination (Constant and Massey,
2002). Neither the surge of circular labor migration around the world in the last several
decades nor the remittances that these migrants send home fit into this simple formulation
of return migration as a permanent migration that has gone bad.
A more sophisticated application of neoclassical theory that is consistent with
circular migration brings intentions to return into the analysis. These intentions are
reflected in behavior during migration: “it is the expected return which links the
economic behavior of the migrant in the host country to the economic situation in the
home country” (Dustmann, 1996). Thus, because wages and the opportunity cost of
leisure are higher in the destination, migrants with an intention to return will work harder
while there, and older migrants will invest less in destination-specific human capital.
Within this model, the reason migrants intend to return is a strong preference for
residence in the community of origin combined with the difficulty earning a living there.
Migrants may have a target level of savings to attain while working in the destination that
they intend to consume in their rural home, either because the costs of that consumption
are lower at home or because the utility they expect to receive from consumption there is
higher (Orrenius, 1999). Alternatively, the “bright lights” of the city may lead migrants
to change their minds and want to stay to enjoy the broad range of available consumption
opportunities, and if they are young and better educated they can benefit from spillover
learning opportunities as well (McCormick and Wahba, 2005).
3
The “new economics of labor migration” takes a different, but not inconsistent,
approach to the issues of return and circulation. The target may be to accumulate savings
for investment because of market failure at home, or the goal might be to diversify
sources of household income across sectors and space to reduce risk. Remittances fit
nicely into this model, not only for altruistic purposes or investment but as a form of
coinsurance between persons at the origin and the destination, and should increase with
the potential for investment there or the insecurity of employment in the destination
(Taylor, 1999). Since remittances are monetary manifestations of the ties of the migrant
to home, return migration should increase with the strength of the same factors that
increase remittances.
3.B: Backing into Settlement: Cumulative Causation and Networks
An alternative formulation of staying versus returning looks not at intentions but
at outcomes, for “settlement has a funny way of creeping up on immigrant workers who
intend to stay only a short while” (Hondagneu-Sotelo, 1995: 1). Not returning is
conceptualized as a postponement, not as a change of heart: “the migrant workers who
entered the various European destination countries, who were seen and saw themselves as
temporary migrants, were in reality settling” (Ganga, 2006: 97). Dustmann (1996)
examined return intentions of foreign workers in Europe and their realization over the
subsequent nine years: 11 percent intended to return and had, 31 percent didn't intend to
return and had not, and 55 percent intended to return but had not. The probability of
actual return increased with age at entry and decreased with years of residence in the
destination. These same results were found in a study of return migration from the
United States, with each additional year of residence lowering the probability of return
more than the previous (Reagan and Olsen, 2000).
4
Several factors have been found to be important in determining whether a strategy
of circular migration turns into settlement, including gender, the presence of family,
networks, and employment. Both men and women initially intend to return, but women’s
preferences seem to change more: “women gain greater personal autonomy and
independence, becoming more self-reliant as they participate in public life and gain
access to both social and economic resources previously beyond their reach”
(Hondagneu-Sotelo, 1995: 146). While male labor migrants often face discrimination in
the destination and seek to return home to regain status, “research shows consistently that
gains in gender equity are central to women’s desires to settle, more or less permanently,
to protect their advances” (Pessar, 2003: 29).
Family and networks interact to produce settlement. Generally, younger parents
who bring their children find them to be a point of entry into the destination society; the
presence of children “forces the parents to take into account the necessity of liaising, for
the first time or in new ways, with services and institutions at the place of residence” and
to develop new social networks (Ganga, 2006: 102). Their children are more exposed to
the host population than are parents, and this assimilation has spillover effects, increasing
the probability of their parents staying in the destination (Dustmann, 1996). A study of
migrants who intended to return but had not found that three of the six principal reasons
they gave for not returning were related to their children (Ganga, 2006).
A final reason for staying is connected with employment. “Return” is usually
thought of by the migrant as going back to the place of origin, but that may not be an
option if there are no jobs there except in low-return agriculture. If migrants move
instead to a regional city – the solution envisioned by Chinese urban planners who
promote the small-city policy – they may see no advantage of moving at all since “it is
5
the same old factory work” (Ganga, 2006). Even so, it is unlikely that low-skill factory
workers can stay in the destination indefinitely, either because they cannot continue to
work so hard or because of employer preference for younger workers. The occupation
that does seem to keep migrants in the destination is successful entrepreneurship (MoranTaylor and Menjívar, 2005). Entrepreneurship provides independence, potentially higher
income, control over work pace, and the opportunity for spouses and children to work
together to earn income.
In sum, the major factors highlighted by theory affecting settlement, whether
intentional or not, are the costs and benefits of consumption in the origin and destination,
considerations related to family and children, the development of networks, employment
opportunities (particularly self employment), and risk. The following section will apply
this analysis to China.
3: Changing Patterns of Migration in China
For a country which once had one of the most restrictive migration policies on
earth, China has developed a remarkably positive attitude toward urbanization during the
last decade. At the 16th Party Congress in 2002, President Jiang Zemin said “all
institutional and policy barriers to urbanization must be removed and the rational and
orderly flow of rural labor guided” (Jacka and Gaetano, 2004: 48). His pronouncement
was recognition of two realities, one urban and one rural. At the urban level, many
scholars believe that China is under-urbanized and that economies of agglomeration are
unexploited (Liu, Li and Zhang, 2003). At the rural level, the solution to poverty is
increasingly seen to lie in the city – in permanent migration and urban citizenship –
rather than in labor-intensive agriculture. This has been called the “the third liberation”
6
of the Chinese peasants, after land reform and the household responsibility system (Sun,
2005).
China classified 36.2 percent of its population as urban in 2000, growing to 43
percent in 2005 (Li and Plachaud, 2006). While there is some confusion regarding
urbanization levels as a result of urban sprawl and shifting administrative boundaries, the
inescapable conclusion is that more than half of the Chinese population, some 870
million people, will be urban within a decade (United Nations, 2006).
Most of the growth in cities has come from increasing rural to urban migration.
The 2000 census and the 2005 One-percent Population Survey show the size of the
“floating population” grew from 144 million to 147 million, and the interprovincial
segment of this population grew even faster, from 42.4 million to 47.8 million (Wang,
2006). The annual migration survey of the Ministry of Agriculture shows an even greater
proportional increase in interprovincial migration, from 21 to 40 million between 1999
and 2003 (Du, Park and Wang, 2005).
Despite the growing numbers of migrants in Chinese cities, the issue of migration
is usually considered separately from urbanization because of the assumption that this
migration is temporary. The popular image of Chinese migration is that it is dominated
by men who leave their wives and children at home while they work in the cities. In fact,
the 2005 One-percent Population Survey shows that 49 percent of the migrants are now
women2, and a longitudinal survey in nine provinces found that after 1996 the migration
rate of young women exceeded that of young men (Mu and van de Walle, 2009). Even
when the migration of women is acknowledged, the assumption is that most of these
women are young and unmarried, and that they will return to the countryside after a few
years to assume their adult status as wives and mothers.
2
Authors’ calculation.
7
This assumption no longer reflects the current reality of China’s rural to urban
migration. Jacka (2006: 275) writes, “There are thousands of rural women living in
Beijing and other cities who are older than the typical dagongmei (maiden workers), are
married and have children, and are either self-employed or care for their children while
their husband earns an income.” Survey research from the mid-1990’s already found that
significant numbers of migrants came with their spouses. In Shanghai, analysis of
surveys of the floating population yield estimates that one-fifth to one-third of migrants
were accompanied by a spouse during the 1990s (Fudan University, 1997; Roberts,
2002; Wang and Shen, 2003). A 1995 survey of migrants in Beijing, Wuhan, Suzhou
and Shenzhen found that one-third were accompanied by a spouse (Knight, Song and Jia,
1999), while a 1999 survey in Beijing and Shanghai found that 44 percent of migrants
were with their spouse (Wu, 2004). A rural survey of returned migrant women in
Sichuan and Anhui provinces found that two-thirds of their migration episodes had
occurred after marriage, that four-fifths of married women had children by the time they
took their first trip, and that half of the married women migrated with their spouse. Of
these, about one fourth brought their children with them (Roberts, et al., 2004).
The presence of family in the city is conducive to long-term stays and settlement,
but data on whether this is, in fact, occurring are difficult to obtain. Surveys of returned
migrants in the late 1990s in Anhui and Sichuan (Bai and He, 2003), and in those two
provinces plus Hebei, Hunan, Shaanxi and Zhejiang (Zhao, 2002), found average
durations of stay in the destination were between three and four years. Rural surveys,
however, miss those migrants who had not yet returned and so might understate
settlement. A 2005 survey undertaken in urban areas of Zhejiang province found 45
percent of migrant households had been in the city for over three years, and that 72
8
percent of married migrants lived with a spouse (Qi and He, 2005). A study by People's
University showed that the majority of the 3.5 million migrants in Beijing had been there
an average of five years (Xinhua, 2007). Urban surveys, however, might also understate
settlement by truncating duration, for it is impossible to know how much longer the longterm residents will stay. Most recently, the National Bureau of Statistics provided
summary data from surveys of the floating population spanning a decade: the proportion
staying less than a year fell from 51 percent to 23 percent between 1993 and 2003, while
those staying more than five years rose from 6 percent to 40 percent by 2000 (Nielsen
and Smyth, 2007).
Table 1 uses the 2000 Census and the 2005 One-percent Population Survey to
compare the percent of male and female migrants who report being in their current
destination for five or more years. In all but three provinces, the proportion of long-term
migrants has increased during this five-year period. While the percent varies by
province, from a low of 23 percent in Zhejiang to a high of 52 percent in Heilongjiang,
on the average of about a third of both men and women are spending extended periods of
time in their destinations.
There have been few studies of the intentions of migrants to stay in Chinese cities.
A 2006 survey in Beijing found that nearly half of the 2,532 migrants surveyed
expressed a strong desire to stay (Hu 2007). A Fujian survey found that, if given a
choice, 46 percent of migrants planned to return home after earning enough money, 21
percent wanted to stay where they were, and the rest wished to move elsewhere or were
undecided (Zhu, 2007).
As discussed above, costs and consumption opportunities emerge as important
factors that both discourage and encourage potential settlement in Chinese cities. The
9
gap between rich urban and poor rural is wide in China, and is expensive for a migrant to
live in the city relative to their income. The average migrant wage nationally was 5,444
yuan in 2002, compared to average expenditure of urban residents of 6,930 yuan (Zhu,
2007). A survey by the National Bureau of Statistics found migrants earned a monthly
average of 966 yuan and spent 463 yuan, two-thirds of it on food and accommodations
(Xinhua, 2006c). In the Fujian survey, most migrants earned 500 to 800 yuan per month,
and only 29 percent said they earned enough money to support their family in the city
(Zhu, 2007).
Sometimes having a spouse in the city can save money. A survey of migrants in
Zhejiang province records one migrant’s reasoning: “We can both find jobs and live on
only one person’s income, so that another’s income can be saved. If only one works in
the city, he will have to spend the same or even more – pay same amount of rent, eat out,
which is more expensive than cooking at home, and he might feel lonely, so he will spend
a lot of money in recreation. In the end, there will be nothing left over” (Qi and He,
2005: 6). This rationale probably lies behind the result of a study of returned migrant
women in Anhui and Sichuan, which found that many of the women who accompanied
their migrant husbands were unemployed: 12, 16 and 22 percent respectively on their first
through third trips (Roberts, et al., 2004). It is ironic that one of the most important
predictors of settlement, having a spouse in the city, would be an element of a strategy to
save money for eventual return, but this phenomenon is completely consistent with the
“backing into settlement” approach discussed above.
One of the biggest expenses and one of the last barriers to settlement with any real
force is housing. Urban China has experienced a remarkable process of privatization of
housing and a surge in property values. Most of the residents in a survey of housing in
10
13 cities had been able to purchase their subsidized rental units at heavily discounted
prices; between 1988 and 1999 space doubled and the proportion of dwellings with toilets
increased from four to 33 percent. Two-thirds of migrants, on the other hand, lived in
rented housing, paying an average of 250 yuan rent per month in provincial-level cities.
They had much less space than residents, and only six percent had toilets. In Beijing,
rent for this substandard housing was more than one-fourth of migrants’ household
expenditure (Sato, 2006).
A significant proportion of migrants live at their place of employment, whether in
restaurants, hair cutting salons, stalls, construction sites or factory dormitories. For
young women in coastal boomtowns same-sex dormitories have been factors contributing
to their isolation and limited duration in the city. However, young women increasingly
socialize with and marry coworkers; in response this and labor shortages in South China
(Wang, Cai and Gao, 2007), factories have recently begun to provide dormitories for
married couples. There also has developed a burgeoning apartment rental market for
young couples, who with a combined income of 1,500 yuan can afford to pay rent of 150
to 400 yuan (Zhang, 2009).
If housing is losing some of its force as a barrier to settlement, the same can not
be said for children’s education. Whether in surveys of migrants or in the popular press,
the education of migrant children is seen as a huge problem in China. The Ministry of
Education estimated that in 2004 there were 6.4 million children of compulsory school
age living in the cities with their parents and another 22 million remaining in rural areas
(Xinhua, 2006a). School attendance for migrant children is now mandatory, but the fiscal
responsibility of their education falls upon local governments in the destination. Despite
widespread publicity and official decrees, urban schools continue to charge migrants
11
additional fees: the National Bureau of Statistics found 17 percent of migrants surveyed
brought children with them, paying an additional 1,226 yuan in fees above regular tuition
(Xinhua, 2006c). Many others send their children to migrant schools, which are
frequently of poor quality. Children of migrants living in urban areas are much more
likely to not complete 9th grade (the final year of compulsory school in China) compared
with non-migrants and compared with children in the rural areas.3 Cho (2009) provides
an account of one middle-age migrant woman's struggle to settle in Harbin. A
particularly interesting and sad part of the account is that the children she had brought
with her completed only primary school because they began to work in the city, and now
they are relegated to menial jobs. This phenomenon will serve to perpetuate the gap
between urban and migrant school completion rates.
In the discussion above, the requirements of urban life and education affect
settlement negatively because of their additional costs. But it is these same factors that in
many cases attract migrants, whether because of the “bright lights” of the city or
enhanced opportunities for education and mobility. This is especially true of migrant
women: of migrants surveyed in Hebei, more women than men envied urban life, wanted
their families with them, and “were more eager to abandon rural life and settle in the
cities” (Song, 1999: 88). Migrant women in Beijing “tend to see a future in the city as
holding greater potential for development than life in the countryside … significant, and
possibly growing, numbers of migrant women wish to stay away from their ‘home’ in the
countryside for as long as possible”(Jacka, 2006: 141).
Opportunities for employment, both at the origin and the destination, are
obviously important factors affecting settlement. Most of the young migrants have come
straight from school and never farmed for a living; they perceive farming to be a dead
3
Authors’ calculation from 2000 Chinese census.
12
end when so many other opportunities are available. They can do hard manual labor in
the cities while young, but not forever. Cai and Wong (2007) studies migrants’ intentions
to stay permanently in nine cities in the Pearl River Delta area in 2006. Using
willingness to give up their land as a proxy for the intention to settle, they found that
those with more education were more likely to want to settle.
Education and training provide mobility for some, but for most migrants the route
to success in an urban area is entrepreneurship. Employment in commerce was found to
be a significant determinant of longer durations of stay in Shanghai for married women
(Roberts, 2002), and was related to intention to settle in Fujian (Zhu, 2007). The survey
of returned women migrants in Anhui and Sichuan found those working in commerce
were both more likely to be accompanied by their husbands and to have engaged in
multiple migrations (Roberts, et al., 2004).
The instability of employment was a major factor given by Fujian migrants for
wanting to return. It was the main reason they offered for not giving up their land, which
would occur if they changed their hukou or didn’t farm it. The land is also seen as a
place to return to when old (Zhu, 2007). These reasons for ties to home – insurance for
unemployment and for old age – are highlighted in the new economics of labor migration
literature. Whether they actually impede settlement remains an unanswered question.
Finally, increased time in the city seems to decrease the likelihood of return in
China, as it does in studies of migration and settlement in other countries. Zhao (2002:
382) surveys returned migrants, and finds “the probability of settlement rises as migrants
accumulate time in the city.” Ren (2006) examines Shanghai data from 2000 and 2003,
and concludes that the longer migrants stay in the city the higher their probability of
long-term residence. While these data sets are not longitudinal, the factors that link
13
duration and settlement are similar to those identified by the longitudinal European
studies discussed in Section 2 above.
4: A Statistical Portrait of Migrants in Five Large Cities
In order to gain a better understanding of settled migrants in urban areas in China
we consider data from the Chinese Urban Labor Survey (CULS). The data were collected
between November 2001 and January 2002 by the Institute for Population Studies of the
Chinese Academy of Social Sciences in the five cities of Shanghai, Wuhan, Shenyang,
Fuzhou, and Xian. Urban households were surveyed using a proportional sampling
frame. The migrant population in the same cities was surveyed with a separate survey
instrument and a separate sampling frame. The migrant sampling frame used the
information in the 2000 Chinese Population Census to identify 60 neighborhoods in each
city where a high proportion of residents were migrants. Once the neighborhood was
selected, the administrative records of the neighborhood committee were used to
construct a sampling frame of all registered migrants. This method excludes short-term
migrants who have not registered for temporary residence permits, but includes
substantially more migrants than would have appeared in survey using only the urban
household sampling frame.
Table 2 compares the length of stay variable for each of the five cities in the 2000
Census and the 2001 CULS.4 The CULS has a very different distribution of duration
than the 2000 Census, with many more long-term migrants in the CULS. Since our goal
4
Our working sample is 2,541 rural-to-urban migrants. The 44 migrants who reported their current hukou
status was rural but that at age 16 it was urban were reclassified as having a rural hukou status at age 16,
because ……….. After that reclassification, the 449 respondents who reported their hukou status at age 16
was urban were omitted, in order to exclude urbanites who had moved from one city to another.
Preliminary analysis showed that the omitted group of urban-to-urban migrants were quite different from
the rural-to-urban migrants. For example, the average years of education of urban-to-urban migrants was
11.6 compared to 8.4 years for the rural-to-urban migrants.
14
is to study determinants of settlement, the oversampling of long-term migrants is not
unwelcome, but we cannot assume the distributions of duration presented below is
representative of the full migrant population in the five cities.
4.A: Length of Stay
Table 3 presents the percent of migrants surveyed in the CULS by length of time
they report having lived in this city. The duration information provided by the CULS
allow us to distinguish between moderately long tenures and very long tenures, whereas
the final category in the 2000 Census is “more than five years” and in the 2005 Onepercent Population Survey is “more than six years.”
A substantial number of registered migrants have been in the five CULS cities for
four or more years. Wuhan, Shanghai and Fuzhou are similar with 61 percent, 60 percent
and 56 percent respectively in the city for four years or more. Shenyang, with 35 percent,
has the lowest percent of long-term migrants, and Xian is in between with 48 percent. In
all five cities, of those who have stayed four years or more most have been there between
four and ten years. These migrants would have come between 1992 and 1997, years
correspond the surge in migration after Deng Xiaoping’s Southern Tour. At the other end
of the spectrum, Wuhan, Shanghai, and Fuzhou are again quite similar, with about 18
percent of the migrants there for less than two years. Shenyang’s migrants are more
recent, with 36 percent of them having lived in there for less than two years, and Xian is
in between, with 27 percent of the migrants there for less than two years.
4.B: Age of Migrants
Table 4 shows the mean age of men and women migrants by length of time in the
city. On the average women migrants are a few years younger than men in each city. As
one might expect, migrants who have been in each city longer are older, but not as much
15
as would be expected if they had all come at the same age. Thus, it appears that migrants
who have stayed longer came to the city when they were younger. In Xian, the average
age of women who have migrated in the last two years is almost 28, while the average
age of women who have been in the city two to four years is 25. This data supports a
finding from a survey of returned women migrants in Anhui and Sichuan, that in recent
years more women in all age cohorts, including older women, are joining the migration
stream (Roberts, et al., 2004).
4.C: Marital Status and Location of Residence of Migrant Spouses, Children and
Parents
Table 5 shows that the majority of both men and women in the CULS migrant
sample are married, consistent with recent studies that show that marital status is not an
important determinant of migration after controlling for age (Mu and van de Walle,
2009). Shenyang is the outlier, with fewer migrant women and a lower percent of these
women married, but for some cities and durations, the proportion of married women
migrants exceeds that of men. The proportion married increases with time in the city;
while clearly related to age, it may also be a result of a higher propensity to stay in the
city if married.
Table 6, Panel A shows that most married women migrants in these five cities are
there with their husbands, and that only the most recent arrivals are migrating without
them. Men are less likely to be accompanied by their wives at every category of
duration. Nevertheless, well more than half of the male migrants are in the city with their
wives.
Table 6, Panel B shows that most married migrants have children under 16 years
old, regardless of time in the city. There is a slight decline in the percent with children in
the “10+ years” category, which is probably because their children are older than sixteen
16
years of age. This is unlikely to occur in the first three duration categories, as the mean
age of migrants in those categories is around 30 years. While at least two thirds of the
married migrant women are in the same city as their husband and more than half of the
married migrant men are in the same city as their wife (Table 6, Panel A), Panel B shows
that far fewer are accompanied by their children. This is made possible by the care
provided by family at home: the survey of female rural labor migrants in Anhui and
Sichuan found 76 per cent of the women who had children by the time of their first
migration had left them with grandparents (Roberts, et al., 2004). In the CULS data, the
proportion accompanied by children increases with time in the city, with more than a
third of women in the city four to ten years (the modal category in terms of number of
migrants), and half of women there over 10 years accompanied by one or more of their
children.
Table 6 Panel C explores coresidence with the parents of adult migrants. It shows
that while the majority of these rural-to-urban migrants have living parents, very few of
their parents have moved to the urban areas. Based on the average age of the migrants,
these parents are in their fifties and sixties and are remaining in the rural areas, caring for
grandchildren and continuing to work the land. Mu and van de Walle (2009), analyzing
data from a longitudinal survey of households in nine provinces, find a significant
increase in time spent working on the farm for women in the 51 to 60 age cohort.
4.D: Remittances
As discussed above, one of the main reasons for migrating is to send remittances
back to rural family members. Table 7 explores differences in the patterns of remittances
by time in the city. Panel A focuses on the percent of migrants who report sending any
remittances home, while Panel B examines remittances as a proportion of the annual
17
income of those migrants who send remittances. Panel A columns one and two use the
full sample of rural to urban migrants. The percent of men who send remittances is
higher than the percent of women and does not seem to be a function of length of time in
the city. This is probably because married men are less likely to be accompanied by their
spouse than are married women, and so are sending remittances to their rural wives.
Columns three and four examine the proportion of married migrants with spouses in the
same city who send remittances home. We find that significant gender difference
remains. Comparing columns three to five and four to six, we find as expected that the
proportion sending remittances home is much higher for migrants whose spouse is not in
the same city. The proportion of migrants sending remittances is particularly high for
males who have been in the city for two to four years. It may be that those men who stay
beyond the first two years are those who find stable employment that provides enough
income that they can successfully save and provide remittances.
Table 7 Panel B shows that male migrants who send any remittances send a larger
percentage of their income home than do women. This gender difference in the
proportion of income remitted disappears when the sample includes only married
migrants who are accompanied by their spouse. Comparing columns three to five and
four to six we see that those married migrants who are not accompanied by their spouses
remit a substantially higher percent of their income than those with accompanied by their
spouses. Nevertheless, remittances by married migrants with spouses in the city are still
between 15 and 20 percent of their annual income. These remittances may be used to
support other family members, to pay school fees for migrants’ children, or to build a
rural home (Ma, 2004). The high level of remittances is consistent with migrants
maintaining strong ties to their rural communities and extended family members.
18
4.E: Self Employment
We discussed above that studies in China and elsewhere associate successful
entrepreneurship with migrating with a spouse, longer durations, and eventual settlement.
Table 8 examines the relationship between duration of stay and self employment, and
shows that the percent of migrants who are self employed increases with their length of
stay in the city. This statement is true for both women and men and in all five cities,
though there are substantial differences across the cities. Shenyang has the lowest
proportion of self-employed migrants, 28 percent of the men and 30 percent of the
women. Shanghai, Fuzhou, and Xian look fairly similar, with more than half the
migrants self employed, while Wuhan has an even higher rate of self employment among
both men and women migrants.
4.F: Changing Hukou Status
The final variable explored in this section of the paper is the only direct indicator
of intentional permanent settlement: changing one’s hukou status from rural to urban.
While in the past only well-educated workers had a chance of changing hukou, some
Chinese cities have been allowing migrants to obtain urban hukou for a fee. Table 9
shows substantial differences among the five cities in the probability of having changed
hukou status. Wuhan has the highest rate of hukou status change, with Shanghai and
Fuzhou being the lowest. It is also interesting to note that changing hukou status seems
to be independent of time in the city. Thus, we should consider it to be a separate aspect
of settlement. Cai and Wang (2007) found that those migrants who signal permanent
migration intentions by declaring their willingness to give up their land are no different
from their temporarily migrating fellow migrants in their desire to change their hukou
status. Changing hukou status is not an urgent issue to them.
19
Of course, Tables 3 through 9 control for only one or two variables at a time. We
know that migrants differ by age, sex, by city of destination, and by many other
characteristics of their past. All of these variables potentially affect their length of stay,
their propensity of have their spouse coresiding, and their propensity of having their child
coresiding. These multivariate relationships are explored in the next section.
5: Multivariate Analysis of Three Aspects of Settlement
We choose to analyze the CULS data because it provides several variables that
can be considered aspects of permanent settlement. As we discussed above, the previous
literature showed that migrants are more likely to settle the longer they stay in the same
place, what we have called “backing into settlement”. This relationship is true regardless
of whether the settlement is intentional or de facto. If it is intentional, then there may be
some permanent settlers among the most recent migrants, but the proportion of migrants
who are permanent settlers should increase with length of stay as the non-settlers return
to their location of origin or move to another migration destination. If the settlement is
de facto, then length of stay is, in part, the cause of settlement. Table 10 presents the
OLS regression model of the determinants of length of time in the city.
Two additional components of settlement are also analyzed; they are having one’s
spouse in the same city and having a child in the same city.5 Both are analyzed using a
5
Originally we considered two additional aspects of migration as components of settlement, self
employment and having changed one’s hukou status from rural to urban. However, in preliminary analysis
of the data (not shown) we found that self employment and changing one’s hukou status from rural to urban
were largely stochastic, at least in terms of the variables available in the CULS. We also tested whether
including current self employment, hukou status, and having one’s spouse in the same city affects the other
coefficients in the length of stay regression model, as one could be concerned about potential endogeneity
of these variables in that equation. It turns out that the coefficients of the other variables are extremely
robust to the addition of these “quasi-independent” variables. Tables comparing the results with and
without self-employment status, hukou status and having one’s spouse in the city are available from the
authors.
20
logistic model, with results presented in Tables 11 and 12 respectively. For each of the
three aspects of settlement, we estimate the model for men and women separately. We
know that empirically the pattern and timing of migration has been different for men and
women. In addition, theory tells us that settlement may be more related to women’s
migration than men’s migration.
5.A: Determinants of Length of Stay
Table 10 shows that determinants of length of stay are qualitatively similar for
men and women migrants. For both, the younger one was at the time of migration, the
longer the duration in the city. Being currently married also increases length of stay,
quantitatively more for men than women. Higher levels of education are correlated with
shorter length of stay, though the effect is quantitatively small. For men, having a spouse
with higher education reduces their length of stay, while there is no effect of spouse’s
education on a wife’s length of stay. Having worked first in agriculture (as opposed to
one’s first job being a migrant) increases the length of stay for both men and women by
similar magnitudes. Also similar is the effect of having living parents, which
substantially reduces length of stay in the city for both men and women. These latter two
effects are likely related to current age of the migrant. Younger people are less likely to
have worked in agriculture and more likely to have living parents.
Those migrants whose location of origin is closer to the city are more likely to
have been there longer, though the effect measured less precisely for women. It may be
that being closer facilitates staying longer, but it is also true that the nature of migration
in China has changed such that more recent migrants go farther from home than migrants
who left their rural homes in the mid 1990s, with the percentage of migration that is
interprovincial increasing steadily over time (Wang, Cai and Gao 2007).
21
Being able to speak the local language upon arrival increases both men’s and
women’s length of stay. However, paradoxically for both men and women, self-reported
poor Mandarin ability upon arrival also predicts more time in the city compared to those
who reported good Mandarin skills. Since the five cities differ substantially in language
spoken and in the provinces from which they are drawing migrants, it is possible that
these variables reflect differences across places that are in addition to those being picked
up with the location dummies. In terms of those location dummies, for both men and
women, migrants in Shenyang and Xian have been resident for a shorter time than
migrants in Shanghai. Wuhan and Fuzhou are not shown to differ from Shanghai in the
base length of stay.
Having a job arranged before one arrives has a different effect on women than on
men. For women, having had their first job arranged before they arrived is associated
with shorter time in the city, while for men the variable is insignificant. This result could
be because of the nature of jobs that can be arranged ahead of time or may proxy for less
assertive personalities.
For women, having her husband in the city is associated with a longer stay in the
city, but the same effect is not found for men. On the other hand, having changed one’s
hukou status is associated with longer stays for men, but not for women. Finally, being
currently self employed is associated with longer stays for both men and women.
It is equally interesting to consider the variables that are not statistically
significant determinants of length of stay, especially the number of children and the
presence of other family members and relatives in the city upon arrival. These results
indicate that children do not impede migration or even affect time in the city, consistent
with the results of studies discussed earlier. The insignificance of the presence of other
22
family members may be because strong migrant networks now exist in most Chinese
urban areas, so that even if one does not have family in the city upon arrival, there are
other fellow villagers and commercial services available to help migrants find
employment.
5.B: Determinants of Residing with One’s Spouse
Tables 11 explore the determinants of another important aspect of settlement,
residing with one’s spouse for the subset of migrants who are currently married. Table
11 reports the log odds instead of the coefficients, with log odds greater than one
meaning that the characteristic is positively associated with the given aspect of settlement
and values less than one meaning the characteristic is negatively associated with
settlement. The results show that for both men and women, a younger age at migration
reduces the odds that one currently lives with one’s spouse. This result is in keeping with
Roberts, et al (2004), which found that many married women migrants migrate without
their husbands during their first migration episode.
The only other significant variables for both men and women are having both
parents be peasants and living in either Wuhan or Shenyang. A migrant whose parents
are both peasants is less likely to reside with his or her spouse. The labor demands for
farming at home may be the explanation, or it may indicate a lack of the resources needed
to move the family to the city. Migrants to Wuhan are more likely to coreside than those
in Shanghai, while those in Shenyang and men in Xian are less likely to coreside than
those in Shanghai.
Self employment is a strong positive predictor of coresidence for men, supporting
the hypothesis that self employment allows men to bring their wives to the city to earn
23
income by working together. Once again, the variables that are not significant predictors
of coresidence with one’s spouse are interesting: education, number of children, distance
to the city, language ability, having relatives in the city when one arrived and current
hukou status do not significantly affect coresidence with one’s spouse.
5.C: Determinants of Coresiding with Children
We saw in Table 6 that while the majority of men and women coreside with their
spouse, many fewer coreside with their children. Table 12 examines the determinants of
having one’s child in the city for the subsample of migrants who are both married and
have at least one child. The specifications are identical to those in Table 11 except for
the addition of a dichotomous variable which indicates if the oldest child is school age.
School seems to be an important decision making point for migrants, with some migrants
sending children back to their village when the children reach school age to avoid the
higher school fees in the city, while others may elect to bring school age children to the
city because they do not need day care arrangements while children are in school or to
enroll them in higher quality schools (Connelly, et al 2008).
For most variables, men and women appear similar in this decision, probably
because both the husband and wife are usually together if the child is coresiding (86
percent of the households with a child present also have the spouse present). Migrants
who are younger at the time of migration are less likely to coreside with their child.
Having any relative in the city upon arrival positively predicts having a child coreside,
probably because these relatives facilitate childcare. Migrant with parents who are
peasants are less likely to have their child coreside with them. Paternal grandparents are
24
the primary source of childcare in rural China (Chen, Short and Entwisle, 2000), and
many migrants leave their children with grandparents in the village (Roberts et al, 2004).
The effect of grandparents as potential caregivers can also be inferred from the
variable “any parent alive?” For male migrants, having any parent alive reduces the odds
that their child resides with him in the city, as does having a school-age child. The
effects are similar for female migrants, but are estimated less precisely. Thus, migrants
appear to be more likely to bring very young children with them and then send them back
to their rural homes for schooling. Connelly et al (2008) came to the same conclusion
using data collected in rural areas of Sichuan and Anhui.
Migrants in Wuhan are more likely than those in Shanghai to have children with
them. For women, those in Xian are also more likely to have children with them. For
men, those in Shenyang are less likely to have children with them. Recall that those in
Shenyang were also less likely to have their wives with them.
In Table 10 we saw that self employment increased the length of time the migrant
spent in the city. For men, self employment also increased the probability that their wife
lived with him in the city. Now, we find in Table 12 that for men self employment also
increases the probability that their child lives in city. Thus, self employment appears to
be a very important economic and social path for Chinese rural to urban migrants, quite
different from a migrant who is an employee. The ability to use additional labor
productively and the gain from contacts gathered over time means that self-employed
migrants tend to stay longer and live with family members. While some may ultimately
go home, as a group they appear more settled than other migrants.
In sum, the three aspects of settlement explored here show a varied pattern of
determinants. Standard demographic characteristics, such as education and number of
25
children, do not appear to matter. Language ability, current hukou status and relatives in
the city also do not appear to be strong predictors of behavior. Variables that do matter
consistently are age at migration and current self-employment status. Differences among
the five cities regularly emerge, indicating that institutional structures and local labor
markets are important considerations in understanding settlement behavior.
Section 6: Concluding Remarks
This paper has explored, both theoretically and empirically, the phenomenon of
permanent settlement among Chinese rural-to-urban migrants. While naïve economic
theory focuses its attention on the decision to migrate permanently, more sophisticated
theoretical explorations of migration model return migration as well. In fact, return
migration may be the goal, making settlement the unintended outcome.
In order to explore migration decision making in China, researchers have until
recently focused exclusively on the phenomenon of circular migration; both Chinese
government policy and de facto institutional structures insured that most migrants were
short-term temporary migrants. But the massive economic reforms since the mid-1980s
have reduced many of the barriers that were keeping migrants from settling in urban
areas. While the hukou system is still official policy, being in a place other than one’s
place of registration has been decriminalized. The availability of food and housing for
purchase means that migrants can now buy that which they need to stay in the cities.
However, education for their children is still a substantial barrier, and we find that
migrants with school age children are less likely to bring their children to the city.
We can get an overview of changing settlement patterns in China through
comparison of the 2000 Census with the 2005 One-percent National Population Survey.
26
The overall percent of migrants who have been in the receiving location for five or more
years has increased during these five years. More importantly, because the absolute
numbers of migrants has increased by much more, there has been a substantial increase in
the population of long-term migrants.
The 2000 Census and the 2005 One-percent National Population Survey do not
allow us to distinguish between medium-term migrants and very long-term migrants; for
that we turned to data from the 2001 Chinese Urban Labor Survey. While the CULS
sampling strategy was weighted toward longer-term migrants and cannot be considered
representative of all migrants, the data can give us a detailed look at the length of stay,
living arrangements, occupations, and remittances of the more settled migrants in five
cities.
Most migrants in the CULS sample are married and more than half have been in
the city for 4 or more years. Fifty-six percent of the men and 76 percent of the women
are living with their spouse, but only 22 percent of the men with children and 28 percent
of the women with children are living with their children. Remittances are substantial,
even among those men and women with spouses in the city. Both the number leaving
their children and the size of the remittances indicate that there continue to be strong ties
with rural areas, and that full permanent settlement has not yet occurred for the majority
of migrants to these five cities in 2001. The most settled group appears to be selfemployed migrants, who are shown in the multivariate analysis to have longer durations
in the cities and are more likely to reside with their spouse and children.
As the length of time migrants are spending in cities grows and most migrants live
with their spouse in the urban areas, China needs to rethink the assumption that labor
migration is temporary, and examine the ramification of the shift towards settlement in
27
terms of the delivery of health and education services. While in the past women returned
home upon marriage and men returned a few years later, over the last ten years a
generation of rural Chinese children is being raised in the countryside without their
parents or in the cities with substantially less access to education than that afforded urban
dwellers. The working migrants until they get hurt or can not longer physically take the
extremely long work hours and difficult conditions of migrant jobs seems inefficient for a
country at the level of development that China is at today. As many Chinese migrants are
now “backing into settlement,” the costs of the unintentionality of this decision will
remain in terms of increased inequality in the urban areas for at least another generation.
28
Table 1: Percent of migrants 16 years or older who have lived in their
current place of residence for five or more years
2000
Hainan
Chongqing
Sichuan
Guizhou
Yunnan
Tibet
Shaanxi
Gansu
Qinghai
Ningxia
Xinjiang
Men
37.1
25.2
27.1
32.0
22.2
28.8
17.4
18.3
28.1
31.2
45.4
20.3
41.5
23.1
27.5
24.8
25.9
23.2
32.7
28.5
20.8
31.2
30.0
23.6
33.0
10.2
26.1
32.3
28.8
25.2
34.9
Total
31.1
Beijing
Tianjin
Hebei
Shanxi
Inner Mongolia
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Fujian
Jiangxi
Shangdong
Henan
Hubei
Hunan
Guangdong
Guangxi
Women
33.1
29.8
22.9
15.2
20.6
20.3
19.8
19.4
24.8
27.5
39.9
17.8
38.5
16.0
25.3
16.7
21.7
25
32.7
27.9
23.5
19.4
32.6
25.9
30.5
12.1
21.7
25.6
27.9
17.0
24.1
28.5
2005
Men
36.4
28.7
38.8
42.5
41.3
41.3
34.2
53.1
36.4
30.9
24.8
32.6
33.2
36.3
30.4
38.7
41.6
28.6
29.8
30.0
40.7
35.1
32.2
42.0
36.8
43.1
34.2
37.4
39.1
33.6
44.5
33.3
Women
36.1
27.6
35.1
45.2
42.5
38.9
33.8
48.9
32.9
26.5
23.5
31.2
28.3
36.4
26.1
35.9
40.4
27.3
24.9
34.8
37.4
31.5
28.2
40.3
35.0
45.3
32.9
37.2
34.3
32.6
40.4
Ranking by size of
2005 migrant pop.
3
4
21
12
11
10
18
17
2
6
5
22
7
29
9
28
13
19
1
23
20
25
15
24
8
31
14
26
27
30
16
30.3
Source: The 0.095% Micro Sample of the 2000 Population Census of China
and the 20% percent sample of the One-percent National Survey of Population, 2005.
Table 2: Percent of migrants by time in city by sex and city,
from the 2000 Chinese census and the 2001 CULS
2000 Census
2001 CULS
Men
0-1 years
2-4 years
5+years
Men
Shanghai
49.7
25.8
24.5
Wuhan
30.2
30.9
36
Shenyang
46.4
15.6
38.0
Fuzhou
56.5
26.6
16.9
Xian
56.7
18.9
24.4
Shanghai
47.1
26.6
26.3
Wuhan
25.8
29.7
32.1
Shenyang
30.5
23.7
45.8
Fuzhou
48.7
27.6
23.6
Xian
47.9
23.4
28.7
Women
0-1 years
2-4 years
5+years
0-1 years
2-4 years
5+years
Shanghai
15.6
19.8
64.7
Wuhan
14.1
19.0
66.9
Shenyang
32.0
27.8
40.2
Fuzhou
18.1
23.2
58.7
Xian
Shanghai
19.7
29.2
51.1
Wuhan
22.7
21.6
55.7
Shenyang
46.3
32.8
20.9
Fuzhou
19.5
27.5
53.0
Xian
24.4
24.1
51.5
Women
0-1 years
2-4 years
5+years
Source: 2001 CULS and 0.095% Micro Sample of the 2000 Population Census of China
33.1
26.4
40.5
Table 3: Percent of migrants by duration in city
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
Mean years
Total Sample
23.3
24.5
35.0
17.3
5.3
Shanghai
17.1
23.2
39.8
19.9
5.8
Wuhan
18.5
20.3
39.9
21.3
5.8
Shenyang
36.1
29.3
24.7
9.9
3.9
Fuzhou
18.8
25.2
33.6
22.4
6.0
Xian
27.2
24.9
36.0
11.9
4.6
Source: 2001 CULS
Table 4: Mean age of migrants by duration, sex and city
Men
Total Sample
Shanghai
Wuhan
Shenyang
Fuzhou
Xian
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
28.2
28.6
31.8
36.5
26.7
30.3
32.5
35.1
28.5
31.0
33.1
35.4
28.0
25.7
30.7
39.1
28.2
29.9
30.7
37.7
29.1
28.1
31.8
36.2
Total
31.2
31.8
32.6
29.4
31.9
30.8
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
25.9
26.6
30.3
34.8
27.7
26.4
30.4
35.2
25.6
28.1
30.3
33.0
22.9
25.2
31.5
32.3
26.6
27.2
29.8
36.1
27.8
25.3
30.5
36.9
Total
28.7
29.3
29.1
25.5
29.6
28.8
Women
Source: 2001 CULS
Table 5: Percent of migrants who are currently married by duration, sex and city
Total Sample
Shanghai
Wuhan
Shenyang
Fuzhou
Xian
Men
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
49.5
50.3
72.1
93.0
53.1
69.4
84.4
97.3
51.4
62.0
79.2
95.7
49.1
27.7
59.2
81.6
46.0
60.9
66.3
91.8
49.4
46.3
67.7
93.3
Total
66.4
79.6
76.4
49.7
68.1
61.5
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
42.7
51.7
76.0
91.2
48.6
50.0
79.4
91.3
45.2
67.8
73.1
97.7
19.4
27.3
57.9
77.8
59.2
55.1
79.5
88.9
48.1
51.2
78.4
86.7
Total
62.9
66.3
69.6
31.3
70.5
62.0
Women
Source: 2001 CULS
Table 6: Location of family members by duration and sex
Panel A
Percent of married migrants whose spouse is
in the same city
Men
Women
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
36.4
57.6
57.7
66.1
62.5
72.5
79.9
86.3
Total
56.6
76.4
Percent of married migrants
with children under age 16
Percent of married migrants with
children under age 16 who have
any of their children in the city
Men
Women
Men
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
66.0
78.0
76.1
78.2
75.9
85.5
84.6
75.0
5.5
16.5
24.3
40.9
12.2
22.8
36.8
48.5
Total
75.4
81.4
21.8
28.2
Panel C
Percent of migrants with at least
one parent still alive
Percent of migrants with a living
parent who have a parent in the city
Men
Men
Women
Panel B
Women
Women
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
91.1
92.1
87.5
82.7
94.7
97.0
91.6
85.3
4.0
2.2
9.3
6.0
2.0
5.0
5.9
6.9
Total
88.4
93.0
5.8
4.7
Source: 2001 CULS
Table 7: Remittances: Incidence and percent of income by location of spouse
Panel A
Percent of migrants
sending remittances
Percent of migrants
with spouse in same
city sending
remittances
Percent of migrants
with spouse NOT in
the same city sending
remittances
Men
Women
Men
Women
Men
Women
0 to 2 years
2 to 4 years
4 to 10 years
10+ years
56.9
66.2
61.7
61.1
45.4*
52.1*
62.0
39.7*
54.2
52.0
59.4
58.4
41.4
47.0
61.6
41.1*
71.8
84.0
64.9
69.5
47.6*
55.3*
56.9
35.3*
Total
61.6
52.0*
57.2
51.0*
70.7
51.4*
Panel B
Percent of income
remitted by migrants
who send any
remittances
Percent of income
remitted by migrants
with spouse in same
city sending
remittances
Percent of income
remitted by migrants
with spouse NOT in
same city sending
remittances
Men
Women
Men
Women
Men
Women
0 to 2 year
2 to 4 years
4 to 10 years
10+ years
29.0
28.0
23.7
21.1
24.0*
22.5*
20.0*
20.9
15.8
18.0
18.4
17.4
19.1
20.9
18.6
18.5
33.5
37.9
30.0
26.7
34.3
24.9*
27.1
NA
Total
25.3
21.7*
17.8
19.1
31.6
29.2
Source: 2001 CULS
* significantly different between men and women at 95% level of confidence
NA not available because cell size is too small
Table 8: Percent of migrants who are is self employed by duration, sex
and city
Total Sample
Shanghai
Wuhan
Shenyang
Fuzhou
Xian
Men
0 to 2 year
2 to 4 years
4 to 10 years
10+ years
33.3
42.9
56.3
70.3
46.9
51.6
58.3
73.3
61.1
70.0
84.8
91.4
16.7
26.6
33.0
47.4
42.0
53.1
53.4
70.8
29.6
30.5
50.8
51.1
Total
51.1
58.8
80.5
27.6
55.8
40.8
0 to 2 year
2 to 4 years
4 to 10 years
10+ years
30.4
45.3
61.5
75.7
20.0
38.0
52.2
68.4
51.7
69.1
81.6
90.5
22.6
36.4
31.6
55.6
29.3
40.6
55.1
75.0
23.1
39.5
54.0
53.8
Total
50.5
43.3
73.5
30.6
48.8
39.9
Women
Source: 2001CULS
Table 9: Percent of migrants who have changed hukou status from rural
to urban by duration, sex and city
Total Sample
Shanghai
Wuhan
Shenyang
Fuzhou
Xian
Men
0 to 2 year
2 to 4 years
4 to 10 years
10+ years
14.1
14.5
15.4
12.6
12.2
12.9
7.8
6.7
24.3
26.0
27.4
15.7
13.9
12.8
19.4
28.9
8.0
9.4
5.6
8.2
14.5
14.6
16.9
11.1
Total
14.4
9.2
23.6
16.9
7.6
15.0
0 to 2 year
2 to 4 years
4 to 10 years
10+ years
18.3
16.9
14.7
16.2
5.7
13.5
7.4
13.0
29.0
27.1
17.6
25.0
17.7
20.5
10.5
22.2
14.3
13.0
15.9
11.1
18.5
9.3
17.6
6.7
Total
16.4
9.6
23.4
17.9
13.9
14.7
Women
Source: 2001 CULS
Table 10: Comparison by sex of determinants of number of years lived in this city
Female
Age at migration
Currently married
Educational level
Spouse’s education
Number of children
First job in agriculture?
Distance to city
Any parent alive?
Could speak local
language when arrived?
Past Mandarin fair?
Past Mandarin bad?
Any family members in city
when arrived?
Any relatives in city when
arrived?
Job arranged when arrived?
Both parents peasants?
Wuhan?
Shenyang?
Fuzhou?
Xian?
Self employed?
Hukou now urban?
Spouse in city?
Constant
Observations
R-squared
-0.292***
(0.018)
3.259***
(0.642)
-0.085**
(0.040)
0.066
(0.050)
-0.217
(0.191)
1.760***
(0.543)
-0.015
(0.010)
-3.732***
(0.477)
0.751***
(0.280)
0.208
(0.258)
0.779*
(0.429)
-0.244
(0.238)
0.020
(0.223)
-0.402*
(0.220)
0.071
(0.280)
-0.286
(0.357)
-0.992**
(0.428)
-0.376
(0.363)
-0.768**
(0.384)
0.875***
(0.257)
-0.180
(0.298)
0.791**
(0.333)
12.963***
(0.911)
930
0.36
Male
-0.352***
(0.015)
6.791***
(0.519)
-0.075*
(0.038)
-0.183***
(0.044)
-0.254
(0.178)
1.764***
(0.505)
-0.020***
(0.007)
-4.778***
(0.379)
1.289***
(0.276)
0.484**
(0.245)
1.079**
(0.441)
-0.167
(0.248)
-0.007
(0.220)
0.247
(0.221)
-0.252
(0.285)
-0.328
(0.381)
-1.041***
(0.388)
0.330
(0.371)
-0.903**
(0.355)
1.064***
(0.253)
0.602*
(0.318)
0.424
(0.288)
15.278***
(0.810)
1510
0.40
Source: 2001 CULS
Standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%
Table 11: Comparison by sex of spouse in same city
Female
Age at migration
Education level
Spouse’s education
Number of children
First job in agriculture?
Distance to city
Any parent alive?
Could speak local
language when arrived?
Past Mandarin fair?
Past Mandarin bad?
Any relatives in city when
arrived?
Job arranged when arrived?
Both parents peasants?
Wuhan?
Shenyang?
Fuzhou?
Xian?
Self employed?
Hukou now urban?
Observations
0.942***
(0.015)
0.976
(0.035)
0.968
(0.038)
1.085
(0.168)
1.035
(0.461)
0.997
(0.008)
0.614
(0.234)
0.751
(0.209)
1.174
(0.314)
0.659
(0.279)
1.371
(0.300)
0.891
(0.194)
0.539*
(0.178)
2.532**
(0.983)
0.325**
(0.146)
0.814
(0.278)
0.736
(0.261)
1.442
(0.333)
0.786
(0.240)
567
Male
0.980**
(0.009)
0.977
(0.025)
0.991
(0.026)
1.097
(0.111)
0.896
(0.258)
0.998
(0.005)
0.898
(0.202)
1.362
(0.267)
1.144
(0.192)
0.890
(0.251)
1.154
(0.168)
0.921
(0.138)
0.600**
(0.121)
1.837**
(0.463)
0.236***
(0.063)
1.026
(0.243)
0.576**
(0.125)
3.254***
(0.508)
1.169
(0.256)
1006
Source: 2001 CULS
Standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1
Table 12: Comparison by sex of children in same city by migrants with children
Female
Age at migration
Education level
Spouse’s education
Number of children
First job in agriculture?
Distance to city
Any parent alive?
Could speak local
language when arrived?
Past Mandarin fair?
Past Mandarin bad?
Any relatives in city when
arrived?
Job arranged when arrived?
Both parents peasants?
School aged child?
Wuhan?
Shenyang?
Fuzhou?
Xian?
Self employed?
Hukou now urban?
Observations
0.937***
(0.020)
0.980
(0.037)
1.089**
(0.045)
1.297
(0.286)
1.163
(0.511)
0.982**
(0.009)
0.759
(0.325)
0.523**
(0.154)
0.857
(0.224)
0.961
(0.381)
1.480*
(0.311)
1.061
(0.223)
0.609*
(0.180)
0.676
(0.178)
2.387***
(0.771)
1.368
(0.736)
1.439
(0.495)
1.932*
(0.679)
1.050
(0.254)
0.829
(0.247)
458
Male
0.938***
(0.013)
0.963
(0.031)
0.956
(0.030)
1.087
(0.181)
1.186
(0.415)
1.008
(0.007)
0.515**
(0.149)
1.116
(0.248)
0.958
(0.181)
0.796
(0.259)
1.394**
(0.228)
1.156
(0.194)
0.620**
(0.138)
0.711*
(0.138)
2.980***
(0.781)
0.583*
(0.183)
0.869
(0.229)
0.986
(0.250)
2.427***
(0.457)
1.155
(0.289)
761
Source: 2001 CULS
Standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%
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