China’s Below-Replacement
Fertility: Government
Policy or Socioeconomic
Development?
Yong Cai
About half of the world’s population now lives under a demographic regime in which fertility is below the critical level of replacing the population
in the long run. In Europe and East Asia, prolonged below-replacement
fertility has already set in motion a negative population growth momentum. A substantial reduction in population size, often accompanied by
population aging and changes in composition through migration, poses an
unprecedented challenge to social and political institutions established on
a growth-based economic model. Below-replacement fertility forebodes
global demographic change with profound long-term social, economic, and
political implications.
China’s national fertility dropped below replacement level in the early
1990s and has continued its downward trend ever since, with current total
fertility estimated at around 1.5 children per woman (Cai 2008; Guo 2004,
2009; Morgan et al. 2009; US Census Bureau 2009). The importance of the
Chinese case to this new global phenomenon comes not only from its sheer
population size—with one-fifth of world population, virtually any demographic change in China has the potential for significant global consequence—
but also from China’s position in the global economic system. For example,
as “the world’s factory,” China’s domestic labor market directly affects the
world economy. China’s below-replacement fertility also has a theoretical
importance: How does the Chinese case contribute to our understanding of
the global demographic transition?
China is often considered as a special case in the literature on belowreplacement fertility (Frejka and Ross 2001; McNicoll 2001; Gu 2008). Such
treatment is based on the understanding that China’s fertility transition took
a different course from transitions in other societies: the most prominent
Population and Development Review 36(3): 419–440 (September 2010)
419
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China’s Below-Replacement Fertility
feature of China’s fertility transition is the heavy-handed government intervention (Greenhalgh and Winckler 2005; Peng 1991; Scharping 2003).
Government intervention came in three stages. First, in the wake of the devastating Great Leap Forward Famine of 1959–61, the Chinese government
started to restrict rural-to-urban migration and to promote birth planning in
urban areas (Peng 1991; Scharping 2003). Second, in the context of the global
debate on rapid population growth, the Chinese government introduced its
Wan, Xi, Shao (later, longer, fewer) policy in the early 1970s. Third, grounded
in a neo-Malthusian concern over the negative effects of population size and
growth on achieving its ambitious economic development goals (e.g., quadrupling GDP per capita in 20 years), the Chinese government launched the
controversial one-child policy in 1979–80 (Peng 1991).
The one-child policy is an unprecedented and highly controversial effort
to control population growth (Greenhalgh 2008). Supported by a well-established bureaucracy devoted to routine surveillance and policy enforcement,
the policy penetrates Chinese society from the highest level of the government down to urban neighborhoods and rural villages. Even with its later
adjustments and modifications, the draconian “one-child per couple” rule
applies to nearly two-thirds of Chinese couples today (Gu et al. 2007a). The
government euphorically claims that its birth planning policy is a great success
and boasts that the policy has prevented 400 million additional births, has led
to China’s economic boom, and is one of the country’s greatest contributions
to the battle against global warming (NPFPC 2007a; Zhao 2009).
Hyperbole aside, should we attribute the fertility decline in China exclusively or in the main to its birth planning policy? Moreover, has fertility
in China been depressed to an artificially low level by this unprecedented
restrictive policy, and, if the one-child policy is lifted, would there be a pronounced fertility rebound?
While it is generally agreed that government intervention played an
important role in China’s demographic transition (Feeney and Wang 1993;
Hesketh et al. 2005), ample evidence suggests that China’s current low fertility
is not simply a prescribed result of the one-child policy (e.g., Chen et al. 2009;
Gu and Wang 2009; Wang 2009; Zheng et al. 2009). Also, as Johnson (1994)
argued, policy alternatives to the one-child policy existed that might have produced fertility decline perhaps even more rapid than was actually achieved—
namely, by removing pronatalist elements in Chinese institutional structures.
It is of course a challenging task to empirically differentiate the role of the
country’s economic and social context from that of the birth control policy.
This is not only because policy and its enforcement interact with socioeconomic
factors, but also because the existence of a strong government intervention
may suppress the variation in fertility that would otherwise be observable.
This article first puts China’s fertility transition in a global context to examine
the effect of socioeconomic development on fertility decline. It then employs a
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Yong Cai
quasi-experimental design to contrast fertility policy in Jiangsu and Zhejiang,
two provinces at the forefront of China’s development and fertility transition,
to probe the sources of China’s below-replacement fertility.
China’s fertility decline in global context
According to classic demographic transition theory, fertility decline, often
with a delay, follows mortality decline, as the high level of fertility in the
pre-transitional period becomes unnecessary to maintain population equilibrium, and as industrialization, urbanization, and the rise in mass education alter both the institutional context and the cost/benefit calculation in
fertility decisions. Although there are many critics of this relatively simplistic
narrative—for example, of its ethnocentric nature, its failure to explain how
and where the transition first started, and the uncertainty of its end point
(Coale and Watkins 1986; Demeny 1997; Kirk 1996; van de Kaa 1996)—it is
still a powerful account of the empirical relationship between socioeconomic
development and fertility level (Bryant 2007; Jones and Tertilt 2008).
The close relationship between socioeconomic development and fertility
is evident in Figure 1, which plots the total fertility rate (TFR) against economic development measured by GDP per capita (purchasing-power-parityFIGURE 1 Total fertility rate and GDP per capita: data from 200 countries
and regions, 1975 and 2005
9
Saudi Arabia
1975
Kuwait 1975
1975
2005
Regression line
95% prediction CI
99% prediction CI
UAE 1975
6
TFR
Equatorial Guinea
2005
3
China 1975
China 2005
0
200
400
1,000
3,000
8,000
15,000 25,000 45,000
GDP per capita, current international dollars (PPP, World Bank estimates)
422
China’s Below-Replacement Fertility
based, at natural log scale) for two time points: 1975 and 2005. Most countries
in the figure cluster in a narrow band along a line defined by a simple regression model—the relationship between those two variables is so robust that it
changed little in the 30 years from 1975 to 2005.1 The figure also shows 95
and 99 percent confidence intervals around this line. Only a few exceptions
appear, notably China in 1975 and four oil-rich countries: Saudi Arabia, Kuwait, and United Arab Emirates in 1975 and Equatorial Guinea in 2005. The
oil-rich countries do not fit the general picture because income increases in
these cases do not correspond to general socioeconomic development.
The Chinese exception in 1975 calls for a different explanation. Figure
1 shows that China’s fertility in 1975 was much lower than would have been
expected from its level of economic development at the time. The explanation behind China’s unexpectedly low fertility in 1975 was the success of the
Wan, Xi, Shao program, which urged couples to marry at later ages, to prolong
birth intervals, and to have fewer children. In less than one decade, China’s
fertility fell by more than half, from a TFR of 5.8 in 1970 to 2.7 in 1978. It is
well documented that fertility control is not a foreign idea in Chinese tradition
(Lee and Wang 1999; Skinner 1997; Zhao 1997; Wang, Lee, and Campbell
1995). The roots of China’s fertility decline can be traced at least to the 1950s,
and the substantial fertility reduction in the 1970s is a result of both social
and economic changes and the implementation of a national family planning
policy (Lavely 1984; Lavely and Freedman 1990; Poston and Gu 1987).
Thirty years later, as shown in Figure 1, China’s fertility in 2005 lies
within the 95 percent confidence interval as expected from its economic development level, though still somewhat below the fitted regression line. In
other words, if the linear relationship between economic development and
fertility at the global level also applies to China, China should have reached
a relatively low level of fertility even without the one-child policy. Whereas
one can argue that the relationship between economic development and
fertility is more complex than that portrayed in this simple figure based on
cross-sectional data, it is evident that one cannot attribute China’s fertility
decline mainly to the birth planning policy, especially to the one-child policy,
unless one believes that the reproductive behavior of Chinese couples follows
an entirely different logic from that of couples elsewhere.
This conclusion is also supported by the history of China’s fertility transition. Figure 2 depicts fertility trends in China between 1950 and 2008. The
figure demonstrates that, in contrast to the rapid decline under the Wan, Xi,
Shao program, the more restrictive one-child policy implemented since 1980
did not achieve an uninterrupted fertility reduction.2 Throughout the 1980s,
when the one-child policy was most vigorously enforced, the observed fertility level in China hovered above the replacement level with visible ups and
downs, a clear reflection of the difficulties in implementing such a draconian
policy. Only in the 1990s did China’s fertility drop below the replacement
level, where it has remained.
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Yong Cai
FIGURE 2 Total fertility rate in China, observed and adjusted values,
1975–2008
8
J
J
6
J
J
J J
J
J
J
Observed
J
J
J
J
J
J
J
J
J
J
J
TFR
J
4
J
J
J
J
J
J
J
J
J
2
NPFPC adjustment
J
J J
Replacement level (TFR = 2.1)
J
J J
J
J
J J
F
F
J
F
J
FFF
FFFFF
J
J J J
J J J
J
J
0
1950
1960
1970
1980
Year
1990
F
J
J J J J J J J
2000
2010
NOTE: NPFPC = National Population and Family Planning Commission of China.
SOURCES: Observed TFR values are from survey results compiled by Yao 1995 (1950–81 from 1982 survey,
1982–87 from 1988 survey, 1988–92 from 1992 survey, and 1993 from 1997 survey), and from tabulations of
ASFRs published in China Population Statistical Yearbook, 1995–2009 based on NBS annual population change
survey/census for 1994–2008. NPFPC adjustments from NPFPC 2007b.
The attainment of below-replacement fertility in China in the early 1990s
came as a surprise to most demographers and was viewed with strong initial
suspicion stemming from concerns about birth underreporting (e.g., Feeney
and Yuan 1994; Zeng 1996). The suspicion of underreporting was grounded
on three assumptions. First, previous instances of below-replacement fertility
occurred mostly in developed countries. It was difficult to believe that China’s
fertility would reach such a low level given its development level and its
agriculture-based economy. Second, the difficulties of implementing the onechild policy in the 1980s suggested that Chinese fertility was more likely to
level off than to decline further. Third, an institutional tightening-up in China’s
birth planning policy implementation was believed to have exacerbated the
problem of underreporting: the central government intensified its birth control efforts in 1991 by making officials at each administrative level directly
responsible for meeting birth planning targets in their jurisdictions, providing
a strong incentive for local officials to hide or underreport births (Merli 1998;
Merli and Raftery 2000). The suspicion of underreporting was also supported
by widespread anecdotal evidence.
After many rounds of careful evaluation, a new consensus has been
reached (Goodkind 2008). While fertility underreporting plagued China’s
statistical system, the fertility decline in the 1990s was genuine and China’s
fertility has indeed reached a level well below replacement (Cai 2008, 2009;
Guo 2004, 2009; Guo and Chen 2007; Goodkind 2008; Morgan et al. 2009;
NBS 2006; NBS and EWC 2007; Retherford et al. 2005; Zhang and Zhao
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China’s Below-Replacement Fertility
2006). Because of the controversy over the accuracy of fertility estimates in
the past two decades, Figure 2 also includes a set of adjusted numbers provided by the National Population and Family Planning Commission of China
(2007b), which serves as an upper bound because research has confirmed
that the NPFPC’s numbers over-adjust in the effort to compensate for underreporting (Cai 2009; Goodkind 2008; Guo 2009). The adjustment does
not change the overall picture of China’s fertility decline. In fact, as shown in
Figure 2, the fertility drop in the early 1990s was a continuation of a decline
that started around 1987.
Several studies have demonstrated that fertility variation in China at
the provincial level is closely related to variations in economic and social development (e.g., Chen et al. 2009; Poston 2000; Poston and Gu 1987). In the
following analysis, taking advantage of the fact that China’s fertility policy is
enacted differently at the provincial level (Gu et al. 2007a), two provinces,
Jiangsu and Zhejiang, are used to examine the effects on fertility of birth
planning policy and socioeconomic development.
Jiangsu and Zhejiang: Similar socioeconomic
development, different birth planning policy
Jiangsu and Zhejiang provinces are located in the Yangtze delta region, next
to the economic powerhouse of Shanghai, and they share many social, economic, cultural, and historical characteristics. Jiangsu and Zhejiang are often
combined and referred to as “Jiangzhe,” since both are part of ancient Wu-Yue
culture, with the Wu dialect as the common linguistic heritage, and the region
historically experienced a high level of commercial development.
Jiangsu and Zhejiang are leading examples of China’s recent drive toward development and reach to global markets. “Jiangzhe” was one of the
first regions to initiate China’s economic reforms with booming township
and village enterprises in the 1980s and 1990s and a large inflow of foreign
investment in the 1990s and later. Jiangsu and Zhejiang (2008 populations of
76.8 and 51.2 million, respectively) are now among the most developed provinces in China. In 2008, among 31 provincial-level units in mainland China,
Jiangsu and Zhejiang ranked fourth and fifth in gross regional product per
capita, behind only three metropolitan cities, Shanghai, Beijing, and Tianjin
(NBS 2009). Jiangsu and Zhejiang are also at the forefront of the globalization of China’s economy. In 2008, exports accounted for 56 percent of gross
domestic product in Jiangsu and 54 percent in Zhejiang. The two provinces
are among the largest recipients (ranked first and fourth) of foreign direct
investment (FDI). By 2008, Jiangsu had a total of $415.9 billion in FDI; Zhejiang’s development relies more on domestic capital, but its total FDI in 2008
reached $158.3 billion (NBS 2009).
Development in Jiangsu and Zhejiang has been characterized by industrialization, improvement in education, and urbanization. For example, in
Yong Cai
425
2000 the share of the primary sector (agriculture) in GDP was 13 percent in
Jiangsu and 11 percent in Zhejiang, declining from 28 percent and 38 percent
in 1978 (SBJS 2001; SBZJ 2001). Educational attainment of women in these
two provinces has also markedly improved. According to the 1982 census,
female illiteracy rates (age 15+) stood at 55 percent and 48 percent for Jiangsu
and Zhejiang. These rates had declined to 12 percent and 13 percent by the
2000 census. Among women aged 20 to 29, primary school education had
become almost universal in 2000.
However, Jiangsu and Zhejiang have different birth planning policies.
Provinces in China have some autonomy in implementing the one-child
policy (Scharping 2003; Gu et al. 2007a). China’s Population and Family
Planning Law provides general guidelines on population planning, while
each province is allowed to stipulate conditions under which couples can
have more than one child. Jiangsu implements one of the most restrictive
versions of the one-child policy, requiring all residents, both rural and urban, to have only one child; Zhejiang’s birth planning policy takes the form
sometimes referred to as the “1.5-child policy,” with different rules applying
to rural and urban couples.
Jiangsu’s Birth Planning Regulations, enacted in 1990, list 14 exemptions permitting couples to have a second child.3 Most of the exemptions are
rare situations applicable only to a very small proportion of the population,
such as child death/disability, returning migrants from overseas, disabled
veterans, and so on. The notable exception is that couples with an agricultural household registration (hukou) can have a second child if one partner is
a single child him- or herself, and that couples with a nonagricultural hukou
can have a second child if both partners are single children. However, because
China’s fertility transition was largely underway by the early 1970s and the
one-child policy was not implemented until the early 1980s, most couples
of reproductive age around 2000 had one or more siblings; thus a very small
proportion of families qualified for this exception. Combined, the exemptions allowed in Jiangsu’s regulations should have had only minor effects on
the fertility level in 2000. According to calculations by Gu et al. (2007a), if
every couple in Jiangsu had the maximum number of children allowed by
the provincial birth planning regulations, the total fertility rate would have
been only 1.06 around the year 2000 (compared with the census-based TFR
of 0.97), barely above the one-child-per-couple rule.
Zhejiang’s Birth Planning Regulations, enacted in 1989, are very similar
to Jiangsu’s, with one major difference. While most of the exemptions to the
one-child rule listed in Zhejiang’s regulations are applicable to a very small
proportion of its population, there is one broadly applicable category: couples
with an agricultural hukou (both partners) are allowed to have a second child
if their first child is a girl. Under normal circumstances, the chance of the first
child being a girl is only slightly lower than one-half; thus couples with an
agricultural hukou could have 1.5 children on average in theory—therefore
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China’s Below-Replacement Fertility
the label “1.5-child policy.” According to Gu et al.’s (2007a) calculation, if
every couple in Zhejiang had the maximum number of children allowed,
the TFR would have been 1.47 around the year 2000 (compared with the
census-based TFR of 1.04).
As shown in the comparison between Jiangsu’s and Zhejiang’s Birth Planning Regulations, household registration, or hukou, is one of the most important elements in China’s birth planning policy (Scharping 2003; Wang 1996).
There are two general categories of hukou: agricultural and nonagricultural
(sometimes referred to as rural and urban). Originally, agricultural identified
those in the collective sector of the economy, and nonagricultural those in the
state sector. Current designations are a legacy of this dual economy surviving
the transition to a mixed economy (Wang 2005). Under this system, a person’s
hukou is determined at birth, and changing hukou is nearly impossible, with
rare exceptions such as rural residents attaining an urban hukou by passing the
national college entrance exam. A nonagricultural hukou is often associated
with certain social and economic privileges, such as the opportunity to attend
college, join the army, and have access to social welfare benefits (Cheng and
Selden 1994; Wu and Treiman 2004). Since the start of economic reform in
the late 1970s, migration, mostly rural-to-urban, and local industrialization
and urbanization have increasingly disassociated people’s hukou status from
their residence or occupation. However, the hukou system has survived decades
of spectacular economic growth and social transformation. An official hukou
remains Chinese citizens’ single most important passport to virtually all social
resources, such as education, health care, and employment. Chinese without
hukou are equivalent to undocumented persons in other societies.
The hukou system is the predominant institutional infrastructure used by
the Chinese government in many areas of public administration, including the
implementation of the one-child policy. Birth planning policy and its implementation are generally more relaxed for those with an agricultural hukou
than for those with a nonagricultural hukou, as in Zhejiang’s 1.5-child policy.
This is partly because the government has greater obligations to persons with
an urban hukou, and partly an acknowledgment of labor needs in rural areas
(Wang 1996). As one of the punishments for birth planning policy violations,
parents of out-of-plan births (births in excess of the official quota) have been
denied official household registration for their out-of-plan child, and often
have to pay extra fees to enter the system (Greenhalgh 2003).
The major difference between birth planning policies in Jiangsu and
Zhejiang, and the prominent role of hukou in policy formulation and implementation, lead to four hypotheses related to the attribution of low fertility
in China to the one-child policy. First, because Jiangsu’s fertility policy is
more restrictive than Zhejiang’s, one would expect Jiangsu to have lower
fertility. Second, because fertility policy is more uniform in Jiangsu than in
Zhejiang, one would expect smaller regional variation within Jiangsu. Third,
Yong Cai
427
because the hukou system provides the institutional basis for the birth planning policy and its implementation, one would expect a direct association
between hukou composition and fertility at the sub-provincial level, and this
association should explain a large proportion of variation in fertility within
each province. Fourth, because Zhejiang’s one-child policy is more closely
attuned to its population’s hukou composition, one would expect a stronger
association between hukou and fertility in Zhejiang. These hypotheses are
examined below, in conjunction with the effects of socioeconomic development and economic globalization on fertility.
Local variation in below-replacement fertility
in Jiangsu and Zhejiang
According to the 2000 census, Jiangsu and Zhejiang reported similarly low
fertility, far below the replacement level: TFR for the year before the census
was 0.97 for Jiangsu and 1.04 for Zhejiang.4 Although fertility underreporting
is a problem in Chinese census data, careful evaluation of empirical data in a
collaboration between China’s National Bureau of Statistics and the East-West
Center (NBS and EWC 2007) validated reported fertility levels in Jiangsu and
Zhejiang in the 1990s. The minuscule difference between reported TFRs in
these two provinces is surprising given their distinct fertility policies. While
Jiangsu’s observed fertility is largely in line with what is prescribed in its
policy, Zhejiang’s observed fertility is much lower than the policy allowance.5
To understand why fertility is similar in these two provinces, fertility variation
within each province is examined at the county level.
County-level units in this analysis include both counties and cities. In
China’s administrative system, county-level units include traditional counties
(xian), county-level cities (xianji shi), urban districts (qu), and autonomous
counties (zizhixian) and banners (qi) (groups of mainly Mongolian peoples)
in minority regions. Because of China’s rapid urbanization, jurisdictional
change occurs frequently and counties close to urban cores are often partially
or wholly reclassified as urban districts. Most official government statistics
combine urban districts (shixia qu, or districts under the direct jurisdiction of a
city) and treat the peripheral districts as counties. There were 77 county-level
units in Jiangsu and 74 in Zhejiang at the end of 2000. They are the basic
units of the following analysis.
Data for this analysis are compiled from two provincial statistical yearbooks of 2001 (SBJS 2001; SBZJ 2001), which include socioeconomic statistics
for the year 2000, and from the 2000 census compilations (NBS 2003a,b).
The definition of variables and the summary statistics used in this analysis
are presented in Table 1, with the first two columns providing summary statistics at the provincial level, and the next four columns providing summary
statistics at the county level within each province.
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China’s Below-Replacement Fertility
TABLE 1 Definitions of variables and summary statistics: data for the
provincial population and county-level means and standard deviations
Total
Variable Definition
Jiangsu Zhejiang
County-level
Jiangsu
(N = 77)
Mean S.D.
TFRTotal fertility rate
Hukou
% with agricultural hukou
Han
% Han population
GDP
GDP per capita
(1,000 RMB yuan)
FDI
Foreign direct investment
per capita (US$)
Education % women aged 20–29 with
middle school education
Net
(1 – hukou population/census
migration enumeration)*100
Zhejiang
(N = 74)
Mean S.D.
0.97
71.1
99.6
1.04
78.7
99.1
1.01
71.3
99.7
0.16 1.15
18.5 80.8
0.3 98.8
0.22
11.0
1.9
11.8
13.5
11.2
7.1 12.4
5.1
87.9
35.1
81.4 160.6 20.7
38.9
83.5
76.7
83.1
8.2 75.8
9.6
3.6
1.9
1.6
11.1 –5.2
16.9
SOURCES: TFR, Hukou, Han, Education, and Net migration variables are from two compilations of census tabulations
relating to 2000 (NBS 2003a and b). GDP and FDI data are from SBJS 2001 and SBZJ 2001.
The county-level TFR summarized in Table 1 is from the 2000 census.
Although Jiangsu and Zhejiang have different fertility policies, they have
similar variability at the county level. Even with a province-wide one-child
policy, fertility in Jiangsu varies substantially across county-level units, only
slightly less than in Zhejiang: TFRs in Jiangsu range from 0.69 to 1.49, with
a mean of 1.01 and a standard deviation of 0.16; and TFRs in Zhejiang range
from 0.68 to 1.87, with a mean of 1.15 and a standard deviation of 0.22.
While part of Zhejiang’s variation is expected, as its 1.5-child policy should
be associated with the population’s hukou composition, the large variation
across Jiangsu calls for further explanation. Extremely low fertility recorded
in some locales in the 2000 census (e.g., a county-level TFR of 0.69) is suggestive of fertility underreporting. It is possible that underreporting could be
selective and region-specific, as suggested by a study in Guangdong (Chen et
al. 2010). However, without sufficient information to assess such a possibility,
the simple working assumption adopted here is that fertility underreporting
is similar across Jiangsu and Zhejiang.
The hukou proportions and ethnic composition in Table 1 are based on
the 2000 census enumeration. Even after rapid urbanization in the 1990s,
both Jiangsu and Zhejiang were still predominantly “agricultural” based on
hukou status in 2000: 71 percent in Jiangsu and 79 percent in Zhejiang. Zhejiang not only has a large proportion of people with an agricultural hukou,
it also exhibits larger across-county variation in fertility. Because the hukou
system provides the institutional basis of the birth planning policy and its
implementation, one would expect hukou composition to be a major explanatory factor for fertility variation across counties, especially in Zhejing.
Yong Cai
429
However, there is only a moderate correlation between a local population’s
hukou composition and its fertility level, with the Pearson correlation at 0.44
for Jiangsu and 0.46 for Zhejiang.
Ethnic or non-Han minorities in general are exempted from China’s
strict one-child rule (Gu et al. 2007a). This exemption, however, is not expected to have much effect in Jiangsu and Zhejiang, because the Han majority accounts for more than 99 percent of their populations, with very limited
cross-county variation. In bivariate analysis, percent of Han has a low negative correlation with county-level fertility.
Economic development and integration with the global market vary
within each province. Based on data on GDP and foreign direct investment
published in the provincial yearbooks (SBJS 2001; SBZJ 2001), the average
GDP per capita6 among 77 county/city units in Jiangsu in 2000 was 11,200
RMB (renminbi), with a high of 30,300 (Taicang city) and a low of 3,000
(Suining county). Zhejiang’s average GDP per capita was slightly higher, at
12,400 RMB, with a high of 27,800 (Ningbo city) and a low of 4,300 (Taishun
county). Similarly, the distribution of FDI is uneven across regions. FDI tends
to concentrate more in large urban centers than in remote rural areas. For
example, according to provincial statistical yearbooks, about 28 percent of
total foreign direct investment in Zhejiang in 2000 was invested in Ningbo
(representing 2.8 percent of the total provincial population); similarly over
15 percent of total FDI in Jiangsu in 2000 went to Suzhou (1.6 percent of the
total provincial population). Overall, Jiangsu and Zhejiang are comparable in
economic development, with somewhat larger regional inequality in Jiangsu
than in Zhejiang. If the general relationship between economic development
and fertility decline found in these two provinces also applies to China, regional inequality might be an important reason behind fertility variation in
the country as a whole. In bivariate analysis, natural-log-transformed GDP
per capita and FDI per capita have statistically significant negative correlations
with county-level TFR.
Improvement in education, especially for women, has been shown
in other settings to have an important depressing effect on fertility (Axinn
and Barber 2001; Bongaarts 2003; Jeffery and Jeffery 1998). According to
the 2000 census, among women of prime reproductive age (20 to 29 years),
primary school education had become almost universal, and the proportion
with middle school or higher education reached 84 percent in Jiangsu and
77 percent in Zhejiang. Regional variation in education across Jiangsu and
Zhejiang could contribute to cross-county fertility differences.
Industrialization and urbanization are accompanied by an increase in
migration. Migration and urbanization could affect fertility both directly and
indirectly as they often interrupt or delay family formation and family function. Net migration is measured here as the difference between the censusenumerated population and the population registered in the hukou system as
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China’s Below-Replacement Fertility
a percentage of the census-enumerated population.7 A negative value means
net out-migration, and a positive value means net in-migration. In Jiangsu,
the difference is 3.6 percent, indicating substantial population growth from
migration. Zhejiang has experienced some net in-migration at the province
level (1.9 percent), but the average county-level change from migration is
negative (–5.2 percent).
The fact that Jiangsu and Zhejiang display a similar pattern of variation
in fertility across county-level units despite different policy regimes suggests
strongly that the one-child policy is not the only force behind fertility variation in China. Fertility transition experiences and routes to below-replacement fertility in other countries, and especially the similarities in Jiangsu’s and
Zhejiang’s socioeconomic development, point to the influence of the forces of
development and globalization on fertility trends in these provinces.
Explaining local fertility variation
in Jiangsu and Zhejiang
To examine factors affecting low fertility in Jiangsu and Zhejiang, OLS regression analysis is used to differentiate the effects of socioeconomic development and of birth planning policy on fertility at the county level. Four
socioeconomic development measures introduced above are included in the
analysis: economic development measured by GDP per capita, the influence
of globalization measured by FDI per capita, and other aspects of social development measured by women’s education level (education) and by changes
in migration and urbanization (net migration).
To capture the effects of policy and policy implementation, three policyrelated variables are used: province (Jiangsu vs. Zhejiang, with Jiangsu coded
as 0), hukou (percent of population with an agricultural hukou), and Han (percent of population that is Han). The contrast between Jiangsu and Zhejiang
measures the overall policy difference between the two provinces. It would
be ideal to have a direct measure of fertility policy for each county-level unit
as Gu et al. (2007a) had at the prefecture level, but no such data were ever
published. The percent of the population with an agricultural hukou is used as
a proxy for policy based on the prominent role of hukou in policy formulation
and implementation and on the strong empirical association between policy
and a population’s agricultural hukou at the prefecture level.8 Although ethnic
composition is not expected to have much effect in Jiangsu and Zhejiang, it
is included as a control measure because She minorities in Zhejiang are concentrated in a few counties.
A stepwise approach is adopted to differentiate the effects of policy and
development on fertility. The first two steps examine the policy effects by
including three policy-related variables. In the later steps, the development
and net migration variables are added to the model. To account for a plau-
431
Yong Cai
sible curvilinear relationship between economic development and fertility,
GDP per capita and FDI per capita are transformed to a logarithmic scale.9
The purpose of this regression exercise is to examine both the coefficient of
individual variables and the overall model fit (R2). Because birth policy is
implemented on the basis of administrative boundaries, regression models
are fitted using the county as the unit of analysis without weighting.10 The
results are presented in Table 2.
The first two models examine policy effects. Model 1 confirms what
would be predicted from the policy difference between Jiangsu and Zhejiang:
fertility is slightly higher in Zhejiang than in Jiangsu. Although still statistically significant after controlling for a population’s hukou composition and
ethnic composition, the difference is very small in absolute terms: only 0.07
children per woman. There is a positive relationship between a population’s
hukou composition and fertility: the higher the percentage of the population
with an agricultural hukou, the higher the fertility. A one-percentage-point
increase in the proportion with an agricultural hukou is associated with a
fertility increase of 0.005 children per woman. Although the effect of ethnic
composition on fertility is consistent with the general direction of China’s
birth planning policy—that is, policy is more relaxed for ethnic minorities—
the effect is not statistically significant. Together, the three variables measuring the policy effects explain 28 percent of fertility variation across 151
county-level units in the two provinces.
An interaction term between province and hukou is introduced in Model
2 to accommodate the fact that the birth planning policy is implemented dif-
Table 2 Regression models based on county-level data predicting fertility
(TFR) in Jiangsu and Zhejiang (N = 151)
Variable
Model 1
Model 2
Model 3
Zhejiang
0.071*
–0.281+
–0.175
% agricultural hukou
0.005***
Model 4
Model 5
Province (Jiangsu as reference)
% Han population
–0.016
Province * hukou
0.004*** –0.001
–0.013
0.005*
0.038
–0.002*
0.013 0.012
0.004*
0.001
log(GDP per capita)
–0.178*** –0.108** –0.026
log(FDI per capita)
–0.025**
% women aged 20–29 with
middle school education
% net migration
Intercept
R2
Note: + p<.1, * p<.05, ** p<.01, *** p<.001
2.197*
0.277
2.026+
0.299
1.451+
0.606
–0.019*
0.000
–0.026***
–0.002
–0.007*** –0.007***
1.026
0.714
1.491***
0.667
432
China’s Below-Replacement Fertility
ferently in Jiangsu and Zhejiang. According to results in Model 1, the difference between county-level units where everyone has an agricultural hukou
and units where everyone has a nonagricultural hukou is about 0.5 children
per women after controlling for province and ethnic composition—exactly
what one would expect given the difference between the strict one-child
policy and the 1.5-child policy. However, as discussed earlier, the 1.5-child
policy was implemented in Zhejiang, but not in Jiangsu; thus the relationship
between a population’s hukou composition and fertility could be different for
Jiangsu and Zhejiang. Model 2 confirms such an observation. In fact, the fertility difference in Model 1 between the two provinces is largely driven by this
interaction. According to Model 2, the effect of hukou composition on fertility
is more than twice as strong in Zhejiang as in Jiangsu, indicated by the fact
that the coefficient of the interaction term is slightly higher than the coefficient for hukou composition. Adding this interaction term, however, has only
a limited effect on model fit, as indicated by R2, which increases from 0.277 in
Model 1 to 0.299 in Model 2. In other words, policy difference at the provincial level and the two most important determinants of policy implementation
at the county level explain at most 30 percent of fertility variation.
The effects of socioeconomic development on fertility can be seen when
the indicators are introduced in the following steps. Model 3 adds two variables: log-transformed GDP per capita, measuring overall economic development; and log-transformed FDI per capita, measuring the potential influence
of globalization. Adding these two variables greatly improves the model fit:
the model now explains 61 percent of the variation in fertility. Both indicators are statistically significant and are in the direction observed in other
societies. More highly developed areas have lower fertility, after controlling
for other variables in the model. Controlling for policy and economic development, greater exposure to global influence is also associated with lower
fertility. Hukou composition now has a statistically significant effect on fertility only in Zhejiang, which is consistent with the policy difference between
these two provinces. Because Zhejiang’s 1.5-child policy is explicitly linked
to hukou, those with an agricultural hukou have higher fertility. This is not
true in Jiangsu.
The role of socioeconomic factors is further illustrated with the inclusion of two additional socioeconomic measures in Model 4: female education
and net migration. Adding these two variables further improves the model fit
from 61 percent to 71 percent. The female education variable has virtually no
effect on fertility. This is likely because educational improvement took place
in close association with other aspects of socioeconomic development already
captured in the analysis. It is also possible that educational differentiation in
fertility observed in other societies (Bongaarts 2003) may be depressed in
China with both universal access to education and ultra-low fertility.11 The
net migration variable has a statistically significant negative effect on fertil-
Yong Cai
433
ity. A one-percentage-point increase in population growth due to migration
is associated with a fertility decline of 0.007 children per woman. In other
words, areas losing population to migration are likely to have higher fertility
than areas gaining from migration, after controlling for other factors. The
current migration process in China is dominated by migration from rural to
urban areas and from less developed to more developed areas. The selective
nature of migration contributes to the differentiation of fertility across various levels of development, because migration is often associated with delayed
marriage and childbearing for migrants and with leaving (or sending back)
pregnant or childrearing women in (or to) places of origin (Guo 2009; Hull
and Hartanto 2009).
To contrast the explanatory power of policy variables with that of the
development variables, Model 5 includes only development variables. Obviously, Model 5 is an incompletely specified model, hence we should be careful
interpreting its coefficients. However, comparing this model with other models is very telling about the effects of policy and development on fertility.The
absence of policy variables in Model 5 in comparison with Model 4 has a very
limited effect on R2: a change from 0.714 to 0.667. In other words, although
the policy variables in Model 4 are important in model specification, what
they pick up in terms of variation in fertility is minuscule after controlling for
development variables.
Together, the results of the regression analysis summarized in Table 2
reveal a clear set of relationships between policy, socioeconomic development,
and low fertility in Jiangsu and Zhejiang provinces. The pronounced policy
difference between Jiangsu and Zhejiang did not translate into a substantial
difference in observed fertility levels. After controlling for other factors, the
fertility difference between these two provinces is small. Similarly, the most
important factor in determining policy influence, hukou status, also has only a
small effect on observed fertility. In contrast, the socioeconomic indicators are
shown to have much stronger effects on fertility. FDI, generally expected to be
highly correlated with measures of development, has a statistically significant
effect on fertility even after controlling for other socioeconomic development
factors, suggesting an independent influence of global economic connection.
A key finding from this exercise is that these development factors are so
powerful that, combined, they explain a much larger proportion of fertility
variation in Jiangsu and Zhejiang than do the policy factors.
Conclusion and discussion
Jiangsu and Zhejiang provinces are the forerunners of China’s socioeconomic
development and economic globalization: what has happened there and in
other highly developed areas in China is likely to be indicative of coming developments in other provinces. Given the rapid pace of social and economic
434
China’s Below-Replacement Fertility
change in China, it is highly likely that what was observed in Jiangsu and
Zhejiang in 2000 has already spread to other parts of China.
The policy contrast between Jiangsu and Zhejiang, and the powerful
association between socioeconomic development and fertility, offer compelling evidence for understanding the current fertility situation in China.
China’s drive to below-replacement fertility might have been jump-started
and accelerated by a heavy-handed government policy, but policy is not the
key factor behind the very low fertility that has emerged. The comparison
presented here suggests that socioeconomic development plays the decisive
role in the transition to below-replacement fertility in China, as it does in
other societies. The empirical evidence from Jiangsu and Zhejiang strongly
supports this argument.
The analysis demonstrates that policy is not the dominant, let alone the
sole factor determining local fertility variation. While a population’s hukou status and ethnic composition are the clear links between provincial regulations
and local fertility policy, other factors affect policy implementation (Short
and Zhai 1998). This is not to gainsay the influence of government policy on
fertility reduction, nor to endorse so-called development determinism. With
institutional supports from the Chinese government’s active participation
in and relentless propaganda on population control, rapid socioeconomic
development and globalization have brought about an ideational shift from
resisting to embracing the “small family” ideal (McNicoll 2001; Merli and
Smith 2002; Tsui 2001; Zhang 2007). At the national level, ideal family size
has declined to around 1.7 children in 2006 (NPFPC 2007c); the number is
even lower in more developed areas where one child is now the dominant
mode of ideal family size (Zheng et al. 2009).
The results presented here are based on aggregated cross-sectional data,
thus they provide no details on the causal mechanisms moving from socioeconomic development and globalization to fertility.12 They nevertheless present
strong empirical support for the association between socioeconomic development and fertility decline. Micro-level longitudinal studies should help illuminate the process of family fertility decisions. Other studies in Jiangsu province
have suggested that the economic squeeze experienced by individuals and
families in a fast-changing and highly competitive society is one of the most
important reasons for young couples delaying or even forgoing childbearing
(Gu et al. 2007b; Zheng et al. 2009). Although the causal mechanisms linking socioeconomic development and low fertility are necessarily complex,
the interpretations offered in many settings—such as the calculation of costs
and benefits associated with childbearing and childrearing; social and institutional contexts that determine a child’s value (Bryant 2007; Caldwell and
Schindlmayr 2003; Johnson 1994; Morgan and Taylor 2006); and ideational
change in the broader context of globalization (Lesthaeghe 1995; Lutz et al.
2006; Wang et al. 2008)—also apply to China.
Yong Cai
435
In recent years the debate on China’s demographic future has focused on
whether and how to alter the now three-decade-long one-child policy (Morgan
et al. 2009; Zeng 2007; Wang 2005). Launched as an emergency measure to
achieve a purely economic goal (Greenhalgh 2008), the policy paid little attention to its social costs and the long-term demographic effects, such as accelerated
population aging, distorted sex ratios, and changes to the Chinese family and
kinship system (Cai and Lavely 2003; Wang 2009; Zhao and Guo 2007). One
of the main obstacles to reforming China’s birth-planning policy is a concern
that fertility in China would rebound to a much higher level should the policy
be relaxed (Jiang 2006; Zhang 2007). This concern in turn is based on the belief
that the low fertility achieved in China is a result of the high-pressure policy.
The analysis above suggests that such a belief is based on a misconception.
Below-replacement fertility in China, as in other societies, is driven to a great
extent by the increasingly global forces of social and economic development.
Notes
Figures in this article are available in color in
the electronic edition of the journal.
This research was supported by the John
D. and Catherine T. MacArthur Foundation.
An earlier version of this article was presented
at the 2008 Shanghai Forum. I am grateful to
Wang Feng and William Lavely for their encouragement and helpful comments.
1 For 1975, the linear relationship between economic development (DVP) and fertility can be summarized in a simple regression
model as TFR = –1.298 * DVP + 14.5, which
accounts for 48.7 percent of variation in fertility. Similarly, for 2005 the linear relationship
is defined by TFR = –1.164 * DVP + 13.3, which
accounts for 65.8 percent of variation in fertility. The combined data produce a linear relationship TFR = –1.260 * DVP + 14.2. When year
is included in the model as a dummy variable
and as an interaction term with development,
neither of them is statistically significant, suggesting that there is no significant change in
the relationship between development and
fertility from 1975 to 2005. The difference
in R2 between the two time points is mostly
a function of a few outliers as identified in
Figure 1.
2 At almost the same time as China
launched its one-child policy, China’s new
marriage law set the legal marriage age to
20 for women and 22 for men, lower than
the de facto marriage age requirement
used in the promotion of the “later, longer,
fewer” policy. The one-child policy probably
has mitigated a resurgence of fertility that
might have resulted from the removal of the
fertility-depressing effect of delayed marriage
and childbearing.
3 Jiangsu updated its regulations in 2002,
but made only minor modification and adjustment in the list of exemptions for having a
second child.
4 The provincial TFRs and county-level
TFRs used in this article are based on the census question on births in the year before the
2000 census. The location of a birth during the
last year is determined by where the woman
was enumerated in the 2000 census. For example, if a woman has an agricultural hukou
but was enumerated in a city, the birth is classified in the census as having occurred in the
city, even if the woman returned home temporarily to have the baby and then returned to
the city, which may be in a different county.
5 Period-based TFR is not always directly
comparable to so-called policy-prescribed
fertility because the latter takes a cohort approach. However, the difference between
observed fertility and policy-prescribed fertility in Zhejiang is far larger than would be
indicated by the tempo effect observed at the
national level.
436
6 The GDP per capita figures used here
are different from those published in the
statistical yearbooks. In the latter, the GDP
per capita figure uses the registered hukou
population as the denominator, which often
excludes large numbers of migrants and thus
leads to an inflated GDP per capita in urban
areas (Chan and Wang 2008). Population
enumerated in the 2000 census is used as the
denominator.
7 The 2000 census counted everyone
living in the area for more than six months,
and those who had not lived in the area for
more than six months but had left their place
of hukou registry for more than six months. In
addition, the 2000 census provided information on the local hukou population, including
everyone registered in the local area, who
may or may not have resided in the area at
the time of the census. Information on the
registered population is published in the NBS
(2003b) tabulation, titled “Table 1-3: Status of
registered population by sex and region.”
8 The correlation between prefecturelevel policy reported in Gu et al. (2007a) and
the population’s hukou composition reported
in the 2000 census is 0.97 in Zhejiang. Given
Jiangsu’s strict one-child policy, Gu et al.
China’s Below-Replacement Fertility
(2007a) reported virtually no variation across
prefectures in Jiangsu.
9 Five counties reported no FDI in 2000.
A small amount is added to them to compensate for the missing values in log transformation.
10 Population-weighted regressions yield
very similar results.
11 Other specifications of the education
variable, such as percent of females with high
school education and percent of females with
college education, were tested. The results are
virtually the same as those presented here.
12 For example, to support causality, it
is useful to have a time lag in the predicting
variables in the model. Because of data limitations, it is not possible to create a time lag
for variables derived from the census. GDP
and FDI data for previous years are available
for most of the county-level units used in the
analysis. For the units with both 1999 and
2000 data, the correlations of GDP and FDI
per capita between 1999 and 2000 are higher
than 0.95. A sensitivity analysis compared the
models presented in the article and models using GDP and FDI statistics for 1999. The results
are essentially the same.
References
Axinn, William and Jennifer Barber. 2001. “Mass education and fertility transition,” American
Sociological Review 66: 481–505.
Bongaarts, John. 2003. “Completing the fertility transition in the developing world: The role
of educational differences and fertility preferences,” Population Studies 57: 321–335.
Bryant, John. 2007. “Theories of fertility decline and the evidence from development indicators,” Population and Development Review 33: 101–127.
Cai, Yong. 2008. “Assessing fertility levels in China using variable-r method,” Demography
45(2): 371–381.
———. 2009. “Do enrollment statistics provide a gold standard for Chinese fertility estimates?,”
Population Research 33(4): 22–33. In Chinese.
Cai, Yong and William Lavely. 2003. “China’s missing girls: Numerical estimates and effects on
population growth,” China Review 3(Fall): 13–29.
Caldwell, John C. and Thomas Schindlmayr. 2003. “Explanations of the fertility crisis in modern societies: A search for commonalities,” Population Studies 57(3): 241–263.
Chan, Kam Wing and Man Wang. 2008. “Remapping China’s regional inequalities, 1990–2006:
A new assessment of de facto and de jure population data,” Eurasian Geography and Economics 49(1): 21–56.
Chen, Jiajian, Robert D. Retherford, Minja Kim Choe, Li Xiru, and Hu Ying. 2009. “Province
level variation in the achievement of below-replacement fertility in China,” Asian Population Studies 5(3): 309–327.
Yong Cai
437
Chen, Jiajian, Robert D. Retherford, Minja Kim Choe, Xiru Li, and Hongyan Cui. 2010. “Effects of population policy and economic reform on the trend in fertility in Guangdong
province, China, 1975–2005,” Population Studies 64(1): 43–60.
Cheng, Tiejun and Mark Selden. 1994. “The origins and social consequences of China’s hukou
system,” The China Quarterly 139: 644–668.
Coale, Ansley J. and Susan Cotts Watkins. 1986. The Decline of Fertility in Europe: The Revised
Proceedings of a Conference on the Princeton European Fertility Project. Princeton, NJ: Princeton
University Press.
Davis, Kingsley. 1945. “The world demographic transition,” Annals of the American Academy of
Political and Social Science 237: 1–11.
———. 1963. “The theory of change and response in modern demographic history,” Population
Index 29: 345–366.
Demeny, Paul. 1997. “Replacement-level fertility: The implausible endpoint of the demographic
transition,” in Gavin W. Jones et al. (eds.), The Continuing Demographic Transition. Oxford:
Clarendon Press, pp. 94–110.
———. 2003. “Population policy dilemmas in Europe at the dawn of the twenty-first century,”
Population and Development Review 29(1): 1–28.
Feeney, Griffith and Wang Feng. 1993. “Parity progression and birth intervals in China: The
influence of policy in hastening fertility decline,” Population and Development Review 19:
61–101.
Feeney, Griffith, and Yuan Jianhua. 1994. “Below replacement fertility in China? A close look
at recent evidence,” Population Studies 48: 381–394.
Frejka, Tomas and John Ross. 2001. “Paths to subreplacement fertility: The empirical evidence,”
Population and Development Review 27(Supp.): 213–254.
Goodkind, Daniel. 2008. “Fertility, child underreporting, and sex ratios in China: A closer look
at the current consensus,” paper presented at the Annual Meeting of the Population Association of America, New Orleans, 17–19 April.
Greenhalgh, Susan. 2003. “Planned births, unplanned persons: ‘Population’ in the making of
Chinese modernity,” American Ethnologist 30: 196–215.
———. 2008. Just One Child: Science and Policy in Deng’s China. Berkeley: University of California
Press.
Greenhalgh, Susan and Edwin A. Winckler. 2005. Governing China’s Population: From Leninist to
Neoliberal Biopolitics. Stanford: Stanford University Press.
Gu, Baochang. 2008. “The arrival of low fertility in China,” in Gavin Jones, Paulin Tay
Straughan, and Angelique Chan (eds.), Ultra-low Fertility in Pacific Asia: Trends, Causes, and
Policy Issues. London and New York: Routledge, pp. 73–95.
Gu, Baochang and Wang Feng (eds.). 2009. An Experiment of Eight Million People—Reports from
Areas with Two-Child Policy. Beijing: China Social Sciences Academic Press. In Chinese.
Gu, Baochang, Wang Feng, Guo Zhigang, and Zhang Erli. 2007a. “China’s local and national
fertility policies at the end of the twentieth century,” Population and Development Review
33(1): 129–147.
Gu, Baochang, Zheng Zhenzhen, Wang Feng, and Yong Cai. 2007b. “Globalization, policy
intervention, and reproduction: Below replacement fertility in China,” paper prepared
for presentation at the Annual Meeting of the Population Association of America, New
York, 29–31 March.
Guo, Zhigang. 2004. “Research and discussion on Chinese fertility level in 1990s,” Population
Research 2004(2): 10–19. In Chinese.
———. 2009. “How come the notable ‘pick up’ of the fertility-rates in recent years? Evaluation
on the 2006 National Population and Family Planning Survey,” China Journal of Population
Science 2009 (2): 2–15. In Chinese.
Guo, Zhigang and Wei Chen. 2007. “Below replacement fertility in mainland China,” in Zhong­
wei Zhao and Fei Guo (eds.), Transition and Challenge: China’s Population at the Turn of the
Twenty-First Century. Oxford University Press, pp. 54–70.
438
China’s Below-Replacement Fertility
Hesketh, Therese, Lu Li, and Weixing Zhu. 2005. “The effect of China’s one-child family policy
after 25 years,” New England Journal of Medicine 353(11): 1171–1176.
Huang, Philip C. 1990. The Peasant Family and Rural Development in the Yangzi Delta, 1350–1988.
Stanford: Stanford University Press.
Hull, Terence and Wendy Hartanto. 2009. “Resolving contradictions in Indonesian fertility
estimates,” Bulletin of Indonesian Economic Studies 45: 61–71.
Jeffery, R. and P. Jeffery. 1998. “Silver bullet or passing fancy? Girls’ schooling and population
policy,” in Cecile Jackson and Ruth Pearson (eds.), Feminist Visions of Development: Gender,
Analysis and Policy. London/New York: Routledge, pp. 239–258.
Jiang, Zhenghua. 2006. “Thinking ahead of population policies in the new era,” Chinese Journal
of Population Science 6: 2–5. In Chinese.
Johnson, D. Gale. 1994. “Effects of institutions and policies on rural population growth with
application to China,” Population and Development Review 20(3): 503–531.
Jones, L. E. and M. Tertilt. 2008. “An economic history of fertility in the U.S.: 1826–1960,” in
P. Rupert (ed.), Frontiers of Family Economics, Vol. 1. Bingley, UK: Emerald Press.
Kirk, Dudley. 1996. “Demographic transition theory,” Population Studies 50: 361–387.
Lavely, William. 1984. “The rural Chinese fertility transition: A report from Shifang Xian,
Sichuan,” Population Studies 38(3): 365–384.
Lavely, William and Ronald Freedman. 1990. “The origins of the Chinese fertility decline,”
Demography 27(3): 357–367.
Lee, James and Wang Feng. 1999. One Quarter of Humanity: Malthusian Mythology and Chinese
Realities 1700–2000. Cambridge, MA: Harvard University Press.
Lesthaeghe, Ron. 1995. “The second demographic transition in Western countries: An interpretation,” in Karen O. Mason and A. M. Jensen (eds.), Gender and Family Change in
Industrial Countries. Oxford: Clarendon Press, pp. 17–62.
Lutz, Wolfgang, Brian O’Neill, and Sergei Scherbov. 2003. “Europe’s population at a turning
point,” Science 299(March 28): 1991–1992.
Lutz, Wolfgang, Vegard Skirbekk, and Maria Rita Testa. 2006. “The
��������������������������������
low fertility trap hypothesis,” Vienna Yearbook of Population Research. Vienna: Austrian Academy of Sciences Press.
McNicoll, Geoffrey. 2001. “Government and fertility in transitional and post-transitional societies,” Population and Development Review 27(Supp.): 129–159.
Merli, M. Giovanna. 1998. “Underreporting of births and infant deaths in rural China: Evidence from field research in one county of Northern China,” The China Quarterly 155:
637–655.
Merli, M. Giovanna and Adrian E. Raftery. 2000. “Are births underreported in rural China?
Manipulation of statistical records in response to China’s population policies,” Demography 37: 109–126.
Merli, M. Giovanna and Herbert L. Smith. 2002. “Has the Chinese family planning program
been successful in changing fertility preferences?,” Demography 39: 557–572.
Morgan, S. Philip and Miles Taylor. 2006. “Low fertility at the turn of the twenty-first century,”
Annual Review of Sociology 32: 375–399.
Morgan, S. Philip, Guo Zhigang, and Sarah R. Hayford. 2009. “China’s below-replacement
fertility: Recent trends and future prospects,” Population and Development Review 35(3):
605–629.
National Bureau of Statistics of China (NBS). 1991–2009. China Population Statistical Yearbook.
Beijing: China Statistics Press.
———. 2003a. The Complete Collection of National and Provincial Population Census Data Assembly.
Electronic version. University of Michigan China Data Center, CDC-S-2003-201.
———. 2003b. The Complete Collection of County/District Population Census Data Assembly. Electronic
version. University of Michigan China Data Center, CDC-S-2004-135.
———. 2006. Population of China 2005. Beijing: China Statistics Press.
National Bureau of Statistics of China and East-West Center (NBS and EWC). 2007. Fertility
Estimates for Provinces of China, 1975–2000. Beijing: China Statistics Press.
Yong Cai
439
National Population and Family Planning Commission of China (NPFPC). 2007a. Report on
the National Strategy of Population Development. «http: //www.gov.cn/gzdt/2007-01/11/
content_493677.htm». In Chinese.
———. 2007b. Data Handbook for Population and Family Planning 2006. Beijing: China Population Press. In Chinese.
———. 2007c. Major Figures from the 2006 National Population and Family Planning Survey. «http://
www.chinapop.gov.cn/fzgh/tjgz/200806/t20080626_154455.htm». In Chinese.
Notestein, Frank W. 1945. “Population—The long view,” in T. Schultz (ed.), Food for the World.
Chicago: Chicago University Press.
———. 1983[1964]. “Frank Notestein on population growth and economic development,”
Population and Development Review 9: 345–360.
Peng, Xizhe. 1991. Demographic Transition in China. Oxford: Clarendon Press.
Poston, Dudley L. 2000. “Social and economic development and the fertility transitions in
Mainland China and Taiwan,” Population and Development Review 26(Supp.): 40–60.
Poston, Dudley and Baochang Gu. 1987. “Socioeconomic development, family planning, and
fertility in China,” Demography 24: 531–551.
Retherford, Robert, Minja Kim Choe, Jiajian Chen, Li Xiru, and Cui Hongyan. 2005. “How
far has fertility in China really declined?,” Population and Development Review 31(1):
57–84.
Scharping, Thomas. 2003. Birth Control in China, 1949–2000: Population Policy and Demographic
Development. London/New York: Routledge.
———. 2007. “The politics of numbers: Fertility data in recent decades,” in Zhongwei Zhao
and Fei Guo (eds.), Transition and Challenge: China’s Population at the Turn of the Twenty-First
Century. Oxford University Press, pp. 34–53.
Short, Susan and Zhai Fengying. 1998. “Looking locally at China’s one-child policy,” Studies
in Family Planning 29: 373–387.
Skinner, G. William. 1997. “Family systems and demographic processes,” in David I. Kertzer
and Tom Fricke (eds.), Anthropological Demography: Toward a New Synthesis. Chicago: University of Chicago Press, pp. 53–95.
Statistics Bureau of Jiangsu Province (SBJS). 2001. Jiangsu Statistical Yearbook 2001. Beijing:
China Statistics Press. In Chinese.
Statistics Bureau of Zhejiang Province (SBZJ). 2001. Zhejiang Statistical Yearbook 2001. Beijing:
China Statistics Press. In Chinese.
Stolnitz, George. 1964. “The demographic transition,” in Ronald Freedman (ed.), Population:
The Vital Revolution. New York: Doubleday.
Tsui, Amy Ong. 2001. “Population policies, family planning programs, and fertility: The record,”
Population and Development Review 27(Supp.): 184–204.
United Nations. 2009. World Population Prospects: The 2008 Revision, Executive Summary. New
York: United Nations, Department of Economic and Social Affairs, Population Division,
Publication St/ESA/SER.A/287/ES.
United Nations Common Database (UNCDB). «http://unstats.un.org/unsd/cdb/». Accessed
26 February 2008.
United States Census Bureau. 2009. China’s Population to Peak at 1.4 Billion around 2026. US
Census Bureau News CB09-191, 15 December.
van de Kaa, Dirk J. 1996. “Anchored narratives: The story and findings of half a century of
research into the determinants of fertility,” Population Studies 50: 389–432.
———. 2001. “Postmodern fertility preferences: From changing value orientation to new
behavior,” Population and Development Review 27(Supp.): 290–331.
Wang, Fei-Ling. 2005. Organizing Through Division and Exclusion: China’s Hukou System. Stanford:
Stanford University Press.
Wang, Feng. 1996. “A decade of one-child policy in China: Achievements and implications,”
in Alice Goldstein and Wang Feng (eds.), The Many Facets of Demographic Change. Boulder:
Westview Press, pp. 97–120.
440
China’s Below-Replacement Fertility
———. 2005. “Can China afford to continue its one-child policy?,” Asia Pacific Issues, No 77,
East-West Center.
———. 2009. “The future of the demographic overachiever: Long term implications of the
demographic transition in China,” paper presented at the Conference on the Long Term
Implications of the Demographic Transition, Madrid, Spain, 24–26 September.
Wang, Feng, Yong Cai, Zhenzhen Zheng, and Baochang Gu. 2008. “Expanding production,
shrinking reproduction: Does globalization have anything to do with below replacement
fertility in China?,” paper presented at the International Conference on Low Fertility and
Reproductive Health in East and Southeast Asia, IUSSP and Nihon University, Tokyo.
Wang, Feng, Guo Zhigang, and Mao Zhuoyan. 2008. “A preliminary study of China’s negative
population growth momentum in the 21st century,” Population Research 32(6): 7–17. In
Chinese.
Wang, Feng, James Lee, and Cameron Campbell. 1995. “Marital fertility control among the
Qing nobility: Implications for two types of preventive check,” Population Studies 49(3):
383–400.
Wang, Jinying, Yunyan He, Zhicheng Wang, and Chengrong Duan. 2004. “An assessment of
total fertility rate of the provinces of China in 2000,” Population Research 28(2): 20–28.
In Chinese.
Wilson, Chris. 2004. “Fertility below replacement level,” Science 304: 207–208.
Wu, Xiaogang and Donald J. Treiman. 2004. “The household registration system and social
stratification in China: 1955–1996,” Demography 41: 363–384.
Yao, Xinwu. 1995. Fertility Data of China, CPIRC/UNFPA. Beijing: China Population Press. In
Chinese.
Zeng Yi. 1996. “Is fertility in China in 1991–92 far below replacement level?,” Population Studies 50: 27–34.
———. 2007. “Options for fertility policy transition in China,” Population and Development
Review 33(2): 215–246.
Zhang, Guangyu and Zhongwei Zhao. 2006. “Reexamining China’s fertility puzzle: Data collection and quality over the last two decades,” Population and Development Review 32:
293–321.
Zhang, Hong. 2007. “From resisting to ‘embracing?’ the one-child rule: Understanding new
fertility trends in a central China village,” China Quarterly 192: 855–875.
Zhang, Weiqing. 2007. “Seeking a path with Chinese characteristics for better coordination in
solving population problems,” Population Research 31(3): 1–6. In Chinese.
Zhao, Baige. 2009. News Conference December 9th, 2009 in Copenhagen, reported in “Population control called key to deal” by China Daily on December 10th, 2010.
Zhao, Zhongwei. 1997. “Deliberate birth control under a high-fertility regime: Reproductive
behavior in China before 1970,” Population and Development Review 23: 729–767.
Zhao, Zhongwei and Fei Guo (eds). 2007. Transition and Challenge: China’s Population at the
Beginning of the 21st Century. Oxford University Press.
Zheng, Zhenzhen, Yong Cai, Wang Feng, and Baochang Gu. 2009. “Below-replacement fertility and childbearing intention in Jiangsu Province, China,” Asian Population Studies 5(3):
329–347.
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