PoPulation and develoPment Review 36(3) : 419–440 (SePtembeR 2010) 419

China’s Below-Replacement Fertility: Government Policy or Socioeconomic Development?

Yong Cai

about half of the world’s population now lives under a demographic re-gime 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 momen-tum. 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 demo-graphic 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 below-replacement 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

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feature of China’s fertility transition is the heavy-handed government in-tervention (Greenhalgh and winckler 2005; Peng 1991; Scharping 2003). Government intervention came in three stages. First, in the wake of the dev-astating 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., qua-drupling 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-estab-lished bureaucracy devoted to routine surveillance and policy enforcement, the policy penetrates Chinese society from the highest level of the govern-ment 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 ex-clusively 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 pro-nounced 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 pro-duced 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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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 equi-librium, and as industrialization, urbanization, and the rise in mass educa-tion 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 eco-nomic development measured by GdP per capita (purchasing-power-parity-

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FIGURE 1 Total fertility rate and GDP per capita: data from 200 countries and regions, 1975 and 2005

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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 regres-sion 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, Ku-wait, 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 explana-tion 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 de-velopment 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 tran-sition. 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 fertil-ity 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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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 one-child 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 con-trol 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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FIGURE 2 Total fertility rate in China, observed and adjusted values, 1975–2008

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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.

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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 pro-vided 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 un-derreporting (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 de-velopment (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, eco-nomic, 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 to-ward 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 prov-inces 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 globaliza-tion 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; Zhe-jiang’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 indus-trialization, improvement in education, and urbanization. For example, in

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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 ur-ban, 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 exemp-tions 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 agricul-tural 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 exemp-tions 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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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 Plan-ning Regulations, household registration, or hukou, is one of the most impor-tant 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 imple-mentation 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 imple-mentation, 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,

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because the hukou system provides the institutional basis for the birth plan-ning 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 develop-ment 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 year-books 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 sta-tistics at the provincial level, and the next four columns providing summary statistics at the county level within each province.

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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 sug-gestive 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. Zhe-jiang 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 ex-planatory factor for fertility variation across counties, especially in Zhejing.

TABLE 1 Definitions of variables and summary statistics: data for the provincial population and county-level means and standard deviations

County-level

Jiangsu Zhejiang Total (N = 77) (N = 74)

Variable Definition Jiangsu Zhejiang Mean S.D. Mean S.D.

tFR total fertility rate 0.97 1.04 1.01 0.16 1.15 0.22Hukou % with agricultural hukou 71.1 78.7 71.3 18.5 80.8 11.0Han % Han population 99.6 99.1 99.7 0.3 98.8 1.9GdP GdP per capita (1,000 Rmb yuan) 11.8 13.5 11.2 7.1 12.4 5.1Fdi Foreign direct investment per capita (uS$) 87.9 35.1 81.4 160.6 20.7 38.9education % women aged 20–29 with middle school education 83.5 76.7 83.1 8.2 75.8 9.6net (1 – hukou population/census migration enumeration)*100 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.

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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 ex-pected to have much effect in Jiangsu and Zhejiang, because the Han major-ity accounts for more than 99 percent of their populations, with very limited cross-county variation. in bivariate analysis, percent of Han has a low nega-tive 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, re-gional 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 func-tion. net migration is measured here as the difference between the census-enumerated population and the population registered in the hukou system as

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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 varia-tion in China. Fertility transition experiences and routes to below-replace-ment 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 re-gression analysis is used to differentiate the effects of socioeconomic devel-opment 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 devel-opment 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 policy-related variables are used: province (Jiangsu vs. Zhejiang, with Jiangsu coded as 0), hukou (percent of population with an agricultural hukou), and Han (per-cent 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 con-centrated 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-

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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 statisti-cally 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 mea-suring 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 Model 4 Model 5

Province (Jiangsu as reference)

Zhejiang 0.071* –0.281+ –0.175 0.038

% agricultural hukou 0.005*** 0.004*** –0.001 –0.002*

% Han population –0.016 –0.013 0.013 0.012

Province * hukou 0.005* 0.004* 0.001

log(GdP per capita) –0.178*** –0.108** –0.026

log(Fdi per capita) –0.025** –0.019* –0.026***

% women aged 20–29 with middle school education 0.000 –0.002

% net migration –0.007*** –0.007***

intercept 2.197* 2.026+ 1.451+ 1.026 1.491***R2 0.277 0.299 0.606 0.714 0.667

note: + p<.1, * p<.05, ** p<.01, *** p<.001

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ferently in Jiangsu and Zhejiang. according to results in model 1, the differ-ence 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 fer-tility 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 coeffi-cient 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 provin-cial 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 vari-ables: log-transformed GdP per capita, measuring overall economic develop-ment; 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 indica-tors 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 devel-opment, greater exposure to global influence is also associated with lower fertility. Hukou composition now has a statistically significant effect on fertil-ity 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 inclu-sion 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-

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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 vari-ous 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. obvi-ously, model 5 is an incompletely specified model, hence we should be careful interpreting its coefficients. However, comparing this model with other mod-els 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 de-velopments in other provinces. Given the rapid pace of social and economic

434 C h i n a ’ s b e l o w -R e p l a C e m e n t f e R t i l i t y

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 com-pelling 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 sta-tus 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 socioeco-nomic development and globalization to fertility.12 they nevertheless present strong empirical support for the association between socioeconomic develop-ment and fertility decline. micro-level longitudinal studies should help illumi-nate 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 link-ing 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 insti-tutional 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.

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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 atten-tion 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 en-couragement and helpful comments.

1 For 1975, the linear relationship be-tween economic development (dvP) and fer-tility can be summarized in a simple regression model as tFR = –1.298 * dvP + 14.5, which accounts for 48.7 percent of variation in fertil-ity. Similarly, for 2005 the linear relationship is defined by tFR = –1.164 * dvP + 13.3, which accounts for 65.8 percent of variation in fertil-ity. the combined data produce a linear rela-tionship 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, sug-gesting 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 adjust-ment 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 cen-sus 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 ex-ample, if a woman has an agricultural hukou but was enumerated in a city, the birth is clas-sified in the census as having occurred in the city, even if the woman returned home tem-porarily 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 ap-proach. However, the difference between observed fertility and policy-prescribed fer-tility in Zhejiang is far larger than would be indicated by the tempo effect observed at the national level.

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