key: cord-0060196-nhufrbgi
authors: Wu, Pengkun
title: Population Size Challenge: Low Total Fertility Rate
date: 2020-08-07
journal: Population Development Challenges in China
DOI: 10.1007/978-981-15-8010-9_3
sha: b7150758ca414e54b91827a57e2a2e34351c0c82
doc_id: 60196
cord_uid: nhufrbgi

The total fertility rate measures the average number of children who will be borne by a woman over her lifetime, and its accurate measurement can help better predict future population development. Despite the efforts of many parties to provide a measure, we still cannot systematically realize the determinants affecting the total fertility rate or accurately estimate it. This chapter conducts a meta-analysis to examine the determinants affecting the fertility intentions of China’s fertile women and the estimations of the total fertility rate in China. Thirty-one determinants affecting China’s total fertility rate are identified considering three aspects: demographic, social, and economic. The methods and data for estimating China’s total fertility rate are analysed, and the estimation results are compared. Notably, research on the total fertility rate is often limited by a lack of authoritative datasets. To alleviate this problem, this chapter compiles and summarizes the existing datasets used to report the total fertility rate.

The total fertility rate, sometimes also called the fertility rate, absolute/potential natality, period total fertility rate, or total period fertility rate, measures the average number of children that will be borne by a woman over her lifetime. Due to some limitations to the indicator definition, scholars have continuously attempted to refine the total fertility rate and accurately measure fertility levels (Bongaarts and Feeney 1998; Gao and Chen 2013) .

The accurate estimation of the total fertility rate is very important for predicting population development and designing a suitable population policy. Due to various obstacles, however, it is very difficult to accurately estimate the total fertility rate. Based on the 2010 population census data (Population Census Office under the State Council and Department of Republation and Employment Statistics National Bureau of Statistics 2012), China's estimated total fertility rate in 2010 was only 1.18, while the actual total fertility rate in cities, towns, and villages was only 0.89, 1.16, and 1.44, respectively. However, most scholars query the population census and think the total fertility rate has been significantly underestimated (Wang and Ge 2013) . The famous demographer and president of the China Population Society, Prof. Zhai Zhenwu, argues that the total fertility rate has been significantly underestimated and that China's total fertility rate should be approximately 1.6 (Guo 2015; Zhai et al. 2015) . Based on data for the number of newborn infants from the China Statistics Bureau, the total fertility rate from 2000 to 2010 should fall into the range of 1.50 to 1.64 (Cui et al. 2013; Peng 2011) . The significant differences between the above total fertility rates estimated for 2010 in China by different authoritative experts and institutions reflect the large difficulties in accurately estimating the total fertility rate.

China has entered a period with a low total fertility rate since the 1990s (Guo 2008; Zhao and Guo 2010) . From 1950 to 2015, the decrease in the total fertility rate in America, Japan, and India were 42.42% ((3.3 − 1.9)/3.3), 53.33% ((3 − 1.4)/3), and 59.32% ((5.9 − 2.4)/5.9), respectively, while that of China was 73.33% ((6 − 1.6)/6). China's current total fertility rate is far smaller than the worldwide average (2.45) and even than the average for developed countries (1.67) (Ren et al. 2019) . A rate of 2.1 is regarded as the standard level for promoting sustainable population development (Goldstein et al. 2009; Guo 2008 Guo , 2010 Huang 2020; Zhang and Chen 2020) . Although under the new two-child policy, the fertility rates became slightly higher for the second and third babies and further, the fertility rate for the first birth saw a large reduction, which led to a decline in the overall fertility rate (Guo 2017) .

Data from the 66 countries and regions that entered the post-transitional stage before 1997 reveal that the risk of a low-fertility trap has spread from 22 countries and regions to other parts of the world (Wu 2019) . China is facing a very high risk of falling into the low-fertility trap (Chen and Zhai 2016; Liu and Chen 2019) ; thus, China has prioritized improving the total fertility rate by designing policies to increase the fertility intentions of fertile women.

Compared with controlling the total population number and encouraging fertility intentions, increasing the total fertility rate creates a greater challenge for governments. The low total fertility rate would have many negative consequences, such as the shrinking workforce, the increasing ageing population, a limited population size, the vanishing demographic dividend, and a serious leftover men phenomenon (Ren et al. 2019) .

However, policymakers still cannot clearly understand the determinants of the low total fertility rate (Wang 2010) . Before encouraging fertility intentions, policymakers should first realize the determinants affecting the fertility intentions of fertile women and the total fertility rate. Existing studies reveal that the determinants include social determinants, economic determinants, and demographic determinants (Cai 2010; Chen et al. 2010; Guo 2000; Morgan et al. 2009; Zhenzhen et al. 2009 ). Although these existing studies indicate the determinants affecting the total fertility rate, they do not allow them to be integrated, understood, and compared. Therefore, this study conducts a meta-analysis to summarize and analyse the determinants affecting the total fertility rate and the estimations of the total fertility rates.

The remainder of the chapter is structured as follows. Section 3.2 presents the research design and some general quantitative findings from the reviewed literature.

Then, Sect. 3.3 conducts the meta-analysis to analyse the determinants affecting the fertility intentions of fertile women and the total fertility rate in China. Subsequently, Sect. 3.4 summarizes the existing authoritative estimations of the total fertility rate, and Sect. 3.5 provides the important datasets. Section 3.6 proposes effective suggestions to improve fertility intentions and the total fertility rate. Finally, conclusions and discussions are presented in Sect. 3.7.

To understand the fertility intentions of the fertility rate and the total fertility rate in China, this chapter conducts the meta-analysis to analyse the existing related literature from Web of Science Core Collection database and CNKI database. The Web of Science Core Collection database is one of the world's largest abstract and citation database of peer-reviewed research literature. The CNKI database is one of China's largest abstract and citation databases.

To obtain full-scale results, this chapter conducts an extensive and systemic search using the combination of these two keywords ("total fertility rate" and "China") from the Web of Science Core Collection database. All articles reviewed herein are obtained as of May 31, 2020. I also analyse the related references of the journal articles.

In the CNKI database, this chapter conducts an extensive and systemic search using the keyword "总和生育率", which is the Chinese keyword representing the "total fertility rate". As all searched articles are written in Chinese for studying the Chinese population, it is not necessary to add the keyword "China".

The search for relevant papers in this process is by no means exhaustive, but the main influence factors affecting the total fertility rate can be found. Only full-length articles are used for the meta-analysis. I thus exclude conference papers, conference reviews, book chapters, editorials, short surveys, and letters from the analysis. Finally, 71 articles are analysed for understanding China's total fertility rate. Among the 71 articles, 55 articles are published in Chinese, and the rest 16 articles are published in English.

Figure 3.1 illustrates the annual number of the identified journal articles on China's total fertility rate. In our identified journal articles, the easiest article was published in 2004, and I can identify significant increasing trends in the number of identified journal articles. Although China's total fertility rate has been studied for more than 16 years, I can still find ever-increasing interesting articles published in high-quality journals. In 2019, the number of English journal articles was as high as six.

The 71 journal articles are distributed across 38 different journals, including 14 English journals and 24 Chinese journals. The specific publication information are presented in Table 3 The top two leading Chinese journals in the demographic field, i.e., Population Research (in Chinese) and Chinese Journal of Population Science (in Chinese), are very interested in the topic about the total fertility rate due to the below two reasons. First, the low total fertility rate is very important for the population development in China. Second, the public still have little understanding about the total fertility rate, and need to know more about the determinants causing the low total fertility rate and the accurate estimation of the total fertility rate. Therefore, Sects. 3.3 and 3.4 would summarize the determinants causing the low total fertility rate and the existing methods and datasets for estimating the total fertility rate.

The determinants affecting the fertility behaviours are complex (Chen 2019; Xu 2010) . The explanations for the low total fertility rate can be summarized considering three aspects: demographic determinants, social determinants, and economic determinants.

The demographic determinants include marriage age, length of the interval between marriage and childbearing, marriage delay, divorce rate, educational background, labour participation, participation in pension insurance, retirement age, infertility rate, and rural residence. The existing studies for analysing demographic determinants are summarized in Table 3 .2. China's marriage age is continuously increasing and causes a low total fertility rate (Guo and Tian 2017; Shi et al. 2019; Wang et al. 2019a; Wei et al. 2018) , as delaying marriage and fertility negatively affect the fertility intentions (Guo and Tian 2017; Shi et al. 2019; Wang et al. 2019a) . The length of the interval between the first marriage and the first childbearing directly affects the fertility level of the fertile women (Fu et al. 2013) . In China, nearly 70% of women give birth to a child within one and a half years of marriage, and 90% of women of childbearing age give birth to a child within two and a half years of marriage (Li and Jiang 2009) . A decrease in nuptiality or in the marital fertility rate would also reduce the total fertility rate (Yip et al. 2015) . One study reveals that marriage deferral can explain approximately two-fifths of the Chinese fertility decline in the 1990s (Retherford et al. 2005 . In China, the current divorce rate is relatively high and thus restrains fertility levels (Yang 2015) .

These marriage-related determinants are highly affected by the educational background of fertile women ). The total fertility rate is negatively affected by education level (Wang and Zhang 2020; Yang et al. 2007) , as education level increases the interval between the first marriage and the first childbearing and thus reduces the total fertility rate (Liang 2013) . Since education is assumed to present a cost at a young age and result in higher productivity during adulthood, the fertility Age interval between marriage and childbearing Fu et al. (2013) , Liang (2013) Age interval between first marriage and first childbearing is increasing and causes the low total fertility rate The 2000 and 2010 population census data

Marriage delay Retherford et al. (2004 Retherford et al. ( , 2005 Marriage deferral can explain Chinese fertility decline in the 1990s with the extant of about two-fifths

The 1990 and 2000 population census data Yip et al. (2015) The decrease in nuptiality and marital fertility rate would reduce the total fertility rate The 1992 The population census data and the 1991 The , 2001 Hong Kong population statistics Divorce rate Yang (2015) The divorce rate restrains the fertility levels Guo (2008) The current high infertility rates reduce the total fertility rate N/A (continued) Rural residency Wang and Chi (2017) The significant positive effect of rural Hukou is found only in places close to Beijing, suggesting that there is some unique rural residency characteristic in this place that operates independently from economic and fertility policy factors

Geocoded 2010 county-level census data rate, which in the long run keeps dependency at a minimum, lies well below replacement fertility both in Europe and China (Striessnig and Lutz 2014) . There is no doubt that a high education level increases the labour participation rate of fertile women. As working women must invest more to have children and address the trade-off between career and family, the labour participation rate of fertile women reduces the total fertility rate (Sasser 2005) . Participating in pension insurance also reduces people's total fertility desire by 14.1%, with the desire to give birth to sons being reduced by 7.2%, and the desire to give birth to daughters by 5.4% . Extending the retirement age would reduce the time that elderly people can spend caring for children and reduce the total fertility rate (Dong and Kang 2020). One serious physical condition is the current high infertility rate, which is estimated to be approximately 15% (Guo 2008) . The high infertility rate directly reduces the total fertility rate. In some specific regions, rural Hukou residency also has a significant positive effect on the total fertility rate (Wang and Chi 2017).

Social determinants include social stability, political freedom, retirement security system, urbanization rate, floating population, regional education quality, environmental pollution, gender ratio, women's social status, social fertility culture, and the family planning policy. The existing studies analysing social determinants are summarized in Table 3 .3.

The fertility intentions of fertile women are affected by whether society is stable. During the period of war, women usually have very slow fertility intentions (Wang and Zhang 2020) . Earthquake disasters have a significant impact on the fertility pattern of the population in the disaster areas and have played an inhibiting role in the fertility level in the short term (Jiao et al. 2019) . Deteriorating political freedom in upper-to middle-income countries exerts downward pressure on fertility rates, while it contributes a positive effect to fertility rates in lower middle-and low-income countries (Wang and Sun 2016) . Changes in retirement security rate have a negative incentive for the marriage structure and the total fertility rate (Wang and Liu 2015; Wei et al. 2018 ). Due to various demographic factors and the current sound social security system, many fertile women marry late (Wang and Liu 2015) and have low fertility intentions.

Fertility intentions differ between cities, towns, and villages. With the accelerated growth in the urbanization rate, the total fertility rate is decreasing (Guo and Yu 2016) . Urbanization was responsible for approximately 22% of the decrease in the total fertility rate from 1982 to 2008, and its effect was especially important from 2001 to 2008. In most provinces, urbanization is associated with a decline in provincial-level fertility (Guo et al. 2012) . The floating population reduces the total fertility rate, as the fertility rate of the floating population is significantly smaller than that of the urban population and even smaller than that of the rural population (Guo 2008 ). The Li and Guo (2014) The fertility level of the floating population is relatively small 2012 floating population monitoring data Regional education quality Wang et al. (2019a, b) Regional education quality has a direct negative impact on the childbearing willingness for a second baby fertility level of the floating population is relatively small (Li and Guo 2014) , and a large number of migrants cause a low total fertility rate (Liang 2006) . The total fertility rates show significant differences between the 31 provinces. Regional education quality has a direct negative impact on the willingness to bear a second baby (Wang et al. 2019b) . Environmental pollution also significantly reduces the total fertility rate. The PM2.5 concentration has a negative impact on the second baby intentions of the floating population, although this impact exhibits marked regional heterogeneity: the desire for a second baby across migrant groups living in South China decreases if the PM2.5 concentration increases, while migrants coming from and living in North China show strong intentions to have a second baby despite an increase in the PM2.5 concentration in northern cities . The optimal fertility level falls even lower when climate change is factored in as well (Striessnig and Lutz 2014) .

Family planning policy and social fertility culture are two important social constraints affecting Chinese families. The family planning policy is an external system that restricts people's fertility behaviours, and the social fertility culture is the societal opinions that affect people's fertility behaviours. Decades ago, the Chinese people strongly considered childbearing to represent continuing the family bloodline, and traditional fertility culture is significantly and positively related to the total fertility rate (Wei et al. 2018 ). However, the traditional "son preference" causes an unbalanced gender ratio, which reduced the total fertility rate (Guo 2008) . Currently, women's social status has significantly increased, and the former "men outside the home, women inside" lifestyle has shifted to become the "equality of men and women". The improvement of women's social status has led young people to abandon traditional opinions about family and children and to develop relatively low fertility intentions (Wu et al. 2016) .

Measured by the prevalence rate for contraception (Wang and Sun 2016) , the family planning policy has been very effective in controlling the total fertility rate in China (Ding et al. 2019; Zhu 2020 ). The two-child policy increased China's total fertility rate in 2016, particularly the willingness to bear a second baby (Li et al. 2019b; Shi et al. 2019; Wang et al. 2019a; Zhang et al. 2019 ). However, some scholars propose that not all women will have increased fertility intentions under the twochild policy because two children increase their opportunity costs by reducing the labour supply, wage income, and healthy human capital Zhu 2020) . Implementation of the two-child policy will have short-term effects on China's future birth rates ) but a limited ability to increase fertility levels and limited effects on the national population size and structure ).

Economic determinants can be divided into social-economic background, family economic structure, and fertility economics for childbearing. The specific economic determinants include globalization, regional human development index, house price, partible inheritance mechanism, income level, household consumption, fertility benefits, childbearing cost, opportunity cost of childbearing, and time pressure. The existing studies analysing economic determinants are summarized in Table 3 .4.

The socio-economic background includes globalization, regional human development index, house prices, and partible inheritance mechanism. The total fertility rate is negatively affected by globalization, as one of the characteristics of globalization is rising economic inequality and increasing pressure from the intermediate social class. As globalization increases, fertility intentions show a significant U curve correlating with economic resources (Wang 2010) . Globalization increases the proportion of families at the middle-income level and thus reduces the total fertility rate. Some studies have found that the total fertility rate is negatively related to the regional human development index (Tao et al. 2017; Zhou 2015) , while others find that the total fertility rate shows a U-shaped relationship with the regional human development index (Chen and Zhai 2016; Myrskylä et al. 2009 ). High house prices restrain the development of the total fertility rate (Guo and Jiang 2018) . Under the traditional partible inheritance mechanism, fertility intentions were significantly negatively associated with birth order (Li and Zhen 2015) .

The family economic structure includes family income and household consumption. The fertility intentions of families with high or low incomes are significantly higher than those with middle incomes. The high fertility rates of people with low incomes create the low-quality labour population (Guo and Yu 2017) . A rural family may reduce the number of births according to the trade-off between quality and quantity, which may be the main cause of the fertility decline in China (Song et al. 2012) . Families with high incomes can provide superior conditions for their children and have a relatively high willingness to give birth (Zhu and Chen 2012) , while families with middle incomes have high life requirements and are under strong social pressure. Therefore, fertility level and household consumption are shown as inverted U-shaped curves (Xue 2016) .

From the perspective of fertility economics, fertility decision-making is mainly determined by fertility benefits and costs. The families in the low or medium classes in terms of fertility benefits have a low desire for a second baby, while those in the higher class for fertility benefits have a high desire. Fertility benefits can be grouped into reasons related to one's path in life, anticipated positive experiences, and feelings drawn towards children. To have a child makes one's family complete; is the next stage of life; provides happiness, fun, and enjoyment; brings care and company in old age; and children are "lovely" and "cute" (Adams 2016) . The significant benefit factors of having a second baby include parenting joy, health risks, mutual care among siblings, and the flourishing of the family . Fertility costs include the childbearing cost, the opportunity costs for childbearing, and time pressure. The fertility intentions of fertile women are reduced by high childbearing costs, which include family childbearing costs and the social childbearing costs (Wang and Liu 2017; Wang and Long 2018; Xia and Yang 2019) . However, the unbalanced childbearing cost allocation mechanism causes China's families to bear most of the childbearing costs (Xia and Yang 2019) . The fertility intentions of some fertile women will not be increased by the two-child policy (Zhou and Chen 2013), since (2010) Globalization causes the low total fertility rate N/A Regional human development index Tao et al. (2017) The total fertility rate is negatively related to the provincial human development index The 1982 The , 1990 population census data Zhou (2015) There is a strong reverse relationship between the regional human development index and the total fertility rate among the 109 studied countries

Data from 109 countries with over 5 million people in 2010

Chen and Zhai (2016) The fertility intention shows a significant U-shaped curve correlation with the regional human development index

The 1990 Li and Zhen (2015) Under the traditional partible inheritance mechanism, fertility intention was significantly negatively associated with birth order

Historical birth data of the Que family from 1670 to 1996 (continued) the two-child policy increases their opportunity costs by reducing the labour supply, wage income, and healthy human capital (Zhu 2020) . The potential opportunity costs significantly reduce the total fertility rate (Ji and Zheng 2018; Wei et al. 2018 ). Time pressure is also a large barrier to fertility desire , and extending the retirement age would significantly increase time pressure (Dong and Kang 2020) . Based on the above meta-analysis, this chapter draws Fig. 3 .2 to analyse the factors influencing the total fertility rate.

To date, China's total fertility rate has not been well measured due to the lack of authoritative datasets. China has more than 1.4 billion people and 9.6 million square kilometres, so it is very difficult to accurately survey all fertile women. Many scholars are continuously searching for ways to survey fertile women and calculate the total fertility rate.

To help realize the estimation of the total fertility rate, this section summarizes and compares the estimation results for China's total fertility rate. The existing estimations of China's total fertility rate since 2000 are summarized in Table 3 .5.

Various methods have been adopted to calculate China's total fertility rate based on different data, and these studies reach different conclusions. The total fertility rate can be the summation of the fertility rate based on birth order (Lu 1989; Zhang 2006) , calculated based on the fertility rate at different ages multiplied by the proportion of fertile women at those ages (Wang , 2019 Xu 2010; Zhang 2006; Zhou and Chen 2013) , or calculated by combining these two methods .

Some scholars obtain population data for selected decades and use the backward survival method to reverse calculate the number of newborn infants and the total fertility rate (Guo 2011; Li and Li 2012; . However, some question whether population census data are scientific, and these data have serious omission problems (Goodkind 2004; Yi 1996; Zhang and Cui 2003) . The estimated total fertility rate as calculated directly based on population census data is usually smaller than 1.5. To overcome the shortfalls in the population census, some scholars first check and amend the population census data and then use the data to estimate the total fertility rate (Chen 2016; Chen and Zhang 2015; Cui et al. 2013; Mi and Yang 2016; Wang and Ge 2013; Wang et al. 2004; Zhao 2015) . The estimated total fertility rate based on amended census population data usually falls between 1.5 and 1.6. Some scholars believe that data from educational institutions or household data are more scientific than data from the population census. They estimate the number of children and fertile women based on education data and residential data from the education (2018), Wei et al (2018) Age Interval between Marriage and Childbearing - Guo (2008) Physical Condition -+ + Household Consumption Wang (2010) Family Income

Zhou (2015), Tao et al (2017) - Zhu (2020) Divorce Rate Retirement Security System Wang and Liu (2015) , Wei et al (2018) - Wang and Liu (2015) + House price Li and Zhen (2015) -U Fu et al (2013) Song et al (2012), Guo and Yu (2017) - Liang (2013) Infertility Rate - Guo et al (2019) , Striessnig and Lutz (2014) Partible Inheritance Mechanism

Fertility Costs - Guo and Jiang (2018) Adams (2016) 

The determinants affecting the total fertility rate China's total fertility rate is smaller than 1.5, and even smaller than 1.4 in some years (continued) and household sectors and use that to calculate the total fertility rate (Chen 2014 (Chen , 2016 Chen and Yang 2014; Yang and Zhao 2013; Zhou and Pan 2010) . The estimated total fertility rate based on education or residential data is usually approximately 1.6 or even higher. The estimated total fertility rate based on the population census data is significantly smaller than that based on education and residential data. In addition to obtaining these official statistical data, some scholars estimate the total fertility rate by conducting surveys (Wei et al. 2018) . In 2017, China conducted an official fertility survey, and the estimated that the total fertility rate based on 

The resident data in 2015

Using the resident data to obtain the number of newborn infants and fertile women, and calculate total fertility rate

The estimated total fertility rate from 2008 to 2010 is at least 1.66, 1.66, and 1.63 (continued) 

The 1990 and 2010 population census data

Amend the population census data and then estimate the total fertility rate From 2005 to 2013, the estimated total fertility rate is at least 1.5, and most probably would be around 1.6 (continued) Population structure was ageing fast, fertility rates continued to decrease to a substantially low level, and three north-eastern provinces displayed notable socio-economic issues associated with low-fertility trap this survey is highly consistent with the estimated results based on education and residential data (Chen and Duan 2019). Although some scholars argue that education and residential data are more scientific, others think that education or residential data may have false report problems due to potential population subsidies. As the indicators described in the above paragraph are hard to obtain, some scholars analyse the relationship between the total fertility rate and some easily obtained indicators and derive formulas for calculating the total fertility rate. For instance, Zhu and Qiao (2018) derived a formula for calculating the total fertility rate based on the birth rate Zhu and Qiao 2018) . Some scholars adopt the variable-r method and use the growth rate in populations of different ages to estimate the fertility level Zhao 2015) . To measure the total fertility rate, some scholars also use related indicators, such as the mean childbearing age at first birth (Wang and Zhong 2015) and the general fertility rate (Gu 2015) .

When performing these estimations, most scholars are worried about the low total fertility rate in China. They believe that China's total fertility rate is far smaller than the replacement level and thus suggest that the family planning policy should be further relaxed (Guo 2011; Li and Li 2012; Zhou and Pan 2010; . New authoritative fertility data provided by the National Health Commission of the People's Republic of China reveal that the total fertility rate between 2006 and 2011 was between 1.60 and 1.70 and fluctuated between 2012 and 2016, peaking between 2012 and 2016 (He et al. 2018) .

The total fertility rate reported from the 2017 China fertility survey is relatively higher. In the 2017 China fertility survey, 12,500 investigators and 3128 supervisors obtained 246,840 samples from 12,500 village sample points representing 6078 towns in 2737 counties of 31 provinces . Because the report is new and authoritative, it is very important for fertility rate tracking and policymaking. The relatively high estimated total fertility rate shows that China's total fertility rate has been significantly underestimated and that the strict family planning policy still plays an important role in controlling the total population number (Chen 2014 (Chen , 2016 Chen and Yang 2014; Chen and Zhang 2015; Yang 2015) .

There are significant differences between the cities, towns, and villages in different provinces in terms of the total fertility rate (Gu et al. 2019; He et al. 2018; Huang 2020; Jiang et al. 2019; Li et al. 2019b; Liang 2013; Shi et al. 2019; Wang et al. 2019a ). The total fertility rate of the provinces with high populations of ethnic minorities has increased to a replacement level in the past 10 years and is higher than the national average (Yuan et al. 2019) . The total fertility rates from 2006 to 2016 estimated from the 2017 fertility survey are presented in Table 3 .6. The total fertility rate in villages is significantly higher than that in cities or towns, but there is a smaller difference in the total fertility rate between villages and cities or towns (Hao and Qiu 2011) .

There is significant global spatial dependency and a significant local clustering trend for the provincial total fertility rate (Dorius 2008; Gu 2015; Guo et al. 2012; Li et al. 2017; Tan and Zeng 2014; Wang and Chi 2017; Wang et al. 2004 Wang 2019; Zhang et al. 2012) . The total fertility rates are low in Beijing, Shanghai, Liaoning, Heilongjiang, Jilin, and Tianjin, which are developed municipalities or are located in the north-eastern regions. The provinces with low total fertility rates are concentrated in the north, north-eastern, and south-eastern provinces (Tan and Zeng 2014) . Three north-eastern provinces displayed notable socio-economic issues associated with the low-fertility trap (Wang 2019) . However, the total fertility rates are relatively high in Guangxi, Guizhou, Xinjiang, and Hainan, which are located in the western and southern regions, and particularly in the south-western regions. The total fertility rates in the western provinces are usually higher than those in the central and eastern provinces (Gu 2015) .

Thus, we should not ignore the spatial effects of the total fertility rate, including interdependence and heterogeneity. More analyses of the spatial aggregation of the 31 provinces in terms of population indicators are conducted in Chaps. 7 and 9. 

As described in Sects. 3.3 and 3.4, I can summarize the data sources for studying China's total fertility rate in Table 3 .7.

Population census data have been widely adopted to study the total fertility rate. The small population census data and the yearly population data, both based on a 1‰ sample, are also adopted by many studies. In addition, some studies adopt provincial and regional data to analyse the population development differences among the 31 provinces in China or among counties. The significant population development differences in China are further analysed in Part II.

In addition to using statistical population data, some scholars use populationrelated statistical data, such as residential data and education data, to estimate China's total fertility rate. To analyse various determinants affecting the total fertility rates, many studies use data from other fields, such as data on the labour participation rate, income, regional development index data, and even environmental data.

The fertility intentions of fertile women vary with time and cannot be directly calculated through any indicators. Thus, ongoing surveys are very important for analysing and estimating the total fertility rate. As authentic data have been provided by the National Health Commission of China, the 2017 fertility survey data have been widely used by many scholars to estimate the total fertility rate. Another important related survey is the Chinese General Social Survey (CGSS). The CGSS 2010 data are widely used by scholars to study the total fertility rate. In addition to these two widely recognized datasets, some individuals and institutes also conduct their own surveys, such as the 2010 Chinese family monitoring survey, the multistage stratified cluster sampling survey, and the annual fertility pattern sampling survey. Some studies design experiments and conduct face-to-face interviews to study the total fertility rate in China.

After summarizing the influencing factors causing the low total fertility rate, this study offers some effective suggestions for improving the total fertility rate, specifically the fertility rate for the first birth. It is extremely important that the fertility level of the first birth be improved; otherwise, policy adjustment will only increase the number of second baby in the short term, and the overall fertility level will thereafter be reduced (Guo 2017) . The suggestions include four main targets: economic support, maternity benefits, social welfare, and population policies. 1982, 1990, 2000, and 2010 population census data Retherford et al. (2004) , Wang et al. (2004) , Retherford et al. (2005) , Liang (2006) 

Population statistical data The national prefecture-level city matching data Guo et al. (2019) Geocoded 2010 county-level census data Wang and Chi (2017) The population statistical data from 109 countries Yang et al. (2007) (continued) Wang and Sun (2016) Data of 109 countries with over 5 million people in 2010

Zhou (2015) Related data of China and countries of ASEAN from 1989 to 2013

Wang and Liu (2015) Population-related statistical data

The household/residence data Zhou and Pan (2010) , Yang and Zhao (2013) , Chen (2014), Zhai et al. (2015) , Chen (2016) The education data Yang and Zhao (2013) , Chen

The data with labour participation rate and income

Sasser (2005) The human development index from the United Nations Development Programme Chen and Zhai (2016) The income data of the 31 provinces from 1978 to 2013

Li ( 

The implementation of the two-child policy and the changing form of the future population require not only a scientific assessment of the cost of the second baby but also a reasonable mechanism for allocating reproductive cost. Reducing childbearing costs can increase fertility intentions and the total fertility rate. There are two main paths for reducing childbearing costs. First, the government can provide monetary support to help families raise their children. In many countries or regions, including France, Finland, Belgium, Italy, England, Australia, Singapore, and the Taiwan Province of China, governments offer a one-time birth subsidy for newborn babies (Yang 2016) . The size of this one-time monetary reward ranges 150-1500 U.S. dollars. Such one-time monetary reward would be a powerful motivator for changing the fertility intentions of fertile women .

Second, ongoing child allowances are also very important for encouraging fertility willingness. Children's allowances can be provided through various methods. First, children could be provided a regular monthly allowance. Some countries, such as France and Sweden, provide the monthly allowance until the children grow to a certain age. The second way for providing an allowance for children is the education allowance. Governments can not only reduce and even eliminate education fees but also provide allowances for children in school. The third way of providing an allowance is tax reduction and exemption. Families experience greater costs to raise children, so their taxes can be reduced and even exempted. Since 2019, China has already implemented a completely new tax mechanism, in which some costs of children can be deducted from the tax base. A tax benefit policy is difficult and complex to introduce and maintain and requires sophisticated targeted moderating (Wang and Sun 2017).

When having a child, family members, especially the mother, experience far greater workloads. If they still need to work and expend effort to balance work and family, they will have very low willingness to have a new baby and may even experience stress. To help families enjoy raising children and even to be willing to have a new child, governments should provide sufficient maternity benefits.

First, maternity leave should be sufficient. As women's bodies present new challenges with increasing age, some countries or regions provide maternity leave related to the number of births. The salaries of fertile women during maternity leave can be provided by both governments and employers.

Second, yearly parental leave can encourage families to have more children. In some countries, family members can obtain parental leave to spend time with their children. Having sufficient time to provide companionship to their children can bring happiness to both the parents and the children, help children grow in a healthy manner, and help parents experience better moods to increase their willingness to have more children.

Third, most maternity benefits are designed for the mothers, but fathers should also have leave to take care of their children and wives. Even though fathers can take holidays to spend with their wives and children, leave for fathers is currently limited. Increasing leave time for fathers can also increase the fertility intentions of families.

Fourth, designing flexible working hours and workspaces can offer fathers and mothers sufficient time to spend with their children. During the period of the coronavirus disease 2019 (COVID-2019), most people had to work from home, but the efficiencies gained were found to be ideal for some kinds of work. Therefore, for families with new babies, employers could provide fathers and mothers with flexible work hours and workspaces. Advanced technologies can help promote the development of this mechanism.

Families would have higher fertility intentions if they could enjoy superior social welfare. Therefore, to encourage the fertility intentions of fertile women, we should continuously improve social welfare.

First, governments need to provide sufficient education and facilities for developing children. If the children cannot obtain a good education from society, families will have a low willingness to have a new child. In addition to governments, employers can establish some facilities for children in their offices.

Second, families with more children experience high housing pressure. As described in Sect. 3.3, high house prices restrain the development of the total fertility rate (Guo and Jiang 2018) . In some countries or regions, families with more children are prioritized to receive the housing welfare provided by governments. If families do not need to worry about the housing conditions for their children, they will have higher willingness to have more children.

Third, improving maternal health services is very important for fertile women. Many puerperae have postpartum health problems. If women cannot experience a pleasant recovery process after childbirth, they will have a relatively low willingness to have new children.

Suitable population policies are very important for controlling the total fertility rate. Family planning policies should match the national situation, including economic levels, traditional cultures, social developments, and population.

China's family planning policies help China control the total population number but have destroyed the demographic structure. Currently, China faces a low total fertility rate and has prioritized relaxing its strict family planning policy. A more detailed analysis of the adjustment of China's family planning policy is conducted in Chap. 6.

When relaxing family planning policies, governments should also continuously improve public services, reasonably allocate educational and medical resources, and strengthen basic education and medical facilities.

A comprehensive understanding of the determinants of the low total fertility rate and an accurate estimation of China's total fertility rate are very important for the scientific adjustment of population policies in China. Although the importance and significant effects of the total fertility rate have been widely recognized, existing studies are limited.

In this study, I identified 71 relevant journal articles, comprising 55 Chinese journal articles and 16 English journal articles published as of May 31, 2020. We first conduct descriptive statistical analyses and obtain some general findings regarding overall growth and publication sources. A total of 31 determinants affecting the total fertility rates are identified, and these 31 determinants are divided into three groups: demographic determinants, social determinants, and economic determinants.

Then, the estimations of the total fertility rate are summarized and evaluated. The methods and data adopted to estimate China's total fertility rate are also summarized. By reviewing these 71 relevant journal articles, the data sources for studying China's total fertility rate are examined.

The main contribution of this study is its summary of the determinants of the total fertility rate in China, which can allow a better response to China's total fertility rate. Moreover, this study helps us better evaluate China's current total fertility rate and determine how to choose suitable data sources for studying the total fertility rate. This study also informs academicians and practitioners in this research field of the current research situation, the implications and limitations of existing studies, and the prospective research directions in this area.

Why do women want children? The case of Hong Kong, China: A lowest-low fertility context

On the quantum and tempo of fertility

China's below-replacement fertility: Government policy or socioeconomic development?

The impact of pension insurance on fertility desire: An empirical study based on Chinese general social survey

Effects of population policy and economic reform on the trend in fertility in Guangdong province

A study on the variation history and mechanism of international fertility level since the 20th century

Individual differences in relative fertility costs and fertility benefits and their effects on fertility desire for a second child in China: A latent profile analysis

Estimation of China's fertility level since

学海 (1)

China's fertility estimation: A generalized stable population approach

基于广义稳定人口模型的中国生育率估计

Estimation of China's fertility level in recent years

中国近年来的生育水平估计

The two-child policy and fertility rate in China

Recent levels and trends of fertility in China

Quantum and tempo of fertility in China

China's fertility in 2010: An indirect estimation using Brass P/F ratio method

A reassessment of China's recent fertility

中国近期生育率的再估计

An evaluation of data accuracy of the 2010 population census of China

对2010 年人口普查数据准确性的估计

Factors determining fertility change and the influence of family planning policy adjustments in East China: An analysis based on 2017 fertility survey

Elder people employee, extended retirement security system, and the restriction for fertility intention

Global demographic convergence? A reconsideration of changing intercountry inequality in fertility

Characteristics of the changes of population fertility in China based on the sixth census

从第六次人口普查看中国人口生育变化的新特点

On intrinsic total fertility rate

The end of "lowest-low" fertility?

China's missing children: The 2000 census underreporting surprise

Why is China's total fertility rate so low? Interplay between postponement and recuperation

中国总和生育率为何如此低?--推延和补偿的博弈

The estimation and the influence analysis of China's total fertility rate

我国总和生育率重估计及其影响分析

Demographic transition during the course of urbanization and the population policy

Wage growth, fertility differential and human capital accumulation: a dynamic general equilibrium study with endogenous fertility and retirement

工资增长、生育率差异与人力资本积累--基于内生生育和退休 的动态一般均衡研究

High housing prices and low fertility: Is it really the housing price TTA caused the trouble? The spatial spillover effect of commercial housing price on fertility rate in China

高房价、低生育率:难道真是房价惹的祸--中国商品住宅价格对生 育率的空间溢出效应研究

Impact of PM2.5 on second birth intentions of China's floating population in a low fertility context

Lifetime fertility of Chinese women: A look at the recent period fertility behaviour

从近年来的时期生育行为看终身生育水平 中国生育数据的去进度效应总 和生育率的研究

China's low fertility and its determinants

中国的低生育水平及其影响因素

China's low fertility and its neglected demographic risk

中国的低生育率与被忽略的人口风险

2010 population census data indicates serious miscount in past population estimation and projection

六普结果表明以往人口估计和预测严重失误

Be aware of the risk of low fertility in China

清醒认识中国低生育率风险

The main features of the low fertility process in China: Enlightenment from the results of the national 1% population sampling survey in 2015

中国低生育进程的主要特征--2015年1%人口抽样调查结果的启示

The effect of the late marraige age of the contemporary youth on the low total fertility rate

The effect of urbanization on China's fertility

A comparative analysis of the fertility of the urban and rural in China since

China fertility status report

The structural characteristics of China's low fertility process

中国低生育进程的结构性特征

China's low fertility rate from the perspective of gender and development

社会性别和发展视角下的中国低生育率

The decline in China's fertility level: A decomposition analysis

Attribution analysis of the change on fertility pattern after earthquake disaster in Wenchuan

汶川地震灾后生育模式变化的归因分析

Fertility level of migrant population: Based on national migrant population dynamic monitoring survey data

Income and fertility: The explanations for the changing of China's fertility rate

收入与生育:中国生育率变动的解释

Spatial-temporal evolution of China's total population fertility rate based on GIS

基于GIS的中国人口总和生育率时空演变研究

Estimating China's fertility level since 2000: Based on the 6th population census

The influence of the universal two-child policy on China's future population and ageing

Fertility rate, fertility intentions and childbearing costs in Chongqing

重庆市生育水平、生育意愿及生育成本

Partible inheritance, birth order, and fertility: Historical investigation from the South-Eastern village in Qing and Republican China

分家析产、财富冲击与生育行为:基于清代至民国初期浙南乡村的 实证分析

Projection of population structure in china using least squares support vector machine in conjunction with a Leslie matrix model

Survey on the fertility intentions of 1047 college students

The dynamics of the first birth interval in China

The analysis of Chinese reproductive women fertility completeness from

Understanding the reasons causing the extremely low total fertility rate

京津沪超低总和生育率形成原因的再认识

China's low fertility trends: An analysis using multiple sources of data

中国的生育率低在何处?

Total fertility rate and the fertility controlling

总和生育率与生育控制

Reassessment of the under-reported rate of the total fertility rate and sex ratio at birth-based on the national census and 1% sample survey data during 1982-2010

China's below-replacement fertility: Recent trends and future prospects

Advances in development reverse fertility declines

Population Census Office under the State Council, and Department of Republation and Employment Statistics National Bureau of Statistics

How to estimate total fertility rate given the crude birth rate

如何利用(粗)出生率来估计总和生育率?

Chinese fertility report

How far has fertility in China really declined? Population and Development Review

Fertility in China; how much has it really declined

中国的生育率:到底下降了多 少?

Gender differences in physician pay: Tradeoffs between career and family

Fertility trends in four provinces in Southwest China before and after the two-child policy adjustment

生育政策调整前后西南四省市妇女生育变动分析

The model and empirical analysis of fertility decision-making in China's rural family

中国农村居民家庭的生育决策模型与实证分析

How does education change the relationship between fertility and age-dependency under environmental constraints? A long-term simulation exercise. Demographic Research

Spatial-temporal pattern analysis and spatial disparity research on provincial transition of mechanisms in stabilizing low fertility in China

我国低生育水平稳定机制的时空演变及空间差异研究

Re-examining China's provincial socioeconomic development and fertility change

中国经济社会发展与生育水平变动关系再探索

Different places, different stories: A study of spatial heterogeneity of county-level fertility in China

World population in the era of globalization and China's choice

The effect of social security tax rate on marriage structure and fertility decision: Modeling and empirical study

The Changing of China's fertility pattern and the estimation of the fertility level from

Assessment of 2010 census data quality and past population changes

2010 年人口普查数据质量评估以及对以往人口变动分析校正

Estimation of the total fertility rates of China's provinces in 2000

中国省级2000年育龄妇女总和生育率评估

Rethinking China's actual and desired fertility: Now and future

中国生育水平、生育意愿的再认识:现实和未来--基 于2017年全国生育状况调查北方七省市的数据

Study on the influence mechanism of regional education quality on residents' second childbearing desire

地区教育质量对居民二孩生育意愿的影响机制研究--来 自CGSS2015经验证据

The countywide differences of China's total fertility rate and an empirical study of its influencing factors

我国总和生育率的县域差异及其影响因素的实证研究

A retrospective and predictive study of fertility rates in China from

The role of socio-political and economic factors in fertility decline: A cross-country analysis

The fertility rate change and the policy implication from some developed countries

A study on estimation and sharing mechanism of the two-child fertility cost

The reduction of the childbearing costs and the fertility rate: A study based on the experiences and data from multiple countries

Pro-birth policies and their effects: International experience, review and outlook

The exploration of measuring CFR based on the mean childbearing age at first birth

Socioeconomic determinants of rural women's desired fertility: A survey in rural Shaanxi

Whether the low-fertility trap exists? Observations on the long-term changes in fertility in post-transitional countries (regions)

Who determines "giving birth to a son": How institution and culture affect women's fertility choices in social transformation

谁来决定"生儿子"?--社会转型中制度与文化对女 性生育决策的影响

The fairness of cost sharing in fertility: Based on the non-balanced state of cost and benefit

我国生育成本分担的公平性研究--基于生育成本收益非均衡状 态的分析

Divergence between low fertility and desired fertility in China

中国低生育水平与意愿生育水平的差距

On relationship between household consumption and fertility choice

中国家庭消费与生育选择的关系研究

China's fertility level since 2000: A reestimation

Has China really fallen into fertility crisis? Population Research

中国真的已陷入生育危机了吗?

Low fertility rate countries' pronatalist policies and the enlightenment to China

低生育水平国家或地区鼓励生育的社会政策及对我国的启示

Empirical analysis on the factors of total fertility

Is fertility in China in 1991-92 far below replacement level? Population Studies

A tale of two cities: A decomposition of recent fertility changes in Shanghai and Hong Kong

Fertility levels and trends in China's ethnic minority provinces

China's recent total fertility rate: New evidence from the household registration statistics

人口研究 (6)

Estimation and analysis on total fertility rate

总和生育率的测算及分析

Estimation of the accuracy of the 2000 population census data in China

对中国2000年人口普查准确性的估计

China's demographic future under the new two-child policy

Spatial-temporal pattern analysis and spatial disparity research on provincial total fertility rate in China

The population policy change and current population development during the 70 years in the new China

An estimation of fertility level in China

China's below replacement fertility: A further exploration

Below-replacement fertility and childbearing intention in Jiangsu province

Quantitative analysis on the relationship between socioeconomic development and fertility

经济社会发展与生育率变动关系的量化分析

A measuring model on TFRs with compensatory births under a loosening birth-policy

Measuring policy fertility and actual fertility in China

中国政策生育水平与实际生育水平的测算

Relationship research on total fertility rate and birth rate based on curve fitting model

Two-child policy, opportunity cost and fertility demand: Based on CGSS

生育政策、机会成本与生育需求--中国综合社会调查的微观证据

Estimation on fertility level in China

From mainlanders' giving birth in Hong Kong to fertility tragedy of the commons

2017 China fertility survey: Practices and reflections

2017年全国生育状况抽样调查的实践与 思考