Jobs and kids: female employment and fertility in China

Seminal contributions to the economic theory of the household show that fertility and job market behavior are interrelated choices, since both strongly affect household time allocation (Becker 1960 1965; Mincer 1962; and Willis 1973). The global fall in fertility and increase in female labor-force participation over the past century might plausibly represent a single causal process of demographic transition, as posited by Soares and Falcao (2008)¹. These two sets of theories support a link between female labor force participation and fertility decisions, with causality flowing in both directions. Several empirical studies confirm these predictions (see for example, Killingsworth and Heckman 1986; Angrist and Evans 1998; Kalwij 2000; and Lehr 2009). Better labor-force opportunities for women appear to have played a role in the historic reductions in fertility that defined the demographic transition that swept Europe and the United States from the 1800 s to the early 20th century (Guinnane 2011). By increasing the opportunity costs of childbearing, locally available industrial employment opportunities (such as the opening of a nearby textile factory) reduced marital fertility by small but significant amounts (Schultz 1985; Crafts 1989; Brown and Guinnane 2002). The study of such transitions in developing countries remains limited, however.

China is a particularly important place to study the relationship between women’s employment and fertility, given its rapid pace of economic development, enormous population, and controversial family planning policies. With more than 1.3 billion people in 2010, China is the most populous nation in the world (Peng 2011). For the past 40 years, China has sought to control population growth. The “one-child” policy, initiated in 1979, limits most urban couples to precisely that, and constrains most rural couples to no more than two children, or one son (Peng 2011). Although fertility rates had already begun to decline steeply before this policy was introduced, the one-child policy appears to have substantially reduced fertility rates and population growth (Banister 1987; Wang 2011; and Peng 2011)².

Our analysis uses 2006 data from the China Health and Nutrition Survey to assess how female employment affects fertility in China. A major challenge in inferring the effect of female employment on fertility is the reverse causal flow, noted above. To overcome this endogeneity problem, we employ an instrumental variable that facilitates access to employment opportunities - the availability of a bus stop in the residence community – to estimate female employment status. To the best of our knowledge, this is the first study to analyze the causal effects of female employment on fertility behavior using data from China³.

We study fertility preferences and actual fertility, and find that off-farm employment significantly reduces both. Controlling for endogeneity increases the estimated effect of female employment status on fertility. Our preferred specification indicates that female employment reduces the preferred number of children by 0.35 on average, and the actual number of children by 0.50. Having a first child who is a son is associated with lower fertility, both preferred and actual.

The rest of the paper is organized as follows. Section 2 provides background information about China’s population control policy, and Section 3 presents a simple conceptual framework. Data and variables are described in Section 4. Section 5 presents our estimation strategy, and Section 6 shows the results. Section 7 summarizes our findings and discusses their policy implications.

Due to its huge population, China has employed various population control policies for the past 40 years. In 1971, when the population was more than 800 million, China integrated population control into its national economic development plan. In 1973, the central government started the “Later, Longer, and Fewer” family-planning campaign to encourage later marriage, longer intervals between births, and fewer children. In 1978, China encouraged couples to have only one child, and set the maximum at two. It also added family planning to its constitution. The next year China’s State Council began implementing the so called “one-child policy” through the family planning administration, emphasizing population control as a strategic requirement for China’s development.

Although China’s policy is called the one-child policy, many couples are allowed to have more than a single child (Peng 2011). Most ethnic minorities (that is, non-Han ethnic Chinese) are permitted to have more than one child. In rural areas, a couple may usually have a second child if the first child is a girl or is disabled. To implement the restrictions on childbearing, local governments provide financial subsidies to families with one child, and impose substantial penalties if a couple violates the population control policies by having an “out of quota” birth⁴.

There are several reasons why enforcement of a strict one-child policy has been difficult in China. Children – especially sons – are valued for contributing to farm labor (Schultz and Zeng 1995) and for providing parents with old-age security (Hussain 1994), since social security and pension systems in China are both recent and limited. The one-child policy is also often linked to the increase in China’s unbalanced sex ratio, enabled by ultrasound technology that permits sex-selective abortion⁵. Our study focuses on how female employment affects fertility in China. If employment reduces fertility, encouraging female employment could be an alternative tool for limiting population growth in China.

where n is the number of children. There are diminishing returns to each argument. To simplify, we assume that household income apart from her earnings are Y, and that off-farm employment requires a time commitment of K hours per week, and that care of each child requires h hours per week. All income goes into consumption, and any time not spent raising children or working (and commuting to work) goes into leisure.

Women differ along two dimensions: preference for children, and opportunities for off-farm employment. Utility from children is non-linear: w(n) = ba ^n − 1, with 0 < a < 1 common to all women. To capture differences in fertility preferences, we assume a distribution of the “taste for children” parameter, b. Differences in off-farm employment opportunities is represented by the distribution of the off-farm employment salary, s.

Three facts should be evident: 1. women offered a higher salary are more likely to accept employment; 2. women with a greater taste for children will desire more children and will require a higher wage before they work; and 3. among women with the same taste for children, women who are employed, having less time to allocate, will prefer fewer children⁶.

where t = 0 with no bus stop and t > 0 with a bus stop (i.e., access to a bus stop saves travel time to employment and thus reduces the time commitment of an off-farm job).

The distribution of taste for children and opportunities for employment will determine how many women choose employment and how many children employed and unemployed women will prefer. The parameters in our simulation of the model (results shown in Figure 1) are as follows: Y = 50, K = 60, a = 0.7, h = 20; s ranges between 0 and 55; and b ranges between 0.2 and 1.1. The values of s and b are such that they form a uniform sampling distribution between the limits given. These parameter values were selected with two considerations: simplicity and their ability to approximate actual fertility results. Drawing on our empirical data, we assume that 815 women reside in communities with no bus stop (t = 0), and 1540 have access to a bus stop (t = 7).

Figure 1 shows the number of children a woman will want as a function of the offered salary and her taste for children. The figure shows cut-off ranges for the preferred number of children in whole numbers (i.e., one or two children). For any given b (the preference parameter for children), there is a minimum salary offer above which a woman will accept off-farm employment. Having access to a bus stop shifts down the off-farm employment threshold, as shown in the shaded area of Figure 1. For women in the intermediate range of taste for children, there is an upward-sloping threshold for employment, indicating that they must be offered a higher salary to accept employment (to compensate for the opportunity cost of lost time to care for children). When these women have access to a bus stop, they change from n* = 2 to n* = 1: employment reduces preferred fertility. Those with the highest taste for children prefer to have more than one child, whether or not they work.

Overall, in our simulation portrayed in Figure 1, 35% of women choose employment off the farm. The preferred number of children among those who choose employment (1.46) is significantly less than among those who do not (1.84). As surmised, access to a bus stop increases the percentage of women who choose employment off the farm (from 26% in non-bus-stop communities to 40% for bus stop communities). In other words, where salary opportunities are poor, only 26% of women accept off-farm employment, but in communities with good salary opportunities, 40% accept employment. The presence of a bus stop, by lowering travel time to higher-salary jobs, encourages more women to seek off-farm employment. Those who are employed include women from the higher tail of the child-preference distribution, and therefore the average number of preferred children among working mothers is higher in the bus stop communities (1.50) than it is in non-bus-stop communities (1.36)⁷.

This model is consistent with what we find in our empirical work below: where opportunities for better-paid off-farm employment are greater, significantly more women accept employment; and regardless of location, employed women prefer fewer children (and are more likely to prefer only one child), compared to women who do not work off the farm.

Our fertility measures are

F_p = preferred number of children, and

F_a = actual number of children.

where

F_i = fertility measure, i = p or a;

X = a vector of other explanatory variables;

E = a binary indicator of whether the woman is employed in an off-farm job;

β₀ - β₂ = coefficients to be estimated; and

ϵ = the disturbance term.

The key coefficient of interest is β₂, the effect of female off-farm employment on fertility. The previous literature has employed ordinary least squares (OLS) (Zhang 1990) and count variable estimation (Poisson) (Schultz 1988) to estimate Equation (1). Given that fertility measures are count variables, Poisson estimation seems more appropriate.

where

IV = instrumental variable;

α₀ – α₂ = coefficients to be estimated; and

u = the disturbance term.

Equation (2) will be estimated by OLS estimation at the first stage in the two-stage least squares model. Traditional two-stage least squares estimation assumes that both the fertility measures and the employment measure are continuous, but in this context obviously they are not. The fertility measure is a count variable, while our employment measure is binary. Therefore, OLS and two-stage least squares are unlikely to provide efficient estimates of the effect of female employment status on fertility. Thus, after presenting traditional results for ordinary and two-stage least squares, we turn to a Poisson estimation procedure. We do so first without correcting for endogeneity, and then present a two-stage Poisson estimation that corrects for endogeneity.

If the coefficient on û proves to be statistically significant, that indicates that female employment status is endogenous (Rivers and Vuong 1988; Smith and Blundell 1986; and Terza et al. 2008) conditional on the validity of our instrumental variable. The endogeneity-corrected coefficient β₂ in Equation (3) provides an unbiased estimate of the effect of female employment status on fertility (Terza et al. 2008). Due to the two-stage feature of this approach, the estimated standard errors in Equation (3) are underestimated (Terza et al. 2008). Thus, we employ bootstrapping techniques with 1,000 replications to obtain the corrected standard errors.

Our prime finding is that off-farm employment reduces fertility for Chinese women. Based on our Poisson estimation with two-stage residual inclusion, which controls for endogeneity of employment status, and holding other factors at the mean for our sample, off-farm employment reduces the preferred number of children by 0.35 and the actual number of children by 0.50.

Why does controlling for endogeneity yield a more powerful negative effect of employment on fertility? We conjecture that controlling for the endogeneity of employment removes the income and wealth effects that positively impact fertility in China,¹⁹ while female employment per se exerts negative substitution effects. High incomes and wealth also allow parents to pay the penalty fines in China if they violate the one-child policy²⁰. Because collinearity precludes us from including both employment and income (for females) in the same regression, the coefficient of non-instrumented employment includes both effects, which push in opposite directions. Once we instrument for employment, the mitigating impact of female income disappears, revealing the negative effect of off-farm employment on fertility. In addition, the effects of fertility on employment may be small. Angrist and Evans (1998) find that Ordinary Least Squares (OLS) without controlling for endogeneity overestimates the effect of fertility on labor supply and conclude that fertility per se may have a smaller impact on female labor supply than one might expect. The reverse causality issue in our study may not be highly consequential, and omitted variable biases (such as those regarding female income and employment opportunity) may dominate the endogeneity of the employment measure.

These findings provide empirical evidence regarding the economic theory of fertility and female labor force participation. In addition, they have potentially important implications for employment and fertility policies in China. Given the Chinese government’s ongoing desire to curb population growth, the finding that female off-farm employment reduces fertility has important implications. Encouraging greater rates of off-farm employment for women could substantially reduce fertility without requiring any of the punishments and penalties for childbearing that have earned China so much criticism. Further improvements in women’s education would complement pro-employment policies by increasing the productivity of employment and multiplying its fertility-reducing effects.

In sum, our study indicates that off-farm employment for Chinese women curbs both preferred and actual fertility. Given that economic performance and population size are two critical concerns for China, it is vital that this negative link be recognized.

¹In the Soares and Falcao (2008) model, increasing adult longevity heightens incentives to invest in human capital, leading to a shift toward women working outside the home and reductions in the gender wage gap. Others have suggested several phases of demographic transition, with fertility first increasing and then decreasing as economy-wide productivity grows (see Lehr 2009).

²Li and Zhang (2007) provide evidence suggesting that low fertility contributed to China’s rapid economic growth since the 1980s.

³Schultz and Zeng (1995) find that female schooling and availability of health and family planning services significantly and negatively affect fertility in rural China. Rosenzweig and Zhang (2009) find that the one-child policy lowered fertility and increased the average “quality” of children; but neither set of authors analyzes female employment behavior.

⁴The benefits for a couple with only one child have included health care, housing, cash, and food subsidies (McElory and Yang 2000). Punishments for the employees of state-owned enterprises and governments who violate the policy may involve loss of promotion opportunities or even jobs; others are subject to cash penalties (Li and Zhang 2009). Unpermitted babies are often not able to register their residency, nor to obtain their identification card until these punishments are carried out. During a particularly zealous period of enforcement in the 1980s, some areas imposed even more draconian measures, such as forced abortions and sterilizations (Hardee-Cleaveland and Banister 1988). Recently, policies have been changed to allow a couple whose two members are only children to have a second child. (China Daily 2006).

⁵The sex ratio at birth (boy/girls) increased from 1.056 in 1982 to 1.153 in 2000. The unnatural excessively male sex ratio at birth raises many challenges for China’s society and economy, and many policies have been designed to ameliorate it (Li 2007). However, the 2010 census revealed that the problem remains acute: for every 100 newborn girls, there are 118 newborn boys in China (Peng 2011).

⁶For simplicity, we assume salary s is the increment to household income that can be attained from the woman switching from work on the farm to off-farm employment, and that the K hours of off-farm employment cannot be combined with childcare in the same way that work on the farm can.

⁷Figure 1 also shows that the cut-off line between n* = 1 and n* = 2 becomes steeper when women have better off-farm employment opportunities (access to a bus stop). Those with the highest salary offers were already employed, but now save time in commuting to work, and a few of them therefore switch to preferring a second child. Thus, even in this simple model of time trade-offs, there are forces pushing in opposite directions, and the impact of employment on fertility is an empirical question.

⁸This number equals the total number of children that a woman gives birth to, minus the number of children who have died, if any. If the woman is currently pregnant, this future birth is also counted as part of the cumulative fertility measure, because the current infant mortality rate in China is very low. Most women in China become pregnant soon after their marriage.

⁹Hesketh et al. (2005) find that 87 percent of married women in China use contraception, and 25 percent of reproductive-age women have at least one abortion.

¹⁰For example, using longitudinal surveys in Anhui and Guangdong provinces, Li et al. (2010) find that daughters’ ability to support their parents has increased, particularly through off-farm labor including temporary migration to urban areas.

¹¹In formulating the fertility preference question as it did, it seems clear that the CHNS surveyors felt that the chances of women preferring to have fewer children were remote.

¹²See Table 1.

¹³We recognize that if there were a combination of three conditions – shocks to fertility across communities unrelated to employment, fertility significantly affected female employment, and female employment significantly influenced whether a bus stop would be installed -- our instrument would measure fertility directly, not merely employment opportunities. This confluence of required conditions strikes us as unlikely. Moreover, if female employment did boost bus stops, the posited instrumental variable relationship would be overstated. This in turn would reduce the absolute impact of using instrumental variables compared to single-stage estimation, contrary to what we find. As reported below, the IV estimates magnify the negative effect of employment on fertility. Thus, if anything, this negative effect is underestimated in OLS, implying the hypothetical scenario outlined in this paragraph does not apply.

¹⁴Using the lagged instrument of bus stop availability may avoid the potential issue of female employment affecting the setup of a bus stop in the same year. The results using lagged bus stop existence are omitted due space limitations, but are available from the authors upon request.

¹⁵As an additional robustness check, we replaced total household income with household income excluding any female income in the multivariate regressions; the results were very similar to those reported in the text.

¹⁶The marriage law in China sets a minimum legal age for women of 20 years.

¹⁷For example, Yao (1999) reports the female employment rate in a rural county of Zhejiang province to be about 33 percent.

¹⁸Although fertility is higher in rural than urban areas, China’s average total fertility per woman has remained under 2 since 1992 (McElroy and Yang 2000).

¹⁹Note that our estimate of a positive effect of income on fertility is consistent with the conceptual model but contrasts with Schultz and Zeng (1995) and most data for higher income countries.

²⁰As most jobs in China are no longer in state-owned enterprises or government agencies, administrative tools are less effective, making penalty fines more powerful (McElroy and Yang 2000).