Tag: Fertility

Short-Run and Long-Run Effects of Sizeable Child Subsidy: Evidence from Russia

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How to design the optimal pro-natalist policy is an important open question for policymakers around the world. Our paper utilizes a large-scale natural experiment aimed to increase fertility in Russia. Motivated by a decade-long decrease in fertility and population, the Russian government introduced a sequence of sizable child subsidies (called Maternity Capitals) in 2007 and 2012. We find that the Maternity Capital resulted in a significant increase in fertility both in the short run and in the long run. The subsidy is conditional and can be used mainly to buy housing. We find that fertility grew faster in regions with a shortage of housing and with a higher ratio of subsidy to housing prices. We also find that the subsidy has a substantial general equilibrium effect. It affected the housing market and family stability. Finally, we show that this government intervention comes at substantial costs.

In all European and Northern American countries the fertility is below the replacement level (United Nations, 2017). Following this concern, most of the developed countries have implemented various large scale and expensive pro-natalist policies. Yet, the effectiveness of these policies is unclear, and the design of the optimal pro-natalist policy remains a challenge.

There are several important open research questions on the evaluation of these programs. The first is whether these programs can induce fertility in the short-run and/or in the long-run horizon. Indeed, very few of these expensive and large-scale policies are proved to be an effective tool to increase fertility (Adda et al, 2017). The next set of questions deals with further evaluation of the programs: What are the characteristics of families that are affected by this policy? How costly is the policy, i.e. how much is the government paying per one birth that is induced by the policy? Finally, what are the non-fertility related effects of these policies? While most of the studies that analyze the effect of pro-natalist policies concentrate on fertility and mothers’ labor market outcomes, these, usually large-scale, policies may have important general equilibrium and multiplier effects that may affect economies both in the short run and long run (Acemoglu, 2010).

In our paper we utilize a natural experiment aimed to increase fertility in Russia to address these questions.

Motivated by a decade-long decrease in fertility and depopulation, the Russian government introduced a sizable conditional child subsidy (called Maternity Capital). The program was implemented in two waves. The first wave, the Federal Maternity Capital program, was enacted in 2007. Starting from 2007, a family that already has at least one child, and gives birth to another, becomes eligible for a one-time subsidy. Its size is approximately 10,000 dollars, which exceeds the country’s average 18-month wage and exceeds the country’s minimum wage over a 10-year period. The recipients of the subsidy can use it only on three options: on housing, the child’s education, and the mother’s pension. Four years later, at the end of 2011, Russian regional governments introduced their own regional maternity programs that give additional – on the top of the federal subsidy – money to families with new-born children.

In our paper, we document that the Maternity Capital program results in a significant increase in fertility rates both in the short run (by 10%) and in the long run (by more than 20%). This effect can be seen from both within-country analysis and from comparing the long-term growth of fertility rates in Russia with Eastern and Central European countries that face similar economic conditions and had similar pre-reform fertility trends. Like Russia, Eastern European countries experienced a drop in fertility rates right after the collapse of the Soviet Union and had similar trends in fertility up until 2007. Our results show that while having similar trends in fertility before 2007, afterward Russia significantly surpassed all the countries from this comparison group.

Figure 1 illustrates the effect of the Maternity Capital on birth rates. The top two panels show monthly birth rates (simple counts and de-seasoned); the bottom panels show total fertility rates in Russia versus Eastern European countries, and versus the European Union and the US.

Figure 1. Total Fertility Rate, Russia, Eastern European countries, USA and EU.

Source: Sorvachev and Yakovlev (2019), and http://www.fertilitydata.org/.

The effects of the policy are not limited to fertility. This policy affects family stability: it results in a reduction in the share of single mothers and in the share of non-married mothers.

Also, the policy affects the housing market. Out of three options (education, housing and pension), 88% of families use Federal Maternity Capital money to buy housing. We find that the supply of new housing and housing prices increased significantly as a result of the program. Confirming a close connection between the housing market and fertility, we find that in regions where the subsidy has a higher value for the housing market, the program has a larger effect: the effect of maternity capital was stronger, both in the short run and long run, in regions with a shortage of housing, and in regions with a higher ratio of subsidy to price of apartments (i.e. those regions where the real price of subsidy as measured in square meters of housing is higher).

Figure 2 below shows the effect of Federal Maternity Capital on birth rates in different regions. It shows no effect on fertility in Moscow, small effect in Saint-Petersburg; whereas the sizable effect of maternity capital in other Russian regions.

Figure 2. Effect of Federal Maternity capital, by regions

Source: Sorvachev and Yakovlev (2019), and http://www.gks.ru/.

These results suggest that cost-benefit analysis of such policies should go beyond the short-run and long-run effects on fertility. Ignoring general equilibrium issues may result in substantial bias in the evaluation of both short-run and long-run costs and benefits of the program.

While there are many benefits of the program, we show that this government intervention comes at substantial costs: the government’s willingness to pay for an additional birth induced by the program equals approximately 50,000 dollars.[1]

For more detailed evaluation of the results see Evgeny Yakovlev and Ilia Sorvachev, 2019, “Short-Run and Long-Run Effects of Sizable Child Subsidy: Evidence from Russia”, NES working Paper # 254, 2019.


  • Acemoglu, Daron 2010 “Theory, General Equilibrium, Political Economy and Empirics in Development Economics”, Journal of Economic Perspectives, 24(3), pp. 17-32. 2010
  • Adda, Jérôme, Christian Dustmann and Katrien Stevens 2017. “The Career Costs of Children”. Journal of Political Economy, 125, 2, 293-337.
  • Ilia Sorvachev and Evgeny Yakovlev, 2019, “Short-Run and Long-Run Effects of Sizable Child Subsidy: Evidence from Russia”, NES working Paper #254 and LSE IGA Research Working Paper Series 8/2019

[1] Roughly, the WTP (US$50,000) exceeds nominal US$10,000 subsidy because the government pays for all (100%) families that give birth to a child to induce additional (20%) increase in fertility. See paper for more accurate elaboration.

Georgian Experience of Gender Biased Sex Selection

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This policy brief presents the evidence on gender biased sex selection (GBSS) in Georgia, giving an overview of the so-called “sex ratio transition” process, and discussing the determinants of GBSS using a demand and supply-side approach. After its independence from the Soviet Union, Georgia started experiencing a significant rise of the sex ratio at birth (SRB) and in 2004 the country had reached one of the highest SRB rates in the world. A traditionally pronounced son preference was further strengthened by deteriorated economic conditions, decrease in fertility and relatively easy and cheap access to technologies for early sex determination and abortion. However, Georgia has managed to reverse and stabilize a skewed SRB rate. Among the factors that might have contributed are the strengthening of the social security system, improved economic conditions, a rise in fertility rates, economic empowerment of women, and the increased cultural influence of Western values. This trend reversal places Georgia in a unique position and may provide valuable insights for other countries who struggle with the same problem.

It is widely recognized that the Caucasus has traditionally been a “male-dominated region,” with a particularly strong son preference. However, before the dissolution of the Soviet Union in the early 1990s, sex ratios at birth in the Caucasus countries were very close to normal levels.

After independence from the Soviet Union, the SRB started rising immediately in Georgia, reaching 114.1 male births per 100 female births by 1999 (while the biologically normal SRB level is 105 male births per 100 female births). In the early 2000s, SRB peaked and stabilized between 112 and 115 male births per 100 female births for several years.  As Figure 1 shows, after reaching historically high levels in 2004, SRB started to decline and finally returned to a normal level by 2016.

Figure 1. Estimated sex ratio at birth in 1990-2016

Source: UNFPA, 2017.

The sex selection here is not discussed as “an archaic practice” in Georgia, but rather a modern reproductive behavior, a rational strategy responding to the surrounding environment – demand and supply factors. Demand-side factors include socio-economic and cultural factors that make having a boy more beneficial for a family and lower the value of girls – leading to son preference. The fertility rate is also accounted as a demand-side factor since low or decreasing fertility can increase incentives to perform selective abortions. As for the supply-side factors, they cover the ease of access to  technologies for early sex determination and selective abortion and its cost, as well as the content of the legislation regulating abortion.

Demand side factors

Factors increasing demand

Son preference and a patrilineal system. The traditional Georgian family is patrilineal. Patrilineality, also known as the male line, is a common kinship system in which an individual’s family membership derives from and is recorded through his or her father’s lineage. It generally involves the inheritance of property, rights, names, or titles by persons related through male kin. In such systems, women join their husbands’ families after marriage and are expected to care for their in-laws rather than their parents. Sons are expected to stay with their parents and take care of them. Thus, patrilineal systems make daughters less beneficial and desirable to their parents compared to sons. UNFPA (2017) concludes that the practice of post-marital co-residence with parents is still quite widespread in Georgian society, and this pattern is biased towards the male kin line, downplaying the role of women and their kin. The patrilocal residence (the situation in which a married couple resides with or near the husband’s parents) is more common in villages (more than 90%) than in urban areas (75%). The incidence of patrilocal residence is the lowest in Tbilisi (69%). In general, patrilocal residence decreases with improving economic conditions.

Demographic change – changes in fertility rates. Low or decreased fertility rates (when other factors favorable for GBSS are in place) mean that families are no longer able to ensure the birth of a son through repeated pregnancies. In societies characterized by strong son preference, and with increasing availability of sex detection technologies, couples start to opt for sex selection because they want to avoid additional births of girls, something that contraception cannot alone ensure. Therefore, low fertility acts as a “squeeze factor,” forcing parents to make choices ensuring the desired gender composition of their family.

An inverse relationship between fertility and SRB is observed in Georgia. The first decade of transition to market economy was severe for the country. Reducing household size was one strategy chosen by Georgian families to cope with increased rates of unemployment, deterioration of the social security system and deprivation of basic needs such as water and electricity. The decline of fertility during the years 1990-2003 coincided with increased SRB levels. When fertility started to rebound in 2003, the “squeeze factor” began to vanish, removing pressure on the SRB. At the same time, the SRB started to decline.

The low value of women. In Georgia, women are stereotypically perceived as natural caretakers, whose core responsibilities involve child care and household duties. They are also expected be obedient to their husbands and let them have leading positions in various activities (UNDP 2013). The majority of the population in the country thinks that men should be the ones who are the family’s decision-makers and that they should also be the main breadwinners. According to a 2010 study, 83% of respondents think that men should be the main breadwinners in the family, and 63% believe that they should also be the family’s decision-makers (CRRC, 2010). It is evident that such attitudes and values contribute to decrease the perceived value of girls in society, compared to boys, and add additional stimulus to GBSS.

Factors decreasing demand

The strengthening of state institutions and the social security system. Georgia has experienced a deep transformation of its social, economic and political systems in the last fifteen years. Reforms were carried out in all sectors. Most importantly, the country totally restructured its social security system, which was practically non-existent in Georgia at the beginning of the 1990’s. Currently, Georgian citizens are offered: a) universal pension system, above the subsistence minimum, which provides a flat rate benefit to all elderly; b) social assistance, which represents a monthly subsidy to poor families, is well targeted, and has contributed to reducing poverty (Kits et al. 2015), and (c) a universal health insurance system which covers all people who are uninsured by private companies and softens the burden of health care expenditures for households.

These changes, together with the improved general economic situation in the country, have decreased the role of the family as a buffer institution offering protection and stability (notably through sons), and provided more formal alternatives for social security, bank loans, contractual employment, etc. Due to this, the (large) intergenerational family is no longer perceived as the only strategy for coping with social and financial uncertainty.

New cultural influence of Western values. From the early 2000s, Georgia has been increasingly exposed to Western norms and culture through media, migration, increased tourism, and the process of economic integration with the European Union. According to experts, this process was accompanied by “media support and an enthusiastic, quasi-propagandistic hail. The general spirit was to promote an image of Georgia as a country open to the world with West-European views and lifestyles” (UNFPA 2017).

Supply side factors

While the availability of technologies for the early determination of sex and for abortion is not the root cause of GBSS, it constitutes a facilitating supply factor. Without prenatal diagnostics and accessibility of abortion, parents would not be able to resort to selective abortions even if they had a pronounced preference for boys.

Currently, Georgia is among the countries offering high-tech reproductive services. Private clinics, hospitals, and special reproductive medicine centers compete to supply reproductive services, and one can easily see the most recent ultrasound technologies in the great majority of the urban facilities. In addition, the cost of an ultrasound test is extremely low, depending on the service provider. This represents only 1.9%-4.8% of the average monthly incomes per Georgian household. In this context, the GBSS-related demand for prenatal diagnostics can easily be accommodated, when it arises.


Georgia has had a unique experience of “sex ratio transition” in the region, which was an integral part of its overall transformation process. The deteriorated social and economic conditions of households following the beginning of the transition process, coupled with easier and cheaper access to prenatal diagnostics were reflected in a skewed SRB and manifested son preference. Only when socio-economic conditions improved, and the country accelerated its institutional strengthening and modernization process, did the SRB returned to its normal level.

It is too early to conclusively state that Georgia is back to normal SRB levels for good. Birth masculinity still remains at a high level i) for third-order births, as the most of the couples are reluctant to have more than three children, and giving birth to a third child is the last chance for families to have a boy; ii) there is a significant urban-rural divide in the context of birth order. For three or higher order births, SRB is significantly distant from normal levels for almost all regions, reaching beyond 145, while in Tbilisi the bias remains moderate; iii) gender-biased sex selection remains high among poor people and ethnic minorities.

If Georgia is to minimize the incidence of GBSS in the future, it needs to act on several fronts: enhance gender equality through qualitative research and civic activism; increase the perceived value of girls and women in the society through policies and initiatives addressing cultural stereotypes, as well as by publicizing illuminated stories of success of girls and women that provide positive role models; monitor SRB trends; support advocacy actions and awareness-raising campaigns on GBSS and encourage the ethical use of sex detection technologies.


Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Career Women and the Family – A New Perspective on the Role of Minimum Wage

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This brief finds that whereas in the 1980s richer women had fewer children than women near the middle of income distribution in the US, it is no longer true today. It argues that the rise in inequality is the main driver for this change. Greater income inequality enables high-income families to outsource household production to lower-income people. Changes to minimum wage laws are thus likely to affect the fertility and career decisions of the rich.

“I have frequently been questioned, especially by women, of how I could reconcile family life with a scientific career. Well, it has not been easy.”

 – Marie Curie, 1867-1934

Much has been made of women “leaning in” at work at a cost to their families. Indeed, this discussion has become more prevalent as women have surpassed men in higher education in most developed countries, and have entered prestigious careers en masse, a fact reinforced by public policy. For example, in 2012 the European Commission published a special report on women in decision-making positions, suggesting legislation to achieve balanced representation of women and men on company boards. One natural question to ask is, how high is the cost of a woman’s career to her family? This is a difficult, multifaceted, and even sexist question to ask.

High-income women have historically had fewer kids (Figure 1 for the year 1980). Social scientists’ leading explanations rely on the difficulty of combining children and a career. Under this view of the world, as more women focus on their careers, they have fewer children. On the other hand, the evidence shows that more educated (or wealthier) women produce more educated children. Given these two regularities, the majority of children are born to poorer mothers, and thus receive an inferior education. Moreover, this creates a feedback loop that depresses the average education through time making us question our ability to sustain a satisfactory average level of education.

Figure 1. Fertility rates by income deciles, 1980 and 2010


Notes: Calculated using Census and American Community Survey Data. The sample is restricted to white, non-Hispanic married women. Fertility rates are hybrid fertility rates, constructed by age-specific deciles. Deciles are constructed using total household income.

However, the negative relationship between family income and fertility ceases to hold after the 2000s. Figure 1 shows that for the year 2010, the cross-sectional relationship between income and fertility has flattened or even become a U-shape. Today, high-income women have higher fertility rates than those of women near the middle of income distribution. This is a result of a substantial increase in fertility among women in the 9th and 10th decile of family income: they increased their fertility by 0.66 & 0.84 children, respectively. The rise in fertility of high-skilled females was first documented in Hazan and Zoabi (2015), discussed in a previous FREE Policy Brief. The implications are profound; children are more likely to be born to wealthier or more educated mothers than in the past. This has a far-reaching impact on the future composition of the population.

How can we understand the change in fertility patterns over time? We argue that rising wage inequality played an important role. Data for the years 1980 and 2010 show that average real hourly wages, quoted in 2010 $ grew from $28 ($51) to $50 ($64) for women (men) in the 10th decile of the income distribution. This increase was accompanied by stagnant wages for women (men) in the 1st decile, precisely the people who are most likely to provide services that substitute for household chores (Figure 2).  Thus, growing wage inequality over the past three decades created both a group of women who can afford to buy services that help them raise their children, and a group who is willing to supply these services cheaply. In a recent paper, we found that the increase in wage inequality from 1980 and 2010 can actually explain the rise in high income fertility (Bar et al. 2017). Moreover, this rise in inequality has resulted in a large increase in college attendance through the changing patterns of fertility. This is because more children are now born to highly educated mothers.

Figure 2. Wives’ Wage by Income Decile 1980 & 2010


Notes: Calculated using Census and American Community Survey Data. The sample is restricted to white, non-Hispanic married men. Deciles are constructed age-by-age, using total household income. Representative wages for each decile is the average of these decile-specific wages from ages 25 to 50.

Our new understanding of the interrelation between income inequality, the relative cost of home production substitutes, fertility pattern and educational choice induces us to rethink some typical economic debates. For instance, consider the minimum wage. The typical debate about the minimum wage is focused on how it affects lower wage individuals in terms of income and their ability to find work. However, if people who earn the minimum wage are disproportionately also those who help raise wealthier families’ children, or simply make running a household easier, then a higher minimum wage can make home production substitutes more expensive for high wage women, making it harder for them to afford both a family and a career. While indirect, this effect can be significant. Figure 3 shows the distribution of the real wage, relative to the minimum wage, both for the industries of the economy associated with home production substitutes and other sectors of the economy. The figure clearly shows that workers in industries associated with home production substitutes are concentrated around the minimum wage and thus are much more likely to earn wages that are close to the minimum wage.

Figure 3. The distribution of real wages, relative to the effective real minimum wage in each state and year, by sector of the economy

Notes: Data from Current Population Survey, 1980–2010, using all workers.

Interestingly, we calculate a change in the cost of home production substitutes following an increase of the Federal minimum wage from $7.25 to $15/hour, as suggested by Bernie Sanders during the 2016 presidential election. It turns out that this increase in the minimum wage would increase the cost of market services that substitute for household chores by about 21.1%. Indeed, the minimum wage has a strong impact on the average wages of workers producing home production substitutes. However, how does this increase affect the economy?

According to our theory, higher costs of home production substitutes would affect women’s choice of how to allocate their time between labor force participation and home production, including raising children. The higher cost of these substitutes induces women to buy less of them and spend more of their time producing home production goods. Indeed, we find that the increase in the minimum wage decreases fertility and increases mothers’ time at home, and more so for higher income households. The magnitudes are large. A 10th (5th) decile household decreases fertility by 12.8% (9.4%), while the mother spends 9.7% (2.5%) more time at home. Notice that these numbers are calculated under the assumption that women can adjust fertility. What about those who are “locked in” their fertility choice? We recalculate changes in mother’s time at home for these mothers using the model’s fertility in 2010 with the increased cost of market services that substitute for household chores. A 10th decile mother increases time at home by 25.9%, while a 5th decile mother increases it by 13.1%. These numbers are larger as the family has not had a chance to scale back fertility. The short run effect on labor supply is also very large. The average reduction in labor supply by women in the 9th and 10th deciles is 3.5%.

Whether an increase in the minimum wage is good or bad for the society is a big question.  Not only does it lie beyond the scope of our theory, but also beyond the scope of social sciences.  However, the one modest contribution we try to make is in observing that an increase in the minimum wage heightens the rivalry between a woman’s career and family. As such, it forces women to forgo one in order to opt for the other.

The sexist nature of our question lay in the implicit assumption that it is the mother’s responsibility to look after the children or home production in general, rather than the father’s. While once this was a nearly universal attitude, it is now increasingly common for fathers to take a more central role in childcare rather than leave everything to the mother. How does this change in gender roles affect our analysis? In modern times, both spouses’ careers are potentially affected by children, as both parents take a role in child care. Fathers are now facing the same tradeoffs as mothers did in the traditional gender role story: children vs. careers. As a result, marketization is more important than ever for career oriented parents.

Talk to a high wage family and no doubt that they’ll readily tell you how important their ability to purchase daycare, prepared food, or other help at home is to their success as parents. Perhaps parents don’t realize that the price of these goods are so intricately linked to inequality or the minimum wage, but the policy maker should bear in mind that these are key factors for career women and the family.


  • Hazan and Zoabi (2015), “Do Highly Educated Women Have Smaller Families” The Economic Journal
  • Bar, Hazan, Leukhina, Weiss, and Zoabi (In progress) “Is the Market Pronatalist? Inequality, Differential Fertility, and Growth Revisited”

Highly Educated Women No Longer Have Fewer Kids

This policy brief summarizes evidence that the cross-sectional relationship between fertility and women’s education in the U.S. has recently become U-shaped. The number of hours women work has concurrently increased with their education. The theory that the authors advance is that raising children and home-making require parents’ time, which could be substituted by services such as childcare and housekeeping. By substituting their own time for market services to raise children and run their households, highly educated women are able to have more children and work longer hours. The authors find that the change in the relative cost of childcare accounts for the emergence of this new pattern.

In 2012, the European Commission published a special report on “women in decision making positions”, suggesting legislation to achieve balanced representation of women and men on company boards. Some countries such as Norway, France, Italy, Belgium and the Netherlands have already taken legal measures in that direction. Trends in women’s education give hope that such goals may be achieved as women are increasingly occupying more prestigious and demanding careers. Indeed, in today’s world, women have surpassed men in higher education in most developed countries (Goldin et al 2006; Hazan and Zoabi 2015a).

What are the consequences of this important development for fertility? Historically, highly educated women have had fewer kids than less educated women (see, for example, Jones and Tertilt 2008). This relationship is deep rooted in the economic and sociological literature to the extent that many theories have already been proposed to explain this relationship. Leading explanations rely on the difficulty to combine children and career (Mincer, 1963; Galor and Weil, 1996) and the quantity-quality tradeoff (Becker and Lewis, 1973; Galor and Weil, 2000; Hazan and Zoabi 2006). The shift in women’s education coupled with more demanding careers for women means that if the cross-sectional relationship between women’s education and fertility is stable over time, then future fertility rates will continue to decline from their already historically low levels.

In Hazan and Zoabi (2015b) we find, however, that the cross-sectional relationship between women’s education and fertility has changed from monotonically declining until the 1990s to a U-shaped pattern during the 2000s. This change is due to a substantial increase in fertility among women with advanced degrees who increased their fertility by 0.7 children, or by more than 50%. This is illustrated in Figure 1, which plots the cross-sectional relationship between fertility and women’s education in 1980 and during the period 2001-2011.

Figure 1: Fertility Rates by Women’s Education, 1980 and the 2000s.


What can explain the rise of fertility among highly educated women during the period that saw the largest increase in the labor supply of highly educated women? We argue that the rise in college premium increased the demand for child-care and housekeeping services by highly educated women and a rise in the supply for such services by low educated women. This ‘marketization’ weakened the tradeoff between career and family life and enabled highly educated women to pursue demanding career without giving up on their desired family size.

To establish the relationship between the rise in the college premium and fertility of highly educated women, we use data from the March CPS for the period 1983-2012. We estimate the average hourly wage in the “child day-care services” industry and allow it to vary by state and year. In addition, we compute the hourly wage of all women in the 25-50 year-old age group who reported a positive salary income. Figure 2 presents the fitted values of the average of this variable for each of our five educational groups. The figure shows that childcare has become relatively more expensive for women with less than a college degree but relatively cheaper for women with a college or an advanced degree.

Figure 2: Linear Prediction of the Log of the Ratio of Average Wage in the Childcare Industry to Average Wage in the Five Educational Groups 1983–2012


To utilize the micro data we estimate regression models where the dependent variable is a binary variable that takes the value of one if a woman, living in a specific state in a specific year gave birth during that year and zero otherwise. Our main explanatory variable is the labor cost in the child daycare industry divided by the own wage of that woman. We show that there is a highly statistically significant and economically large negative correlation between this measure of childcare cost and the probability of giving a birth. In our empirical analysis we find that this change in the relative cost can account for about one-third of the increase in the fertility of highly educated women. We use a battery of tests to show that this correlation is not driven by selection of women into the labor market, by the endogeneity of wages, or by specific years over the last three decades.

Figure 3: 2000s Actual and Hypothetical Fertility under the 1980s prices of Childcare


Figure 3 uses the estimates from the regression models described above and shows a hypothetical fertility for 2001-2011 under the 1983-1985 relative childcare cost. The figure shows that the hypothetical fertility curve is obtained by a clockwise rotation of the actual fertility curve around the group of women that has some college education.

Direct evidence on paid childcare services is consistent with this view. Figure 4 shows the average weekly paid childcare hours by all women aged 25-50 in 1990 and 2008. The figure has two salient features. First, in each of these years, paid childcare is increasing with women’s education. Secondly, between 1990 and 2008, paid childcare hours have stagnated for women with up to some college education but have sharply increased for highly educated women.

Figure 4: Paid Childcare Weekly Hours for Women aged 25-50.


We then rule out potentially other explanations. What if the increase in labor supply stems from women who did not give birth during that year? To address this concern we shows that the cross-sectional relationship between education and usual hours worked for the sub-sample of women age 15-50 who gave birth during the reference period exhibit the same positive correlation. Another concern might be that it is in fact the spouses who respond to a birth by lowering their labor supply enabling their wives to work more. Find that men who are married to highly educated women work more than men who are married to women with lower levels of education. Interestingly, fathers to newborns work more than husbands who do not have a newborn at home, regardless of the education of their wives. More importantly, usual hours worked by fathers to newborns monotonically increased with their wives’ education. Thus, the spouses of highly educated women are not the ones substituting in childcare for their working wives.

Another concern our model may raise is that marriage rates differ across different educational groups. If married women have higher fertility rates and if more educated women have higher marriage rates, more educated women’s higher fertility rates may not be caused by the availability of relatively cheaper childcare and housekeeping services, but rather simply by their higher marriage rates. We find that the fraction of women with advanced degrees who are currently married is somewhat lower than that of women with college degree.

Figure 5: Number of birth per 1,000 White Women in the US in Age Groups 35-39, 40-44 and 45-49: Women with Advanced Degrees (2001-2011) and Historical Rates.


A final potential explanation might be related to recent advancements in Assisted Reproductive Technology (ART) that enable women to combine long years in school without scarifying parenthood. We address this possibility in three ways. First, we show that historical levels of fertility rates among women above age 35 were higher than the levels during the 2000s (see Figure 5). This stands in contrast to the argument that highly educated women were not able to have higher fertility rates in the past due to medical reasons. Secondly, we note that ART accounts for less than 1% of births occurred during the 2000s. Finally, fifteen U.S. states have infertility insurance laws that provide coverage to infertile individuals. We compare fertility patterns by women’s education in these states to the rest of the country and find no difference in fertility rates during the 2000s between the two groups of states.

The results of this study have several implications. For public policy, it highlights potential benefits from pro-immigration policies. Unskilled immigrants can potentially have positive effect on fertility via an increase in the supply of cheap home production substitutes. For many developed countries that are facing aging and shrinking population this may be something to consider. It also has consequences for economic growth. Given the strong correlation between parents’ education and kids’ education, an increase in the relative representation of kids coming from highly educated families means that the next generation is going to be relatively more educated. These are good news for economic growth.


  • Gary S. Becker and Gregg H. Lewis. On the interaction between the quantity and quality of children. Journal of Political Economy, 81:S279–S288, 1973.
  • Oded Galor and David N. Weil. The gender gap, fertility, and growth. American Economic Review 86(3): 374–387, 1996.
  • Oded Galor and David N. Weil. Population, technology, and growth: From Malthusian stagnation to the demographic transition and beyond. American Economic Review 90(4): 806–828, 2000.
  • Claudia Goldin, Lawrence Katz, and Ilyana Kuziemko. The homecoming of American college women: A reversal of the college gender gap. Journal of Economic Perspectives 20(4): 133–156, 2006.
  • Moshe Hazan and Hosny Zoabi. Does longevity cause growth? A theoretical critique. Journal of Economic Growth, 11 (4), 363-376, 2006.
  • Moshe Hazan and Hosny Zoabi. Sons or Daughters? Endogenous Sex Preferences and the Reversal of the Gender Educational Gap. Journal of Demographic Economic, Vol 81, pp: 179-201, 2015a.
  • Moshe Hazan and Hosny Zoabi. Do highly educated women choose smaller families? Economic Journal, 125(587):1191–1226, 2015b.
  • Larry E. Jones and Michele Tertilt. An economic history of fertility in the u.s.: 1826-1960. In Peter Rupert, editor, Frontiers of Family Economics, pages 165 – 230. Emerald, 2008.
  • Jacob Mincer. Market prices, opportunity costs, and income effects. In Carl F. Christ, editor, Measurement in economics: Studies in mathematical economics and econometrics in memory of Yehuda Grunfeld. Stanford University Press, pages 67-82, 1963.

For Some Mothers More Than Others: How Children Matter for Labor Market Outcomes When Both Fertility and Female Employment Are Low

20190114 How Are Gender-role Attitudes Image 01

Authors: Krzysztof Karbownik and Michal Myck, CenEA.

Wide spread entry of women into the labor force has been one of the most pronounced socio-economic developments in the 20th century, and high levels of female employment are crucial from the point of view of continued economic growth and financial stability of many welfare systems (Galor and Weil, 1996). At the same time, demographic changes determined by the current and future fertility levels will play a vital role in shaping these developments and will affect the costs of social programs. Given the potentially strong link between female employment and family size, it seems that understanding the relationship between the two ought to be at the heart of policy discussions, especially in countries that are characterized by both low fertility and low female employment. In particular, in light of rising unemployment in low-fertility countries, which have been most severely affected by the economic crisis such as Greece, Spain and Latvia, our findings may serve as a guide with respect to the relationship between fertility and labor supply in an environment, which will be more common in Europe in the near future.