metadata: authors: 0: author: Trako,Iva
count: South Eastern Europe and Balkans
docna: 0: docna: Fertility and Parental Labor-Force
            Participation : New Evidence from a Developing Country in theBalkans
docty: Policy Research Working Paper
subtopic: Labor Markets,Educational Sciences,Rural Labor Markets,Demographics
teratopic: Social Protections and Labor,Education,Rural Development,Health, Nutrition and Population
abstracts: cdata!: This paper examines the effect of
            fertility on parental labor force participation in a
            developing country in the Balkans, with particular attention
            to the intervening role of childcare provided by
            grandparents in extended families. To address the potential
            endogeneity in the fertility decision, the analysis exploits
            the Albanian parental preference for having sons combined
            with the siblings' sex-composition instrument as an
            exogenous source of variation. Using a repeated
            cross-section of parents with at least two children, the
            analysis finds a positive and statistically significant
            effect of fertility on parental labor supply for parents who
            are more likely to be younger, less educated, or live in
            extended families. The IV estimates for mothers show that
            they increase labor supply, especially hours worked per week
            and the likelihood of working off-farm. Similarly,
            fathers' likelihood of working off-farm and having a
            second occupation increase as a consequence of further
            childbearing. The heterogeneity analysis suggests that this
            positive effect might be the result of two plausible
            mechanisms: childcare provided by non-parental adults in
            extended families and greater financial costs of maintaining
            more children.
repnme: repnme: Fertility and Parental Labor-Force
            Participation : New Evidence from a Developing Country in theBalkans
display_title: Fertility and Parental Labor-Force
            Participation : New Evidence from a Developing Country in theBalkans
listing_relative_url: /research/2019/07/31222526/fertility-parental-labor-force-participation-new-evidence-developing-country-thebalkans
topicv3: Labor Markets m1326488 855,Education m1327048 470,Labor Force Participation m1504050 2746,Labor Supply m1504055 2751,Fertility Rate m1504357 2662
publishtoextweb_dt: 2019-07-01T00:00:00Z
historic_topic: Social Protections and Labor,Education,Rural Development,Health, Nutrition and Population
no_of_pages: 72
author_keys: 0: author_key: 1630031
model_extractions: Policy Research Working Paper 8931 Fertility and Parental Labor-Force Participation New Evidence from a Developing Country in the Balkans _Iva Trako_ Education Global Practice July 2019
Policy Research Working Paper 8931

# **Abstract**

This paper examines the effect of fertility on parental labor force participation in a developing country in the Balkans, with particular attention to the intervening role of childcare provided by grandparents in extended families. To address the potential endogeneity in the fertility decision, the analysis exploits the Albanian parental preference for having sons combined with the siblings’ sex-composition instrument as an exogenous source of variation. Using a repeated cross-section of parents with at least two children, the analysis finds a positive and statistically significant effect of fertility on parental labor supply for parents who are more likely to be younger, less educated, or live in extended families. The IV estimates for mothers show that they increase labor supply, especially hours worked per week and the likelihood of working off-farm. Similarly, fathers’ likelihood of working off-farm and having a second occupation increase as a consequence of further childbearing. The heterogeneity analysis suggests that this positive effect might be the result of two plausible mechanisms: childcare provided by non-parental adults in extended families and greater financial costs of maintaining more children.

This paper is a product of the Education Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The author may be contacted at itrako@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Fertility and Parental Labor-Force Participation: New Evidence from a Developing Country in the Balkans**<sup>_∗_</sup>

Iva Trako<sup>_†_</sup>

**JEL Classification** : J13, J22, C26 **Keywords** : fertility, parental labor-force participation, instrumental variables

> _∗_ I would like to thank and recognize my advisor Karen Macours for her special support and guidance throughout the elaboration of this paper. Helpful comments and advice from Ekaterina Zhuravskaya, Oliver Vanden Eynde, Gustavo Bobonis, John Giles, Marc Gurgand, Andrew Clark, Jamele Rigolini, Iv ́an Torre and Martin Rossi are also gratefully acknowledged. I also benefited from comments by two annoymous referees and seminar participants at PSE, Royal Economic Society Conference 2016, GRETHA 2016 and the Spring Meeting of Young Economists 2016. The views expressed in this paper are those of the author and do not necessarily represent those of Paris School of Economics. I am responsible for all remaining errors.

> _†_ Paris School of Economics and The World Bank, `iva.trako@psemail.eu`
# **1 Introduction**

The relationship between fertility and labor supply has been of longstanding interest in economics. The vast majority of the empirical studies focus on female labor supply and they report a negative relationship between the two variables, particularly among countries that grew rapidly in the second half of the 20th century (e.g. Angrist and Evans, 1998; Boca, Pasqua and Pronzato, 2005; Cristia, 2008; Bruijns, 2014; Hupkau and Leturcq, 2016). There is also a scattering of studies in developing countries (low- and middle-income countries) which has found not only negative but also mixed results (e.g. Porter and King, 2012; Ag ̈uero and Marks, 2011; Bloom et al., 2009; Cruces and Galiani, 2007).

A more recent literature pointing in the direction of a negative effect is suggestive that this result could be extrapolated to other contexts. This is something examined extensively by Dehejia, Pop-Eleches and Samii (2015) and Bisbee et al. (2015), who find that quasi-experimental evidence generalizes more readily to countries which share closer geographical, education, time and labor force participation characteristics. In addition, a parallel literature that uses a wide array of countries and over 200 years of history has emphasized a small and insignificant effect of fertility on labor supply at low levels of development and an economically large and negative effect at higher levels of development (e.g. Aaronson et al., 2017).

The contribution of this paper is to build upon this previous literature by arguing that, contrary to most of the existing literature, the effect of fertility on parental labor supply can be positive and statistically significant in the context of a developing country in the Balkans (Albania). Furthermore, this paper presents a comparative analysis on the relationship between fertility and labor supply based on the type of instrument. By decomposing the same-sex instrument, the results found in the paper suggest that in a context characterized by a strong son preference, all the relevant effect is coming from the _two girls_ siblings sex composition.

To clearly identify the relationship between fertility and labor force participation an exogenous source of variation in family size is needed.<sup>1</sup> In contrast to American parents who prefer to balance the sex composition of their children, Albanian parents have another fertility preference which is generally known as _son preference_ .<sup>2</sup> Albania is characterized by a patriarchal family system where parents prefer sons to daughters, especially until they have at least one son. Therefore, in the same spirit as Angrist and Evans (1998), I exploit Albanian parental preference

> 1Two methods based on natural experiments have been mainly used in the literature to tackle this endogeneity problem in the fertility decision. The first strategy was first introduced by Rosenzweig and Wolpin (1980) and uses the natural occurrence of multiple births or twinning at first birth to identify the effect of fertility on labor supply. They find that, although women who have had twins withdraw temporarily from the labor market, their labor-force participation is not affected overall. The second strategy was first proposed by Angrist and Evans (1998) and uses the preference of American parents for balancing the sex composition of their children. They find that fertility has a negative effect on the labor supply of women, but no effect on the labor supply of men.

> 2There are several previous papers that use parental preference for sons as an instrument for fertility, especially in developing countries. See Ebenstein (2009) for Taiwan, China Chun and Oh (2002) for the Republic of Korea, Lee (2002) and, Arnold and Zhaoxiang (1986) for China.

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for having sons combined with the siblings sex-composition instrument as an exogenous source of variation in the fertility choice. Thus, the analysis focuses on a specific margin: I estimate the impact of having a third child or higher order on parental labor supply outcomes in comparison to those with only two children.

The data used in this paper come from four different surveys conducted in Albania between 2002 and 2012. More specifically, I use the 2002, 2005 and 2012 Albanian Living Standard Measurement Surveys (LSMS) and the 2008-09 Albanian Demographic Health Survey (DHS). The advantage of these surveys is that they contain not only rich information on individuals’ socioeconomic and demographic characteristics, but they also contain detailed information on the family structure of each one of the households, including information about the children no longer living in the household, which makes possible the construction of the entire parental fertility history. For the purpose of this analysis, I construct a repeated-cross section of married mothers and fathers with two or more children whose oldest child is younger than 18 years old.

The main results of this paper argue that an increase in family size has a _positive_ impact on parental labor-force participation in the context of Albania. More precisely, for the sample of mothers I find that having an additional child (third or higher order) increases on average a mother’s likelihood of _working off-farm_ by 5 percentage points and it also increases the working time by around 4.4 _hours per week_ on average. Similarly relevant is the finding that fathers also change positively their labor-market behavior in response to a change in family size. In particular, having an additional child increases fathers’ likelihood of _working off-farm_ by 6.7 percentage points, and also their likelihood of having a _second occupation_ by 4 percentage points.

The second focus of the paper is to pinpoint the channels through which these results operate. I propose two plausible mechanisms behind the positive effect of fertility on parental labor supply for the case of Albania. First, family structure in developing countries, especially in rural areas, is characterized by the presence of extended families where several generations co-reside in or near the same household (Rosenzweig and Wolpin, 1985). In response to an increase in fertility, grandparents may adjust their time allocation by supplying more time in childcare and household chores. Being freed from such tasks reduces the reservation wage for the parents, leading to an increase in labor supply. Thus, for extended families the effect of fertility on parental labor supply depends on the substitutability between grandparent’s time and parent’s time in caring for children.<sup>3</sup> Second, children do not only require costs in terms of time dedicated to them but as well in terms of direct costs such as food, clothing, education or health. Given that a large part of the household budget in developing countries is used to cover basic necessities, such as food and shelter, an increase in financial costs might induce a negative income effect that is

> 3Several studies have examined the effect of family structure on women’s labor supply. They find that coresidence seems to increase the labor supply of women who have children (e.g. Wong and Levine, 1992; Sasaki, 2002; Gong and Van Soest, 2002; Maurer-Fazio et al., 2011; Compton and Pollak, 2014; Garcia-Moran and Kuehn, 2017; Posadas and Vidal-Fern ́andez, 2013; Shen, Yan and Zeng, 2016; Landman, Seitz and Steiner, 2017).

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sufficiently large to drive some parents into the labor force.

To this end, I perform a heterogeneity analysis where I analyze whether the results vary by parent’s education, parent’s birth cohort and family structure. In line with these hypotheses, the analysis suggests that the labor-market consequences of fertility are more likely to be driven by poorer, less educated, and younger parents. In particular, mothers living in extended families experience the largest positive effects of fertility on labor supply suggesting that childcare provided by grandparents in extended families reduces the parental time cost of looking after children. However, the positive effect of fertility on father’s labor supply is mostly driven by those living in non-extended families, which suggests that in this type of families parents do not count on childcare provided by grandparents and therefore the mother has to stay in the household while the father probably supplies more labor in the market.

In this regard, this paper not only contributes to the traditional literature on fertility and labor supply but it also adds new important insights into the functioning of labor markets in developing countries as a response to an increase in fertility. First, this paper contributes to a more recent literature on the role of grandparental co-residence in household behavior. In particular, it sheds light on the intervening role of childcare provided by grandparents in extended families in the relationship between fertility and parental labor supply. Second, I analyze parental response to an increase in fertility on the type of work they do and the varying degrees of flexibility in the labor market, such as work off-farm, work on-farm and self-employed. This is essential in a developing country since labor markets in this context are characterized by higher levels of informality and a considerable share of the employment in rural regions.<sup>4</sup> Third, since there are still few studies that consider the effect of fertility on men’s labor-force outcomes, I examine how the mentioned effects differ across gender by including not only women but also men in the analysis. Lastly, this study is, to the best of my knowledge, the first that exploits Albanian parental preference for having sons combined with the siblings sex-composition instrument to examine the causal link between fertility and parental labor supply.<sup>5</sup> The results of this paper also have important policy implications. The main finding indicates that with lower childcare costs provided by the presence of grandparents in extended families but also greater child costs, parental labor supply is not reduced as a consequence of an increase in family size, suggesting that as an informal childcare provision mechanism, extended families

> 4In developing countries, women are under-represented in higher proportions in the labor market and, therefore, primarily engaged in family activities. In addition, the degree of informality in the labor market reveals an additional dimension of inequality in labor outcomes. Evidence suggests that women are more likely to be engaged in the agricultural sector and informal labor market (e.g. self-employed or unpaid family worker) (Blunch et al., 2001).

> 5Albania has experienced a drastic fertility decline during the last fifty years, which has fallen from almost 7 children per woman in 1960 to only 1.65 in 2012 (Gjon ̧ca, Aassve and Mencarini, 2008). In addition to low fertility levels, Albania is also characterized by a declining employment rate for both men and women during the last years. According to the Albanian Institute of Statistics (INSTAT), labor-force participation has continuously fallen during the last twenty-five years from 75 % in 1989 to 62 % in 2013, women being the most damaged from this decline. Therefore, the setting of a declining fertility rate accompanied by declining employment rates and combined with a patriarchal society make Albania an interesting case for this analysis.

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play an important mitigating role for the time cost of children. However, as family structure in developing countries becomes more nuclear with economic development, the time cost of children may increase for parents which may lead to further fertility decline and fewer opportunities for non-parental household members to help with childcare or household chores. In view of this decline in intergenerational co-residence over time, governments in developing countries should establish a subsidized and universally accessible public childcare system in order to promote labor supply and sustainable economic development.

The remainder of the paper proceeds as follows. Section 2 reviews some relevant previous literature. Section 3 provides a brief summary on fertility and labor-force participation for the case of Albania. Section 4 describes the datasets and some descriptive statistics. Section 5 presents the identification strategy and empirical estimation. The econometric results of the paper are presented in Section 6 and discussed in Section 7. Section 8 briefly concludes.

# **2 Literature Review**

There is an extensive empirical literature attempting to explain the effect of fertility on labor supply. While earlier studies considered fertility to be an exogenous determinant of female labor supply, recent papers have recognized the endogeneity problem by aiming to establish a causal relationship between fertility and labor supply.<sup>6</sup> To address this endogeneity problem, economists have used different natural experiments to exploit exogenous variation in family size: twinning at first birth, siblings sex-composition and fertility shocks (Clarke, 2017).

There is considerable empirical evidence from developed countries, especially the U.S, supporting a negative impact of fertility on female labor-force participation, though not universally so. Examples include Rosenzweig and Wolpin (1980); Bronars and Grogger (1994); Jacobsen, Pearce and Rosenbloom (2001), who use twinning at first birth as a source of exogenous variation in order to estimate the effect of having a second child. Angrist and Evans (1998) exploit parental preferences for mixed-sex siblings in order to estimate the effect of a third or higher order child. They find that in the U.S. fertility reduces female labor supply significantly but that there is no significant change in male labor supply. Chun and Oh (2002) argue that while

> 6Some of the earlier papers that have tried to establish a relationship between fertility and female labor supply can be categorized in several groups according to how the authors have tried to tackle the problem of endogeneity. The first group is illustrated by the studies of Gronau (1973); Heckman (1974) and Heckman and Willis (1977) who assume that fertility is exogenous and established a strong negative correlation between female labor supply and fertility. A second group of studies (Cain and Dooley, 1976; Schultz, 1978; Fleisher and Rhodes, 1979) acknowledge the endogeneity of the fertility decision and tried to deal with the problem by estimating simultaneous equation models. These studies find a much smaller estimate when treating fertility as an endogenous variable. The biggest challenge of this approach is that it is quite difficult to find plausible exclusion restrictions that could identify the underlying structural parameters. A third group of studies incorporates actual fertility as a regressor but adds the lagged dependent variable (i.e. labor supply) to control for unobserved heterogeneity across women. Nakamura and Nakamura (1992) recommended this approach, and it has been used by a number of authors (Even, 1987; Lehrer, 1992). Although adding the lagged dependent variable can help control the unobserved heterogeneity, it still does not address accurately the problem of the endogeneity of the fertility decision.

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U.S. households prefer balancing the sex composition of their children, Korean families prefer sons. They use the first child’s sex as an instrument for fertility and find that having children reduces the labor force participation of married Korean women. More recent papers use different instruments that rely on childless mothers undergoing infertility treatments (Cristia, 2008; Lundborg et al., 2017) or miscarriage in a women’s first pregnancy (Hotz, McElroy and Sanders, 2005) or natural experiments like the use of the contraceptive pill at the state level (Bailey, 2013) or changes in abortion legislation (Bloom et al., 2009; Angrist and Evans, 1996) similarly conclude that fertility has a negative impact on mother’s labor force-participation or earnings.

The empirical literature from developing countries is relatively small and the evidence found is not unified. Some studies in developing countries have also found negative or no impact. Cruces and Galiani (2007) generalize the results for the U.S. found by Angrist and Evans (1998) to the populations of two Latin American countries (Argentina and Mexico) and find a negative effect of fertility on female labor force participation. Using data from a social experiment in Bangladesh, Schultz (2009) also finds a negative effect of family planning programs on female labor-force participation. Using son-preference as an instrument, Lee (2002) finds no significant effect of fertility on rural female labor supply in China. Ebenstein (2009) also uses son-preference but he reports a negative effect of fertility on maternal labor force participation in Taiwan, China. A more recent study by Ag ̈uero and Marks (2011) uses self-reported infertility as an instrument for family size. Based on data from 26 low- and middle-income countries, their estimation results show that the presence of children affects neither the likelihood of work nor its intensity for women.

However, there is also a scattering of papers in developing countries which show mixed or even positive effects of fertility on labor supply. Based on data from Demographic and Health Surveys covering 59 developing countries, Porter and King (2012) report that while many women in developing countries are less likely to work when they have more children, some are more likely to work due to greater financial costs of feeding more children. Bloom et al. (2009) combine data from Demographic and Health Surveys with abortion legislation laws in each country, and also find mixed results of fertility. There is also a micro study from Priebe (2010), who uses data from Indonesia and finds a positive effect of fertility on female labor supply, which is mostly driven by women which are poorer, less educated and who live in rural areas.

All these studies report LATEs that hold consistent results for alternative populations and compliers, and so do not provide external validity for inference in other populations. However, a more recent literature suggests that the negative effect could be observed in other contexts. External validity of the labor supply-fertility local average treatment effect is extensively examined by Dehejia, Pop-Eleches and Samii (2015) and Bisbee et al. (2015), who find that quasi-experimental evidence generalizes more readily to countries which share closer geographical, education, time and labor-force participation characteristics. There is also a novel strand of literature which documents how the impact of childbearing on female labor-force participa5
tion has evolved over time (the last two centuries) and across countries. Using twin births and siblings sex composition, Aaronson et al. (2017) find that the effect of fertility on labor supply is large and negative at high levels of income, but small and often indistinguishable from zero at low levels of income. These effects are consistent both across time looking at the historical time series of currently developed countries and at a contemporary cross section of developing countries.

Although most recent research suggests a negative effect of fertility on female labor supply, the contribution of this paper is that the effect of fertility on parental labor supply can be positive in the context of a developing country, similar to Porter and King (2012); Bloom et al. (2009) and Priebe (2010). Moreover, this paper presents a comparative analysis on the relationship between fertility and labor supply based on the type of instrument. By decomposing the samesex instrument, the results found in the paper suggest that in a context characterized by a strong son preference, all the relevant effect is coming from the _two girls_ siblings sex composition. This finding might provide external validity implications for other similar settings.

# **3 Background**

## **3.1 The Evolution of Total Fertility Rate in Albania**

In the mid-to-late 20th century, when modern contraceptive methods were developed and popularized in other countries, Albania was a Popular Socialist Republic, which promoted an aggressive pro-natalist policy that banned abortion. Modern family planning methods were virtually unknown and, although some were available, access was strictly controlled. The communist government believed that a larger population was necessary in order to protect the country from foreign influences that could exploit its natural resources. When communists took over the government of Albania at the aftermath of the II World War, the country had a population of just over 1.1 million people. In fact they had already found a pro-natalist environment which was reinforced by traditional patriarchal norms. After communism collapsed in 1990, the population had tripled in a period of less than 45 years to 3.3 million. With a total fertility rate of 6 children per woman in 1950, Albania had the highest fertility in Europe, which reached a peak of almost 7 children per woman by 1960 (Gjon ̧ca, Aassve and Mencarini, 2008). This rise in fertility during the 1950s and early 1960s mirrors the experience of many European countries during the same period, with the famous _baby boom_ period of the mid-1960s.

Even though during several decades Albania has had one of the highest levels of fertility in Europe, the country has experienced a substantial fertility decline during the last fifty years, which has fallen from almost 7 children per women in 1960 to 1.65 in 2012. Figure 1 shows the evolution of the total fertility rate in Albania. The reduction in the fertility rate during the communist regime occurred in the absence of modern contraception and abortion, which suggests that other social and economic policies, in particular the ones that improved the social 6
agenda in the country, might have had an indirect effect on fertility in Albania. Most significant of these were policies focused on the improvement of education in the country. For instance, the investment in education, with particular focus on the improvement of female education was unprecedented in Albania. Female illiteracy improved from 92% in 1945 to less than 8% in 1989, and by 2002 it was less than 5%, similar to most developed European countries (Gjon ̧ca, Aassve and Mencarini, 2008).

After the collapse of the communist regime in 1990, the decline in the total fertility rate has been even more substantial due to the introduction of many new laws and social policies which have aimed to regulate the transition to a more market-oriented and modern society. One of the first changes in legislation that the Albanian government introduced in 1995 has been the legalization of abortion. Also, family planning methods have become widely available, even though the level of information and education for its use still remains low. In addition, the political openness in the early 1990s has permitted people to move freely and also to emigrate. As a consequence, an enormous emigration mass took place in a very short period of time which was concentrated in the reproductive age groups. While the move towards market economy has been associated with the emancipation of the society in general and women in particular, it has also generated negative consequences in terms of employment. The collapse of industry brought back a large unemployment, especially for women (UNFPA, 2012; Gjon ̧ca, Aassve and Mencarini, 2008).

During the transition period studied in this paper (2002 - 2012), it is clear that Albania has a new setting with regards to fertility compared to the communist period. The existence of means of birth control which were not present before 1990, the high female unemployment rates, the economic crisis and the continuing emigration are several factors that might have contributed to the declining fertility rate during this decade.

# **3.2 Labor-Force Participation in Albania**

During the communist regime, the labor market in Albania was characterized by a state controlled individual decision-making and a high degree of centralization. In this system, there were social and economic policies that promoted continuously the equality between women and men in different social spheres, including the labor market.<sup>7</sup> Since the communist regime was interested in full female employment, the government provided support to the families through social and economic policies including childcare benefits and maternity leave schemes, complemented by a state-sponsored system of day-care nursing and kindergartens across the whole country. In addition, the prices for a number of essential products for children were subsidized by the state. As a result, women were freed from childcare responsibilities and were thus able

> 7For instance, the constitution of the People’s Socialist Republic of Albania (Article 41) stated _“The woman enjoys equal rights with a man in the work place, payment, holidays, social security, education and in all socialpolitical activities as well as in the family”_ (Kuvendi Popullor, 1976).

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to work. In 1989, female labor-force participation had reached 72.8%, an increase of more than 50% compared to 1960 (35.9%) and by that time there were only slight differences in labor-force participation between men (77.2%) and women (72.8%) (Gjon ̧ca, Aassve and Mencarini, 2008; INSTAT, 2004).

After the fall of the communist regime, Albania went through many radical demographic, economic and political changes. During this transitional period, women in particular have faced a substantial withdrawal from the labor market due to several reasons. First, state enterprises, where women made up the greatest percentage of the workforce before 1990 collapsed due to their inefficiency and so did social protection associated with these jobs (Tarifa, 1994). Second, childcare deteriorated and at the same time many day-care nurseries and kindergartens were closed. For instance, compared to 1990, the number of kindergartens had fallen by 60% in urban areas and by 49% in rural areas in 2004 (IMF, 2006).<sup>8</sup> Third, during this period the country also witnessed a massive male emigration, which has left the wives at home taking care of the children, engaging in housework or informal market and thereby decreasing their working hours out of the house. Also, the internal migration to urban areas has damaged the labor supply of women since they face more problems entering the urban labor market in the current economic environment. Consequently, women’s schedules have required more accommodation giving rise to long-term structural discrimination in the labor market and high female unemployment rates.

Labor force participation has still remained low in Albania during the last decade, especially for young people and women. Statistics from INSTAT (2014) show that the labor-force participation rate for women between 15-64 years old is 50.1% whereas for men it is 70.2%. Employed women are still finding it more difficult to balance career and family as the availability of state financed social services is quite low and the number of pre-school facilities has not recovered to the levels previous to the collapse of the communist regime (see Figure 3). As a result, two decades after the fall of the communist regime, one may observe that the mutual support between family members has assumed a great role in attenuating the shock of poverty inherited from the communist regime, and that informal channels of support function better than the state social provisions and assistance (Danaj, 2014).

Therefore, a distinguishing feature of this study is that it is quite interesting to analyze the effect of fertility on parental labor force participation in a developing country characterized by a combination of low levels of employment and also low fertility rate. Figure 2 presents these trends since 1990 until 2012 for the case of Albania, where we can clearly observe a decrease in both variables. The timing of these events suggests that there might exist a causal relationship between them.

> 8See Figure 3 for more detail on the situation of pre-school in Albania during the period analyzed in this study.

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# **4 The Data**

The data used in this paper come from surveys conducted in Albania in four different moments in time: the 2002 Living Standard Measurement Survey (LSMS), the 2005 Living Standard Measurement Survey (LSMS), the 2008-09 Demographic Health Survey (DHS) and the 2012 Living Standard Measurement Survey (LSMS). The LSMS surveys were undertaken by the Albanian National Institute of Statistics (INSTAT) with the technical assistance of the World Bank. The 2008-09 DHS was conducted by the INSTAT but also by the Institute of Public Health (IPH). These surveys correspond to different wave rounds, but it is important to note that they do not form a panel database. They are nationally representative surveys for the whole country, as well as at regional and at the urban/rural level. Each survey contains a wide range of information on individuals’ demographic and socioeconomic characteristics (i.e. fertility, health, employment, migration and education among many others). In each one of these databases, the country is stratified into four regions (strata), Tirana, Coastal, Central and Mountain. All the surveyed individuals belong to the 36 districts in the country, with all regions nearly equally represented.

These surveys interviewed both women and men with respect to their fertility decisions, thereby permitting the unique opportunity to incorporate information in my study regarding the fertility history of each household. In other words, each one of these surveys contains detailed information which helps identify children by birth of order and match them with their biological mother and father. For instance, in the 2008-09 DHS survey, all the children ever born are already matched to each one of their corresponding mother and father, which makes the DHS a perfect database for studying the fertility history of the parents. In contrast, in the LSMS surveys, the fertility history information is not as clearly identified as in the DHS, which means that the children are not already linked to their corresponding parents. However, the advantage of the LSMS surveys is that they provide a direct mother and father identifier code, which is used to link the children to their corresponding parents. In addition, the Albanian LSMSs databases are a special case in terms of fertility compared to other LSMS surveys because they contain very detailed information on the family structure of each one of the households, including information about the children no longer living in the household, which makes possible the construction of the entire fertility history of each parent in the databases.<sup>9</sup> Following similar studies in the literature, I limit the analysis to mothers aged between 20 and 49 years old with at least two children whose oldest child was at most 18 years old at the time of the surveys. Firstly, women who are younger than 20 years old are excluded from the analysis because none of them have two children. Since the instrumental variable used in this study is

> 9The 2002 LSMS contains a specific module on fertility, where it is possible to identify the maternity history of every woman in the database. This type of module is not included in the 2005 and 2012 LSMS surveys, but for these cases the Migration module and Sons and Daughters Living Away module are used to construct the fertility history.

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based on a comparison of the sex of the parent’s previous children, it is necessary to include only individuals with two or more children. Secondly, mothers with children older than 18 years old at the time of the survey are also excluded from the sample. This restriction ensures that the first child has not yet moved from home at the time of the survey.<sup>10</sup> Additionally, mothers with a child below the age of 1 are also excluded from the analysis in order to avoid potential bias due to lower labor market activity of mothers during the initial months following childbirth.

Taking into account these restrictions, with these four surveys I construct two repeated-cross section subsamples. The first includes mothers with two or more children whose oldest child is younger than 18 years old. The second includes fathers (husbands of the married mothers) with two or more children whose oldest child is younger than 18 years old. I do not carry out a separate analysis on the subsample of married women because in my final sample the married women represent 98% of the total (see Table 2), which makes no significant difference with respect to the whole sample. Thus, the final samples are made up of 7,480 observations of mothers and 5,496 observations of fathers with at least two children under the age of 18.<sup>11</sup>

# **4.1 Descriptive Statistics**

Descriptive statistics for mothers’ fertility in Albania are given in Table 1. As the independent variable of primary interest for this analysis is fertility, the variable _number of children ever born per mother_ is used as a measure of fertility.<sup>12</sup> Using the sex of the oldest two children, I define the siblings sex composition pairs as _same sex_ if they have the same gender and _mixed sex_ if otherwise. The former is also decomposed to define sibling pairs of _two girls_ and _two boys_ .

Table 1 indicates that the average number of children ever born for Albanian mothers with at least two children is 2,60. Some families have as many as 9 children. Among all mothers with two children, about 41% considered having a third child, an event indicated by the variable _More than 2 children_ . Both the number of children and the proportion of mothers with three or more children are quite similar to other studies in the literature (e.g. Angrist and Evans, 1998). Moreover, just 50% of the households with at least two children had either a girl or a boy as a firstborn and also just 50% of all two child households had children of the same sex. However, the occurrence of two boys in a row is slightly higher (25%) than the occurrence of two girls

> 10In Albania, it is increasingly likely for a child over 18 years old to have moved to a different household. For instance, using the LSMS surveys, which provide information on the sons and daughters who have left the household, I find that the average age at which a child in Albania left his home is 23.66 during the period studied. Moreover, the age at which a child left the household is quite different between males and females. For example, the average age at which a girl left home is 21.92 years old, while for boys it is 25.41. These descriptive statistics indicate that Albanian girls leave their homes quite earlier compared to boys and this is generally due to marriage.

> 11It is important to note that the difference in observations between the married mothers (7,480) and the married fathers (5,496) is due to the number of observations as provided in the official 2008-09 Albanian DHS. In other words, there are more observations of women than men. A detailed description of the LSMS surveys and the DHS survey for Albania and on the construction of the subsamples and some key variables is provided in appendix A. See Table A-1 in the Appendix for more information.

> 12This measure of fertility, _number of children ever born_ , also includes the deceased children.

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# (24%).

Demographic and labor-force participation descriptive statistics for mothers and fathers are shown in Tables 2 and 3, respectively. These tables include variables such as parent’s age, age at first birth, years of education, household size, residential region and indicators for religion among others. The labor-force participation variables are based on questions concerning the employment status of the parent during the last 7 days and 30 days previous to the moment of the surveys. The four surveys (LSMS and DHS) contain labor supply indicator variables which measure whether the parents worked for somebody other than a household member ( _worked off-farm_ ), whether they worked on a farm owned by a household member ( _worked on-farm_ ) and whether the parents worked on own account ( _self-employed_ ). It is important to notice that these working activities are not exclusive, which means that each parent might be doing more than one. Thus, I define another indicator variable that combines these three variables and takes the value of 1 if the parents performed at least one of these working activities during the last 7 days ( _worked in last 7 days_ ) and 0 otherwise.

Just the LSMS surveys also contain other labor supply variables that measure whether the parents have a _second occupation_ , their usual number of _hours worked per week_ and also their amount of _labor income per month_ in old leks.<sup>13</sup> The latter two variables are set to zero for those parents who reported not working during the last 7 days.

The descriptive statistics in Tables 2 and 3 indicate that the mean age is 35 for the sample of mothers and almost 40 for the fathers (husbands or partners of mothers). On average, women become mothers at the early age of 23 compared to 28 for men. Parents in Albania complete a similar number of years of education, being 10 years for the mothers and 11 for the fathers. Half of the households in the sample live in urban areas and around 38% of them live in an extended family.

About 44.5% of the mothers with at least two children were working during the last 7 days previous to the surveys, whereas this number rises up to 78.7% for the sample of fathers. This difference of 34.2 percentage points in favor of labor-force participation of men reflects their much more active involvement in the labor market of Albania. In addition, fathers are much more likely of having a second occupation (5.8%) compared to mothers (1.4%). From the sample of mothers with at least two children, 16.3% were _working off-farm_ , 21.7% were _working on-farm_ and only 6.6% were _self-employed_ . While, for the husbands or partners of mothers, 39.3% were _working off-farm_ , 23.6% were _working on-farm_ and 19.7% were working on own account. The summary statistics indicate that men in Albania dominate in the non-agricultural sector, while women make up a higher proportion of employed persons in the agricultural sector.

Overall (i.e., including zeros), the average number of _hours worked per week_ is 16.6 among the mothers, but it is 40 hours among those that effectively work. On the other hand, fathers

> 13The 2002 and 2005 LSMS surveys also contain information on the number of _weeks worked per year_ , but unfortunately this variable is not availabe for the rest of the surveys and for this reason it is not used as an additional dependent variable in this study

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in the sample worked 34.2 hours per week (i.e., including zeros) and this number rises to 44.8 for those who worked a positive number of hours. Lastly, the average monthly labor income for mothers with at least two children is 50,166 old leks (221,591 without zeros), whereas fathers earn on average 191,841 old leks (331,172 without zeros), which is quite more compared to mothers.<sup>14</sup> Once again, it is important to notice the gender inequality in terms of labor-force participation and earnings in Albania during the period analyzed in this study.

# **5 Empirical Strategy: Instrumental Variables**

## **5.1 Son Preference in Albania and Siblings Sex-Composition**

In this context, I exploit Albanian parental preference for having sons combined with the siblings sex-composition as an exogenous source of variation in the fertility decision. For this empirical strategy to identify the parameter of interest, the instrument sibling sex-composition must satisfy two basic conditions: (i) must be strongly correlated to the fertility choice and (ii) it must have no correlation with factors directly affecting parental labor-force participation other than through its impact on fertility.

Several demographic analyses have confirmed that son preference is a distinctive feature of Albania’s population (UNFPA, 2012; Gjon ̧ca, Aassve and Mencarini, 2008). It is well documented that if the first child of an Albanian couple is a daughter, they will try to have at least one more child (Zickel and Iwaskiw, 1994). Son preference in Albania is partially driven by the desire and need to perpetuate the family name, but is also reinforced by a collection of customs that make a son desirable economically. For instance, Albanian sons are considered more economically productive than daughters not only because they obtain higher wages, but also because they tend to remain part of the extended family, while daughters and their contribution to the family where they are born counts only for a few years.

Old-age support from mature sons is another influential factor in parental decisions to have sons in Albania. They are still more preferred than daughters because they provide a greater source of protection and expected support for the parents at old age, a need reinforced by the uncertainties of the economic and social environment since the exit from the communist regime. Moreover, Albanian tradition and culture dictates that sons should provide financial support and protection for parents. In particular, Albanian custom obliges the youngest son (and his wife) to take care of his parents in their old age - indeed the youngest son is referred to in Albania as “the son of old age” (King and Vullnetari, 2006; King, Mata-Codesal and Vullnetari, 2013).

On the contrary, the obligation of daughters is much weaker, in part because they are considered as transient members of their native family and also because they are thought to be

> 14Monthly labor income is in real terms with base year 2007 using the national CPI provided by the Albanian National Institute of Statistics (INSTAT).

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responsible for their husband’s parents. The newly married wife automatically switches her family to become part of her husband’s family, and also part of that family’s system of honor and economic support. According to custom, and in the absence of social insurance, parents are better served by ensuring the presence of a son and daughter-in law than the presence of a daughter and a son-in-law.

Given this patriarchal Albanian context, the idea behind the identification strategy is that parents whose first two children are girls should have higher fertility in pursuit of the male child compared to parents with other sibling’s sex-compositions. Similarly, parents whose two first children are boys should be less likely to have an additional child because they have already reached the goal of having at least one son.

Therefore, a set of dummy variables indicating whether a mother’s first two children are _two girls_ , _two boys_ or whether they have the _same sex_ can be used as instrumental variables for higher order fertility. This identification strategy is akin to Angrist and Evans (1998), but since parental sex preferences in the Albanian context are different from the ones in the United States, I argue that the instrumental variable ( _two girls_ ) should be more relevant for influencing progression to higher parity compared to the instrument _same sex_ used by the authors. However, as the phenomenon of parental preference for balancing the sex-composition of the children has been widely documented in previous studies, I also use this alternative source of exogenous variation for comparative reasons.

# **5.2 The Relevance Condition**

Table 4 reports raw estimates of the impact of child sex and the sibling’s sex-composition on fertility. Panel A presents sex preference in households with at least one child, conditional on the sex of the first child. The figures show that around 50,6% of mothers have a boy as a firstborn, while approximately 49,3% correspond to mothers whose first child is a girl. The next three columns show the fraction of mothers with either a boy or a girl as a firstborn that had a second birth for the entire sample and by rural/urban area. It can be observed that mothers with a female firstborn child are more likely to have a second birth than those with a male firstborn child. The difference is statistically significant at the 1% level and is bigger in rural areas. This estimate suggests that subsequent fertility is a function of the sex of this first child and it is the first evidence of son preference in Albania.

Panel B of Table 4 documents parental sex-mix preference in households with at least two children, conditional on the sex of the first two children. Estimates in column (1) suggest that Albanian mothers with two children of the same sex are much more likely to have a third child than those with a mixed-sex siblings composition. More precisely, only 34,7% of mothers with a mixed sex siblings composition have a third child compared to 48.7% of mothers with a same sex siblings composition. This difference is statistically significant at the 1% level and rises up to 14 percentage points, which is much bigger than the difference found in previous papers.

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Furthermore, the correlation between sibling’s sex-composition and the probability of additional childbearing is even stronger for mothers whose two first children are girls, reaching a statistically significant difference of 26 percentage points compared to mothers with a different sex-composition. For instance, estimates in column (1) indicate that around 61,4% of Albanian mothers with two girls have a third child compared to only 36,4% for those with two boys or even less for those with a mixed sex combination. Columns (2) and (3) indicate that fertility rate is higher in rural areas compared to urban areas and that parental preferences for sibling’s sex-composition differ slightly by rural-urban decomposition, but the same pattern remains in both areas. These correlations suggest that Albanian parents have a clear preference for sons, which is slightly more pronounced in rural areas compared to urban areas.<sup>15</sup> Overall, even though the total fertility rate has declined during the period studied, fertility patterns following _two girls_ demonstrate the persistence of parental preference for sons. This result also indicates that, for Albanian parents, balancing the sex-composition of their children is not as preferred as having sons because if they did, they should want to have a girl if they already had two boys and this does not seem to be happening.<sup>16</sup>

# **5.3 The Exclusion Restriction**

In addition to the relevance condition, the exclusion restriction requires that the sibling sexcomposition has no correlation with other factors directly affecting labor-force participation other than through its impact on fertility. This condition means that it is of primary interest that the instrument has an as close a resemblance as possible to a random assignment. Basically, sibling sex-composition is supposed to be unrelated to any unobserved factors that might affect parental labor supply because in essence it is virtually randomly assigned by a biological natural phenomenon.

Even though the sex of a child is plausibly randomly assigned, there exist several concerns that might put this statement into doubt and threaten the identification strategy of this analysis. One important concern is the prevalence of the sex-selective abortions in Albania. In view of a manifest preference for sons, the ratio of men to women has recorded a significant rise since the mid-1990s due to the legalization of abortion and also the modernization of the available

> 15Figure 4 shows a graphical representation of Table 4 each one of the four databases used in this study. Mothers who give birth to a girl followed by another girl have a much higher fertility than those who give birth to mixed sex siblings or two boys in a row. On the contrary, mothers who give birth to _two boys_ in a row are less likely to have an additional child compared to those with an otherwise sex-mix.

> 16It is important to notice that the relationship between sibling’s sex composition and further childbearing is confirmed in each one of the databases used in this study (LSMS and DHS surveys). This is important because, unlike the 2005 and 2012 LSMS surveys where information about fertility is partly based on my own household matching between the children and their corresponding parents, the 2002 LSMS and 2008-09 DHS contain detailed fertility histories for each parent, including information on the dates of birth and sex of each child among others. This serves as a cross check for the relevance condition of the instrument. Tables A-2 and A-3 in the Appendix report estimates of the impact of child sex and sibling’s sex-composition on fertility for each one of the four surveys.

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reproductive equipment, reaching 114 male births per 100 female births around 2005 (UNFPA, 2012). Hence, if the parents who prefer to have sons or the mothers who want to return to work are willing to engage in sex selection, the instrument will not be randomly assigned. Despite the fact that Albania has a high male-female ratio, the evidence from the sample of mothers and fathers used in this paper suggests that the sex-ratio at first and second order births is very close to the natural rate, which makes this issue a minor concern (see Tables 1 and 4).<sup>17</sup> Another simple way to check whether the instrument is as good as random is to examine whether parents differ in demographic characteristics by the sex-compositions of their two first children (Angrist and Evans, 1998; Ag ̈uero and Marks, 2008). The idea is that if there is no correlation between the instrument and other variables affecting parental labor supply, then there should be no systematic differences in demographic characteristics between parents who have same-sex and mixed-sex sibling compositions, and similarly between those who have two girls and another sibling composition or two boys and otherwise. Examples of such variables are _age, age at first birth, years of education, rural area_ and _religion_ .

Table 5 reports the difference in means in demographic characteristics between parents (mothers and fathers) with different sibling’s sex-composition (same-sex, two girls and two boys). Columns (1) and (4) indicate that mothers (fathers) with children of the same sex and those with children of mixed-sex, have similar demographic characteristics before the treatment, that is, the arrival of the third child. The rest of the estimates in Table 5 show that in general there are no statistically significant differences in demographic characteristics between parents with two boys and those with another sibling composition, and also between those with two girls and otherwise, except for the variable _age_ . Parents with two girls and just the fathers with two boys seem to be slightly older than those with another sibling composition. The magnitude of these differences represents only 1% of the sample means of age for mothers and fathers, which is quite small. However, the variable _age_ is used as a control in all the specifications of the paper in order to avoid any concerns.

Another possible threat to the validity of the exclusion restriction in this identification strategy is put forward by Rosenzweig and Wolpin (2000). They argue that having mixed sex siblings may violate the exclusion restriction by directly affecting both the marginal utility of leisure and child rearing costs and, thus, labor-force participation. For example, if spending on various child-related goods is different for parents who have a son versus those who have a daughter, the analysis will be contaminated by the direct impact of a child’s sex on childcare costs. Using Indian data, they find that expenses for clothing of the third child are significantly lower if the older siblings are of same sex. They attribute this effect to “hand-me-down” savings, which are

> 17Several methods to discriminate among unborn girls co-exist today in the world. The most recent methods are based on pre-conception selection and require access to the elaborate equipment necessary to perform sperm sorting, pre-implantation genetic diagnosis (PGD) or in-vitro fertilization (IVF). Cost and accessibility factors, however, restrict these technologies to developed countries and to the most affluent populations. These services were not generally offered by the public health service in Albania during the period studied. On the contrary, sex selective abortions offer a far easier and more accessible route to avoid female births (UNFPA, 2012).

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more likely to arise when there are children of the same sex in the household for items such as clothing or footwear. Since these items represent a sizeable fraction of the Indian household’s expenditures (11% of the household income), they note that the sex composition of children plausibly alters female labor supply through mechanisms other than through fertility change alone.

Table 6 reports data on budget shares of child-related goods and mean household expenditure differences by sibling sex composition for Albania.<sup>18</sup> The statistics show that Albanian households devote about 55% of their budget to food, 5.4% to health, 4.6% to clothing and 2.5% to children’s education. In the clothing category, children’s clothing expenditure represents only 2% of the entire budget. This estimate seems to be too small compared to the Indian case in order to account for a meaningful reduced form relationship between the sibling sex composition and parental labor supply.<sup>19</sup> In addition, the evidence in Table 6 shows that expenditure patterns of households in Albania are not significantly affected by the sex composition of children.<sup>20</sup> For instance, in one of the cases where the difference between budget shares is statistically significant, the sign contradicts the presence of economies of scale, since households whose first two children are girls spend a higher share of their budget on clothing. Also, even though Albanian parents with same-sex siblings seem to spend a lower proportion of their budget in children’s education, the magnitude of this difference is too small to make a real impact, given the fact that children’s education represents only 2.5% of the entire household budget. These statistics suggest that there is not a clear expenditure pattern of the Albanian parents by sibling sex composition. Therefore, the instrument seems not to be related to any indirect income effects that might question its exogeneity.<sup>21</sup> Lastly, it can be argued that another possible threat to the exogeneity of the instrument is the fact that having two girls as the oldest children can make it easier for the parents to increase their labor supply as the older girls can do household chores and take care of the younger siblings. However, it is worth pointing out that this may be a bigger concern for the results 18The data used for analyzing the expenditure patterns in Albania come only from the 2002, 2005 and 2012 Albanian LSMS surveys. Unfortunately, there are no available expenditure data on the 2008 DHS survey. The LSMS surveys contain very detailed information on household food and non-food expenditures. These databases have also the advantage of making possible the separation of child clothing and education expenditures from adult’s expenditures.

> 19Cruces and Galiani (2007) make a similar argument for the cases of Argentina and Mexico. They indicate that sex composition in unlikely to have a noticeable effect on clothing and footwear expenditure for these Latin American countries due to the fact that only around 4.8% of the budget was used for clothing and footwear in the year 2000 in Mexico, while 6.7% for the case of Argentinean households (for all members).

20B ̈utikofer (2010) contributes to the debate over the usage of the same-sex sibship as an identifying instrument by analyzing whether families with same-sex siblings composition face larger economies of scale in consumption in a variety of countries. She finds no significant differences between the estimated equivalence scales of families with different siblings sex composition in richer countries including the case of Albania. This analysis provides further evidence that household economies of scale do not crucially differ with siblings’ sex-composition.

> 21Huber (2012) developed a test to assess the validity of an instrumental variable in just-identified models and applied it to the Angrist and Evans database finding evidence for the validity of _same-sex_ .

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of the mothers, but is unlikely to explain results for the fathers.<sup>22</sup> In addition, parents may practice selective neglect of children based on gender. In the light of the patriarchal culture of Albania, parents could value taking care of two girls less and decide to keep working. Or, they may be less reluctant to give up a job when they have two girls, anticipating that they may not have a son to take care of them when they are old. Therefore, having two girls might have a direct effect on parental labor supply. In order to deal with this issue, in the estimation strategy I control for the gender of the first and second child.

# **5.4 The Econometric Framework**

## **5.4.1 Potential Drawbacks of OLS**

This section discusses the ordinary least square (OLS) and the instrumental variables (IV) techniques and presents the regression models relating parental labor-force participation and fertility. To begin with, I examine the effect of fertility on parental labor-force participation by using OLS through the following linear model: Here, _LFPijs_ is a measure of labor-force participation of the parent _i_ residing in district _j_ and observed in survey year _s_ (i.e. dummy indicator for _worked in last 7 days_ or _hours worked per week_ among others); _Fijs_ is the endogenous fertility variable measured through the number of children ever born per parent _i_ ; and _εijs_ is the error term associated with unobserved heterogeneity for the parent. The parameter of interest, _β_ 1<sup>_OLS_</sup> , represents the mean effect of having an additional child (third or higher order) on parental labor-force participation.

It is of most importance to notice that when we estimate the model in equation 2 by ordinary least squares (OLS), the estimator _β_ 1<sup>_OLS_</sup> is likely to be biased due to reverse causality and omitted variables. In particular, the magnitude of _β_ 1<sup>_OLS_</sup> is likely to be biased upwards due to unobserved ambition or ability which positively influences the outcome variable but is probably negatively correlated with having an additional child.

## **5.4.2 Instrumental Variables Estimation: LATE**

In order to disentangle the causal mechanism linking fertility and parental labor supply, I use sibling sex-composition as an instrument that induces plausibly exogenous variation in _Fijs_ (the number of children ever born). Under reasonably general assumptions (independence and monotonicity), the estimate _β_ 1<sup>_IV_</sup> captures the local average treatment effect (LATE), first discussed

> 22In order to further address this concern, I also check the robustness of the main results for the mothers when the sample is limited to families in which the oldest child is younger than 13. As in Albania the average age for finishing primary school is 13, it is reasonable to argue that girls would not be asked to take care of siblings if they are younger than 13 years old. In the Appendix, estimates in Table A-5 indicate that the main results remain unchanged after limiting the sample of mothers to those whose oldest child is younger than 13 years old.

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by Imbens and Angrist (1994). The _β_ 1<sup>_IV_</sup> estimate can, then, be interpreted as the average effect of _Fijs_ on _LFPijs_ for those parents whose fertility has been affected by the sex-mix of their previous children. Following the terminology in Angrist and Evans (1996), in order to better understand for which subgroup of parents with two children the average treatment effect can be consistently estimated, it is useful to classify them into the following 3 sub-populations: those who will have a third child even following a son ( _always takers_ ), those who will never have a third child even following two daughters ( _never takers_ ), and those who will have a third child following two daughters but would otherwise stop ( _compliers_ ).

Hence, _β_ 1<sup>_IV_</sup> can consistently estimate the average effect for individuals who have one more child because their first two children are girls (i.e. compliers) provided that the instrument satisfies monotonicity. Basically, what is needed to be assumed is that there are no _defiers_ , those that change their behavior in the opposite direction due to the instrument. In other words, monotonicity requires that having never had a son only makes one more likely to have a third child, a reasonable assumption given the pervasive son preference in Albania.<sup>23</sup> The IV approach fails to identify the effect among two sub-populations: the _always takers_ , who generally have lower costs to childbearing than compliers, and the _never takers_ , who will generally have higher costs to childbearing than compliers.

Therefore, the second-stage regression model that links the endogenous fertility measure _F_<sup>ˆ</sup> _ijs_ with labor supply variables for the parents is the following: where _LFPijs_ measures labor-force participation of the parent _i_ residing in district _j_ and observed in survey year _s_ ; _F_<sup>ˆ</sup> _ijs_ is the endogenous fertility variable measured through the number of children ever born per parent _i_ ; _Xijs′_<sup>isasetofcontrolvariablesthatareplausiblyexogenousto</sup> fertility, such as _parent’s age, parent’s age squared, parent’s age at first birth_ and _parent’s years of education_ ; _b_ 1 and _b_ 2 are indicators for the sex of the first and the second child of parent _i_ , respectively, and _εijs_ is the error term associated with unobserved heterogeneity for the parent. The variables _b_ 1 and _b_ 2 are included to control for potential additive effects of child gender, which might affect labor supply for reasons other than fertility. For example, as mentioned in Angrist and Evans (1998), this effect could arise if parents behave differently towards boys and girls, or whether a father’s commitment to the family is contingent on the sex of the child. For this reason, the sex of the first-born and the second child, _b_ 1 and _b_ 2, are included in the equation to minimize any omitted variable bias caused by additive effects of child sex. I also control for the gender of the first child in order to address potential concerns about the exclusion restriction

> 23However, when relying upon siblings-sex composition as an instrument for fertility, the condition of monotonicity might be violated. Even though son preference is well documented for the case of Albania, a possibly minor fraction of parents might still prefer to have at least two children of the same sex (e.g. three boys), such that monotonicity would not hold. Following De Chaisemartin (2017), in the Appendix B, I show that the 2SLS estimator is still valid, even under the presence of defiers, provided the “compliers-defiers” condition is satisfied.

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related to the fact that having two girls might have a direct effect on parental labor supply.

Initially, the first-stage regressions for the just-identified models that link the potentially endogenous fertility variable to only one instrument are the following: where the sibling sex-composition instrument is measured by three dummy variables, _same sex_ , _two girls_ and _two boys_ , indicating whether the sex of the first child is the same as that of the second child. Given the Albanian parental preference for sons, _Fijs_ is expected to be positively correlated with _same sex_ and _two girls_ , but negatively correlated with _two boys_ . Both the first and second stage regressions include fixed effects for districts _λj_ and survey years _μs_ . Also, in order to avoid potential biases in the estimation of the standard errors, an arbitrary structure of covariance is allowed by computing clustered robust standard errors at the primary sample unit (PSU) level.<sup>24</sup> Furthermore, since the _same sex_ binary variable is easily decomposed into two variables indicating the sex composition of the first two children, namely _two boys_ and _two girls_ , an overidentified model with these two instruments and one endogenous variable can be estimated by the following first-stage regression: In this specification, either _b_ 1 or _b_ 2 must be dropped from the list of covariates because _b_ 1, _b_ 2, _two boys_ and _two girls_ are linearly dependent. Thus, I chose to drop _b_ 2. It is important to clarify that the results are not sensitive to this choice, or to the elimination of both _b_ 1 and _b_ 2, as is shown in the first-stage results presented in the following section.

# **6 Results**

## **6.1 First-Stage**

Apart from the raw estimation analysis used to test the relevance condition of the instruments, this section examines in more depth this condition through the first-stage estimation. Table 7 reports the first-stage results linking sex-mix and fertility, where columns (1) to (3) show the results for the just-identified models without covariates, columns (4) to (6) show the results after adding covariates, and column (7) shows the results for the over-identified model with covariates.

> 24The primary sampling units (PSUs) are geographically defined area units, which are selected with a probability proportional to size and they are very similar to a village level unit. The PSUs are already constructed in all the LSMS surveys and also in the DHS.

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The top half of the table (Panel A) gives the estimation results for the sample of mothers, while the bottom half (Panel B) gives the results for the sample of fathers (husbands of the married women).

The results from the first-stage estimation in column (1) suggest that mothers with two children of same sex have on average 0.22 more children than mothers with children of mixed sex. The instrument _same sex_ seems to be much stronger for the case of Albania compared to the one reported by Angrist and Evans (1998) and Cruces and Galiani (2007), who find that mothers with two children of the same sex have only 0.07 more children on average.<sup>25</sup> Moreover, the results in columns (2) and (3) show that the effect of sibling sex composition on fertility is even much stronger if the first two children are girls, but weaker if they are boys. More specifically, having two girls in an Albanian household increases on average the number of children ever born by 0.47. This coefficient is twice as large as the coefficient for _same sex_ , which means that the instrument _two girls_ is better capturing the exogenous variability in fertility. On the contrary, having two boys decreases the number of children ever born by about 0.16, which suggest that the parents are less likely to have additional children following sons.

The next three columns (4) to (6) present similar results after controlling for several covariates such as _parent’s age, parent’s age squared, parent’s age at first birth, parent’s years of education_ and also whether the first and the second child are boys, _boy1st_ and _boy2st_ . After the inclusion of these covariates, the instruments _same sex_ and _two girls_ still have a positive and statistically significant impact on fertility and the magnitude of the estimates remains quite unchanged. More specifically, having children of the same sex increases fertility by 0.22, but having two girls leads to even a bigger increase which reaches up to 0.43.<sup>26</sup> All these results are significant at the 1% level of significance and in each case the F-statistic on the excluded instruments is higher than 10, considered to be the rule of thumb threshold by Stock, Wright and Yogo (2002).

Conversely, the first-stage estimate in column (6) that uses _two boys_ as an instrument becomes zero in magnitude and it is not statistically significant anymore. In addition, the R- squared and the F-statistic of the excluded instrument from this specification are zero, which

> 25Following Angrist and Evans (1998), if the indicator variable _More than 2 children_ is used as a dependent variable in the first-stage estimation, I obtain very similar results which are significant at the 1% level and in each case the F-statistic on the excluded instruments is higher than 10. Compared to Angrist and Evans (1998), who find that the effect of the _Same sex_ instrument to be around 6 percentage points, my first-stage estimates using the indicator _More than 2 children_ seem to be much stronger. For instance, I find that Albanian mothers with two first children of the same sex are estimated to be 13.1 percentage points more likely to have a third child. This estimate rises up to 25.5 percentage points if the first two children are girls, which is very big. On the contrary, I find that mothers with two boys are on average 7.7 percentage points less likely to have a third child. These results are available upon request.

> 26This is also equivalent to an increase of 24 percentage points in the probability of having a third child when the indicator _More than 2 children_ is used as a measure for fertility. This coefficient is three times bigger than the one found by Angrist and Evans (1998) -7.1 percentage points in the U.S.- and five times bigger than the one found by Cruces and Galiani (2007) -5.3 percentage points for married women in Argentina and 4.6 percentage points for married women in Mexico.

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clearly indicates that _two boys_ is a weak instrument in the context of Albania. For this reason, it will not be used in the second-stage estimation.

Lastly, the first-stage estimates of the over-identified model in column (7), which uses both _two girls_ and _two boys_ as instruments, also indicate that having two girls increases the number of children by 0.43 on average and this result is statistically significant at the 1% level. On the contrary, having two boys does not seem to produce an effect on the number of children and the result is also statistically insignificant, proving to be a weak instrument once more. Thus, the over-identified specification is neither a good candidate for the second-stage estimation.

As a whole, the first-stage results in Table 7 confirm once more that Albanian parents have a strong preference for having sons. In particular, having two girls increases the likelihood of having an additional child, while having two boys seems to have no effect on fertility after controlling for several covariates. Even though the instrument _same sex_ seems to have a positive and statistically significant effect on fertility, it does not mean that Albanian parents prefer to balance their children’s sex-composition because this variable is only capturing the variability generated by _two girls_ . Therefore, the second-stage estimation will be based mainly on the exogenous variability of the instrument _two girls_ . The _same sex_ instrument will be used only for comparative analysis.<sup>27</sup>

# **6.2 Main Results: OLS and Second-Stage**

This section presents the main results of the effect of fertility on parental labor-force participation. The OLS and second-stage results are estimated separately for the mothers and the fathers because women and men in Albania differ substantially in the type and amount of labor they supply. Tables 8 and 9 report OLS estimates in column (1) and two sets of IV estimates (i.e. _same sex_ and _two girls_ as instruments) in columns (2) and (3) for the sample of mothers and fathers, respectively.<sup>28</sup> All the specifications include the same set of control variables as in Table 7. The upper panel of these tables reports the estimates for the different measures of labor force participation (e.g. _worked in last 7 days, work off-farm, work on-farm, self-employed_ ), while the bottom panel reports estimates for _hours worked per week, second occupation_ and _monthly labor earnings_ .<sup>29</sup>

> 27The corresponding first-stage estimates for the sample of fathers presented in Panel B of Table 7 are almost exactly the same as the ones for the sample of mothers.

> 28The first-stage specifications of columns (4) and (6) in Table 7, which use _same sex_ and _two girls_ as instruments for fertility, are the ones selected for the second-stage estimation because these are the ones that proved to be the strongest instruments after controlling for covariates.

> 29The variables presented in the bottom panel of Tables 8 and 9 such as _hours worked per week, second occupation_ and _monthly labor income_ are only available in the Albanian LSMS surveys, but not in the Albanian DHS survey. For this reason, the sample of mothers is reduced to 4,862 observations and the sample of fathers to 4,530 observations. The first-stage estimates for these reduced samples are very similar to the ones shown in Table 7, but very slightly smaller in magnitude. Once again _two girls_ and _same sex_ prove to be valid instruments for fertility, while _Two boys_ seems to be a weak instrument. The first-stage estimates for these samples are reported in Table A-4 of the Appendix.

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The OLS estimates in Tables 8 and 9 indicate that the correlation between fertility and likelihood of working is very small and statistically insignificant for mothers, but positive and statistically significant for fathers. In particular, if the analysis is separated by type of work, the presence of an additional child has a negative and statistically significant correlation with parents’ likelihood of working off-farm, being self-employed and also monthly earnings, but it has a positive and statistically significant correlation with both parent’s likelihood of working on-farm. Fertility also seems to be positively correlated with father’s likelihood of having a second occupation.

Although the OLS estimates suggest that parent’s withdrawal from the labor market or their further participation as a consequence of an increase in family size depend on the type of job they are performing, they should be taken with caution because they could well be biased. After correcting for the endogeneity problem, the second-stage results tell a completely different story. Once _same sex_ and _two girls_ are used as instruments, some of the IV estimates of the effect of fertility on parental labor-supply change sign and magnitude compared to the OLS estimates.

When using _same sex_ as an instrument for fertility, the IV estimates show that having an additional child (third order or higher) increases the likelihood of participating in the labor market for both parents, but most of these coefficients are statistically insignificant. One reason for this result may be linked to the fact that _same sex_ does not capture the exogenous variability of fertility as precisely as the _two girls_ instrument in the context of Albania, which may probably lead to imprecise estimates.

The IV estimates using _two girls_ as instrument indicate that there is a positive effect of fertility on mother’s likelihood of working off-farm and this coefficient is statistically significant at the 5% level. More specifically, having an additional child (third order or higher) increases on average a mother’s likelihood of working off-farm (+5 p.p), which represents a 30% increase in the average participation rate of mothers’ work off-farm. But, the presence of an additional child does not seem to have a statistically significant impact on mother’s likelihood of working on-farm or being self-employed. In addition, the two sets of IV estimates indicate that having an additional child seems to also have a positive and statistically significant impact on mother’s hours worked per week. To be more precise, each additional child increases the working time of a mother by about 4.4 - 4.6 hours per week. This coefficient is quite big given that it represents 26% of the average working time of the mothers in the sample.<sup>30</sup>

> 30A distinguishable characteristic of Albania during the years of this study is the combination of low fertility with low female participation rates. Female labor force participation has stagnated or even decreased during the last two decades despite a significant drop in fertility rates. The combination of these two stylized facts does not necessarily mean that there exists an inverse relation between fertility and female labor supply, as it has been stated in various developed countries. A study from Da Rocha and Fuster (2006) corroborates in part this mechanism. These authors find that labor market frictions determine how employment and fertility are associated across economies. In particular, they find that fertility and employment are positively associated across economies with low employment ratios (low probability of finding a job). On the other hand, they find that fertility and employment are negatively associated across economies with high probability of finding a job. Their findings also suggest that the sign of this relationship could change as the job-finding rate of females increases.

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The labor-supply effects estimated using the sample of fathers are quite similar to those for the mothers, except for the outcome _hours worked per week_ . The IV estimates in Table 9 using _two girls_ as instrument indicate that having an additional child increases father’s likelihood of working off-farm (+6.7 pp) and also their likelihood of having a second occupation (+4.0 pp). These two coefficients are statistically significant at the 5% and 10% level of significance, respectively. For practical reasons, I do not present the coefficients on all the controls. However, I do present the coefficients for _boy1st_ and _boy2nd_ in Tables A-6 and A-7 of the Appendix in order to test whether the sex of the children affects parental labor supply for reasons other than fertility. In all the specifications in Tables A-6 and A-7, the coefficients of _b1_ and _b2_ are statistically insignificant for all the relevant outcomes of the analysis, which indicates that the instruments do not have a direct effect on parental labor-force participation.

Therefore, a plausible interpretation of the positive effect found between fertility and parental labor supply in Albania is that having an additional child induces parents with at least two children to work more for somebody rather than a household member, which means that they increase their labor supply in the non-agricultural sector. But, why would parents decide to augment their chances of being employed in a kind of job that might be considered as more stable or with a greater formality as a response to an increase in family size?

One way of interpreting these findings is by looking at the payment of a job as a bundle of services, such as wages, schedule flexibility, social status, security etc. Thus, an increase in fertility would not only increase the cost of time intensive activities but also the attractiveness of some jobs (scheme of payments) that are compatible with bigger family size versus others. For the case of mothers, this type of job might be more temporary than permanent due to the fact that part-time is easier to combine with motherhood tasks. Conversely, for the case of fathers this type of job might be more permanent than temporary due to the better benefits, such as higher earnings among others.

# **7 Discussion**

## **7.1 Two plausible mechanisms**

The regression analysis implies a significant and positive effect, as Albanian parents, men and women alike, are more likely to be working off-farm as a consequence of further childbearing (third order or higher) relative to parents with just two children.<sup>31</sup> Through which channels does this positive effect operate? In this section, I propose two main plausible explanations:

> 31These results confirm the common view in labor economics that children are an important determinant of parental labor supply. However, in contrast to most of the findings in the previous literature, children might not only restrict the opportunity of parents to participate in the labor market but as well create an incentive to search for employment. In order to shed some light on the mechanisms behind these results, a simple theoretical model that links childcare costs and family structure with fertility and parental labor supply is derived in the Appendix C.

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first, childcare provided by non-parental adults (e.g. grandparents) in extended families; and, second, greater financial costs of maintaining more children.

Extended families are composed by several generations consisting of grandparents, aunts, uncles, and cousins all living nearby or in the same household. A typical example is a married couple that lives with either the husband’s or wife’s parents. Thus, if indeed the parents have help in the household from the grandparents, they might not be forced to leave the workforce when they have an additional child. Under this scenario, the effect of fertility on parental labor supply depends on the extent of substitutability between the time spent by grandparents and parents in childcare and household chores. In response to an increase in fertility, grandparents may adjust their time allocation by supplying more time in childcare and household chores and, thus, parents are freed from such tasks and not forced to drop out of the labor market.<sup>32</sup> Indeed, several demographic studies have documented the rather particular nature of the Albanian family structure, characterized by extended families (e.g. Gjon ̧ca, Aassve and Mencarini, 2008; King, Mata-Codesal and Vullnetari, 2013)<sup>33</sup> In terms of care duties, caring for one’s older parents is also strongly-felt duty in Albania. According to the long-established tradition and custom, middle-aged and elderly parents are to live with one of their sons, usually the youngest, and his wife. Indeed the youngest son is referred to as “the son of old age”, whose role and duty is to look after his parents in their later years. Moreover, to respect and care for one’s parents is not only a duty but highly honorable in Albanian society (King and Vullnetari, 2006). Therefore, in the context of Albania where extended families are quite prevalent and professional childcare is rather rare and expensive, non-parental household members such as grandparents may be the perfect candidates for taking care of the children.

Similarly, the positive labor supply effects attributable to an increase in family size can also be rationalized on the bases of greater financial costs of feeding more children. Naturally, fertility can affect parental labor supply in two directions: on the one hand, it can provoke parents to withdraw from the labor market due to child caring and higher child costs; on the other hand, given that modern child caring and child costs are assumed to be very expensive, an increase in fertility may reduce the standard of living in the household and also stimulate parents to participate in the labor market in order to finance basic expenditures on their children.

> 32Several previous studies have examined the effect of family structure on female labor supply and they have found that the presence of grandparents in the household increases the labor supply of women who have children (e.g. Wong and Levine, 1992; Sasaki, 2002; Gong and Van Soest, 2002; Maurer-Fazio et al., 2011; Compton and Pollak, 2014; Garcia-Moran and Kuehn, 2017; Posadas and Vidal-Fern ́andez, 2013; Shen, Yan and Zeng, 2016; Landman, Seitz and Steiner, 2017).

> 33During most of the 20th century, the extended family in Albania was the basic single residential unit and economic entity. Basically, it was formed by a married couple with their married sons and their offspring, as well as any unmarried daughters. The size of these families was very large, and by the end of WWII some numbered as many as 60 to 70 members (Gjon ̧ca, Aassve and Mencarini, 2008). Even though the profound post-communist transformation and emigration have started to break down this tradition, extended families with three generations are still very common in rural Albania. For instance, the datasets used in this paper indicate that around 38% of the households live in extended families. This number is slightly higher in rural areas where it increases up to 42%.

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Therefore, for the case of Albania the latter constraint might be stronger than the former. It is possible to suggest that poorer, less educated and younger parents are the ones that need to provide more for their families compared to richer, more educated and older parents. This mechanism could be particularly true for developing countries such as Albania because in this context households generally act under tighter budget constraints where a large share of income is devoted to food and other basic needs. For instance, in Table 6 it can be observed that Albanian households dedicate more than half of their budget to food expenditure (54.8 %).

# **7.2 Heterogeneity Analysis**

In order to shed light on the mechanisms proposed, this section examines whether the effect of fertility on parental labor-force participation may be sensitive to certain sub-populations.<sup>34</sup> For this purpose, I perform a heterogeneity analysis by exploring whether the effect of fertility on parental labor supply varies with: _parent’s education level, parent’s birth cohort_ and _family structure_ . Moreover, it seems essential from a policy point of view to be able to identify which one of the sub-populations has the greatest response to the effects of fertility on parental labor market outcomes, in particular in relation to income or wealth level.

First, Table 10 presents the heterogeneity analysis of the effect of fertility on parental labor supply by _parent’s educational level_ . For this analysis, all the parents in the sample are divided into two groups by taking as a reference their primary school completion: below or completed primary level ( _≤_ 8 _years of schooling_ ) and above primary level ( _>_ 8 _years of schooling_ ). This separation is based on two simple facts: the average schooling years for mothers and fathers with at least two children in Albania are 10 and 11, respectively; and parents who have completed primary school (8 years) represent about 50% of the observations in each sample.

As can be seen in Table 10, the IV coefficients on _hours worked per week_ for mothers belonging to the lowest educational level have a positive sign and are statistically significant. In addition, the IV coefficient on _second occupation_ for fathers belonging to the lowest educational level also has a positive and statistically significant effect. On the contrary, the labor supply effects for parents with a higher level of education are imprecisely estimated. Thus, it seems reasonable to argue that fertility increases labor-force participation for less educated parents and, hence, possibly less economically well-off parents in order to respond to an increased demand in the household, namely need for income.

Second, Table 11 explores whether the effect of fertility on parental labor-force participation is likely to vary with _parent’s birth cohort_ . The birth cohort threshold is set at the median

> 34Gronau (1988) and Angrist and Evans (1998) suggest that the relationship between labor supply and childbearing is likely to differ by women’s educational level. They find that the labor supply of less educated women is more sensitive (more negative) to the presence of children than the labor supply of more educated women. Angrist and Evans (1998) also explore how the female labor-market consequences of childbearing vary with the earnings of the husbands. They find that the effect of fertility on women’s labor supply declines in magnitude (less negative) with husbands’ earnings.

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birth year in order to allow the division sample into two subsamples of similar size. On the one hand, the sample of mothers is divided between mothers born before 1972 (included) and mother’s born after 1972. On the other hand, the sample of fathers is divided between fathers born before 1966 (included) and those born after 1966.<sup>35</sup> Mothers of younger cohorts show a positive and statistically significant effect of fertility on _hours worked per week_ at the 1% level. Also, the IV estimates for younger fathers show a positive and statistically significant effect on father’s likelihood of having a _second occupation_ as a consequence of childbearing. On the contrary, the coefficients on fertility for mothers and fathers of older cohorts are lower in magnitude and statistically insignificant. Hence, I can confirm that there exists a degree of heterogeneity in the link between fertility and labor market outcomes by parent’s birth cohort, where the positive effect seems to be driven mostly by younger parents. This result also suggests that the positive effect of fertility on parental labor-supply is not driven by parents whose older children in the household are taking care of the younger siblings, which is reassuring in terms of the exclusion restriction.

Third, Table 12 reports the effect of fertility on parental labor supply conditional on the _family structure_ . Given the Albanian context, it could be argued that extended families in this country are a given characteristic of society since they are already established by strong traditional and social norms. To give more evidence on this assumption, I use the 2002 Albanian LSMS which contains detailed information on the fertility history of mothers from old birth cohorts in order to calculate the proportion of parents in extended families living with their sons by their son’s birth order. Indeed, Figure 5 shows that most of the parents in extended families live with their youngest married son (61.1 %).

However, there still remains the concern that the fertility decision and the co-residence decision might be jointly determined. Given the strong son preference in the context of Albania, grandparents may encourage parents with two daughters to have a third child in exchange for moving in and helping out in providing childcare. In other words, grandparents may bargain with parents for having a third child, which could affect their willingness to co-reside and take care of the children. Also, grandparents may just be more willing to move in if the parents are more likely to have three children.

In order to test this, I perform a falsification exercise on the first-stage to check whether siblings sex composition is a significant determinant of the co-residence decision. The results are reported in Table 13 and the specification are identical to those reported in Table 7. The effect of siblings sex composition on the likelihood of living in an extended family is small and insignificant in all regressions. There is even a negative correlation between having two girls and

> 35The average year of birth in the sample of mothers aged 20 to 49 years old with at least two children is 1972, while the average year of birth in the sample of fathers (husbands or partners of the married mothers) is 1966. Mothers born before 1972 (included) represent 49.5 % of the sample, while mothers born after 1972 represent 50.5 % of the sample. Similarly, fathers born before 1966 (included) represent 50.2 % of the sample, while fathers born after 1972 represent 49.8 % of the sample.

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living in an extended family, which contradicts the idea of co-residence in exchange for more children and childcare. Overall, these results suggest that children’s sex mix is not a predictor for living in an extended family structure, which reinforces the idea that extended families are a product of a strong social norm.

For this heterogeneity analysis both samples (mothers and fathers) are divided into two types of households: those that have grandparents older than 50 years old living in the same household as the parents ( _extended families_ ) and those that do not ( _non-extended families_ ). Conforming to the first mechanism proposed, the IV estimates in Table 12 show that mothers living in extended families experience the largest positive effects of fertility on labor supply. In contrast, there is no statistically significant link between additional fertility and labor supply for mothers living in non-extended families. Another interesting and important result is that the positive effect of fertility on father’s labor supply is mostly driven by those living in non-extended families. Since parents in non-extended families do not count on childcare provided by grandparents or other relatives, it is very likely for the mother to stay in the household to take care of the children, whereas the father probably searches for a second occupation.

Last, in Table 14 I examine whether the effect of fertility on family expenditure per capita depends on family structure and the wealth level of the household. For this estimation, households are pooled together into five expenditure quintiles i.e. all households in quintile 1 belong to the lowest expenditure level. As one would expect, parents in poorer quintiles are more likely to be younger, to have children at a younger age, to have a third child and to live in rural areas, but they are less likely to live in an extended family. Moreover, having an additional child reduces the family expenditure per capita in all quintiles. This result clearly suggests that an increase in fertility leads to a tighter budget constraint in the household.

When these estimates are analyzed by family structure, I find that the negative effect of fertility on expenditure per-capita is smaller in magnitude (less negative) for extended families and it is only statistically significant in two quintiles. On the contrary, non-extended families experience larger negative effects of fertility on family expenditure per-capita and these results are statistically significant in all quintiles. Also, the estimates for non-extended families show a stronger negative effect in the lowest expenditure quintiles.

To sum up, these heterogeneity analysis results suggest that the positive labor supply effect can be attributed to parents who are less educated (poorer), younger and who live in extended families. These results seem to support the view that higher fertility associated with greater child costs and lower childcare costs provided by grandparents in extended families are two important mechanisms that influence the labor supply decision of parents in Albania.

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# **8 Conclusion**

The purpose of this paper is to investigate whether there is a causal effect of fertility on parental labor-force participation in the context of a developing country in the Balkans such as Albania. In order to address the endogeneity in the fertility decision, I exploit Albanian parental preference for having sons combined with the siblings sex-composition instrument proposed by Angrist and Evans (1998) as an exogenous source of variation in the fertility decision. Using a repeated cross-section of Albanian mothers and fathers with at least two children, I find that Albanian parents have a strong and persistent preference for having sons. In particular, the results from the first-stage specifications suggest that having _two girls_ increases on average the number of children ever born by 0.43, which is equivalent to an increase of 24 percentage points (almost 60% of the sample mean) in the likelihood of having an additional child.

While most of the previous studies on this topic have found a negative relationship between fertility and labor supply, especially for women’s labor supply, there are also some studies that contradict these findings and indicate a positive relation (Porter and King, 2012; Priebe, 2010; Bloom et al., 2009). Hence, in the same line as the latter group of studies, the point estimates reported in this paper suggest that fertility has a positive effect on parental labor-force participation in the context of Albania.

More precisely, I find that having an additional child (third or higher order) increases on average a mother’s likelihood of _working off-farm_ by 5 percentage points and it also increases the working time by around 4.4 _hours per week_ on average. Similarly relevant is the finding that fathers also change positively their labor-market behavior in response to a change in family size. In particular, having an additional child increases father’s likelihood of _working off-farm_ by 6.7 percentage points, and also their likelihood of having a _second occupation_ by 4 percentage points.

The second focus of this study is to shed light on the channels through which these results operate. I propose two plausible mechanisms behind the positive effect of fertility on parental labor supply. The first one suggests that childcare provided by non-parental adults (e.g. grandparents) may act as a substitute for parental childcare in developing countries, thus, allowing them to increase labor supply as a consequence of further childbearing. The second one suggests that households have to face a tighter budget constraint as a response to a increase in fertility which reduces the standard of living in the household and forces parents to participate in the labor market. Conforming to the mechanisms proposed, the heterogeneity analysis suggests that the labor-market consequences of fertility are more likely to be driven by poorer, less educated, and younger parents, who also happen to live in extended families.

Lastly, the findings in this paper might have important implications in terms of public policy. In many developed countries much attention has been given to the role of childcare costs/subsidies, including direct provision of public pre-school, on female labor supply (Blau and Robins, 1998; Connelly, 1992; Kimmel, 1998; Gelbach, 2002). The main finding of this paper 28
implies that with lower childcare costs provided by the presence of grandparents in extended families but also greater child costs, parental labor supply is not reduced as a consequence of an increase in family size, suggesting that as an informal childcare provision mechanism, extended families play an important mitigating role for the time cost of children.

However, as family structure in developing countries becomes more nuclear with economic development, the time cost of children may increase for parents which may lead to further fertility decline and fewer opportunities for non-parental household members to help with childcare or household chores. In view of this decline in intergenerational co-residence over time and also the inadequate provision of public childcare in the context of Albania, one possible public policy intervention should be the implementation of childcare subsidies including direct provision of day-care nurseries, public kindergartens and pre-schools in order to promote labor supply and sustainable economic development.

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33
Table 1: Descriptive Statistics for Mother’s Fertilty in Albania (2002 - 2012)

|Variables|Observations|Mean|Standard<br>Deviation|Min|Max|
|---|---|---|---|---|---|
|_Sample: Mothers aged 20 to 49 years old with _<br>Fertility|_2 or more child_<br>7480|_ren youn_<br>2.600|_ger than 18 _<br>(0.871)|_years _<br>2|_old_<br>9|
|_(Number of children ever born)_||||||
|More than 2 children|7480|0.418|(0.493)|0|1|
|_(=1 if mother had 3 or more children)_||||||
|First child boy|7480|0.492|(0.499)|0|1|
|_(=1 if frst child was a boy)_||||||
|First child girl<br>_(=1 if frst child was a girl)_|7480|0.508|(0.499)|0|1|
|Second child boy|7480|0.514|(0.499)|0|1|
|_(=1 if second child was a boy)_||||||
|Two boys|7480|0.254|(0.435)|0|1|
|_(=1 if frst two children were boys)_||||||
|Two girls<br>_(=1 if frst two children were girls)_|7480|0.247|(0.431)|0|1|
|Same sex<br>_(=1 if frst two children have the same sex)_|7480|0.502|(0.500)|0|1|
|Mixed sex<br>_(=1 if frst two children have diferent sex)_|7480|0.497|(0.500)|0|1|

_Notes:_ The data used are the 2002 LSMS, the 2005 LSMS, the 2008-09 DHS and the 2012 LSMS 34
Table 2: Descriptive Statistics for Mother’s Labor-Supply in Albania (2002 - 2012)

|Variables<br>Observations|Mean|Standard<br>Deviation|Min|Max|
|---|---|---|---|---|
|**Mother’s Labor Supply**|||||
|Worked in last 7 days<br>7445|0.444|(0.496)|0|1|
|Worked of-farm<br>7445|0.163|(0.369)|0|1|
|Worked on-farm<br>7445|0.217|(0.412)|0|1|
|Self-employed<br>7445|0.066|(0.249)|0|1|
|Second occupation<br>4903|0.014|(0.120)|0|1|
|Hours/week (total)<br>4903|16.60|(21.24)|0|112|
|Hours/week (of-farm)<br>4903|7.17|(16.20)|0|70|
|Hours/week (on-farm)<br>4903|7.52|(15.64)|0|70|
|Hours/week (self)<br>4903|2.35|(11.15)|0|112|
|Monthly labor income<br>4903|50166.4|(114456)|0|1217661|
|**Other characteristics of mothers**|||||
|Age<br>7480|35.04|(5.691)|20|49|
|Age at frst birth<br>7480|23.22|(3.489)|14|41|
|Years of education<br>7404|10.47|(3.135)|0|21|
|Rural<br>7480|0.482|(0.499)|0|1|
|Household size<br>7480|5.188|(1.478)|1|16|
|Extended family<br>7480|0.381|(0.485)|0|1|
|Marital status (married)<br>7480|0.980|(0.137)|0|1|
|Muslims<br>7480|0.816|(0.387)|0|1|
|Catholics<br>7480|0.081|(0.273)|0|1|
|Orthodox<br>7480|0.067|(0.251)|0|1|
|Coastal region<br>7480|0.264|(0.440)|0|1|
|Central region<br>7480|0.282|(0.450)|0|1|
|Mountain region<br>7480|0.291|(0.454)|0|1|
|Tirana region<br>7480|0.161|(0.367)|0|1|

_Notes:_ The data used are the 2002 LSMS, the 2005 LSMS, the 2008-09 DHS and the 2012 LSMS 35
Table 3: Descriptive Statistics for Father’s Labor-Supply in Albania (2002 - 2012)

|Variables<br>|Observations|Mean|Standard<br>Deviation|Min|Max|
|---|---|---|---|---|---|
|**Father’s Labor Supply**||||||
|Worked in last 7 days|5496|0.787|(0.409)|0|1|
|Worked of-farm|5496|0.393|(0.488)|0|1|
|Worked on-farm|5496|0.236|(0.424)|0|1|
|Self-employed|5496|0.197|(0.398)|0|1|
|Second occupation|4566|0.058|(0.234)|0|1|
|Hours/week (total)|4566|34.23|(23.06)|0|112|
|Hours/week (of-farm)|4566|18.50|(23.43)|0|99|
|Hours/week (on-farm)|4566|9.10|(18.71)|0|99|
|Hours/week (self)|4566|7.63|(19.09)|0|112|
|Monthly labor income (old leks)|4566|191841.9|(333208.7)|0|12000000|
|**Other characteristics of fathers**||||||
|Age|5737|39.92|(5.855)|22|64|
|Age at frst birth|5737|28.33|(4.177)|15|58|
|Years of education|5541|11.08|(3.426)|0|20|
|Rural|5737|0.478|(0.499)|0|1|
|Household size|5737|5.210|(1.424)|1|16|
|Extended family|5737|0.364|(0.481)|0|1|
|Marital status (married)|5737|0.998|(0.032)|0|1|
|Muslims|5737|0.798|(0.401)|0|1|
|Catholics|5737|0.082|(0.275)|0|1|
|Orthodox|5737|0.069|(0.254)|0|1|
|Coastal region|5737|0.262|(0.440)|0|1|
|Mountain region|5737|0.285|(0.451)|0|1|
|Tirana region|5737|0.164|(0.370)|0|1|

_Notes:_ The data used are the 2002 LSMS, the 2005 LSMS, the 2008-09 DHS and the 2012 LSMS 36
Table 4: Fraction of Households that had Another Child by Parity and Sex Composition in Albania (2002- 2012)

|**Sex of the frst child**|||||
|---|---|---|---|---|
|**in households with**|Fraction||Fraction that||
|**one or more children**|of the sample|ha|d another ch|ild|
|||All<br>(1)|Urban<br>(2)|Rural<br>(3)|
|_Panel A: _<br>_1 or more_|_Mothers aged 20 _<br> _children younge_|_to 49 years o_<br>_r than 18 yea_|_ld with_<br>_rs old_||
|(1) one girl|0.493|0.809|0.781|0.841|
|||(0.005)|(0.008)|(0.007)|
|(2) one boy|0.506|0.764|0.752|0.777|
|||(0.006)|(0.008)|(0.008)|
|Diference (2) - (1)|0.012|-0.044|-0.028|-0.063|
||(0.010)|(0.008)***|(0.011)***|(0.011)***|
|Observations|9509|9509|5049|4460|
|**Sex of frst two children**|||||
|**in households with**<br>|Fraction<br>||Fraction that<br>||
|**two or more children**|of the sample|ha<br>|d another ch<br>|ild<br>|
|||All|Urban|Rural|
|||(1)|(2)|(3)|
|_Panel B: _<br>_2 or more_|_Mothers aged 20 t_<br> _children younge_|_o 49 years o_<br>_r than 18 yea_|_ld with_<br>_rs old_||
|one boy, one girl|0.237|0.352|0.265|0.441|
|||(0.011)|(0.014)|(0.016)|
|one girl, one boy|0.260|0.343|0.247|0.449|
|||(0.010)|(0.013)|(0.016)|
|two boys|0.254|0.364|0.277|0.458|
|||(0.011)|(0.014)|(0.016)|
|two girls|0.247|0.614|0.501|0.736|
|||(0.011)|(0.016)|(0.014)|
|(1) mixed combination|0.497|0.347|0.256|0.445|
|||(0.007)|(0.009)|(0.011)|
|(2) both same sex|0.502|0.487|0.387|0.595|
|||(0.008)|(0.011)|(0.011)|
|Diference (2) - (1)|0.005|0.140|0.131|0.150|
||(0.011)|(0.011)***|(0.014)***|(0.016)***|
|Observations|7480|7480|3874|3606|

_Notes:_ The data used are the 2002 LSMS, the 2005 LSMS, the 2008-09 DHS and the 2012 LSMS. * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%. Standard errors are in parenthesis.

37
Table 5: Differences in Means for Demographic Characteristics by Sex Composition

||Mo|thers _(N=74_|_80)_|Fa|thers _(N=54_|_96)_|
|---|---|---|---|---|---|---|
||Same-sex|Two boys|Two girls|Same-sex|Two boys|Two girls|
|Variables|(1)|(2)|(3)|(4)|(5)|(6)|
|Age|0.1252|-0.1683|0.3394|0.0045|-0.3907|0.4085|
||(0.1316)|(0.1510)|(0.1523)**|(0.1546)|(0.1769)**|(0.1795)**|
|Age at frst birth|-0.0160|-0.0414|0.0206|-0.1199|-0.2101|0.0546|
||(0.0807)|(0.0926)|(0.0934)|(0.1102)|(0.1362)|(0.1281)|
|Years of education|-0.0186|0.0020|-0.0270|0.0086|-0.0392|0.0520|
||(0.0728)|(0.0835)|(0.0843)|(0.0920)|(0.1054)|(0.1069)|
|Rural|-0.0014|0.0011|-0.0030|0.0122|0.0241|-0.0083|
||(0.0115)|(0.0132)|(0.0133)|(0.0131)|(0.0150)|(0.0153)|
|Muslim|-0.0121|-0.0109|-0.0051|-0.0082|-0.0109|0.0001|
||(0.0089)|(0.0102)|(0.0103)|(0.0105)|(0.0121)|(0.0123)|
|Catholic|0.0051|0.0057|0.0009|0.0065|0.0078|0.0007|
||(0.0063)|(0.0072)|(0.0073)|(0.0072)|(0.0083)|(0.0084)|
|Orthodox|0.0020|0.0085|-0.0059|0.0003|0.0087|0.0094|
||(0.0058)|(0.0066)|(0.0067)|(0.0067)|(0.0076)|(0.0078)|

_Notes:_ Differences in means (mean of the relevant group minus mean of the rest of the population) and their standard errors (in parentheses). * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%. The sample of mothers consists of 7480 Albanian women aged 20 to 49 years old with two or more children aged 18 or younger. The sample for fathers consists of 5496 husbands of the married women with two or more children aged 18 or younger. The data used are the 2002 LSMS, the 2005 LSMS, the 2008-09 DHS and the 2012 LSMS 38
Table 6: Differences in HH Budget Shares by Sex Child Composition in Albania (2002 - 2012)

||Budget Share||||
|---|---|---|---|---|
|Variables|(All)|Same-sex|Two boys|Two girls|
||(1)|(2)|(3)|(4)|
|HH Food Expenditure (S)|0.548|-0.001|-0.008*|0.006|
|||(0.004)|(0.004)|(0.004)|
|HH Health Expenditure (S)|0.054|-0.003|0.002|-0.007**|
|||(0.002)|(0.003)|(0.003)|
|HH Clothing Expenditure (S)|0.046|0.001|-0.000|0.001|
|||(0.001)|(0.001)|(0.001)|
|Children’s Education Expenditure (S)|0.025|-0.001|-0.002*|0.001|
|||(0.001)|(0.001)|(0.001)|
|Children’s Clothing Expenditure (S)|0.020|0.001*|-0.000|0.002***|
|||(0.000)|(0.000)|(0.000)|
|Children’s Education Expenditure (S.p.c)|0.010|-0.001***|-0.000*|-0.001*|
|||(0.000)|(0.000)|(0.000)|
|Children’s Clothing Expenditure (S.p.c)|0.008|-0.000|-0.000|-0.000|
|||(0.000)|(0.000)|(0.000)|
|Children’s Clothes (S.p.c.)|0.005|-0.000|-0.000|-0.000|
|||(0.000)|(0.000)|(0.000)|
|Children’s Footwear (S.p.c.)|0.003|-0.000|-0.000|-0.000|
|||(0.000)|(0.000)|(0.000)|

_Notes:_ Differences in means (mean of the relevant group minus mean of the rest of the population) and their standard errors (in parentheses). * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%. The data used are the 2002 LSMS, the 2005 LSMS and the 2012 LSMS. The sample consists of 7480 Albanian mothers aged 20 to 49 years old with two or more children aged 18 or younger. (S) refers to the share of a particular expenditure over total expenditure, while (S.p.c) refers to the respective share divided by the number of children aged 18 or younger still living in the household.

39
Table 7: First-Stage Specifications - Albania (2002 - 2012) Dependent Variable: Fertility (Number of children ever born) (1) (2) (3) (4) (5) (6) (7) _Panel A: Mothers aged 20 to 49 years old with 2 or more children younger than 18 years old_

|Boy frst|—|—|—|-0.2461***|-0.4655***|-0.0255|-0.0283|
|---|---|---|---|---|---|---|---|
|||||(0.0178)|(0.0267)|(0.0227)|(0.0234)|
|Boy second|—|—|—|-0.2175***<br>(0.0177)|-0.4370***<br>(0.0267)|0.0031<br>(0.0226)|—|
|Two girls|—|—|0.4723***<br>(0.0254)|—|—|0.4412***<br>(0.0346)|0.4381***<br>(0.0267)|
|Two boys|—|-0.1621***<br>(0.0209)|—|—|0.0029<br>(0.0226)|—|0.0024<br>(0.0226)|
|Same sex|0.2289***<br>(0.0192)|—|—|0.2202***<br>(0.0173)|—|—|—|
|R-squared|0.1197|0.1090|0.1569|0.2982|0.2665|0.2982|0.2982|
|Observations|7480|7480|7480|7404|7404|7404|7404|
|Mean dep. var.|2.60|2.60|2.60|2.60|2.60|2.60|2.60|
|F-stat excl. inst.|140.1|61.2|343.3|161.7|0.02|268.7|134.4|
|Survey FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|District FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Controls|No|No|No|Yes|Yes|Yes|Yes|
|_Panel B: _<br>Boy frst|_Husband’s of t_<br>—|_he married w_<br>—|_omen with 2 _<br>—|_or more child_<br>-0.2393***|_ren younger _<br>-0.4619***|_than 18 year_<br>-0.0115|_s old_<br>-0.0153|
|||||(0.0204)|(0.0309)|(0.0262)|(0.0277)|
|Boy second|—|—|—|-0.2240***<br>(0.0205)|-0.4465***<br>(0.0304)|0.0057<br>(0.0266)|—|
|Two girls|—|—|0.4703***<br>(0.0280)|—|—|0.4591***<br>(0.0400)|0.4465***<br>(0.0304)|
|Two boys|—|-0.1615***<br>(0.0235)|—|—|-0.0003<br>(0.0268)|—|-0.0014<br>(0.0269)|
|Same sex|0.2252***<br>(0.0216)|—|—|0.2225***<br>(0.0201)|—|—|—|
|R-squared|0.1160|0.1059|0.1530|0.2743|0.2415|0.2743|0.2743|
|Observations|5737|5737|5737|5460|5460|5460|5460|
|Mean dep. var.|2.60|2.60|2.60|2.60|2.60|2.60|2.60|
|F-stat excl. inst.|113.9|43.12|275.3|131.4|0.07|220.2|110.2|
|Survey FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|District FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Controls|No|No|No|Yes|Yes|Yes|Yes|

_Notes:_ Standard errors clustered at the PSU level are in parentheses. Other covariates in the models are the following: _Age, Age Squared, Age at First birth, Years of Education_ and also indicators for _Boy 1st_ and _Boy 2nd_ . Each model is estimated with survey and district fixed effects. * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%.

40
Table 8: OLS and IV Estimates of Mother’s Labor-Supply Models in Albania (2002 - 2012)

|Method||OLS|IV|IV|
|---|---|---|---|---|
|Instrument for Fertility:|||||
|_(Number of children ever born)_||—|_Same-sex_|_Two girls_|
|Survey Fixed-Efects||Yes|Yes|Yes|
|District Fixed-Efects||Yes|Yes|Yes|
|Controls||Yes|Yes|Yes|
|Dependent variable<br>Mean|Obs.|(1)|(2)|(3)|
|_Panel A: All data_|_bases (LS_|_MS and DHS)_|||
|_Worked in last_ 7 days<br>0.445|7404|-0.0063<br>(0.0073)|0.0474<br>(0.0474)|0.0360<br>(0.0340)|
|_Worked of-farm_<br>0.164|7404|-0.0291***<br>(0.0045)|0.0052<br>(0.0354)|0.0503**<br>(0.0258)|
|_Worked on-farm_<br>0.218|7404|0.0347***<br>(0.0066)|0.0125<br>(0.0396)|-0.0019<br>(0.0280)|
|_Self-employed_<br>0.067<br>_Panel B: On_|7404<br>_ly LSMS _|-0.0086**<br>(0.0037)<br> _databases_|0.0404<br>(0.0270)|-0.0107<br>(0.0182)|
|_Hours per week (total)_<br>16.69|4862|-0.203<br>(0.3867)|4.697*<br>(2.5509)|4.409**<br>(1.8866)|
|_Hours per week (of-farm)_<br>7.21|4862|-1.429***<br>(0.255)|-0.078<br>(1.902)|2.683*<br>(1.449)|
|_Hours per week (on-farm)_<br>7.56|4862|1.924***<br>(0.321)|2.303<br>(1.779)|1.570<br>(1.332)|
|_Hours per week (self)_<br>2.36|4862|-0.470**|2.841**|0.225|
|||(0.181)|(1.444)|(1.024)|
|_Second occupation_<br>0.014|4862|0.004<br>(0.002)|0.010<br>(0.014)|0.002<br>(0.011)|
|_Log(Monthly Labor Income)_<br>50498.2|4862|-0.3972***<br>(0.0778)|0.4172<br>(0.5740)|0.8679<br>(0.4384)|

_Notes:_ Standard errors clustered at the PSU level are in parentheses. All the models include the following covariates: _Age, Age Squared, Age at First birth_ and _Years of Education_ . IV Models in columns (2) and (3) also include indicators for _Boy 1st_ and _Boy 2nd_ . The sample includes mothers aged 20 to 49 years old with 2 or more children younger than 18 years old. Each model is estimated with survey and district fixed effects. * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%.

41
Table 9: OLS and IV Estimates of Father’s Labor-Supply Models in Albania (2002 - 2012)

|Method||OLS|IV|IV|
|---|---|---|---|---|
|Instrument for Fertility:<br>|||||
|_(Number of children ever born)_<br>||—|_Same-sex_|_Two girls_|
|Survey Fixed-Efects<br>||Yes|Yes|Yes|
|District Fixed-Efects||Yes|Yes|Yes|
|Controls||Yes|Yes|Yes|
|Dependent variable<br>Mean|Obs.|(1)|(2)|(3)|
|_Panel A: All data_|_bases (LS_|_MS and DHS)_<br>|||
|_Worked in last_ 7 days<br>0.790|5460|0.0124*<br>(0.0067)|0.0581<br>(0.0445)|0.0257<br>(0.0314)|
|_Worked of-farm_<br>0.394|5460|-0.0234***<br>(0.0080)|0.0365<br>(0.0537)|0.0671*<br>(0.0401)|
|_Worked on-farm_<br>0.218|5460|0.0347***<br>(0.0066)|0.0125<br>(0.0396)|-0.0019<br>(0.0280)|
|_Self-employed_<br>0.198<br>_Panel B: Onl_|5460<br>_y LSMS _|-0.0137**<br>(0.0063)<br>_databases_|0.0215<br>(0.0437)|-0.0072<br>(0.0319)|
|_Hours per week (total)_<br>34.39|4530|0.1056|-0.2895|-1.1751|
|||(0.4501)|(2.8443)|(2.0713)|
|_Hours per week (of-farm)_<br>18.60|4530|-1.609***<br>(0.426)|-4.3926<br>(2.8683)|-0.8306<br>(2.1766)|
|_Hours per week (on-farm)_<br>9.15|4530|2.744***|2.3598|0.5399|
|||(0.390)|(2.2198)|(1.6274)|
|_Hours per week (self)_<br>7.65|4530|-0.741**|2.7154|-0.0305|
|||(0.331)|(2.3503)|(1.7875)|
|_Second occupation_<br>0.058|4530|0.008*<br>(0.004)|0.0321<br>(0.0289)|0.0406*<br>(0.0230)|
|_Log(Monthly Labor Income)_<br>193092.2|4530|-0.3816***<br>(0.1144)|-0.6700<br>(0.7176)|-0.0883<br>(0.5305)|

_Notes:_ Standard errors clustered at the PSU level are in parentheses. All the models include the following covariates: _Age, Age Squared, Age at First birth_ and _Years of Education_ . IV Models in columns (2) and (3) also include indicators for _Boy 1st_ and _Boy 2nd_ . The sample of fathers includes the husbands of the married women aged 20 to 49 years old with 2 or more children younger than 18 years old) Each model is estimated with survey and district fixed effects. * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%.

42
|**el**|IV<br>_Two girls_|(6)|0.073<br>(0.060)<br>119.3<br>4.514<br>(3.632)<br>85.07<br>0.068<br>(0.063)<br>117.6<br>0.026<br>(0.037)<br>87.25<br>Yes<br>Yes<br>Yes<br>_red, Age at First birth_<br>cludes women aged 20<br>ith 2 or more children<br>** Indicates statistical<br>ge estimation.|
|---|---|---|---|
|**Educ. Lev**<br>_schooling)_|IV<br>_Same-sex_|(5)|-0.023<br>(0.080)<br>77.94<br>3.398<br>(4.660)<br>62.51<br>0.034<br>(0.077)<br>90.03<br>0.008<br>(0.044)<br>72.56<br>Yes<br>Yes<br>Yes<br>_ge, Age Squa_<br>of mothers in<br>ied women w<br>nce at 10%. <br> the frst-sta|
|**e Primary **<br>_8 years of _|OLS<br>—|(4)|-0.059***<br>(0.011)<br>-1.755**<br>(0.728)<br>-0.017<br>(0.013)<br>0.018**<br>(0.007)<br>Yes<br>Yes<br>Yes<br>ovariates: _A_<br>The sample <br>s of the marr<br>ical signifca<br>orresponds to|
|**Abov**<br>_(>_||Obs.|3504<br>2284<br>3040<br>2482<br>llowing c<br>_oy 2nd_. <br> husband<br>es statist<br>uments c|
|||Mean|0.286<br>19.09<br>0.482<br>0.062<br>clude the fo<br>_y 1st_ and _B_<br>includes the<br>s. * Indicat<br>luded instr|
||IV<br>_Two girls_|(3)|_Mothers_<br>0.033<br>(0.021)<br>161.8<br>4.092*<br>(2.185)<br>95.82<br> _Fathers_<br>0.060<br>(0.049)<br>104.2<br>0.052*<br>(0.028)<br>85.45<br>Yes<br>Yes<br>Yes<br>he models in<br>cators for _Bo_<br>le of fathers <br>t fxed efect<br>tic of the exc|
|**c. Level**<br>_chooling)_|IV<br>_Same-sex_|(2)|_Panel A: _<br>0.014<br>(0.028)<br>90.22<br>5.523*<br>(3.012)<br>58.72<br>_Panel B: _<br>0.030<br>(0.077)<br>48.10<br>0.055<br>(0.040)<br>44.69<br>Yes<br>Yes<br>Yes<br>theses. All t<br> include indi<br>d. The samp<br>y and distric<br> The F-Statis|
|**imary Edu**<br>_8 years of s_|OLS<br>—|(1)|-0.019***<br>(0.004)<br>0.140<br>(0.461)<br>-0.024**<br>(0.010)<br>-0.000<br>(0.006)<br>Yes<br>Yes<br>Yes<br> are in paren<br> and (3) also<br>n 18 years ol<br>d with surve<br>ance at 1%.|
|**Pr**<br>_(≤_||Obs.|3900<br><br>2578<br>2420<br>2048<br>PSU level <br>lumns (2)<br>unger tha<br>s estimate<br>al signifc|
|||Mean|0.054<br>14.56<br>0.283<br>0.054<br>d at the <br>dels in co<br>hildren yo<br> model i<br>s statistic|
||t for Fertility:|t variable|**_of-farm_**<br>_F-stat FS_<br>**_r week_**<br>_F-stat FS_<br>**_of-farm_**<br>_F-stat FS_<br>**_ccupation_**<br>_F-stat FS_<br>xed-Efects<br>xed-Efects<br> errors clustere<br>_ucation_. IV Mo<br>with 2 or more c<br> years old. Each<br>%. *** Indicate|
||Method<br>Instrumen|Dependen|**_Worked _**<br>**_Hours pe_**<br>**_Worked _**<br>**_Second o_**<br>Survey Fi<br>District Fi<br>Controls<br>_Notes:_ Standard<br>and _Years of Ed_<br>to 49 years old <br>younger than 18<br>signifcance at 5|

43
|IV<br>_Two girls_|(6)|_2 (incl.)_|0.048<br>(0.032)<br>173.4<br>1.599<br>(2.180)<br>124.18<br>_6 (incl.)_<br>0.063<br>(0.050)<br>123.3|0.015<br>(0.027)<br>105.75<br>Yes<br>Yes<br>Yes<br>_red, Age at First birth_<br>cludes women aged 20<br>ith 2 or more children<br>** Indicates statistical<br>ge estimation.|
|---|---|---|---|---|
|**arent**<br>IV<br>_Same-sex_|(5)|_n before 197_|-0.011<br>(0.045)<br>94.65<br>-0.010<br>(3.043)<br>72.02<br>_n before 196_<br>0.008<br>(0.064)<br>65.95|-0.005<br>(0.032)<br>67.18<br>Yes<br>Yes<br>Yes<br>_ge, Age Squa_<br>f mothers in<br>ied women w<br>nce at 10%. <br> the frst-sta|
|**Older P**<br>OLS<br>—|(4)|_Mothers bor_|-0.031***<br>(0.006)<br>-0.007<br>(0.484)<br> _Fathers bor_<br>-0.036***<br>(0.010)|0.008<br>(0.005)<br>Yes<br>Yes<br>Yes<br>ovariates: _A_<br> The sample o<br>s of the marr<br>ical signifca<br>orresponds to|
||Obs.|_l A.2. _|4151<br>2843<br>_el B.2. _<br>2741|2336<br>lowing c<br>_y 2nd_. <br>husband<br>s statist<br>ments c|
||Mean|_Pane_|0.205<br>20.05<br>_Pan_<br>0.439|0.061<br>ude the fol<br> _1st_ and _Bo_<br>cludes the <br> * Indicate<br>uded instru|
|IV<br>_Two girls_|(3)|_1972_|0.058<br>(0.043)<br>108.15<br>10.584***<br>(3.723)<br>69.69<br>_1966_<br>0.070<br>(0.069)<br>96.03|0.079*<br>(0.042)<br>76.03<br>Yes<br>Yes<br>Yes<br> the models incl<br>dicators for _Boy _<br>ple of fathers in<br>ict fxed efects. <br>istic of the excl|
|**Parent**<br>IV<br>_Same-sex_|(2)|_born after _|0.032<br>(0.056)<br>71.82<br>14.292***<br>(5.066)<br>50.98<br> _born after _<br>0.083<br>(0.096)<br>61.55|0.095<br>(0.058)<br>47.54<br>Yes<br>Yes<br>Yes<br>ntheses. All <br>o include in<br>old. The sam<br>ey and distr<br>. The F-Stat|
|**Younger **<br>OLS<br>—|(1)|_.1. Mothers_|-0.024***<br>(0.007)<br>-1.002<br>(0.687)<br>_.1. Fathers _<br>-0.009<br>(0.013)|0.009<br>(0.007)<br>Yes<br>Yes<br>Yes<br>el are in pare<br>2) and (3) als<br>han 18 years <br>ted with surv<br>cance at 1%|
||Obs.|_Panel A_|3253<br>2019<br>_Panel B_<br>2719|2194<br>PSU lev<br>lumns (<br>unger t<br>s estima<br>al signif|
||Mean||0.111<br>11.95<br>0.349|0.056<br>d at the <br>dels in co<br>hildren yo<br>h model i<br>s statistic|
|t for Fertility:|variable||**_f-farm_**<br>_F-stat FS_<br>**_r week_**<br>_F-stat FS_<br>**_f-farm_**<br>_F-stat FS_|**_ccupation_**<br>_F-stat FS_<br>ed-Efects<br>xed-Efects<br> errors clustere<br>_ucation_. IV Mo<br>with 2 or more c<br> years old. Eac<br>%. *** Indicate|
|Method<br>Instrumen|Dependent||**_Worked o_**<br>**_Hours pe_**<br>**_Worked o_**|**_Second o_**<br>Survey Fix<br>District Fi<br>Controls<br>_Notes:_ Standard<br>and _Years of Ed_<br>to 49 years old <br>younger than 18<br>signifcance at 5|

44
|IV<br>_Two girls_|(6)|0.038<br>(0.032)<br>167.24<br>3.536<br>(3.278)<br>67.53<br>0.072<br>(0.049)<br>133.3|0.071**<br>(0.028)<br>109.8<br>Yes<br>Yes<br>Yes<br>_red, Age at First birth_<br>cludes women aged 20<br>ith 2 or more children<br>** Indicates statistical<br>ge estimation.|
|---|---|---|---|
|**d Family**<br>IV<br>_Same-sex_|(5)|-0.001<br>(0.044)<br>92.89<br>3.620<br>(3.294)<br>66.87<br>-0.005<br>(0.071)<br>71.78|0.027<br>(0.038)<br>63.27<br>Yes<br>Yes<br>Yes<br>_ge, Age Squa_<br>f mothers in<br>ied women w<br>nce at 10%. <br> the frst-sta|
|**n-Extende**<br>OLS<br>—|(4)|-0.025***<br>(0.006)<br>-0.043<br>(0.462)<br>-0.027***<br>(0.009)|0.008<br>(0.005)<br>Yes<br>Yes<br>Yes<br>ovariates: _A_<br>The sample o<br>s of the marr<br>ical signifca<br>orresponds to|
|**No**|Obs.|4600<br>3133<br>3493|2923<br>llowing c<br>_oy 2nd_. <br> husband<br>es statist<br>uments c|
||Mean|0.165<br>16.31<br>0.414|0.057<br>clude the fo<br>_y 1st_ and _B_<br>includes the<br>s. * Indicat<br>luded instr|
|IV<br>_Two girls_|(3)|_: Mothers_<br>0.077*<br>(0.046)<br>104.76<br>6.982*<br>(3.564)<br>57.64<br>_: Fathers_<br>0.061<br>(0.071)<br>77.33|-0.012<br>(0.040)<br>57.09<br>Yes<br>Yes<br>Yes<br> the models in<br>icators for _Bo_<br>ple of fathers <br>ict fxed efect<br>istic of the exc|
|**Family**<br>IV<br>_Same-sex_|(2)|_Panel A_<br>0.020<br>(0.060)<br>71.02<br>7.532*<br>(4.303)<br>49.54<br>_Panel B_<br>0.107<br>(0.091)<br>61.30|0.044<br>(0.048)<br>50.66<br>Yes<br>Yes<br>Yes<br>ntheses. All <br>o include ind<br>old. The sam<br>ey and distr<br>. The F-Stat|
|**Extended **<br>OLS<br>—|(1)|-0.037***<br>(0.008)<br>-0.663<br>(0.715)<br>-0.013<br>(0.015)|0.009<br>(0.007)<br>Yes<br>Yes<br>Yes<br>l are in pare<br>) and (3) als<br>an 18 years <br>ted with surv<br>cance at 1%|
||Obs.|2804<br>1729<br>1967|1607<br>PSU leve<br>lumns (2<br>unger th<br>s estima<br>al signif|
||Mean|0.162<br>17.37<br>0.359|0.060<br>d at the <br>dels in co<br>hildren yo<br> model i<br>s statistic|
|t for Fertility:|t variable|**_of-farm_**<br>_F-stat FS_<br>**_r week_**<br>_F-stat FS_<br>**_of-farm_**<br>_F-stat FS_|**_ccupation_**<br>_F-stat FS_<br>xed-Efects<br>xed-Efects<br> errors clustere<br>_ucation_. IV Mo<br>with 2 or more c<br> years old. Each<br>%. *** Indicate|
|Method<br>Instrumen|Dependen|**_Worked _**<br>**_Hours pe_**<br>**_Worked _**|**_Second o_**<br>Survey Fi<br>District Fi<br>Controls<br>_Notes:_ Standard<br>and _Years of Ed_<br>to 49 years old <br>younger than 18<br>signifcance at 5|

45
Table 13: Falsification Exercise: Determinants of Living in an Extended Family - Albania (2002 - 2012)

|||Dependent|Variable:||
|---|---|---|---|---|
||Livi|ng in an Ex|tended Fa|mily|
||(1)|(2)|(3)|(4)|
|Boy frst|0.0065|0.0247|0.0159|0.0064|
||(0.0131)|(0.0165)|(0.0110)|(0.0159)|
|Boy second|-0.0002|0.0180|0.0092||
||(0.0167)|(0.0156)|(0.0114)||
|Two girls|-0.0187|||-0.0186|
||(0.0228)|||(0.0156)|
|Two boys||-0.0176||0.0004|
|||(0.0227)||(0.0166)|
|Samesex|||-0.0091||
||||(0.0114)||
|R-squared|0.2982|0.2665|0.2982|0.2982|
|Observations|7404|7404|7404|7404|
|Mean dep. var|0.381|0.381|0.381|0.381|
|Survey FE|Yes|Yes|Yes|Yes|
|District FE|Yes|Yes|Yes|Yes|
|Controls|Yes|Yes|Yes|Yes|

_Notes:_ Standard errors clustered at the PSU level are in parentheses. Other covariates in the models are the following: _Age, Age Squared, Age at First birth, Years of Education_ and also indicators for _Boy 1st_ and _Boy 2nd_ . Each model is estimated with survey and district fixed effects. * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%.

46
Table 14: IV Estimates of the Effect of Fertility on Family Spending per-capita - Heterogeneity Analysis by Expenditure Quintiles and Family Structure - Albania (2002 - 2012)

||||Expe|nditure Quint|iles||
|---|---|---|---|---|---|---|
|Variables|All|Q1<br>(Poorest)|Q2<br>(Poorer)|Q3<br>(Middle)|Q4<br>(Richer)|Q5<br>(Richest)|
|Mother’s age|35.04|34.38|34.82|35.03|35.35|35.91|
|Mother’s age at 1st birth|23.22|23.06|23.02|23.11|23.33|23.70|
|Father’s age|39.91|38.77|39.85|39.98|40.36|40.95|
|Father’s age at 1st birth|28.33|27.86|28.14|28.23|28.60|29.01|
|% Rural|0.482|0.699|0.656|0.492|0.309|0.209|
|% Third child|0.418|0.488|0.445|0.430|0.384|0.310|
|% Extended Family|0.381|0.313|0.384|0.386|0.394|0.451|

Dependent variable: Ln (Per-capita Expenditure)

|||**Pa**|**nel A: Exten**|**ded Family**||||
|---|---|---|---|---|---|---|---|
|Fertility||||||||
||IV _(same sex)_|-0.0890|0.1579|-0.0252|-0.1985***|-0.0309|-0.2110|
|||(0.0826)|(0.1811)|(0.1036)|(0.0632)|(0.1505)|(0.1321)|
||IV _(two girls)_|-0.1563**|-0.0948|-0.0979|-0.2180***|-0.1487|-0.2967**|
|||(0.0674)|(0.1184)|(0.0683)|(0.0585)|(0.0950)|(0.1162)|
||Observations|1699|248|340|401|450|260|
|||**Pane**|**l B: Non-Ext**|**ended Fami**|**ly**|||
|Fertility||||||||
||IV _(same sex)_|-0.1600**|-0.2860***|-0.2088***|-0.2170***|-0.1769***|-0.1614|
||IV _(two girls)_|(0.0649)<br>-0.2054***|(0.0795)<br>-0.2444***|(0.0634)<br>-0.2314***|(0.0367)<br>-0.1898***|(0.0683)<br>-0.2254***|(0.1187)<br>-0.1884*|
|||(0.0465)|(0.0578)|(0.0429)|(0.0270)|(0.0384)|(0.0985)|
||Observations|3081|784|684|666|646|301|
|Survey F|ixed-Efects|Yes|Yes|Yes|Yes|Yes|Yes|
|District|Fixed-Efects|Yes|Yes|Yes|Yes|Yes|Yes|
|Controls||Yes|Yes|Yes|Yes|Yes|Yes|

_Notes:_ Standard errors clustered at the PSU level are in parentheses. The IV models include the following covariates: _Age, Age Squared, Age at First birth, Years of Education, Boy1st_ and _Boy 2nd_ . Each model is estimated with survey and district fixed effects. * Indicates statistical significance at 10%. ** Indicates statistical significance at 5%. *** Indicates statistical significance at 1%.

47
Figure 1: Evolution of the Total Fertility Rate in Albania (1960 - 2012) <!-- Start of picture text --> 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010<br>Year<br>Total Fertility Rate (Source: World Development Indicators)<br>Total Fertility Rate (Source: INSTAT)<br>7<br>6<br>5<br>4<br>3<br>Number of children<br>2<br>1<br><!-- End of picture text --> _Notes: According to Gjon ̧ca et al (2008), the total fertility rate rose during the 1950s reaching a peak of almost 7 children per woman by 1960. This was followed in the 1970s by a steady decline, with a total fertility rate of less than 4 in 1980 and just over 3 children per woman in 1990. The 1990s saw a continuing reduction which reached the replacement level of 2.2 children per woman in 2002, which at the same time was the highest fertility rate in Europe. During the 2000s the total fertility rate has decreased even further reaching a level of 1.65 children per women in 2012, which currently characterizes Albania as a country with a very low fertility rate._ 48
Figure 2: Labor-Force Pariticpation and Total Fertility Rate - Albania (1990 - 2012) <!-- Start of picture text --> 1990 1995 2000 2005 2010 2015<br>year<br>Male (ages 15+) Female (ages 15+) TFR<br>80<br>3<br>70<br>2.5<br>60<br>2<br>Total fertility rate (TFR)<br>50<br>Labor-force participation (%)<br>40 1.5<br><!-- End of picture text --> _Notes: Source: Albanian Institute of Statistics (INSTAT)_ 49
<!-- Start of picture text --> 2015<br>2010<br>2012)<br>-<br>(1990<br>2005<br>Albania<br>in<br>year<br>2000<br>Pre-school<br>3: Number of kindergartens Numer of children enrolled in kindergartens<br>Figure<br>1995<br>1990<br>Nro of children enrolled in kindergartens<br>110000 100000 90000 80000 70000<br>3500 3000 2500 2000 1500<br>Nro of kindergartens<br><!-- End of picture text --> 50
<!-- Start of picture text --> by<br>0.35 2012<br>Decomposed<br>- 0.37 2008<br>Two boys (BB) 0.35 2005<br>old)<br>0.39 2002<br>Composition<br>years<br>Sex 18<br>and than 0.45 2012 0.38 2012<br>0.46 2008<br>Parity<br>0.51 2008<br>by younger 0.43 2005<br>0.48 2005 Otherwise (BG,GB,GG)<br>Child Same sex (BB, GG) 0.46 2002<br>0.50 2002<br>children<br>2<br>Another<br>had least 0.30 2012<br>at 0.53 2012<br>that 0.37 2008<br>with 0.65 2008<br>0.35 2005<br>old Mixed sex (BG, GB)<br>Households 0.37 2002 Two girls (GG) 0.62 2005<br>of years<br>0.65 2002<br>49<br>to<br>Fraction<br>20 0.32 2012<br>of<br>0.37 2008<br>Version<br>(Mothers<br>0.35 2005<br>Otherwise (GB, BG, BB)<br>0.38 2002<br>Graphical<br>4:<br>.8 .6 .4 .2 0<br>Fraction of mothers that had a 3rd child<br>.5 .4 .3 .2 .1 0<br>Fraction of mothers that had a 3rd child<br>.8 .6 .4 .2 0<br>Fraction of mothers that had a 3rd child<br><!-- End of picture text --> 51
Figure 5: Proportion of parents in extended families living with their married son by their son’s birth order <!-- Start of picture text --> 61.03<br>17.66<br>14.18<br>4.726<br>2.405<br>youngest middle oldest unknown more<br>Birth order<br>Source: 2002 Albania LSMS<br>60<br>40<br>Percent<br>20<br>0<br><!-- End of picture text --> _Source: 2002, 2005 and 2012 Albanian LSMS; 2008-09 Albanian DHS_ 52