The relationship between fertility and female participation in the labour force in OECD countries 2000-2020: It is (again) negative

Milovanović, Miloš Article The relationship between fertility and female participation in the labour force in OECD countries 2000-2020: It is (again) negative Central European Economic Journal (CEEJ) Provided in Cooperation with: Faculty of Economic Sciences, University of Warsaw Suggested Citation: Milovanović, Miloš (2023) : The relationship between fertility and female participation in the labour force in OECD countries 2000-2020: It is (again) negative, Central European Economic Journal (CEEJ), ISSN 2543-6821, Sciendo, Warsaw, Vol. 10, Iss. 57, pp. 254-274, https://doi.org/10.2478/ceej-2023-0015 This Version is available at: https://hdl.handle.net/10419/324593 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ ISSN: 2543-6821 (online) Journal homepage: http://ceej.wne.uw.edu.pl To cite this article Milovanović, M. (2023). The Relationship between Fertility and Female Participation in the Labour Force in OECD Countries 2000–2020: It Is (Again) Negative. Central European Economic Journal, 10(57), 254-274. DOI: 10.2478/ceej-2023-0015 To link to this article: https://doi.org/10.2478/ceej-2023-0015 This article was edited by Guest Editor: Martin Klesment Tallinn University, Estonia as part of the “Special issue on Fertility response to economic insecurities in the CEE countries“ The Relationship between Fertility and Female Participation in the Labour Force in OECD Countries 2000–2020: It Is (Again) Negative Miloš Milovanović Open Access. © 2023 M. Milovanović, published by Sciendo. This work is licensed under the Creative Commons Attribution 4.0 International License. Miloš Milovanović Linköping University, Department of Culture and Society (IKOS), Division of Ageing and Social Change (ASC) , Linköping University, Sweden corresponding author: [email protected] The Relationship between Fertility and Female Participation in the Labour Force in OECD Countries 2000–2020: It Is (Again) Negative Abstract The cross-sectional association between female labour force participation rates and fertility in developed countries shifted from negative to positive during the 1980s. Ever since then, researchers have applied different statistical approaches; therefore, the present study re-evaluates the results by applying a distinct strategy to the data from 2000 to 2020 for 32 countries belonging to the Organization for Economic Co-operation and Development (OECD). Specifically, the data analysis discussed here implemented the so-called „unified“ model, thereby extending the analysis beyond the limitations of the fixed effects (FE) method; namely, by decomposing coefficients within (time-series) and between (cross-sectional) countries‘ effects, the study increased the explanatory power of our statistical model on the relation between fertility level and female labour force participation rate. Eventually, the selected statistical approach has shown the potential to offer a better interpretation of results in comparison to previous studies. Finally, this study confirmed the persistence of a negative trend in a time-series association between labour force participation and fertility. Keywords Female labour force participation | fertility rate | global financial crisis | total fertility rates JEL Codes J13, J21, C33, C18 1. Introduction OECD countries, at least most of them, have undergone a considerable rise in female labour force participation (Thévenon, 2013). Precisely, at the beginning of the 21st century, the female labour force participation (FLFP) rates (Figure 1) varied from just 46.3% in Italy and 50.5% in Greece to 83.3% in Norway (OECD, 2022a). A decade later, the same pattern was perceived; namely, the lowest rates of female participation have been recorded in Italy with only 51.1 % but now instead of Greece, we have South Korea in second place with 54.5%, while the highest recorded rates remained in Iceland with 81.1% (OECD, 2022a). In 2020, the countries with the lowest participation rates were Italy and Greece with 54.7% and 59.3%, while Iceland remained on the top with 80.7% (OECD, 2022a). The reasons for the observed differences are various. The earlier findings suggest a U-shaped relationship between FLFP and economic development (Goldin, 1995). Arguably, while the early stages of economic growth are accompanied by lower participation of women in the labour force, the share eventually increases as income rises further (Goldin, 1995). In addition, researchers suggest the influence of cultural patterns, e.g., gender roles and position in the household are also important factors in curbing the observed level of female participation in the labour force (Clark, Ramsey & Adler, 1991; Uberti & Douarin, 2023). According to the report regarding policy and action implemented until 2020 in G20 countries, the persistent gap in female participation rates between, for example, Mediterranean countries (e.g., Italy and Greece) and Nordic countries (e.g., Iceland and Sweden), could be, to some extent, rooted in culture CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 256 and social norms, but at the same time may reflect economic realities in the particular country (ILO and OECD, 2020). Regarding the trends in fertility rates recorded at the beginning of the time frame that this study explores (2000–2020), the Czech Republic and Spain recorded the fewest children per woman at 1.14 and 1.23, respectively, in 2000 (Figure 2). On the other hand, the United States and Israel at 2.23 and 2.95, respectively, recorded the highest number of children per woman in 2020 of all OECD countries (OECD, 2022b). In the middle of the observed time interval, we find Hungary and South Korea with only 1.26 and 1.23 children per woman, respectively, while Iceland with 2.2 and Israel with more than 3 children per woman occupied the first two places (OECD, 2022b). Finally, in 2020, the lowest level of total fertility rates (TFR) has been recorded in South Korea, with just 0.86 children per woman, while Israel stayed on the top with 2.93 children per woman (OECD, 2022b). To account for the recent trends experienced across OECD nations regarding fertility rates,authors of these reports suggest that institutional variation and labour market insecurity may play a role (e.g., Adserà, 2004), accompanied by well-elaborated and documented inverse associations between age at first marriage, education, female labour force participation, and so forth. (Kohler, Billari & Ortega, 2002). Arguably, every exit from the labour market at childbirth hints at a potential loss of income, a lower wage after returning to the job market, and a higher risk of unemployment (Adserà, 2004). Consequently, the wide range of labour market arrangements across OECD countries sets the childbearing and participation decisions of women. Government answers usually focus on the compatibility of work and family for women. But, with an increase in female labour force participation, family formation becomes irreconcilable with career. Furthermore, the dual responsibility for women induces a trade-off between the size of the family and employment. As an illustration, across OECD countries in 2011, the mean personal ideal number of children for women was around 2.3 (OECD Family Data Base, 2022). Furthermore, most adults prefer to have two children: more than 50% of 15to 64-yearFigure 1. Female labour force participation rates by OECD member countries, 2000–2020 CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 257 old women consider two children to be an appropriate ideal family size in most OECD countries (OECD Family Data Base, 2022). Eventually, the mean actual number of children was just around 1.3 children per woman (OECD Family Data Base, 2022). It is clear that women adopted plans intentionally to integrate the two spheres of life through the timing of motherhood and return to the labour force (Ni Bhrolchain, 1986). Given that both FLFP rate and fertility could have a decisive role in determining women’s position in society and family, there has been huge interest in the relationship between them (Behrman & GonalonsPons, 2020). Arguably, the cross-sectional correlation between FLFP rates and fertility in developed countries shifted from negative to positive during the 1980s (Esping-Andersen,1999; Brewster & Rindfuss, 2000), and the general view is that the positive link is false due to “the country-specific heterogeneity”, while the time-series association remained negative (Kögel, 2004). Therefore, Kogel’s assertion that the time-series association between TFR and FLFP is negative motivated me to explore whether this is still valid for the latest data. In particular, it may not hold because both welfare support for the reconciliation between paid work and childcare and the involvement of men in childcare have expanded since 2000, which should facilitate the positive relationship between TFR and FLFP. Furthermore, Oshio, after utilizing annual data from 1970 to 2017, concluded that “the more recent the data set used, the more likely it is that the time-series association will be positive between FLFP and TFR” (Oshio, 2019, p. 1284). In addition, he contended that by using a more recent data set, the inconsistency between cross-country and time series should disappear; that is, both would indicate a positive association between FLFP and TFR (Oshio, 2019, p. 1284). On the other hand, many advanced economies experienced declines in fertility rates after the global financial crisis in 2008, so the trend for the TFR–FLFP relationship may have changed. Figure 2. Total fertility rates by OECD member countries, 2000–2020 CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 258 In order to examine the above assumptions, this study will investigate the relationship between TFR and FLFP using a macro approach, with an ambition to enrich the body of evidence about the time-series relationship between the total fertility rates and female labour force participation rates in advanced economies since the year 2000. For this purpose, I have compiled a dataset with variables obtained from the OECD database. All examinations were performed at the country level and explore aggregated connections between employment and fertility. The benefit of employing aggregated data is “that the experience of living in a country where many women are employed may have an important spill over effect even among unemployed women” (Behrman & Gonalons-Pons, 2020, p. 40). Arguably, the increase in women’s engagement could advance the onset of broader transformations in norms on gender and fertility even among women who are not engaged but just uncovered new modes of behaviour (Behrman & Gonalons-Pons, 2020, p. 40). In the next section, the theoretical underpinnings of the relationship between fertility and employment are presented. After that, it presents the data, followed by the employed methodology and results. The paper closes with a short discussion of the advantages of the applied method and conclusions. 2. Theoretical background The prominent economist Becker (1965) proposed the microeconomic theory of fertility and women’s labour supply emphasising the role of specialization within the family. He stressed that women are merely additional income providers. Importantly, according to the author, women’s employment and fertility decisions depend on the price effect. Finally, the suggested model expects the price effect to exceed the income effect. Consequently, it predicts an inverse correlation between female labour supply and fertility. The opposite sign of the correlation is assumed by Oppenheimer’s most famous pieces, published in 1977 and 1997, which criticized the role specialization assumption (Oppenheimer,1977;1997). Namely, women’s participation in the labour force increased significantly around Europe, thus reducing the duration of family-related employment gaps. Therefore, she has argued that in contemporary societies, women’s earnings contribute more than ever to the home budget, especially in highly developed countries of the global north where female employment is more promoted and socially accepted (e.g., Sweden, Norway, Denmark). Consequently, the income effect of women’s employment should exceed the price effect, thus making the correlation between female participation and fertility positive. Similarly, Esping-Andersen and Billari (2015) argued that the gender revolution and the departure from the traditional woman-homemaker family model brought about a decline in fertility. With time, according to the gender equilibrium theory, new and more egalitarian gender arrangements will be established because societies begin to settle into the new balance regarding family forms, i.e., more genderegalitarian family arrangements (Esping-Andersen and Billari, 2015). By adopting this nontraditional shift in gender role, a positive relationship between female labour participation and the fertility rate is to be expected. Moreover, Nordic countries, characterized by high values for the human development index (HDI) and relatively high fertility, served as role models for the supporters of this theory. For example, Myrskylä, Kohler, and Billari (2009) argued that in developed countries with a higher human development index (HDI), the association between female participation in the labour force and fertility would also turn from negative to positive once the level of HDI reaches the higher values. Namely, in countries such as Norway, the US, the UK, and Denmark, among others, the TFR reversed and became positive between 1975 and 2005. Unfortunately, the problem was the design of the study, which was based on measurements in a crosssection. According to Lesthaeghe (2020), the study by Myrskylä et al. is a case of what Arland Thornton (2005) calls “reading history sideways”. Arguably, the future evolution of societies in this area was based on a single and static cross-sectional pattern, that is, without including time as a factor (Thornton, 2005). Similarly to the gender equilibrium theory, Goldscheider, Bernhardt, and Lappegård (2015) argue that there has been a weakening and reversal of entrenched traditional gender roles since the employment of women became a common practice. They refer to these shifts in gender relationships as the gender revolution. Namely, the higher female participation in the labour force should be perceived just as the initial phase of the gender revolution. Subsequently, with the higher involvement of men in the private sphere of the family, according to the gender revolution theory, the stability of the family will increase (Goldscheider et al., 2015). Arguably, the negative aspects of family change (e.g., CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 259 low fertility and increase in divorce rates) induced by the movement of women into the labour market, will be lessened by the higher involvement of men in the home (Goldscheider et al., 2015). Eventually, a positive relationship between female labour supply and fertility rates is expected, with an increase in welfare support for combining paid work, childcare, and men’s involvement in childcare. Assertion of how the cross-sectional relationship between FLFP and fertility rates across developed countries has changed from negative to positive, has also further fuelled a debate about the association between work and childbearing (Oshio, 2019). Arguably, the shift in the connection between fertility and female employment occurred because of the reduced collision in women’s function as mother and worker (Rindfuss, Guzzo & Morgan, 2003), followed by the boost in womens’ salaries (Ahn & Mira, 2002). By using panel data on fertility and FLFP rates, Ahn and Mira (2002) showed how the correlation shifted from negative to positive around 1985. Namely, during the 1970s and up to 1985, the correlation was negative and significant while from 1985 until 1995 it become positive and significant (Ahn & Mira, 2002). A similar change in the positivity of correlation was confirmed by Rindfuss and colleagues (2003). By employing data from 1960 until 1997 for 22 lowfertility countries, they noted a shift in the association of fertility levels to women’s levels of labour force participation. Moreover, the study documented the same positive association between the country-level TFR and the proportion of births to unmarried women. Arguably, these shifts in the associations are the result of the adopted policies that have reduced both the incompatibility between women’s roles as mother and worker and decreased the link between marriage and childbearing (Rindfuss, Guzzo, & Morgan, 2003). Contrary, Kögel (2004) did not detect a positive association between fertility and female participation when using time-series data for OECD countries. Arguably, the reversal in the sign of the cross-country correlation is most likely due to the existence of unmeasured country-specific elements, and due to “the country-heterogeneity in the magnitude of the negative time-series association between fertility and female employment” (Kögel, 2004, p. 46). Namely, the existence of country-specific effects suggests that differences between countries regarding public policies or labour market practices may be the main cause for why some countries have high fertility and high female employment while others have low levels of both (Kögel, 2004). Therefore, he applied FE models to country-level time-series data from countries that are members of the OECD by dividing the analysis period into two timespans: 1960–1985 and 1985–2000. Subsequently, he confirmed that the time-series connection between female participation and fertility is inverse and that the negative sign of this relationship has weakened since 1985. Kögel (2004) illustrated that the relationship between TFR and FLP remains negative and significant once we include country dummy variables in pooled time series and cross-country data. Accordingly, Engelhardt and Prskavetz (2004) have tried to find omitted variables that may be behind dummy country variables. Therefore, they clustered countries according to the dynamics exerted regarding FLFP. Afterwards, they employed several economic and social variables that have changed following a transition in female labour supply by using a descriptive approach. Although descriptive pieces of evidence cannot strongly prove that a shift in crosscountry correlation between fertility and female employment occurred because of the country-specific characteristics, they concluded how both the trend in the labour market and demographic indicators are consistent with new home economics theory; therefore, a negative association between TFR and FLFP is expected (Engelhardt & Prskavetz, 2004). Following a path similar to that of Kögel (2004), Oshio (2019) estimated the time-series association between TFR and FLFP by fixed-effects regression models, which can be controlled for country-specific heterogeneity, and found that more recent the data set we use, the more likely it is that the time-series association will be positive (Oshio, 2019). The FLFPTFR correlation diverted from negative to positive when FLFP surpassed a value of 0.6 for data on 24 countries belonging to the OECD from 1970 to 2017 (Oshio, 2019). Although the current study is on the macro level, it is important to highlight the significant contributions of the papers that dealt with the relationship between fertility and labour participation on the individual level in developed countries. For most Western economies, studies on the micro level support the existence of a negative correlation between female employment and childbearing, indicating a prevalence of the “price” effect over the “income” effect (Matysiak & Vignoli, 2008). Furthermore, the delay of motherhood and avoidance of subsequent childbearing occurs CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 260 in countries where the labour market institutions are not following the need for female work, i.e., in Mediterranean countries (Adserà, 2005). In contrast to the above, in countries that were once members of the Eastern Bloc, studies have offered evidence that the probability of having a first child did not depend on a woman’s employment status (Matysiak, 2009). Having in mind that these countries experienced the eradication of public support for working parents after the fall of state socialism, the results of the studies are even more puzzling. In addition, cultural norms regarding work–family balance that prevail in formerly socialist countries are similar to Mediterranean countries (Thévenon, 2011), therefore making this issue even more interesting from the researcher’s point of view. Arguably, since the female participation rates were always high in Eastern Europe, probably because women have a long history of being income providers in comparison to their counterparts in the West (Matysiak & Vignoli, 2013). Overall, in light of the premises cited above, in this study I expected to find strong friction between fertility and women’s participation rates across the OECD member countries, originating from predominantly unfavourable circumstances for work and family reconciliation. Nevertheless, I anticipated time series that is, within-country differences between the fertility and participation rates, in order to dig deeper into the relationship beyond simple association. Moreover, by clustering countries according to their historical and cultural experience, the occurrence of a positive correlation between the total fertility rates and female labour participation on the OECD level will be further investigated. 3. Data The study uses annual data from 32 countries out of the 38 in the OECD. The analysis excluded five countries (Chile, Colombia, Mexico, Turkey, and Costa Rica), because the full data set for 2000–2020 was not available. In addition, Israel is excluded due to the much higher values of TFR. Two essential variables in this study are FLFP and TFR, the data for which was downloaded from the databases of the OECD website (https://stats.oecd.org). Also, the model incorporates the gender wage gap, the share of part-time employed women, public expenditure on family (in cash and in-kind) as a share of GDP per capita using purchasing power parity rates, the share of women (15–64) with tertiary education, mean age at birth, and the categorical variable that grouping OECD countries in five clusters. The study employed the FE model and linear random intercept model (maximum likelihood), a so-called “unified” model (Bartels, 2009). The critical value chosen was 0.05. The particular advantages and shortcomings of the models used will be elaborated on in the Methods section. The significance codes used are: < 0.05**; <0.001***. All estimations were conducted using the STATA 16 statistical software package. 3.1. Variables 3.1.1. Dependent variable The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her childbearing years and with the prevailing agespecific fertility rates (OECD, 2022a). It is calculated by totalling the age-specific fertility rates as defined over five-year intervals. Assuming no net migration and unchanged mortality, a total fertility rate of 2.1 children per woman ensures a broadly stable population. 3.1.2. Independent variable The FLFP is calculated as the labour force divided by the total working-age female population. The working-age population refers to people aged 15 to 64 (OECD, 2022b). Since labour participation assumes females that aren’t employed currently but still looking for a job, it also covered those who are not detected by unemployment statistics. Specifically, the female participation rates pool captures those who currently do not have work (also those in the army, prison, or other institution) but actively search for a job. In contrast, by exclusively using employment rates as a dependent variable, those groups of females who are not currently employed, but are actively searching for a job would have been omitted from the study. CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 261 3.1.3. Control variables Female part-time employment rates are defined as women in employment (whether employees or selfemployed) who usually work less than 30 hours per week in their main job, and this indicator shows the proportion of those employed part-time among all employed women (OECD, 2022c). By adding part-time employment rates, the study will be able to quantify the effect of part-time work on fertility. Arguably, in some countries (Belgium, Ireland, and The Netherlands) the use of part-time rates, in order to reconcile childbearing and work, enhance fertility (Ariza, Goiricelaya & Olazabal, 2003). Also, since infertility is associated with working extra hours, especially in young-aged workers, it can be important to control for the differences in working time (Ahn et al., 2021). Following Oshio (2019), I gathered data for the study for public expenditure on families from the OECD Social Expenditure Database (SOCX) (2023) as a ratio of the gross domestic product (GDP). Public expenditure on families includes cash and benefitsin-kind. Cash benefits include family allowances, including maternity and parental leave, while benefits in kind include early childhood education, care, and home help/accommodation. Data is available for 2000 to 2020 with gaps; therefore this study employed linear interpolation for missing values. Importantly, different policy measures also aim at different stages of childcare. Maternity leave aims at facilitating childbearing for women, providing job security at a diminished wage, while parental leave tries, as much as possible, to incorporate men in childrearing and to promote gender-equal parenting. Both maternity and parental leave could be crucial , because childbearing normally takes place during the early stages of the career (Taniguchi, 1999). In contrast, benefits-in-kind are aimed at older children and cover longer periods, thus could have a significant effect on their success in the future (Duncan, Morris & Rodrigues, 2011; Aizer et al., 2016). The gender wage gap is defined as the difference between the median earnings of women relative to the median earnings of men (OECD, 2022d). I expected to find a direct correlation between fertility and the relative wages of women to men. Increasing the relative size of women’s wages in comparison to men, i.e., reducing the wage gap, would also increase the cost of a child. Because the possible gains from a woman’s participation in the labour market has increased, the number of children decreases (Galor & Weil, 1996; Waldfogel, 1997). Given the many linkages between education and family behaviour, incorporation of the share of women (aged 25–64 years) with tertiary education as a control variable may have important consequences for study results. Since the establishment of Becker’s new home economics theory (1981), the negative relationship between total fertility rates and the expansion of higher education among women is a consistent finding across the countries (Basten, Sobotka & Zeman,2014; Ní Bhrolcháin & Beaujouan, 2012). Recently, the results have emphasised the beneficial effect of gender equality on the increase in fertility (Impicciatore & Tomatis, 2020). The mean age at childbearing is the mean age of mothers at the birth of their children if women were subject throughout their lives to the age-specific fertility rates observed in a given year. It is calculated as the sum of age-specific fertility rates weighted by the mid-point of each age group, divided by the sum of the age-specific rates (UNDP, 2020). Arguably, the postponement of first births is an important determinant of declined fertility rates (Roustaei et al., 2019). In order the check for the progress of TFR through the observed period, the study included a control variable for the level of TFR in 2000. The control variable is able to quantify the significance of the values of TFR and exclude the dependence of levels of TFR for 2000–2020 on the values before the period of interest. The region is a variable operationalized by clustering countries into five groups based on their similarity in historical development and geographical proximity. For group 1, the study included the non-European countries: USA, Canada, Japan, The Republic of Korea, and New Zealand. For group 2, the following countries were included: Austria, Belgium, France, Germany, Republic of Ireland, Luxemburg, the Netherlands, Switzerland, and Great Britain. For group 3, the transition countries (Kögel, 2004) were included, i.e., former members of the socialist block: Czech Republic, Hungary, Poland, Slovakia, Estonia, Latvia, Lithuania, and Slovenia as the only country from the “other side of the Iron curtain”. The next group are Scandinavian countries: Denmark, Finland, Iceland, Norway, and Sweden are included in group 4. Finally, group 5 includes the Mediterranean countries: Greece, Italy, Portugal, and Spain. The reason for including a variable that controls for the geographical CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 268 After considering the above, the study applied interrupted time series (ITS) analysis. This quasiexperimental design can evaluate an intervention or event using longitudinal data. Furthermore, it will be able to quantify both the immediate and long-lasting effects of the 2008 GFC on TFR. Consequently, ITS analysis does not ignore effects before and after the event of interest, making it the most powerful quasiexperimental approach for assessing the longitudinal effects of some events (Wagner et al., 2002). The results presented in Table 6 show that the immediate effect of the 2008 GFC on TFR was negative and caused a reduction in TFR by 0.026. The long-lasting effect after the GFC prevails over the trend before the GFC because it is larger, and one can conclude that GFC’s long-lasting negative effect reduced the level of TFR recorded before the financial crisis by –0.019. As an illustration of the above, Figure 4 shows countries that had above-average levels of TFR before the 2008 global recession and that TFR has fallen even further without any signs of recovery. Finally, Figure 5 illustrates the evolution of the correlations between TFR and FLFP. It compares the estimated coefficient (β) of the correlation between the total fertility rate and female labour force participation rate across countries (cross-sectional association) and within countries (time-series association) from 2000 to 2020. Estimated coefficients demonstrate clear divergence in trends since 2011, when time-series correlation coefficients changed from positive to negative, while the cross-sectional correlation coefficient remained positive throughout the observed period (Figure 5). 6. Discussion In Table 7, the study juxtaposes the estimation of the correlation coefficients between the TFR and explanatory variables for both models that were utilized. First, by introducing the lag variable for the change in TFR, the study confirmed the conditionality of the current level of TFR on the past values. Consequently, life in a country with a higher level of TFR could have “spillover effects” even among childless women (Behrman & Gonalons-Pons, 2020). Eventually, a positive correlation across countries, captured by unified models, explains higher than average values of TFR in Scandinavian countries until the 2008 GFC and the long-lasting trend of higher values of TFR could explain the smallest negative time-series association that Kögel (2004) stressed for these countries. Figure 5. Cross-sectional and time-series association between total fertility rate and female labour force participation Source: Author’s calculation based on OECD (2022) CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 269 Further, one can notice that the positive effect of FLFP on TFR was captured at 0.05 alpha level only by the unified approach because FE makes the effects of independent variables exclusively within-cluster. Eventually, the cross-sectional association captured by the unified approach, as Oshio (2019) already emphasised, ignores country-specific effects, thus these estimations are biased. Regarding time-series association, based on the results of both previous studies (Kogel, 2004: Oshio, 2019) and the current one, the FE and unified models are shown as the most promising approaches to detecting the true nature of the relationship between TFR and FLFP, and both have suggested an inverse relationship between our variables of interest. Even though neither FE nor unified approaches captured the association between TFR and FLFP within a 95% confidence interval, further dividing the sample from 2000 to 2010 and from 2011 to 2020 reveals the real nature of the relationship. Importantly, it is not that a unified approach is superior to the FE, moreover, the within-effects in the unified model show basically the same results as the FE model, but it has the possibility, by decomposing the effect of FLFP on TFR, to detect the opposite signs in correlation across and within countries. Besides the negative effect of the GFC in 2008 on TFR, results in Table 6 depict how TFR dropped significantly under the level observed before the GFC in many advanced economies, suggesting the negative influence of other factors beyond the GFC. Therefore, a purely economic logic that focuses on financial insecurity cannot solely explain the negative correlation between fertility development and FLFP that the study finds after the 2010s. Consequently, we need to adopt a more inclusive theory that combines additional views beyond the exclusively economical ones (Comolli et al., 2020). Having said that, Vignoli Table 7. Comparison of estimates between models Statistical models Fixed Effects Linear random intercept Variables Coef. SE pBetween/within Coef. SE p TFR(t–1) 0.917 0.018 0.001 TFR (t–1) 0.92 0.018 0.001 FLFP –0.0001 0.001 0.89 FLFP_bw 0.008 0.004 0.05 FLFP_wi –0.0001 0.001 0.87 Share of women (aged 25–64) with tertiary education –0.002 0.0007 0.001 Share with tertiary_bw 0.003 0.003 0.20 Share with tertiary_wi –0.002 0.0007 0.001 Mean age at birth 0.029 0.007 0.001 Mean age at birth_bw –0.009 0.04 0.82 Mean age at birth_wi 0.028 0.007 0.001 Gender wage gap 0.002 0.0008 0.010 Gender wage gap_bw –0.001 0.004 0.70 Gender wage gap_wi 0.002 0.0008 0.01 Expenditure on family in cash 0.026 0.011 0.02 In cash_bw 0.08 0.053 0.12 In cash_wi 0.026 0.011 0.02 Expenditure on family in-kind –0.05 0.018 0.006 In-kind_bw 0.204 0.084 0.01 In-kind_wi –0.051 0.018 0.005 Female part-time employment rate 0.0007 0.001 0.484 Part-time_bw 0.002 0.003 0.34 Part-time_wi 0.0007 0.001 0.48 TFR in 2000 – – – TFR in 2000 0.289 0.129 0.02 “Old” Europe – – – “Old” Europe 0.010 0.075 0.89 Former Socialist block – – – Former Socialist block 0.058 0.123 0.64 Scandinavian – – – Scandinavian –0.097 0.126 0.44 Mediterranean – – – Mediterranean 0.088 0.122 0.47  rho | 0.97102756  rho | 0.8652498 CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 270 and his colleagues (2022) suggested the way in which people build their narratives of the future as a fruitful avenue for understanding the decrease of TFR in the years following the GFC (or Great Recession) in 2008. Arguably, individual decisions regarding fertility are not just the function of one’s past but also of one’s future with all uncertainties based on upcoming imagined scenarios (Vignoli et al., 2022). Hence, the decision to have a child is more complex because it involves not only economic facts but also one’s perception of the future in a national and global context. Eventually, in the context of Nordic countries, cuts in social and family policies during and after the crisis could have a more pronounced effect on fertility reduction because individuals are used to relying on it (Comolli et al., 2020). The next variables are the share of women with tertiary education, mean age at birth, and expenditure on family in cash, effects that were captured by both the models. Again, only a unified model enables an unambiguous interpretation of results, by separating betweenand within-country effects. Regarding the gender wage gap, not only was the positive time association captured by the unified model, but also the FE model captured its effect. Importantly, the former suggested a statistically significant difference between cross-section and time series associations (see Table 3, 3rd column). Consequently, the clarity of the unified model provides more information regarding the effect of the gap in wages between men and women on TFR by offering a fresh avenue for the research by indicating the importance of national context in the relationship, since the within-country coefficient is statistically significant and has the opposite sign from the coefficient across countries. Eventually, the estimated coefficient for the effect of expenditure on family in-kind fully demonstrated the advantage of the unified model. While the FE approach offered a one-sided interpretation of the relationship between TFR and in-kind payments for families, the unified model delivered a more holistic perspective of the nature of the association, subsequently increasing the accuracy of interpretation. In the end, for region-specific effects, the unified model didn’t manage to detect statistically different values of TFR, for the 2000–2020 period, between regions. 7. Conclusion The present paper, besides the inclusion of a wider set of explanatory variables, has also included more recent data (2000−2020) and expanded the sample to 32 OECD countries, in comparison to the previous studies. In line with Kögel (2004), the results confirmed a negative time-series association between female employment and fertility, although not at the conventional 0.05 alpha level. However, the paper verified a negative and statistically significant correlation for the latest period, i.e., 2011–2020. Moreover, it endorsed findings from previous studies regarding the negative effects of the 2008 GFC on the total fertility rate (Sobotka et al., 2011; Camolli, 2017; Camolli et al., 2020). In contrast to this view, Oshio (2019) suggested that if a more recent data set is used, the time series correlation between FLFP and TFR will be positive. If we look back to the past, Rindfuss et al. (2000) discovered that the cross-country association between the TFR and the FLFP in OECD countries (which was negative until 1985) has changed to positive. Correspondingly, by employing the crosssectional association, the paper confirmed a positive cross-sectional association between FLFP and TFR, for the 2000–2020 period, but further offered reasons why positive cross-country association is biased. With the intention of explaining some limitations of the FE method, which was suggested by researchers who are interested in the relationship between TFR and FLFP, the study proposed a unified approach (Bartels, 2009), by retaining the best characteristics of the former method, while proposing a strategy that offers a better interpretation of results. Notably, it provides researchers with the opportunity to be more accurate when interpreting the results of longitudinal data. Eventually, it could have an impact on the policymakers who are considering whether a particular policy should be implemented. In the end, it is important to emphasise some limitations of the study that should be addressed in the future. Primarily, researchers are constrained by data availability, thus using TFR, as Oshio (2019) nicely emphasised, was the second or third best solution due to the lack of data regarding cohort TFR. Also, it was limited only to the OECD countries, so widening our sample beyond the limits of developed countries should be sine qua nonfor subsequent researchers. Importantly, the current study has examined the association within the latest data set, because there is already enough evidence on both the sign and size of the correlation CEEJ • 10(57) • 2023 • pp. 254-274 • ISSN 2543-6821 • DOI: 10.2478/ceej-2023-0015 271 between TFR and FLFP from 1960 until 2000 (Kogel, 2004) and from 1980 to 2017 (Oshio, 2019). Eventually, given the bi-directional relationship between TFR and FLFP (Engelhardt & Prskawetz, 2004; Mishra & Smyth, 2010; Subramaniam et al., 2018), it is inappropriate to draw strong causal inferences at this point. Nonetheless, it is clear that shifting FLFP and change in TFR are closely interrelated. Abbrevations Notation Definitions TFR Total fertility rate FLFP Female labour force participation FE Fixed effects method OECD The organization for economic co-operation and development SE Standard errors S.D. Standard deviations Min Minimum Max Maximum GDP Gross domestic product ITS Interrupted time-series analysis GFC Global financial crises HDI Human development index AUS Australia AUT Austria BEL Belgium CAN Canada CZE Czech Republic DEU Deutschland DNK Denmark ESP Espana EST Estonia FIN Finland FRA France GBR Great Britan GRC Grrecce HUN Hungary IRL Republic of Ireland ISL Iceland ITA Italy JPN Japan KOR Republic of Korea LTU Lithuania LUX Luxemburg LVA Latvia NLD Netherland NOR Norway NZL New Zeland POL Poland PRT Portugal SVK Slovakia SVN Slovenia SWE Sweden SWI Switzerland USA United States of America References Adserà, A. (2004). Changing Fertility Rates in Developed Countries. The Impact of Labor Market Institutions. 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