Policy Research Working Paper 10653 Unraveling the Factors behind Women’s Empowerment in the Labor Market in Colombia Ana María Iregui-Bohórquez Ligia Alba Melo-Becerra María Teresa Ramírez-Giraldo Ana María Tribín-Uribe Héctor M. Zárate-Solano Development Economics Global Indicators Group December 2023 Policy Research Working Paper 10653 Abstract This paper examines the evolution of Colombian wom- patterns. From 1980 to 1995, factors such as diminishing en’s participation in the labor market from 1960 to 2018, fertility, declining infant mortality, and varying economic shedding light on the complex factors that influence their conditions influenced women’s labor involvement. From labor opportunities. The study emphasizes the significance 1995 to 2010, higher education emerged as a key driver, of the historical context in understanding these factors. accompanied by shifting societal norms, and from 2010 This research uncovers nuanced insights using a two-step to 2018, the period witnessed positive contributions from methodology involving principal component analysis and fertility rates, minimum wage, and male labor participation. time-varying effect modeling. The results indicate that This study underscores the intricate relationship between the transition from high to low fertility rates significantly education, demographics, social norms, and economics in influenced female labor participation until the late 1970s. shaping women’s labor force participation, providing valu- Educational advancements, economic growth, and chang- able insights for gender-inclusive policies and promoting ing marital dynamics also played a role in shaping evolving women’s economic empowerment. This paper is a product of the Global Indicators Group, Development Economics. 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 authors may be contacted at atribinuribe@worldbank.org, airegubo@banrep.gov.co, lmelobec@banrep.gov.co, mramirgi@banrep.gov.co, and hzaratso@banrep.gov.co. 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 Unraveling the Factors behind Women's Empowerment in the Labor Market in Colombia♦ Ana María Iregui-Bohórquez ♣ Ligia Alba Melo-Becerra ♣ María Teresa Ramírez-Giraldo ♣ Ana María Tribín-Uribe ♥ Héctor M. Zárate-Solano♣ JEL Classification: C29, J16, N36. Keywords: female labor participation, Time-Varying Effect Modeling, demographic transition, Colombia ♦ We are especially grateful to Juliana Jaramillo-Echeverri and Andrea Otero-Cortés for their comments and suggestions. We also thank Manuela Monterroza-Rubiano who provided excellent research assistance. Project Digna based at Los Andes University supported throughout the development of the paper. The opinions contained in this document are the sole responsibility of the authors and do not commit Banco de la República nor its Board of Directors. E-mail addresses: airegubo@banrep.gov.co (AM Iregui-Bohórquez) (ORCID: 0000-0001-7527-8953), lmelobec@banrep.gov.co (LA Melo-Becerra; corresponding author) (ORCID: 0000-0003-0895-9753), mramirgi@banrep.gov.co (MT Ramírez-Giraldo) (ORCID: 0000-0002-6097-1605), atribinuribe@worldbank.org (AM Tribín-Uribe) (ORCID: 0000-0002-9422-8596), and hzaratso@banrep.gov.co (H Zárate-Solano) (ORCID: 0000-0003-1568-5789). ♣ Unidad de Investigaciones, Banco de la República, Bogotá, Colombia. ♣ Unidad de Investigaciones, Banco de la República, Bogotá, Colombia. ♣ Unidad de Investigaciones, Banco de la República, Bogotá, Colombia. ♥ Senior Economist, World Bank, Washington D.C., USA. ♣ Unidad de Econometría, Banco de la República, Bogotá, Colombia. I. Introduction During the twentieth century, one of the most important achievements for Colombian women was the remarkable increase in their labor force participation, especially during the second half of the century. Women’s participation increased from 18% in 1951 to 26% in 1978, 47% in 1992, 55% in 2000, and 60% in 2018. 1 The upward trend in female labor participation can be attributed to the remarkable advancements in education, fertility, sanitation, civil rights, and political engagement that women experienced during this period. The contribution of married women to the growth of labor participation was a key driving force behind this significant improvement. They seemed to be more responsive to economic cycles and to the legislation introduced in the first half of the twentieth century, which allowed married women to enter the workforce. This paper contributes to identifying the main drivers of women's participation in the labor market since the second half of the 20th century, tracing the transformation of women's roles and opportunities. The changing nature of female labor force participation and its determinants highlights the importance of considering the historical moment and context in which these variables are examined. We present evidence that the effects of these variables have changed over time. To this end, we follow a two-step approach in which, first, we implement a principal component dimension reduction to summarize the whole set of variables (fertility, education, mortality, marriage, labor force participation, violence, female political participation, and some macroeconomic variables) with a few components. Second, we employ the Time-Varying Effect Modeling (TVEM) method to find the dynamic pattern evolution for the coefficients over time under different specifications on the female labor force participation determinants. We use annual aggregate data from 1960 to 2018. The literature on female labor participation, drawing from both cross-country comparisons and individual country analyses, has produced valuable insights. 2 Among OECD countries, several studies have shed light on the determinants of female labor participation, with Cavalcanti and Tavares (2008) highlighting the impact of increased availability and lower prices of domestic appliances, Mishra and Smyth (2010) noting a negative correlation with fertility rates, and Gonzales, Chandra, 1 This trend was interrupted by the Covid-19 pandemic in 2020. Since the beginning of 2022, the participation of women started to recover. For more details, see, for example, García-Rojas, Herrera-Idárraga, Morales, Ramírez-Bustamante, and Tribín-Uribe (2020). 2 Another strand of the literature uses individual datasets from population surveys and censuses. See, for example, Blau and Kahn (2007), Fernández (2013), Gangl and Ziefle (2009), Gasparini and Marchionni (2015, 2017), Goldin (1988, 2006), Goldin and Mitchell (2017), Olivetti (2014). 2 Kochhar, and Newiak (2015) emphasizing the role of education and household size. In the context of G7 nations, Mishra, Nielsen, and Smyth (2010) found that lower fertility rates were linked to higher female labor participation. Additionally, research by Shami, Islam, and Rayhan (2019) explored the influence of gross national income, secondary education enrollment, and fertility rates on female participation in India and neighboring countries. Mammen and Paxson (2000) contributed insights into the U-shaped relationship between income and female labor participation during early development stages. Furthermore, the evolving dynamics in high-income countries have been recently examined by Doepke, Hannusch, Kindermann, and Tertilt (2022), highlighting the growing importance of factors facilitating work-family balance, a notion also emphasized by Goldin (2006). In individual country studies, Junaid et al. (2019) identify factors in Pakistan, such as higher education promoting female labor participation while increased output, number of children, female unemployment, and poverty levels hinder it. In India, Mehrotra and Parida (2017) find higher education and salaries encourage participation in urban areas from 1983 to 2015. In Vietnam, Narayan, Nguyen, and Nghiem (2021) highlight positive effects of economic integration, particularly through trade with high-income countries. For the United States, Eckstein and Lifshitz (2011) discuss the rise in married women's participation, emphasizing education, wages, reduced child-rearing costs, technological advancements, changing social norms, declining fertility rates, and increased divorces during 1962-2004. Extensive research into the determinants of female labor force participation in Colombia has predominantly relied on microdata, offering valuable insights into the intricate factors at play. Noteworthy studies conducted by Angulo and López de Rodríguez (1975), López de Rodríguez and León de Leal (1977), and Vélez and Winter (1992) have underscored the significance of various variables, including marital status, household size, education, and occupation, in explaining female labor participation. A recurring finding across these studies is the inhibitory effect of having young children on women's labor force participation. Further investigations conducted by researchers such as Ribero and Meza (1997), Tenjo and Ribero (1998), and Sánchez and Núñez (2003) have delved into the complex interplay of factors influencing women's labor participation in urban Colombia. These studies have consistently identified education and lower fertility rates as key determinants, while also shedding light on the roles of family unemployment, age, and household dynamics. Moreover, studies focusing on specific demographic 3 groups, including married women and mothers, such as those by Castañeda (1981), Magnac (1992), Arango and Posada (2007), Amador, Bernal, and Peña (2013), González and Daza (2015), and Santamaría and Rojas (2001), have contributed unique perspectives. They have highlighted the positive influence of education on labor participation and the challenges posed by childcare responsibilities and young children. This paper contributes to further our understanding of the drivers behind the behavior of female labor participation in Colombia for almost seventy years. To our knowledge, this is the first paper that uses historical aggregate data for an emerging economy, considering that the relationship between female labor participation and its determinants has changed over time. Moreover, Colombia could serve as an example for promoting the rapid economic empowerment of women through progressive reforms and advancements. The country could provide a reference point for countries currently struggling with low female labor force participation. This study underscores the significance of allowing variables to evolve and recognizing the importance of historical context in shaping women's empowerment. It is important to acknowledge that history cannot be condensed into a single average, as it is through historical analysis that we gain insights into the dynamics and transformations of women's empowerment. The analysis reveals the significance of the demographic transition, educational opportunities, economic conditions, social norms, and key events such as the peace process on female labor participation over time. The findings emphasize the need for policies and interventions that address barriers, promote gender equality, and create inclusive labor markets. By understanding and addressing these drivers, society can foster greater gender equity and unlock the full potential of women as contributors to economic growth and development. The remainder of the paper is organized as follows. Section II describes the data and the empirical strategy used in our analysis. Section III presents the principal component analysis results and the individual variables' effect on the female labor force participation rate in Colombia. Section IV concludes. II. Empirical strategy and data A. Empirical strategy 4 The empirical strategy used in this paper follows a two-step approach. First, we implement a principal component dimension reduction to summarize the data in fewer than the original number of dimensions without losing essential information. Second, we use the Time-Varying Effect Modeling (TVEM) method to find the pattern evolution for the estimated coefficients over time under different specifications, including the principal components and individual variables, on female labor force participation in Colombia. 1. Principal component dimension reduction The exploratory analysis of the dataset relied on a non-supervised dimensional reduction technique known as Principal Components Analysis (PCA), which aims to identify linear combinations of the variables that best explain the data variability. PCA is a statistical technique that explains the matrix of variances and covariances of a set of m variables through a few linear combinations. This transformation converts a set of correlated variables into a set of uncorrelated variables through an orthogonal transformation. The visual inspection of the principal components was done through summary statistics from the covariance matrix via the scree, eigenvalue, and variance plots. These plots provide the distribution of the eigenvalues, which tell us about the decrease in the variance of the scores, and it is useful to determine the optimal number of components representing the data. Additionally, we consider two-dimensional scatterplots of the three principal components to find further patterns in the data. 3 2. Time-Varying Effect Modeling Method In the second stage, we employ a time-varying effect modeling (TVEM) method to analyze Colombia's female labor force participation rate. TVEM is a natural extension of linear regression models, wherein coefficients of variables vary over time. 4 This approach allows us to examine the overall shape and inflection points of each variable's impact on female labor force participation directly from observations. We use a variable-selection method incorporating automated model building and the Least Absolute Shrinkage and Selection Operator (LASSO) methods to determine the most relevant variables. Moreover, our specifications consider the impact of the three principal component scores. 5 3 For an in-depth overview of high-dimensional data analysis, see, for example, Koch (2013). 4 For details see, for example, Prüser and Schlösser (2020) and Lanza and Linden-Carmichael (2021). 5 Hastie, Tibshirani and Friedman (2001) provide details on this issue. 5 Formally, a TVEM is defined as: = 0 () + 1 ()1 + ⋯ + () + (1) where 0 (), 1 (), … , () are unknown dynamic coefficient functions that are assumed to be smooth over time ; 1 , … are the set of selected variables according to the shrinking dimension reduction technique. The inference of the TVEM follows a two-step procedure. First, approximate the function of each coefficient over a small sub-interval with low-order polynomials. Therefore, within each subinterval, the functions are estimated with combinations of spline basis, 6 and estimation of (∙) is made by + 2 + 1 quadratic penalized-spline basis functions, P−splines: 2 0 () = 0 + 1 + 2 + � 2+ ( − )2 =1 (2) () = 0 + 1 + 2 2 + � 2+ ( − )2 =1 Where are the specified inner knots. The coefficients , ( = 0,1, … , + 2) of these truncated power functions represent the number of jumps in the estimation of (∙), which are relevant for the smoothness of the estimated functions. In other words, estimation of ()( = 0,1, … , ) is transferred to the estimation of , , respectively. Second, fit a TVEM by approximating the linear combination of these functions. B. Data In this paper, we use information from a database previously assembled by Iregui-Bohórquez, Melo- Becerra, Ramírez-Giraldo, and Tribín-Uribe (2021), who examine the long-term transformation of the role of women in areas such as employment, education, fertility, and political participation in Colombia from 1905 to 2018. Since our main interest relies on female labor participation, we had to 6 A spline is a segmented function consisting of a polynomial function joined together so that the whole curve and its first and second derivatives are continuous. 6 shorten the period of study, starting in 1960, because the data before that year were scattered and not strictly comparable. 7 The initial selection of variables is taken from the literature on the determinants of the female labor participation rate. We mainly focus on analyzing the relationship between the female participation and fertility rate, education (primary, secondary, and tertiary, for both men and women), infant mortality (total, male and female), maternal mortality, marriage rate, male labor force participation rate, homicide rates (for both men and women), female political participation in both the senate and the chamber of representatives, and some macroeconomic variables such as the real GDP per capita growth and real minimum wage for a total of twenty-two variables. Tables A1.1 and A1.2 in Appendix 1 present the variables used in this paper, their definitions and sources, and their main descriptive statistics, respectively. III. Results In this section, we examine the findings of the principal component analysis and identify the variables that have the most significant impact on the variability of the female labor force participation rate (f_lfp_r). We also evaluate the effect of individual variables on the f_lfp_r in Colombia using the TVEM method. A. Principal Component Analysis In the PCA we set three main component scores to reduce the original process of dimension twenty- two. The results are shown in Figures 1, 2, and 3. In particular, the left panel of Figure 1 shows the size of the eigenvalues on the y-axis against their index on the x-axis. We note that the first eigenvalue is large compared with the second and third ones. Thus, the eigenvalue of the first component is approximately 15.5, while the second and third components have eigenvalues under 2.0. Moreover, the lower curve in the right panel, the contribution in percentage to the total variance, and the upper curve shows the cumulative contribution to the total variance. The largest eigenvalue contributes over 70 per cent of the total variance, and the three principal components account for almost 90% of the total variance. Despite that an elbow at the second eigenvalue is visible, the similar value of the third eigenvalue led to decide that three principal components are required to represent the data. 7 Data on the female labor participation rate from 1960 to 1983 was constructed using census data, and the missing observations were fit by a spline curve to the observed values. 7 Figure 1: Scree plot: selection of the three principal components Source: Own calculations. Next, we present the pattern profile of each component (Figure 2). The first component, which explains approximately 71% of the total variance, is closely related to human capital and demographic change, since education, fertility, life expectancy, and mortality are highly correlated with this component. For example, component one shows a positive correlation with education and a negative correlation with mortality and fertility. The second component, which accounts for 10% of the total variance, is primarily associated with violence, specifically the homicide rate. The third component, explaining 9% of the total variance, is mainly related to male labor force participation and female political participation (see Appendices 2 and 3). Figure 2: Component pattern profiles 8 Source: Authors’ calculations. Figure 3 illustrates how the three principal components have evolved between 1960 and 2018. The first component has shown a consistent upward trend throughout the period, mainly due to improvements in education, increased life expectancy, and reduced fertility and mortality. The second component significantly increased from the mid-1980s until the late 1990s, driven by political and drug violence surges. The third component has presented an upward trend reflecting the rise in women's political participation because of the implementation of significant legislative measures to enhance women's political representation in the country, such as the gender quotas for electoral lists. Figure 3: Evolution of the first three components 6.0 3.0 Percentage points 0.0 -3.0 -6.0 1960 1970 1980 1990 2000 2010 2020 Component 1 Component 2 Component 3 Source: Own calculations. 9 In the next stage, we employ the TVEM method to find the dynamic evolution for the estimated coefficients in a specification with the f_lfp_r as the dependent variable and the first principal component as the explanatory variable (Figure 4). Throughout the entire period, the effect of the so- called human capital and demographic component is positive, albeit decreasing. The beginning of the period showed the highest impact, as the female participation was low. Later, the effect is reduced, though remaining positive, as the f_lfp_r increases. Specifically, the human capital effect remained high during the first decade (1960-1969), with a coefficient of 6.8 percentage points (pp), whereas during the decade (2000-2018), the estimated coefficient was 3.1pp, on average. It is worth noticing that during 1960-1990 the behavior of the component is similar to the evolution of the fertility rate. Figure 4: First principal component 8.0 6.0 Percentage points 4.0 2.0 0.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Component 1 Source: Own calculations. The second component, primarily linked to violence, had a relatively stable impact on the f_lfp_r until the early 1990s, when it began to increase (Figure 5). Between 1960 and 1991, the coefficient averaged 0.7 pp. However, between 1992 and 2018, there was an upward trend with 3.0 pp on average. The results indicate that men were more affected by political and drug-related violence than women, increasing women's participation, as discussed in more detail in the next section. 10 Figure 5: Second principal component 15.0 10.0 Percentage points 5.0 0.0 -5.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Component 2 Source: Own calculations. Regarding the third principal component, mainly associated with the male labor force participation rate (m_lfp_r) and women’s political participation, we observe a substantial initial impact on the f_lfp_r, with an average coefficient of 5.1pp between 1960 and 1977, mainly due to the positive relationship between these two variables, as we will discuss later on (Figure 6). From 1978 to 2005, the effect remained positive but decreased to an average of 4.5pp, indicating a weaker positive relation between these two variables. Female participation continued increasing at a lower rate than men's, but towards the 2000s, it stagnated. However, since the beginning of the 21st century, we have seen a change in the trend of this component’s effect on the f_lfp_r. As discussed below, two important laws were enacted to promote women’s political participation: Law 581 of 2000 and Law 1475 of 2011. Law 581, also known as the “quota law,” stipulated that women must hold 30% of decision-making positions in the public sector. This law has increased employment opportunities for women in the public sector (Pachón and Aroca, 2017; Wills, 2007). Law 1475, on the other hand, mandates that for elections to collegiate bodies, lists with five or more candidates for popularly elected corporations must be composed of at least 30% of one gender. In the case of Parliament, the quota law has risen the number of female candidates and the number of elected women, as highlighted by Iregui-Bohórquez et al. (2021). 11 Figure 6: Third principal component 8.0 6.0 Percentage points 4.0 2.0 0.0 -2.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Component 3 Source: Own calculations. B. Analysis of individual variables on the f_lfp_r In this section, we examine the effect of some individual variables on the f_lfp_r in Colombia using a TVEM method. Their correlation with the principal components dictated the choice of variables. It is worth mentioning that both long and short-run factors can affect female participation in the labor market. In the long run, better education, reduced fertility and infant mortality, changes in women's marriage decisions, and changes in social norms can affect the evolution of female participation. In the short run, the f_lfp_r responds to changes in economic activity. i) Fertility rate Colombia experienced the demographic transition since the end of the 1960s from high fertility rates (6.2 children in 1967) to low fertility rates (1.8 in 2018). The reduction in the fertility rate was mainly the result of greater education for women, access to contraceptive methods, and the decline in infant mortality (Iregui-Bohórquez et al., 2021). Based on the coefficients obtained through the TVEM, our analysis suggests that the relationship between fertility and women's labor participation varied over time from 1960 to 2018 (Figure 7). The results show a strong negative marginal effect from the fertility rate to the female labor participation. During 1960-1969, we observed a strong negative relation between fertility and women's labor participation, signaling that a reduction of one child per woman during this period was associated with an increase of 5.63pp in the f_lfp_r, on average. Therefore, any reduction in fertility rates during this period was crucial for empowering women economically by enabling them to participate more 12 fully in the labor force. Between 1970 and 1979, we observed a weaker negative impact of the labor participation rate, with an estimated coefficient of -4.66pp, suggesting that the negative impact of fertility on labor participation was still present but to a lesser degree than in the previous decade. Between 1980 and 1989, this impact further weakened, with an estimated coefficient of -2.52pp. That way, the impact of fertility on labor participation continued to diminish over time. In Colombia, the negative association between fertility and female labor force participation follows the same pattern found in high-income countries during the 1960s-1980s. This relationship has been explained by the quantity-quality trade-off and the time cost of raising children. It has historically resulted in a strong negative association between female labor force participation and fertility (De la Croix and Doepke, 2003, Galor and Weil, 1996). Figure7: Effect of the fertility rate on the female labor force participation rate 10.0 5.0 Percentage points 0.0 -5.0 -10.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Fertility rate Source: Own calculations. During the first few decades studied, married women and women with children faced significant obstacles to joining the labor market. As a result, any reduction in fertility rates during this period was associated with a larger increase in labor force participation rates for women. From 1960 to 1985, Colombia underwent one of the most rapid declines in fertility worldwide, with the number of children per woman decreasing from 7 to 3 (Jaramillo-Echeverri, 2023; Iregui-Bohórquez, et al., 2021). However, since the 1990s, there has been a marked increase in the labor force participation rates of married women and women with children, reaching between 40% and 50% for this population segment. Therefore, from 1990 to 1999, the coefficient of 1.04pp suggests a positive effect of fertility on labor force participation, within the range of fertility rates observed during this period, as fertility rates were relatively low (with an average of approximately three children per woman). 13 During the 2000-2009 period, a coefficient of 5.20pp suggests a strong positive influence from fertility to the women labor force participation, even as fertility rates continued to decline. Similarly, the robust positive estimated coefficient of 6.63pp during the 2010-2018 period suggests the positive impact has continued to strengthen, despite a recent stagnation and fluctuation in the f_lfp_r and a continued decline in fertility rates (although to a lesser extent than in previous decades). Within the range of fertility rates observed during this period, women with higher fertility rates were even more likely to participate in the labor force than in the previous decade. Our findings are consistent with recent trends in labor force participation rates for women of fertile age. In 1985, these women had a labor force participation rate of 55%, which had increased to approximately 60% by 2018 (Iregui- Bohórquez et al., 2021). This finding suggests that changes in social norms and policies may have contributed to the observed positive association between fertility and labor participation in more recent decades, allowing women with higher fertility rates to participate more fully in the labor market. These changes are important for promoting gender equality, work-life balance, and economic empowerment. As studied by Goldin (2020, 2021), career-family compatibility has recently become a major focus on women who aspire to have a family and a career at the same time. Similar changes in the relationship between fertility and female labor force participation have been observed in high- income countries (Doepke et al., 2022). New theories in the economics of fertility highlight the importance of family policy, cooperative fathers, favorable social norms, and flexible labor markets in enabling women to balance career and family goals and even reversing the female participation- fertility relationship. ii) Female enrollment rate in higher education During the study period, education enrollment increased for both men and women, the gaps in primary and secondary education closed, and there was a rapid increase in female participation in higher education. The country's economic transformation increased the demand for human capital, as did investment in human capital. Concerning higher education, despite the increase in enrollment rates, they continued to be very low for both men and women. The results from the TVEM method indicate that the relationship between female enrollment rate in higher education (f_enrol_h) and f_lfp_r from 1960-2018 has varied over time (Figure 8). The changing nature of this relationship highlights the importance of considering the historical moment and context in which these variables are examined. In the 1960s, when women's participation in university enrollment started to increase, there was a positive relation between these two variables, 14 with an average coefficient of 0.83pp, indicating that as more women pursued higher education during this decade, their participation in the labor force also increased. Figure 8: Effect of the female enrollment rate in tertiary education on the female labor force participation rate 3.0 2.0 Percentage points 1.0 0.0 -1.0 -2.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Female enrollment rate tertiary education Source: Own calculations. In the following years, while female participation continued to increase, women's enrollment in higher education also grew but at a slower pace; thus, the increase in female participation could be attributed to increases in secondary education rather than in higher education, given that there was still room for improvements in the enrollment rate in secondary education. The relationship between higher education and female labor participation could be associated with the low enrollment rates for both men and women, despite the increase in women's enrollment. In fact, in 1985, Colombia's higher education coverage rate (10%) was still much lower than that of other countries, such as Argentina (38%), Chile (14%), Spain (29%), and the United States (64%). Furthermore, the careers that women studied, which according to Vélez and Winter (1992), were oriented towards educational fields that led to low-paying careers, may have harmed their labor force participation. Also, cultural and social norms regarding gender roles and expectations may have affected the relationship between female enrollment in higher education and female labor force participation. Since the mid-1990s, the country started experiencing changes in social norms and economic conditions and increased access to education and employment opportunities for women. From 1995 to 2010, the female enrollment rate in higher education increased from 13.4% to 23.9%, mainly due to the measures established in the 1991 Constitution and Law 30 of 1992, which recognized education as a right and increased the contributions from the national government budget for higher education. 15 The relationship between female enrollment in higher education and female labor force participation was positive, with average coefficients of 0.84pp and 1.01pp, in the 2000s and 2010s, respectively. During the last two decades, women's enrollment rates in higher education increased significantly, from 9% in 1986 to 37% in 2018. It is worth highlighting that since 1990, the women's enrollment rate in higher education exceeded that of men. With respect to women's labor force participation, Colombia experienced a sharp increase, rising from nearly 40% in 1985 to 60% in 2018. The country has the steepest increase in female participation within the region, going from having the lowest female labor participation to having the highest rates in the last three decades (Elías and Ñopo, 2010). This increase in labor force participation during this period was observed for women between 41 to 65 years old, followed by the group of 31 to 41 years old, whose rates passed from 55% and 33%, respectively, in 1985 to 65% and 85% in 2018. These two groups used to have low participation rates, which reflects changes in social norms over time (Iregui-Bohórquez et. al., 2021). Thus, the increase in female labor force participation over the analyzed period follows from a long-term process in which women's education plays a significant role. iii) Infant mortality rate Regarding the relationship between infant mortality and female labor participation, we observe a U- inverted pattern where the regression results change significantly over time (Figure 9). The behavior of the infant mortality rate and the demographic and epidemiological transitions that took place in Colombia are important in explaining the changes in the estimated coefficients. During the 1960s and 1970s, the average coefficient indicated that a 1% decrease in infant mortality led to a 0.75pp increase in female labor force participation. In the following decades, the coefficients suggest a weaker effect of the infant mortality rate on the f_lfp_r. This finding could be attributed to the reduction in infant mortality and improvements in health infrastructure and medical technology, which reduced the time women spent caring for sick children and created better conditions for women to participate in the labor market. 8 By 1985, infant and maternal mortality rates reached their lowest levels, and the decrease in neonatal mortality rates during 1990-2015 contributed to the overall reduction in infant mortality rates. It is worth noting that 8 See Bhalotra, Venkataramani and Walther (2022) for a study about the labor market responses to reductions in infant mortality. 16 improvements in women's education also contributed to reducing child mortality rates and improving their children's education (Iregui-Bohórquez, et al., 2021). Since the late 1990s, the estimated coefficients have decreased, suggesting that the effect of infant mortality on female labor participation is losing importance over time as the infant mortality rate is reduced. Figure 9: Effect of the infant mortality rate on the female labor force participation rate 2.0 1.0 Percentage points 0.0 -1.0 -2.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Infant mortality rate Source: Own calculations. iv) Marriage rate We also consider the changing relationship between the marriage rate (per 100,000 inhabitants) and women's labor participation in Colombia (Figure 10). From 1960-1979, a mild positive correlation was observed between these two variables, suggesting a moderate positive effect of higher marriage rates on labor force involvement from women during this period when marriage was more prevalent. However, a significant shift in this relationship occurred from 1980 to 2009. The coefficient dropped to -0.36pp in the 1980s, deepened to -1.06pp in the 1990s, and settled at -0.42pp in the early 2000s. This negative partial correlation indicates that as the marriage rate decreased, there was a corresponding increase in women's labor participation. According to Valdés and Gomáriz (1993), the proportion of cohabitating couples increased from 8% in 1970 to 13% in 1985. Moreover, Esteve, Saavedra, López-Colás, López-Gay and Lesthaeghe (2016) found that Colombia was a notable example of the surge in unmarried couples choosing to live together. In fact, over the period of 1973 to 2005, the percentage of women aged 25 to 29 who opted for cohabitation rose dramatically from 20% to 66%. This trend towards cohabitation could have contributed to the marginal decrease in marriage rates while enabling women to participate more fully in the labor force. However, the increase in marriage rates since 1990 coincided with the approval of divorce by Law 25 of 1992. As explained by Iregui Bohórquez et al. (2021), before the enactment of this law, many couples chose to 17 establish de facto marital relationships. After its promulgation, some of them decided to formalize their unions. According to Sun and Zhao (2016), in societies where divorce is permitted, couples exhibit distinct behavior, with women having greater power in negotiations, leading to increased autonomy and empowerment, which could lead to greater labor participation for women. Figure 10: Effect of the marriage rate on the female labor force participation rate 6.0 4.0 Percentage points 2.0 0.0 -2.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Marriage rate Source: Own calculations. In contrast with the previous decades, the period from 2010-2018 saw a dramatic shift, with the coefficient surging to 2.84pp. This marked change suggests a significant transformation in the dynamics between marriage rates and women's labor participation. Amador, Bernal, and Peña (2013) noted that this surge in female labor participation was largely driven by the increasing participation rates of married or cohabiting women. v) Male homicide rate During the late 1960s, Colombia experienced a period of social unrest marked by various factors. According to Luna and Villarreal (1994), the political structure of the National Front 9 started showing signs of exhaustion during this time, leading to the emergence of peasant self-defense groups and radicalized urban sectors that eventually transformed into guerrilla organizations. In addition, drug- related violence, starting with the marijuana wars and later evolving into the cocaine wars, became more prominent in the mid-1970s. Furthermore, the 1980s witnessed the emergence of paramilitary groups. Throughout this period, the homicide rate per 100,000 inhabitants fluctuated around 61. 9 The National Front was a political coalition between the conservative and liberal parties between 1958 and 1974 to face a period of violence and partisan retaliation that affected the country. 18 During these years, violence was constantly present and fluctuating, while women experienced increasing economic empowerment and consequently increased their participation in the labor market. It is worth noting that Colombia, one of the longest-standing democracies in Latin America, has a history marked by widespread violence and human rights abuses. Colombia has consistently ranked among the most violent countries in the world. 10 In this context, it is observed that men are generally more prone to acts of violence compared to women. Numerous studies have consistently shown that men commit a higher number of offenses and, as a result, are more likely to experience casualties in situations of internal conflict (Knight, Ponce de Leon, and Tribin, 2021; Smith, 2014; Steffensmeier and Allan, 2005; Buzawa, Buzawa and Stark, 2017). Warfare has been known to impact women's participation in the labor market. For instance, research conducted by Doepke, Hazan, and Maoz (2015) suggests that World War II had a lasting influence on women's employment, leading to a significant increase in women entering the workforce. From 1960 to 1989, the relationship between the male homicide rate and women's labor participation can be negative, small, and sometimes negligible (Figure 11). Between 1960 and 1969, the coefficient of -0.04pp suggests that as the male homicide rate decreased, women's labor participation exhibited a slight tendency to increase. Similarly, in 1970-1979, the coefficient of -0.03pp indicates a continued negative relationship. Moving forward to 1980-1989, the coefficient of 0.00pp suggests no significant relationship between the male homicide rate and women's labor participation. These coefficients highlight the limited impact of changes in the male homicide rate on women's labor participation from 1960 to 1989. During the 1990s and the early 2000s, a positive relationship existed between these two variables. As the violence related to drug trafficking escalated in Colombia, resulting in the murder of many men, women began to enter the labor market at a higher pace (Iregui-Bohórquez et al., 2021). This increase in women's labor participation can be attributed to the need to offset income losses and the demand for women's skills in urban labor markets (Calderón, Gáfaro, and Ibáñez, 2011); hence, their participation showed a slight improvement compared to men. The employment rate also displayed a positive trend, reaching approximately 50% by the end of the period, indicating a modest 10 Data from Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2021. https://ourworldindata.org/homicides. 19 advancement in women's employment opportunities relative to men (Iregui-Bohórquez et al., 2021). In this challenging environment, women played a crucial role in the labor force by reaching new heights of participation and filling the gaps left by men affected by the war. Their increased participation demonstrated their resilience and underscored their contribution to sustaining the workforce during the cycles of violence. Figure 11: Effect of the male homicide rate on the female labor force participation rate 0.2 0.1 Percentage points 0.0 -0.1 1960 1970 1980 1990 2000 2010 2020 Range of variation Male homicide rate Source: Own calculations. It is worth mentioning that at the beginning of the 2000s, the government, in response to the prevailing violence, deployed a strong military presence, although the impact of this militarization was complex and had mixed effects (Castro Torres and Urdinola, 2018). Since 2005, with the “Justice and Peace Program” 11 and later with the initiation of the peace agreement process in 2012, the male homicide rate decreased. There was a significant de-escalation compared to the violence experienced during the 1990s and 2000s. During this period the relationship between the male homicide rate and female labor participation continued to be positive although the confidence intervals widen, indicating increased uncertainty in this relationship. vi) Female political participation Regarding the relationship between women's labor participation and their political participation, the overall findings suggest a complex and nuanced relationship. There are periods of positive and 11 The Justice and Peace Program was established by Law 975 of 2005. This program aimed to incentivize paramilitaries to demobilize and reintegrate into society. This law offered various incentives, including reduced sentences for individuals involved in human rights violations (Tribin, 2015). 20 negative associations, but the influence of political participation on labor participation is relatively small with wide confidence intervals (Figure 12). Figure 12: Effect of female political participation (chamber of representatives) on the female labor force participation rate 0.6 0.4 Percentage points 0.2 0.0 -0.2 -0.4 1960 1970 1980 1990 2000 2010 2020 Range of variation Female political participation Source: Own calculations. In the 1960s and 1970s, the average coefficient was -0.12pp indicating a negative relationship between women's labor and political participation. Women's political involvement during this time primarily consisted of voluntary and community work, lacking meaningful representation and power. Their participation rates remained lower than men's, and their voting rates consistently lagged, possibly influenced by their traditional homemaker roles (Luna and Villarreal, 1994; Pinzón de Lewin and Rothlisberger, 1977). The unstable and fluctuating growth of women's political participation during these years may have contributed to the observed small or negative correlation, as their labor participation was gradually increasing but still relatively low. From 1980-1989, the coefficient of 0.15pp suggests that women's labor participation also exhibited an upward trend as political participation increased. This positive association gains further strength with the coefficient of 0.34pp from 1990-1999, indicating a stronger relationship between the two variables, which coincides with significant developments in legislation and policies promoting gender equality and women's participation in politics. For instance, the Political Constitution of 1991 recognized the equality of men and women and guaranteed the participation of women in politics (Iregui-Bohórquez et al., 2021). 12 Notably, the participation of women in the chamber of representatives saw a significant jump from 4% to 10% between 1989 and 1991. The positive trend 12 For a more detailed explanation of the effects of the Colombian constitution of 1991 on female labor participation, see Galindo-Silva and Herrera-Idárraga (2023). 21 continues from 2000-2009, signifying that higher political participation is accompanied by a notable increase in women's labor participation. The positive correlation between political participation and women's labor participation continued from 2010-2018. This period saw the implementation of significant legislative measures to enhance women's political representation in Colombia. In particular, the introduction of Law 1475 in 2011 established gender quotas for electoral lists, ensuring a minimum level of female representation. This initiative increased the percentage of female candidates and a higher overall presence of women in political bodies. However, it is important to acknowledge that despite these advancements, Colombia still lags behind many other Latin American countries regarding women's representation in parliament (Iregui-Bohórquez et al., 2021). Additionally, although the participation of women in the chambers reached its historical peak during this period, their labor force participation experienced only a modest and relatively stable growth. As a result, the impact of political participation on women's labor participation may not have been as significant during this time. It is commonly anticipated that women's political and labor force participation would mutually reinforce each other. This phenomenon is observed globally, with increased female representation in legislatures paralleling women's rise in the labor force (Iversen and Rosenbluth, 2008). However, in the context of Colombia, this relationship seems to be less pronounced, potentially attributed to the considerable challenges and barriers that women encounter in achieving substantial growth in political participation (Iregui-Bohórquez et al., 2021). vii) Real GDP per capita growth The effect of real GDP per capita growth on the f_lfp_r can be divided into four periods (Figure 13). The first period, from the 1960s to the late 1970s, shows a positive coefficient. A fast and sustained economic growth characterized this period because of rising coffee prices and exports and a shift away from activities in primary sectors such as agriculture and mining towards manufacturing industries, commerce, finance, and services which fostered female participation (Iregui-Bohórquez, et al., 2021). The involvement of women in the labor market began to increase with a lag compared to that of men; female labor participation increased considerably, from 17.3% in 1964 to 30.6% in 1980. During this period, the demographic transition, better access to higher education for women, and changes in social norms also contributed to female labor participation. 22 Figure 13: Effect of real GDP per capita growth on the female labor force participation rate 0.8 0.6 Percentage points 0.4 0.2 0.0 -0.2 1960 1970 1980 1990 2000 2010 2020 Range of variation GDPpc Source: Own calculations. In contrast, the second period, from 1980 to 1995, displays a negative trend. This period includes the economic crises of the early 1980s. According to Magnac (1992), during this crisis, young women withdrew from the labor force but re-entered the market as soon as the crisis was over. It is worth mentioning that according to Tenjo, Álvarez, and Jiménez (2016), the gap between unemployment rates among men and women widens during economic recessions. The third period, between 1996 and 2002, exhibits a change in the trend, compared to the previous period, from negative to positive in the effect of the real GDP per capita growth on the female labor participation, starting in 1996 (Figure 13). This period was characterized by an increase in unemployment and by a dramatic deterioration in economic activity, which worsened in 1998 and 1999 due to the international crisis that deteriorated the country’s terms of trade and reversed capital flows, in a context of economic instability. 13 This economic crisis reduced family income, which led to an increase in the labor supply of some household members to compensate for this loss of income; in particular, the wives who, until then, did not participate in the labor market. This effect is known as the “added worker” effect. 14 The fourth period, from 2003 to 2018, was characterized by continuous economic growth, except for 2008-2009 and 2016-2017 when there was a slowdown in economic activity. The growth during this period was mainly driven by the boom in raw material prices. The impact on the f_lfp_r was positive and increasing, with an average coefficient of 0.29pp. During the first years of this period, 2003- 13 For more details about the crisis of 1999, see Pérez-Reyna (2017). 14 See, for example, López Castaño (2001) and Santamaría and Rojas (2001) for an analysis of the added worker effect during the 1999 economic crisis in Colombia. 23 2009, the effect was positive but small, whereas between 2010 and 2018 the effect was larger. For example, in 2018, a 1% increase in real GDP per capita growth led to a 0.62pp increase in the f_lfp_r (Figure 13). 15 viii) Male labor force participation Men's and women's labor force participation rates have a positive relationship that reflects complementarity in their work (Figure 14). Men have maintained consistently high participation rates of around 73% for decades with minor fluctuations. In comparison, women began with a low participation rate of 18% in the 1960s but increased to 61% in the 2010s (Figure 15), which implies that male participation rates remained high and were not impacted as women began to participate more (Tenjo and Ribero, 1998). Figure 14: Effect of the m_lfp_r on the f_lfp_r 3.0 2.0 Percentage points 1.0 0.0 -1.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Male labor force participation rate Source: Own calculations. The coefficient of 0.50pp in the 1960s suggests a weak positive relationship between men's and women's labor force participation rates. As men's participation rates increased by one percent, women's participation rates increased by only half a percentage point. The scarce participation of women during this period, around 18%, may have contributed to this result. In contrast, the coefficients of 1.29pp and 1.23pp during the 1970s and 1980s suggest a much stronger positive 15 Although our estimations do not cover the period of the Covid-19 pandemic, it is important to mention that the participation of women in the labor market was the most affected by the economic downturn, which is in sharp contrast with previous economic crises where men's employment was more affected. According to García- Rojas et al. (2020), the pandemic expelled women from formal to informal occupations, occupied to unemployed, and unemployed to inactivity; consequently, more women were pushed into domestic work. 24 relationship between the labor force participation rates of men and women. These coefficients imply that women's participation rates increased at a faster rate than men's participation rates. During this period, the participation of women increased sharply, reaching a rate of 39%, while the participation rates of men also recovered from a slowdown the decade before. This trend was especially pronounced among married women, as Iregui-Bohórquez, et al. (2021) noted. In contrast to other countries, an increase in f_lfp_r in Colombia did not reduce m_flp_r, as male participation had also increased. 16 During the 1990s and 2000s, the coefficients of 0.93pp and 0.90pp, respectively, indicate a weaker positive relationship between men's and women's labor force participation rates. Women's participation rates slowly increased during the 1990s but stagnated towards the 2000s, while men maintained high participation rates. Figure 15: Male and female labor force participation rates 1960-2018 (Average seven cities) 90.0 80.0 70.0 60.0 Percentage (%) 50.0 40.0 30.0 20.0 10.0 0.0 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 mlfp flfp Source: Own calculations based on Iregui-Bohórquez et al. (2021). The coefficient of 1.51pp for 2010-2018 indicates a strong positive relationship between men's and women's labor participation rates in recent years. During this period, women's participation reached its highest point of 61%, resulting in a decrease in the gap (15pp), the lowest ever experienced. This positive association between labor force participation for men and women is not only due to having more workers but also because women bring new skills to the workplace. These skills reflect social norms, upbringing, social interactions, risk preferences, and response to incentives. Therefore, 16 See Tenjo and Ribero (1998). 25 bringing women into the labor force adds an economic benefit from the diversity over and above the benefit of simply having more workers (Ostry, Alvarez, Espinoza, and Papageorgiou, 2018). ix) Real minimum wage Overall, the results indicate a positive relationship between the real minimum wage (rminw) and female labor force participation in Colombia from 1960 to 2018, although the effect varies over time with a quadratic trend (Figure 16). In the 1960s, a 1% increase in the real minimum wage led to a 0.20pp increase in female labor force participation. In the 1970s, 1980s, and 1990s, the coefficient increased to 3.13pp, 8.06pp, and 11.76pp, respectively, indicating a much stronger effect of the rminw on female labor force participation. These findings may be attributed to increased women's education access during this period, improved economic growth, and expanded opportunities for women in the labor market. Policy changes to reduce income inequality and promote gender equality have also contributed to this higher effect. In the 2000s, the coefficient remained high, although with wide confidence intervals, at 11.01pp, but decreased to 3.36pp in the 2010s, which could be linked to changes in economic policies and labor market conditions. Another factor to consider is the role of women in balancing work and family responsibilities, which could have affected their labor force participation in recent years. Figure 16: Effect of the real minimum wage on the female labor force participation rate 20.0 10.0 Percentage points 0.0 -10.0 -20.0 1960 1970 1980 1990 2000 2010 2020 Range of variation Minimum wage Source: Own calculations. The relationship between the minimum wage and female labor force participation can be influenced by the difference in reservation wages between women and men and by the presence of children and 26 dependents in the family. Some studies have shown that the opportunity cost of accepting a job is higher for women with children and that women's reservation wage tends to be higher than men's (Brown, Roberts and Taylor, 2011; Gronau, 1973). However, in middle-income countries like Colombia, nowadays the presence of children may incentivize women to work, reducing their reservation wage for finding a job. According to a recent study by Flórez, Melo-Becerra and Posada (2021), the reservation wage in Colombia is generally higher for men than women. Individuals with children reported a lower reservation wage than those without children. This study also suggests that other factors, such as job flexibility and the accessibility and affordability of public childcare services, may reduce the gender reservation wage gap in Colombia compared to developed countries where such services are less available and more expensive. Flórez et al. (2021) also raise awareness of the impact that the earlier retirement age of women (age 57) compared to men (age 62) can have on their lower reservation wages. As a result, women may be willing to lower their reservation wage to secure a job and receive a future retirement pension. IV. Conclusions This research paper adds to the understanding of the key factors influencing women's engagement in the labor market from 1960 to 2018, shedding light on the evolution of women's roles and opportunities. By examining the shifting dynamics of female labor force participation and the factors driving it, we emphasize the significance of considering the historical period and context in which these variables are analyzed. Our findings show that the impacts of these variables have changed over time. One of the most important transformations affecting female labor force participation since the end of the 1960s was the demographic transition. This transition mainly resulted from decreasing infant mortality, access to contraceptive methods, and greater education access for women. From 1960 to the late 1970s, lower fertility and infant mortality rates were associated with increased female labor participation in Colombia. Education, marriage rates, and economic growth also played roles. A higher real minimum wage positively influenced participation. Between 1980 and 1995, the impact of fertility and infant mortality rates diminished. Economic crises temporarily affected participation, but women re-entered the labor market afterward. Drug-related violence and gender equality policies also influenced participation. In the 1980s, men and women's labor participation showed a stronger positive correlation but weakened in the early 1990s. The real minimum wage continued to impact female participation. From 1995 to 2010, higher education, changing gender norms, and economic growth drove increased female labor participation. Marriage rates, male 27 homicides, and economic conditions also played roles. In the 2010-2018 decade, low fertility rates, a rising real minimum wage, and stable male labor force participation positively impacted female participation. This period saw women's labor force participation reach its peak, reflecting shifting societal norms and economic conditions. Overall, this study underscores the significance of educational opportunities, demographic transition, changes in social norms, and economic factors in understanding the determinants of female labor force participation during the examined period. Policy makers and stakeholders should consider these findings to develop strategies that promote gender equality, create inclusive labor markets, and empower women to participate fully in the workforce. By recognizing and addressing the factors that influence women's labor force participation, society can foster greater gender equity and harness the untapped potential of women as contributors to economic growth and development. 28 Referencias Amador, D., Bernal, R., and Peña, X. (2013). The rise in female participation in Colombia: Fertility, marital status, or education? Ensayos sobre política económica, Vol. 31, No. 71, pp. 54-63. Angulo, A., and López de Rodríguez, C. (1975). Female participation in economic activity in Colombia. Population and Employment, Working Paper No. 9, World Employment Programme, Population and Employment Project, International Labour Organisation, Geneva. Arango, L.E., and Posada, C.E. (2007). Labor Participation of Married Women in Colombia. Revista Desarrollo y Sociedad, second semester, pp. 93-126. Sonia R. Bhalotra, S.R.; Venkataramani, A.; and Walther, S. (2022). Fertility and labor market responses to reductions in mortality. NBER Working Paper 30316. http://www.nber.org/papers/w30316 Blau, F., and Kahn, L. (2007). Changes in the Labor Supply Behavior of Married Women: 1980- 2000. Journal of Labor Economics, Vol. 25, No. 3 (July 2007), pp. 393-438. Brown S., Roberts J., and Taylor K. (2011) The gender reservation wage gap: Evidence from British panel data. Economics Letters, Vol. 113, No. 1, pp. 88-91. Buzawa, E.S., Buzawa, C.G., and Stark, E. (2017). Responding to domestic violence: The integration of criminal justice and human services (5th ed.). Los Angeles, SAGE. Calderón, V., Gáfaro, M., and Ibáñez, A. M. (2011). Desplazamiento forzoso, participación laboral femenina y poder de negociación en el hogar: ¿Empodera el conflicto a las mujeres? Documentos CEDE 009252, Universidad de los Andes – CEDE Castañeda, T. (1981). La participación de las madres en el mercado de trabajo urbano en Colombia. Revista Desarrollo y Sociedad, No. 6 (July), pp. 363-377. Castro Torres, A.F., Urdinola, B.P. (2019). Armed Conflict and Fertility in Colombia, 2000–2010. Population Research and Policy Review 38, pp. 173–213. https://doi.org/10.1007/s11113-018-9489- x. Cavalcanti, T., and Tavares, J. (2008). Assessing the "Engines of Liberation": Home Appliances and Female Labor Force Participation. The Review of Economics and Statistics, Vol. 90, No. 1, pp. 81- 88. De la Croix, D., and Doepke M, (2003). “Inequality and Growth: Why Differential Fertility Matters.” The American Economic Review, Vol. 93, No. 4, pp.1091-113. Doepke, M., Hannusch, A., Kindermann, F., and Tertilt, M. (2022). “The Economics of Fertility: A New Era”. NBER Working Paper No. 29948. 29 Doepke, M., Hazan, M., and Maoz, Y. D. (2015). The baby boom and World War II: A macroeconomic analysis. The Review of Economic Studies, Vol. 82, No, 3, pp. 1031-1073. Eckstein, Z., and Lifshitz, O. (2011). “Dynamic Female Labor Supply”, Econometrica, Vol. 79, No. 6, pp. 1675-1726. Elias, J.; and Ñopo, H. (2010). “The Increase in Female Labor Force Participation in Latin America 1990-2004: Decomposing the Changes” (mimeo), Inter-American Development Bank, Washington, D. C. Esteve, A.; Saavedra, A.C.; López-Colás, J.; López-Gay, A.; and Lesthaeghe, R.J. (2016). The Boom of Cohabitation in Colombia and in the Andean Region: Social and Spatial Patterns. In: Esteve, A., Lesthaeghe, R. (eds) Cohabitation and Marriage in the Americas: Geo-historical Legacies and New Trends. Springer, Cham. https://doi.org/10.1007/978-3-319-31442-6_7 Fernández, R. (2013). Cultural Change as Learning: The Evolution of Female Labor Force Participation over a Century. The American Economic Review, Vol. 103, No. 1, pp. 472-500. Flórez, L.A.; Melo-Becerra, L.A.; and Posada, C.E. (2021). "Estimating the reservation wage across city groups in Colombia: A stochastic frontier approach," Borradores de Economía 1163, Banco de la República de Colombia. Flórez, CE. (2000). Las transformaciones sociodemográficas en Colombia durante el siglo XX. Bogotá: Banco de la República y Tercer Mundo Editores. Galindo-Silva, H. and Herrera-Idárraga, P. (2023). Culture, Gender, and Labor Force Participation: Evidence from Colombia. arXiv:2307.08869v1 [econ.GN] https://doi.org/10.48550/arXiv.2307.08869. Galor, O., and Weil D. N. (1996). The Gender Gap, Fertility, and Growth. The American Economic Review, Vol. 86, No.3, pp. 374-387. Gangl, M., and Ziefle, A. (2009). Motherhood, Labor Force Behavior, and Women's Careers: An Empirical Assessment of the Wage Penalty for Motherhood in Britain, Germany, and the United States. Demography, Vol. 46, No. 2, pp. 341-369. García-Rojas, K., Herrera-Idárraga, P., Morales, L., Ramírez-Bustamante, N., and Tribín-Uribe, A.M. (2020). (She)cession: The Colombian female staircase fall. Borradores de Economia No. 1140, Banco de la República de Colombia. Gasparini, L., and Marchionni, M. (2017). Deceleration in Female Labor Force Participation in Latin America. Economía, Vol. 18, No. 1, pp. 197-224. 30 Gasparini, L., and Marchionni, M. (editors). (2015). Bridging gender gaps? The rise and deceleration of female labor force participation in Latin America. CEDLAS Center for Distributive, Labor and Social Studies, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, First edition, La Plata. PDF eBook ISBN: 978-950-34-1287-9. Goldin, C. (1988). Marriage Bars: Discrimination against Married Women Workers, 1920's to 1950's, NBER, Working Paper No. 2747. Goldin, C. (2006). The quiet revolution that transformed women's employment, education,and family. The American Economic Review, Vol. 96, No. 2, pp. 1-21. Goldin, C. (2014). “A Grand Gender Convergence: Its Last Chapter.” The American Economic Review, Vol. 104, No. 4, pp. 1091-1119. Goldin, C. (2020). Journey across a Century of Women. The 2020 Martin S. Feldstein Lecture. NBER Reporter, No. 3. Goldin, C. (2021). Career and Family: Women’s Century-Long Journey Towards Equity. Princeton: Princeton University Press. Goldin, C. and Mitchell, J. (2017). The New Life Cycle of Women’s Employment: Disappearing Humps, Sagging Middles, Expanding Tops. Journal of Economic Perspectives, Vol. 31, No. 1, pp. 161-182. Gonzales, C.; Chandra, S. J.; Kochhar, K., and Newiak, M. (2015). “Fair Play: More Equal Laws Boost Female Labor Force Participation”, IMF Staff Discussion Notes 2015/002, International Monetary Fund. Gonzalez, N.I., and Daza, N.A. (2015). Determinantes y perfiles de la participación laboral en Colombia en el periodo 2002-2013. Revista de Economía del Rosario, Vol. 18, No. 1, January-June, pp. 5-59. Gronau R. (1973) The intrafamily allocation of time: The value of the housewives' time. The American Economic Review, Vol. 63, No. 4, pp. 634-651. Hastie, T., Tibshirani, R., and Friedman, J. (2001). The Elements of Statistical Learning, New York: Springer Verlag, Inc. Iregui-Bohórquez, A. M., Melo-Becerra, L. A., Ramírez-Giraldo, M. T., and Tribín-Uribe, A. M. (2021). El camino hacia la igualdad de género en Colombia: Todavía hay mucho por hacer. Banco de la República, Bogotá. 31 Iversen, T. and Rosenbluth, F. (2008). Work and Power: The Connection between Female Labor Force Participation and Female Political Representation. Annual Review of Political Science, Vol. 11, No. 1, pp. 479-495. Jaramillo-Echeverri, J. (2023) Fertility, education, and social mobility in 20th century Colombia. PhD thesis, London School of Economics and Political Science. Jaramillo-Echeverri, J.; Meisel-Roca, A.; and Ramírez-Giraldo, M.T. (2019). More than one hundred years of improvements in living standards: The case of Colombia, Cliometrica, vol. 13, No. 3, pp. 323-366. Junaid, N., Sultana, N., Jabeen, S., and Ali, J. (2019). “Determinants of Female Labour Force Participation Rate in Pakistan”, Dialogue, Vol. 14, No. 2, pp. 218-228. Knight, B. G., and Ponce de Leon, M.M., and Tribin, A. (2021). "Crime and Gender Segregation: Evidence from the Bogota "Pico y Genero" Lockdown," NBER Working Papers 28686, National Bureau of Economic Research, Inc. Koch, I. (2013). Analysis of Multivariate and High-Dimensional Data (Cambridge Series in Statistical and Probabilistic Mathematics). Cambridge: Cambridge University Press. Lanza, S.T. and Linden-Carmichael, A.N. (2021). A Conceptual Introduction to Time-Varying Effect Modeling. In: Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-70944-0_1 López de Rodríguez, C., and León de Leal, M. (1977). “El trabajo de la mujer”. In M. León de Leal (Research director), La mujer y el desarrollo en Colombia, Asociación Colombiana para el Estudio de la Población (ACEP), Bogotá. López Castaño, H. (2001). Características y determinantes de la oferta laboral colombiana y su relación con la dinámica del desempleo. Consideraciones teóricas y de política. In Urrutia Montoya, M, (ed.) Empleo y Economía, Memorias del Seminario, Banco de la República, Bogotá. Luna, L.G. and Villarreal, N. (1994). Historia, género y política: Movimiento de mujeres y participación política en Colombia 1930-1991. Edición del Seminario Interdisciplinar Mujeres y Sociedad, Barcelona. Taken from: http://www.ub.edu/SIMS/libros4.html. Accessed on 4 May 2020. Magnac, T. (1992). Female labor market participation and wages in Colombia. In: G. Psacharopoulos and Z. Tzannatos (Editors), Case studies on women's employment and pay in Latin America, The World Bank, Waskington, D.C, pp. 169-195. Mammen, K., and Paxson, C. (2000). “Women’s Work and Economic Development” Journal of Economic Perspectives, Vol. 14, No. 4, pp. 141-164. 32 Mehrotra, S., and Parida, J. K. (2017). “Why is the LFP of women declining in India?” World Development, Vol. 98, No. C, pp. 360-380. Mishra, V; Nielsen, I., and Smyth, R. (2010). “On the relationship between female labour force participation and fertility in G7 countries: evidence from panel cointegration and Granger causality”, Empirical Economics, Vol. 38, No.2, pp. 361-372. Mishra, V., and Smyth, R. (2010). “Female labor force participation and total fertility rates in the OECD: New evidence from panel cointegration and Granger causality testing”, Journal of Economics and Business, Vol. 62, No. 1, pp. 48-64. Narayan, S., Nguyen, T., and Nghiem, X. (2021). Does Economic Integration Increase Female Labour Force Participation? Some New Evidence from Vietnam. Bulletin of Monetary Economics and Banking, Vol. 24, No. 1, pp. 1-34. Olivetti, C. (2014). "The Female Labor Force and Long-Run Development: The American Experience in Comparative Perspective," NBER Chapters, in: Human Capital in History: The American Record, pp. 161-197, National Bureau of Economic Research, Inc. Ostry, J.D., Alvarez, J. A., Espinoza, R. A., and Papageorgiou, C. (2018). "Economic Gains from Gender Inclusion: New Mechanisms, New Evidence," IMF Staff Discussion Notes 2018/006, International Monetary Fund. Pachón, M. and Aroca, M. (2017). “Effects of Institutional Reforms on Women’s Representation in Colombia, 1960-2014”, Latin American Politics and Society, Vol. 59, No. 2, pp. 103-121. Pérez-Reyna, D. (2017). Historia del Banco de la República. Crisis de 1999. In Uribe, J.D. (ed.) Historia del Banco de la República, 1923-2015. Banco de la República, Bogotá. Pinzón de Lewin, P. and Rothlisberger, D. (1977). Participación política de la mujer. En M. León de Leal (Research director), La mujer y el desarrollo en Colombia, Asociación Colombiana para el Estudio de la Población (ACEP), p. 38-64. Taken from: http://bdigital.unal.edu.co/41976/. Accessed on 15 May 2020. Prüser, J. and Schlösser, A. (2020). On the Time-Varying Effects of Economic Policy Uncertainty on the US Economy. Oxford Bulletin of Economics and Statistics. Vol. 82, pp. 1217-1237. https://doi.org/10.1111/obes.12380 Ribero, R., and Meza, C. (1997). Determinantes de la participación laboral de hombres y mujeres en Colombia: 1976-1995. Documento No. 063, Archivos de Macroeconomía, Departamento Nacional de Planeación, Bogotá. Romero-Prieto, J., and Meisel-Roca, A. (2019). Análisis demográfico de la Violencia en Colombia. Cuadernos de Historia Económica, No. 50, Banco de la República. 33 Sánchez, F., and Núñez, J. (2003). A dynamic analysis of human capital, female work-participation, returns to education and changes in household structure in urban Colombia, 1976-1998. Colombian Economic Journal, Vol. 1, No.1, pp. 110-149. Santamaría, M., and Rojas, N. (2001) La participación laboral: ¿qué ha pasado y qué podemos esperar? Planeación y Desarrollo, Vol. 32, No. 1, pp. 5-34. Shami, A.H.M.S., Islam, T., and Rayhan, I. (2019). "Investigating the Macroeconomic Factors That Determine a Female Worker to Participate in the Labor Force: Evidence from the South Asian Countries," Journal of Business, Vol. 4, No. 2, pp. 12-18. Smith G. (2014), Long-Term Trends in Female and Male Involvement in Crime, in R. Gartner and B. McCarhty (eds.). The Oxford Handbook of Gender, Sex, and Crime, pp. 139–57. Oxford University Press. Steffensmeier, D., and Allan, E. (1996). Gender and crime: Toward a gendered theory of female offending. Annual Review of Sociology, Vol. 22, No. 1, pp. 459-487. Sun, A. and Zhao, Y. (2016). Divorce, Abortion and Children's Sex Ratio: The Impact of Divorce Reform in China. Journal of Development Economics, Vol. 120, pp. 53-69. https://doi.org/10.1016/j.jdeveco.2015.11.006 Tenjo, J.; Álvarez, O.; and Jiménez, M. C. (2016). “Diferencias en las tasas de desempleo por género”, en L. E. Arango, F. Castellani y E. Lora (eds.), Desempleo femenino en Colombia, Bogotá: Banco Interamericano de Desarrollo y Banco de la República Tenjo, J., and Ribero, R. (1998). Participación, desempleo y mercados laborales en Colombia. Documento No. 081, Archivos de Macroeconomía, Departamento Nacional de Planeación, Bogotá. Tribín, A.M. "Paramilitaries and Electoral Support" Peace Economics, Peace Science and Public Policy, vol. 21, no. 2, 2015, pp. 191-216. https://doi.org/10.1515/peps-2014-0050 Valdés, T. and Gomáriz, E. (1993). Mujeres latinoamericanas en cifras: Colombia. Instituto de la Mujer, Ministerio de Asuntos Sociales de España y Facultad Latinoamericana de Ciencias Sociales (FLACSO), Santiago de Chile. Velez, E., and Winter, C. (1992). Women’s labor force participation and earnings in Colombia. In G. Psacharopoulos and Z. Tzannatos (Eds.), Case studies on women's employment and pay in Latin America, The World Bank, Washington, D.C., pp. 197-207. Wills, M. E. (2007). Inclusión sin representación: la irrupción política de las mujeres en Colombia (1970-2000), Bogotá: Norma. 34 Appendix 1 Table A1.1 Definitions, abbreviations, and sources of the variables Variables Abbreviations Definition Source Labor force participation rate (Males) m_lfp_r It is the percentage relationship Censuses and Household surveys between the economically active (DANE), average seven cities population (PEA) and the working-age population (PET), % Labor force participation rate (Females) f_lfp_r It is the percentage relationship Censuses and Household surveys between the economically active (DANE), average seven cities population (PEA) and the working-age population (PET), % Life expectancy at birth (Females) f_life_exp Life expectancy at birth indicates Flórez, CE. (2000), DANE vital the number of years a newborn statistics, United Nations World would live if the mortality Population Prospects, and the patterns at birth remained the World Bank (2016 - 2018) same throughout their lives Life expectancy at birth (Males) m_life_exp Life expectancy at birth indicates Flórez, CE. (2000), DANE vital the number of years a newborn statistics, United Nations World would live if the mortality Population Prospects, and the patterns at birth remained the World Bank (2016 - 2018) same throughout their lives Infant mortality rate inf_mort_r Infant mortality is the number of Flórez, CE. (2000), DANE vital children who die before their first statistics, the UN Inter-agency birthday per 1,000 live births per group for child mortality estimation year (UNICEF, WHO, World Bank, UN DESA Population Division) at childmortality.org Infant mortality rate (Males) m_inf_mort_r Infant mortality is the number of Flórez, CE. (2000), DANE vital children who die before their first statistics, the UN Inter-agency birthday per 1,000 live births per group for child mortality estimation year (UNICEF, WHO, World Bank, UN DESA Population Division) at childmortality.org 35 Table A1.1 (Cont.) Definitions, abbreviations, and sources of the variables Variables Abbreviations Definition Source Infant mortality rate (Females) f_inf_mort_r Infant mortality is the number Flórez, CE. (2000), DANE of children who die before their vital statistics, the UN Inter- first birthday per 1,000 live agency group for child births per year mortality estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at childmortality.org Maternal mortality rate mat_mort_r Number of maternal deaths per Iregui-Bohórquez et al. 100,000 live births (2021) Fertility rate fert_r The total fertility rate represents Flórez, CE. (2000), page 17, the number of children a Table 2,1 woman would have if she lived to the end of her childbearing years and had children according to age-specific fertility rates for the specified year Marriage rate mar_r Demographic indicator that DANE, Anuario General de indicates the number of Estadística, and United marriages per 1,000 (thousand) Nations Demographic inhabitants. Yearbook; authors’ calculations Gross enrollment rate primary education (Males) m_enrol_p The gross coverage rate in Jaramillo-Echeverri, Meisel- primary education is the ratio Roca y Ramírez-Giraldo between students (men) (2019), and Ministerio de enrolled and the projected Educación Nacional (MEN) population between 7 and 11 years of age, % 36 Table A1.1 (Cont.) Definitions, abbreviations, and sources of the variables Variables Abbreviations Definition Source Gross enrollment rate primary education (Females) f_enrol_p The gross coverage rate in primary Jaramillo-Echeverri, education is the ratio between students Meisel-Roca y Ramírez- (women) enrolled and the projected Giraldo (2019), and population between 7 and 11 years of age, Ministerio de Educación % Nacional (MEN) Gross enrollment rate secondary education (Males) m_enrol_s The gross coverage rate in secondary Jaramillo-Echeverri, education is the ratio between students Meisel-Roca y Ramírez- (men) enrolled and the projected population Giraldo (2019, database) between 12 and 17 years of age, % Gross enrollment rate secondary education (Females) f_enrol_s The gross coverage rate in secondary Jaramillo-Echeverri, education is the ratio between students Meisel-Roca y Ramírez- (women) enrolled and the projected Giraldo (2019, database) population between 12 and 17 years of age, % Gross enrollment rate higher education (Males) m_enrol_h The gross coverage rate in higher education Jaramillo-Echeverri, is the relationship between students (men) Meisel-Roca y Ramírez- enrolled at the undergraduate level Giraldo (2019), and (university) and the projected population Ministerio de Educación between 17 and 21, % Nacional (MEN) The enrollment data corresponds to that reported by higher education institutions for the first semester of the reference year Gross enrollment rate higher education (Females) f_enrol_h The gross coverage rate in higher education Jaramillo-Echeverri, is the relationship between students Meisel-Roca y Ramírez- (women) enrolled at the undergraduate Giraldo (2019), and level (university) and the projected Ministerio de Educación population between 17 and 21, % Nacional (MEN) The enrollment data corresponds to that reported by higher education institutions for the first semester of the reference year 37 Table A1.1 (Cont.) Definitions, abbreviations, and sources of the variables Variables Abbreviations Definition Source Homicide rate (Males) m_hom_r Number of homicides (men) per 100,000 Revista Criminalidad (Polícia Nacional, individuals https://www.policia.gov.co/revista- criminalidad/editorial?page=2), Romero-Prieto and Meisel-Roca (2019), and Forensis (Medicina Legal, https://www.medicinalegal.gov.co/cifras- estadisticas/forensis) Homicide rate (Females) f_hom_r Number of homicides (women) per Revista Criminalidad (Polícia Nacional, 100,000 individuals https://www.policia.gov.co/revista- criminalidad/editorial?page=2), Romero-Prieto and Meisel-Roca (2019), and Forensis (Medicina Legal, https://www.medicinalegal.gov.co/cifras- estadisticas/forensis) Chamber of representatives (Females) f_chamber Women in the Colombian House of Parline database on national parliaments Representatives is calculated by dividing (https://data.ipu.org) the current number of women by the total current number of members, % Senate (Females) f_senate Women in the Colombian Senate is Parline database on national parliaments calculated by dividing the current number (https://data.ipu.org) of women by the current total number of members in the Senate, % Real minimum wage Rminw The minimum wage in Colombia The real minimum wage was assembled using corresponds to the current legal monthly National Government decrees, information from minimum wage (SMMLV), which is set the Ministry of Labor, and Banco de la for periods of one year, and its payment República. periodicity is monthly. expressed in Colombian pesos of 2018 Real GDP pc growth rgdppc_g GDP per capita is the gross domestic Banco de la República (Greco) and DANE product divided by the population at mid- year, expressed in Colombian pesos of 2015. Then we take logs and the first difference. 38 Table A1.2 Descriptive statistics 1960-2018 Standard Variables Abbreviations Average Minimum Maximum deviation Labor force participation rate (Males) m_lfp_r 73,97 2,00 67,90 79,70 Labor force participation rate (Females) f_lfp_r 49,02 11,89 17,30 61,83 Life expectancy at birth (Females) f_life_exp 67,22 10,11 46,00 79,86 Life expectancy at birth (Males) m_life_exp 61,26 9,28 41,90 74,33 Infant mortality rate inf_mort_r 54,40 34,95 12,20 126,43 Infant mortality rate (Males) m_inf_mort_r 60,44 39,76 11,84 143,51 Infant mortality rate (Females) f_inf_mort_r 47,79 30,82 9,53 109,34 Maternal mortality rate mat_mort_r 135,80 112,97 25,96 412,57 Fertility rate fert_r 4,05 1,86 1,81 6,78 Marriage rate mar_r 3,60 1,35 1,07 5,82 Gross enrollment rate primary education (Males) m_enrol_p 101,01 19,83 53,31 125,29 Gross enrollment rate primary education (Females) f_enrol_p 95,72 18,52 50,57 117,39 Gross enrollment rate secondary education (Males) m_enrol_s 46,40 30,22 5,49 99,49 Gross enrollment rate secondary education (Females) f_enrol_s 50,02 34,17 4,19 108,44 Gross enrollment rate higher education (Males) m_enrol_h 11,63 7,37 1,68 30,02 Gross enrollment rate higher education (Females) f_enrol_h 11,10 10,31 0,22 37,24 Homicide rate (Males,) m_hom_r 79,64 36,02 37,45 169,11 Homicide rate (Females) f_hom_r 6,98 2,75 3,53 14,05 Chamber of representatives (Females) f_chamber 8,30 4,65 2,74 19,88 Senate (Females) f_senate 7,15 6,53 0,88 25,38 Real minimum wage rminw 530.563 144.249 200.000 781.242 Real GDP pc growth rgdppc_g 9.182.336 3.669.089 4.363.586 17.188.519 Source: Authors’ calculations. 39 Appendix 2 Figure 2.1: Component pattern 40 Source: Own calculations 41 Appendix 3 Table A3.1 Correlation between each variable and its component Variable Abbreviation PC1 PC2 PC3 Life expectancy at birth (Females) f_life_exp 0.25 0.03 -0.04 Life expectancy at birth (Males) m_life_exp 0.25 -0.04 -0.03 Infant mortality rate inf_mort_r -0.25 0.00 0.08 Infant mortality rate (Males) m_inf_mort_r -0.25 0.01 0.08 Infant mortality rate (Females) f_inf_mort_r -0.25 -0.01 0.06 Fertility rate fert_r -0.25 -0.07 0.02 Labor force participation rate (Males) m_lfp_r -0.03 0.40 0.53 Gross enrollment rate primary education (Males) m_enrol_p 0.22 -0.09 -0.29 Gross enrollment rate primary education (Females) f_enrol_p 0.21 -0.09 -0.36 Gross enrollment rate secondary education (Males) m_enrol_s 0.24 -0.01 0.17 Gross enrollment rate secondary education (Females) f_enrol_s 0.24 0.01 0.16 Gross enrollment rate higher education (Males) m_enrol_h 0.23 -0.15 0.20 Gross enrollment rate higher education (Females) f_enrol_h 0.23 -0.03 0.30 Marriage rate mar_r -0.21 0.12 0.02 Maternal mortality rate mat_mort_r -0.24 -0.05 0.12 Chamber of representatives (Females) f_chamber 0.22 0.05 0.23 Senate (Females) f_senate 0.21 0.01 0.37 Homicide rate (Males,) m_hom_r 0.09 0.58 -0.24 Homicide rate (Females) f_hom_r 0.06 0.61 -0.19 Real minimum wage rminw 0.20 -0.06 -0.02 Real GDP pc growth rgdppc_g 0.01 -0.26 -0.06 Source: Own calculations. Note: PC corresponds to principal component. 42