Women at Work: Unveiling the Impact of FLFPR and Adolescent Fertility on India's Economic Landscape

doi:10.21203/rs.3.rs-4878773/v1

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Women at Work: Unveiling the Impact of FLFPR and Adolescent Fertility on India's Economic Landscape

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This paper explores the relationship between female labour force participation (FLFPR), adolescent fertility rates, and economic development in India from 2012 to 2022. Drawing on regression analysis and secondary data sources, including the World Bank and the International Labour Organisation, the study investigates the impact of FLFPR, normalised weight (FGERSE), and adolescent fertility rates on GDP per capita. Results indicate a strong positive correlation between FLFPR and GDP per capita, highlighting the significant role of women in driving economic growth. Conversely, adolescent fertility rates exhibit a negative correlation with GDP per capita, emphasising the need for policies to address reproductive health outcomes. The findings underscore the importance of promoting gender inclusivity education to foster sustainable economic development and gender equality in India.

Gender Studies

Development Economics

Female Labour Force Participation

Adolescent Fertility

Economic Development

India

Gender Inclusivity

Regression Analysis

GDP per Capita

The economy of a country, encompassing the production, distribution, and consumption of goods and services across various sectors, is intricately linked with labour dynamics. Labour serves as a fundamental component in each sector, from agricultural production and industrial manufacturing to service delivery and financial transactions. The interactions between labour, businesses, and government entities not only drive economic productivity but also determine employment opportunities, wage levels, and overall economic stability (Forgha & Mbella, 2016) .

For example, in agriculture, labor is crucial for planting, harvesting, and processing crops, directly impacting food production and rural employment. In the industrial sector, skilled labour drives innovation and manufacturing efficiency, contributing to technological advancement and export competitiveness. Meanwhile, the services sector heavily relies on labour to deliver essential services like education, healthcare, and banking, which are vital for societal well-being and economic growth(Cai, 2010). Adequate labour supply, along with efficient utilization of labour, is essential for enhancing productivity and fostering economic prosperity. Moreover, labour markets influence wage levels, income distribution and social mobility within a society (Role_of_Labour_in_India_Development, 2022). Gender inclusion in the labour force is crucial for several reasons. The global population stands at approximately 7.9 billion, with women comprising slightly over 49 percent of this figure (Facts and Figures: Economic Empowerment | UN Women – Headquarters, n.d.). India is one of the world's most populous countries where women represent approximately 48.5 percent of the population, which exceeds 1.3 billion (Pal & Shekhar, 2024). The participation of women in socio-economic sectors of India represents an important aspect of the global discourse on gender equality and economic development, transcending geographical boundaries and societal contexts. Across the world, engagement of women in the workforce is not just matter as individual empowerment but it is a crucial force for economic growth, social progress, and sustainable development (World Economic Forum, 2021). The engagement of women in the workforce is critical for the economic development of any region as they contribute an almost half of its population but despite significant efforts in various fields, Indian women face considerable challenges that hinder their full participation in the economy. Factors such as social norms, safety concerns, lack of access to education, and inadequate infrastructure contribute to low labour force participation rates among women (Das et al., 2020). The labour force participation rate for women in India was around 20.3% in 2019, significantly lower than the global average of about 47% (World Bank, 2021).

Efforts to address these challenges have been undertaken at multiple levels. The Indian government has launched several initiatives aimed at promoting gender equality and women's economic empowerment. For example, the Beti Bachao Beti Padhao (Save the Girl Child, Educate the Girl Child) scheme focuses on improving the welfare of girls and ensuring their education and participation in social sector. (Ministry of Women and Child Development, 2020). Other than this, the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) ensures that at least one-third of beneficiaries are women, providing them with opportunities for paid work, financial independence and social security. (Ministry of Rural Development, 2019).

The introduction of policies like the Maternity Benefit (Amendment) Act, 2017, which ensures paid maternity leave to 26 weeks and the Pradhan Mantri Mudra Yojana, which offers financial support to women entrepreneurs, has enhanced the participation of women in workforce (Ministry of Labour and Employment, 2017; Ministry of Finance, 2021). These measures, while progressive, need to be supported by broader societal changes and effective implementation then only a more enabling environment for women can be created.

Corporate India has also started to recognise the value of gender inclusivity to drive business to success. Companies are rapidly adopting gender diversity policies and creating more inclusive workplaces. The Securities and Exchange Board of India (SEBI) has mandated the inclusion of at least one woman on the boards of various listed companies, aiming to improve gender diversity in corporate leadership (SEBI, 2018).

Despite these efforts, significant work is still remains to be done. Minimizing the gender gap in India requires a multifaceted approach that includes policy reforms, societal changes, and the active participation of all stakeholders, including government, private sector, and both urban rural societies. Learning from global practices, while tailoring suitable solutions to the unique Indian context, is needed to accelerate progress toward gender equality and women's empowerment (UN Women, 2023).

Nations such as Sweden, Norway, and Iceland have led the charge by adopting comprehensive strategies that prioritize the needs of working women, while Western countries have made notable progress in this regard, challenges persist, particularly in developing nations like India. Here, entrenched gender norms, socio-cultural barriers, and structural inequalities continue to pose significant obstacles to women's full integration into the workforce. The Indian context presents a complex tapestry of socio-economic dynamics, characterized by vast disparities in women's labor force participation rates across different states and regions.

Recognizing the significance of women's participation in economic development is paramount, both on a global scale and within the context of India.

Neglecting the participation of women in the economy means overlooking a significant portion of the workforce and talent pool (Verick et al., 2014). By excluding women from economic activities, countries limit their potential for growth and innovation. Furthermore, promoting gender equality in the workforce is essential for achieving sustainable development goals. Research consistently demonstrates that empowering women economically leads to broader socioeconomic benefits, including poverty reduction, improved health outcomes, and greater social inclusion (Angala Eswari, 2019a). Women's participation in the labour force contributes to higher household incomes, increased consumer spending, and enhanced overall productivity (Klasen et al., 2012).

Women's economic participation contributes significantly to GDP both globally and in India, encompassing various sectors and roles. Globally, women contribute an estimated $18 trillion to GDP (Women and Growth March 2019 | Volume 56), representing a substantial portion of the world's economic output. In India, women's economic participation is similarly vital, with a diverse range of contributions across industries. In the formal sector, women participate in various roles, including manufacturing, services, finance and technology. In many countries, including India, women are increasingly joining the workforce, driving productivity and innovation. However, gender disparities persist, with women often facing lower wages, limited career advancement opportunities, and underrepresentation in leadership positions (Akhtar et al., 2023).

In the context of a country like India, where gender disparities in the labour force are prevalent, addressing barriers to women's economic participation is imperative for realizing its full developmental potential. Policies and initiatives aimed at promoting women's education, skills development, and access to employment opportunities are essential for fostering inclusive growth and advancing towards becoming a developed nation.

This paper underscores the indispensable nature of women's involvement in economic development initiatives. It contends that involving women in economic processes not only empowers their rights but also facilitates the potential for rapid and inclusive GDP development. According to the World Bank, closing the gender gap in workforce, participation could increase India's GDP by 27%. Gender Overview: Development News, Research, Data | World Bank, 2023. Moreover, research by A.D.B. (Asian Development Bank, 2016) suggests that advancing gender equality could add $12 trillion to global GDP by 2025.

During the 1980s, the Gender and Development (GAD) approach emerged from the examination of Women in Development (WID) initiatives. Gender and Development acknowledged the significance of gender dynamics in improving women's lives, emphasising the need to focus on both women and men. This approach highlights that merely including women and girls in existing development processes is insufficient; addressing the root causes of their exclusion and power imbalances is essential.

In India, women fulfil dual roles as producers of goods and services alongside their domestic responsibilities as wives and mothers (Angala Eswari, 2019b). Despite this multifaceted contribution, their role in economic development has often been overlooked. Commonly cited challenges include issues related to health, malnutrition, frequent childbearing, and access to education. To enhance women's participation in economic development, it is imperative to provide them with essential services such as training in income-generating activities, easy access to low-interest loans, and family planning services to enable them to control childbearing.

Globally, it has been evident that educating and empowering women serve as catalysts for rapid socioeconomic growth. Societies with greater gender equality not only provide enhanced socio-economic opportunities for women but also experience accelerated and more equitable growth (Agarwala & Hazarika, 2004). This is evidenced by gains in poverty reduction, environmental sustainability, consumer choice, innovation, and broader participation in decision-making processes. Economic development and gender equality are intrinsically linked, as lowering barriers faced by women facilitates their integration into economic activities in various sectors, fostering inclusive growth. Notably, a significant proportion of women operate micro, small, and medium-sized enterprises MSMEs, with women owning more than 30% of such enterprises. However, there remains considerable untapped potential, as only one in five women participates. (Angala Eswari, 2019b).

Over time, economic growth models have evolved to emphasise the human factor in economic progress leading to the development of endogenous growth theories in scholarly literature. These theories predominantly focus on growth catalyzed by input advancements rooted in investments in human capital. The endogenous growth theory aims to elucidate economic growth, particularly per capita GDP, through the accumulation process itself, without relying on external, exogenous components (Herrera, 2006). Scholars such as Pal, Shekhar, Sajid and Omran (Pal & Shekhar, 2024),(Sajid et al., 2021),(OMRAN et al., 2022) underscore the significance of female labour force participation, female education and fertility rate in driving economic growth.

Within the framework of the endogenous growth model, labour force participation emerges as a key determinant, explored by scholars across various dimensions such as age, race, sex and income groups (Willis et al., 2020).

Gender studies concerning labour participation remain pertinent, reflecting ongoing concerns in development discourse for several countries. Examining Lucas's endogenous growth model, it becomes evident that the relationship between economic growth and female labour force participation holds dual significance. An increase in the female labour force participation rate not only fosters economic growth but also contributes to women's empowerment, indicating a mutually reinforcing relationship between economic development and gender equality (Ernesto et al., 2013)

Scholars widely acknowledge that empowering women can enhance efficiency, provided they have access to education, healthcare, and earning opportunities, underscoring the importance of addressing gender disparities for sustained economic growth (Duflo, 2012);(Klasen, 2020). Moreover, the long-term benefits of increasing women's education positively impact growth, as educated women are positioned for better careers, higher incomes, and increased opportunities for economic advancement.

Recent research has shed further light on the intricate relationship between female labour force participation and economic growth. For instance, a study (Balafoutas & Sutter, 2012) found that increasing women's participation in the labour force in India led to significant improvements in household welfare, including better child health and education outcomes. Similarly (Klasen et al., 2009) and (Yıldırım et al., 2020) demonstrated that reducing gender disparities in access to education and employment opportunities could substantially boost economic growth and reduce poverty in developing countries.

Researchers such as Stella Tsani, Chinasa Urama and Nivedita Jha, etc. (Hwa et al., 2020; Jha et al., 2019; OMRAN et al., 2022; Tsani et al., 2015; Urama et al., 2022) continue to devote considerable attention to exploring the correlation between female labour force participation and economic growth, delving into the intricacies of this relationship.

Objective:

To analyze the contribution of women to India's workforce from 2012 to 2022 and evaluate its impact on the country's economic development.

The dependent variable of the study is gross domestic production (GDP) per capita, and data are in (constant 2015 US $). The source of the variable is World Bank national accounts data (World Bank- 2023, n.d.) and OECD (India - OECD, n.d.) national accounts data files. The explanatory variable used to demonstrate and independent variable of the study is the female labour force participation rate (FLFPR).

FLFPR is the ratio of the economically active female population to all economically active people. The source of the variable is the International Labour Organization ‘ILOSTAT’ (Data Catalogue - ILOSTAT, n.d.) and World Bank database (World Bank, Labour force participation rate, female (% of female population ages 15+). The control variables in this study are Normalized Weight (FGERSE): This variable serves as a control variable in the regression model.

The conversion of FGERSE percentages to weights and subsequent normalization followed a two-step process. Initially, percentages were converted to weights by dividing each percentage by 100. Then, these weights were normalized by dividing each by the sum of all weights, ensuring a proportional contribution. This methodology, drawn from standard statistical practices, facilitated the establishment of normalized weights representing the relative significance of FGERSE values. This approach, commonly utilized in research analyses, enhances data interpretation and analysis accuracy (Izonin et al., 2022) and (Gangopadhyay, n.d.). Adolescent Fertility Rate: The fertility rate is another control variable that generally has a trend of decrease in female labour force participation since women are generally excluded from work for a while or permanently after giving birth. The fertility rate indicates the average number of children born per 1,000 women if a woman manages to live to the end of her childbearing period (World Bank, Fertility rate, total births per 1,000 women). These variables are included as control variables in the regression model to account for their potential influence on GDP per capita, independent of the main variables of interest (FLFPR and GDP per capita).

The variables of the study were chosen based on the endogenous growth model and the literature on the relationship between economic growth and the female labour force. Thus, female labour force participation, fertility rate, and education enrolment are used in the model considering their proposed relationship with GDP. For instance, most studies indicate that a reduced fertility rate through education contributes to the empowerment of women (Forgha & Mbella, 2016). The relationship between fertility and female labour force level is inverse or weakly inverse or does not exist at all. Data are collected for 11 consecutive years. The list of years is available in Table 1. The study covers the period of 2012–2022. The time period is selected based on availability. Table 2 displays descriptive statistics of the variables.

Table 1

Temporal Trends and Key Indicators of Economic Growth, Female Labour Force Participation, and Adolescent Fertility Rates in India (2012–2022)
YEAR	FLFPR	GDP per capita ($)	Normalized weight (FGERSE)	Female gross enrollment ratio in secondary education (FGERSE) in %	Adolescent fertility rate (births per 1,000 women ages 15–19)
2012	27.06	1,434	0.092	66	35
2013	27.17	1,438	0.093	67	34
2014	27.26	1,560	0.100	72	35
2015	27.38	1,590	0.101	72	22
2016	27.47	1,714	0.102	73	20
2017	27.55	1,958	0.103	72	20
2018	27.6	1,974	0.101	72	19
2019	27.76	2,050	0.102	73	18
2020	27.89	1,913	0.103	74	17
2021	28.00	2,238	0.106	76	17
2022	28.09	2,389	0.109	78	17
Source: World Bank, United Nations, and OECD. Calculated values based on regression analysis conducted by the authors

This study employs secondary data analysis, drawing from sources such as the National Sample Survey Office NSSO, OECD STATS, the World Bank website, etc. The focus lies on examining the relationship between female labour force participation and economic development over the period from 2012 to 2022. Utilizing regression analysis (Na-Chiengmai, n.d.; Omair et al., 2020; Thaddeus et al., 2022) as the primary methodology and Cochran's C test performed to assess the presence of first-order autocorrelation, also known as serial correlation, in the residuals of a regression model.

It examines the differences between adjacent residuals to determine if there is a pattern of correlation over time (Cai, 2010). The test produces a p-value, which indicates the significance of the autocorrelation (Table 2), the study seeks to uncover the nuanced dynamics between women's engagement in the workforce and the broader economic landscape. Through this approach, it aims to provide empirical evidence to inform policies aimed at promoting gender equality and fostering inclusive economic growth.

The regression model used in the analysis can be represented by the following formula:

GDP per capita = β ₀ + β₁ × FLFPR + β₂ × FGERSE + β₃ × Adolescent fertility rate + ε

Where:

Explanation of Variables and Coefficients

GDP per capita: This is the dependent variable in the model, representing the Gross Domestic Product per person in a given population. It is a measure of economic output that is used to gauge the economic health and prosperity of a country or region.

FLFPR (Female Labour Force Participation Rate): This independent variable measures the percentage of women in the labour force out of the total female population. It indicates the level of female engagement in economic activities and is crucial for understanding gender dynamics in the labour market.

FGERSE (Female Gross Enrollment Ratio in Secondary Education): This independent variable reflects the proportion of females enrolled in secondary education relative to the total female population. It indicates educational attainment among women, which is closely linked to their future economic opportunities and contributions.

Adolescent Fertility Rate: This independent variable measures the number of births per 1,000 women aged 15–19. It indicates the rate of adolescent pregnancies, which can have significant implications for the economic prospects of young women, affecting their education and labour market participation.

β0 (Intercept): The intercept is the constant term in the regression equation. It represents the expected value of GDP per capita when all independent variables (FLFPR, FGERSE, and Adolescent fertility rate) are zero. In practical terms, it provides a baseline level of GDP per capita.

β1, β2, and β3 (Coefficients): These are the coefficients associated with the respective independent variables. They indicate the change in GDP per capita for a one-unit increase in each of the independent variables, holding other factors constant.

β1 (Coefficient for FLFPR): Represents the change in GDP per capita for a one-unit increase in the Female Labour Force Participation Rate. A positive β1 suggests that higher female labor force participation is associated with higher GDP per capita.

β2 (Coefficient for FGERSE): Represents the change in GDP per capita for a one-unit increase in the Female Gross Enrollment Ratio in Secondary Education. A positive β2 indicates that higher enrollment rates in secondary education among females contribute to economic growth.

β3 (Coefficient for Adolescent Fertility Rate): Represents the change in GDP per capita for a one-unit increase in the Adolescent Fertility Rate. A negative β3 suggests that higher adolescent fertility rates are associated with lower GDP per capita, likely due to the economic disadvantages faced by young mothers.

ε (Error Term): The error term captures the discrepancies between the observed values of GDP per capita and the values predicted by the regression model. It accounts for the variance in GDP per capita that is not explained by the independent variables included in the model ( See Table 3 for detailed calculation).

Table 2

Regression Coefficients and Statistical Significance
Variable	Coefficient (B)	Std. Error	t-value	p-value	95% Confidence Interval
Constant	-25513.761	7201.051	-3.543	0.009	(-42541.541, -8485.980)
FLFPR	986.308	293.318	3.363	0.012	(292.721, 1679.895)
Normalized Weight (FGERSE)	576.288	15652.112	0.037	0.726	(-36435.075, 37587.651)
Adolescent fertility rate	3.261	8.946	0.365	0.365	(-17.894, 24.416)

Source: Calculated values based on regression analysis conducted by the author using SPSS

Table 3

Regression Analysis Summary and Diagnostic Statistics for Factors Impacting GDP per Capita
Variable	Value
Cochrane-Orcutt Test Results
Autocorrelation Coefficient (AR1)	-0.826
p-value	0.001
Descriptive Statistics
Mean GDP per capita	1841.64
Std. Deviation GDP per capita	320.047
Mean FLFPR	27.600
Std. Deviation FLFPR	0.3317
Mean Normalized Weight (FGERSE)	0.10064
Std. Deviation Normalized Weight (FGERSE)	0.004925
Mean Adolescent fertility rate	23.09
Std. Deviation in Adolescent fertility rate	7.595
Correlations
Pearson Correlation (GDP per capita, FLFPR)	0.962
Pearson Correlation (GDP per capita, Normalized Weight (FGERSE))	0.873
Pearson Correlation (GDP per capita, Adolescent fertility rate)	-0.826
Model Summary
R	0.963
R Square	0.927
Adjusted R Square	0.896
Std. Error of the Estimate	103.135
R Square Change	0.927
F Change	29.766
df1	3
df2	7
Sig. F Change	0.000
ANOVA
Sum of Squares (Regression)	949842.921
df (Regression)	3
Mean Square (Regression)	316614.307
F (Regression)	29.766
Sig. (Regression)	0.000
Coefficients
(Constant)	-25513.761
FLFPR	986.308
Normalized Weight (FGERSE)	576.288
Adolescent fertility rate	3.261
95.0% Confidence Interval for B
(Constant)	Lower Bound: -42541.541, Upper Bound: -8485.980
FLFPR	Lower Bound: 292.721, Upper Bound: 1679.895
Normalized Weight (FGERSE)	Lower Bound: -36435.075, Upper Bound: 37587.651
Adolescent fertility rate	Lower Bound: -17.894, Upper Bound: 24.416
Residuals Statistics
Minimum Predicted Value	1382.34
Maximum Predicted Value	2319.75
Mean Predicted Value	1841.64
Std. Deviation Predicted Value	308.195
Mean Residual	-206.029
Std. Deviation Residual	126.810
Std. Predicted Value	-1.490
Std. Residual	-1.998

(Calculated values based on regression analysis conducted by the author using SPSS)

Interpretation of the Model

This regression model aims to quantify the impact of female labor force participation, female education, and adolescent fertility on economic growth in India. By analyzing the coefficients:

A positive β1 implies that policies and initiatives aimed at increasing female labor force participation could significantly boost economic growth.

A positive β2 highlights the importance of investing in female education, as higher secondary education enrollment rates among females are associated with higher GDP per capita.

A negative β3 suggests that reducing adolescent fertility rates could positively impact economic growth, as early pregnancies can limit the economic potential of young women.

Displayed in Fig. 1.

The histogram of GDP per capita exhibits a slight negative skewness, indicating that higher values of GDP per capita tend to be associated with lower Adolescent fertility rates, higher Female Labour Force Participation Rates (FLFPR), and higher Normalized Weight values (FGERSE). This distribution suggests that as economic output per person increases, there is a tendency for lower rates of adolescent pregnancies and greater participation of women in the labor force, coupled with better educational attainment among females.

The scatter plot reveals a clear positive correlation between GDP per capita and FLFPR. Points on the graph show a consistent upward trend from left to right, indicating that higher levels of female labor force participation are generally linked with higher GDP per capita. This correlation underscores the economic benefits of integrating more women into the workforce, contributing to overall economic growth and productivity.
In contrast, the correlation between GDP per capita and Normalized Weight (FGERSE) appears weaker compared to FLFPR. While there is some variability in GDP per capita across different levels of FGERSE, the trend line is less steep, suggesting that improvements in female secondary education enrollment have a less pronounced impact on economic output per capita compared to female labor force participation.

The regression analysis conducted on the dataset spanning the period from 2012 to 2022 in India revealed several significant insights into the relationship between economic growth, measured by GDP per capita, and various contributing factors such as female labor force participation rate (FLFPR), normalized weight (FGERSE), and adolescent fertility rate.

Correlation Analysis

The correlation analysis highlighted strong positive correlations between GDP per capita and FLFPR (r = 0.962, p < 0.001), indicating that higher female labor force participation is strongly associated with higher GDP per capita. This shows that as more women participate in the labor market, the overall economic output increases, reflecting the critical role of gender inclusion in economic development.

A strong positive correlation was found between FLFPR and normalized weight (FGERSE) (r = 0.906, p < 0.001). The normalized weight, representing the female gross enrollment ratio in secondary education, underscores the interdependence between education and labor force participation. This implies that higher educational attainment among women leads to greater participation in the labor force, reinforcing the importance of education in empowering women to contribute economically.

A moderate positive correlation was observed between GDP per capita and normalized weight (FGERSE) (r = 0.873, p < 0.001). This relationship indicates that improvements in female education are moderately associated with increases in economic growth, emphasizing the role of education in enhancing economic productivity.

A strong negative correlation emerged between GDP per capita and adolescent fertility rate (r = -0.826, p < 0.001). This implies that higher rates of adolescent fertility are associated with lower economic growth, highlighting the economic drawbacks of early pregnancies, which can limit educational and employment opportunities for young women, thereby hindering economic progress.

Regression Model

The regression model exhibited a high degree of explanatory power, with an R-squared value of 0.927, indicating that approximately 92.7% of the variance in GDP per capita could be explained by FLFPR, normalized weight (FGERSE), and adolescent fertility rate. This high R-squared value signifies that these factors are highly predictive of economic growth in India, showcasing their importance in economic analysis and policy formulation.

Moreover, the ANOVA test results were significant (F(3,7) = 29.766, p < 0.001), indicating that the regression model adequately fits the data. The significant ANOVA results confirm that the overall model is statistically robust and that the relationships identified are not due to random chance.

Coefficients

Regarding the coefficients, FLFPR demonstrated a significant positive effect on economic growth, with a coefficient of 986.308 (p = 0.012). This suggests that for every unit increase in the female labor force participation rate, there is an associated increase of approximately 986.308 units in GDP per capita, holding other factors constant. This finding underscores the substantial impact of female labor participation on economic performance, indicating that policies aimed at increasing FLFPR could significantly boost economic growth.

This comprehensive study resonates deeply with the economic landscape of India, emphasizing the pivotal role of female labour force participation (FLFPR) in propelling economic growth. The consistent positive correlation observed over the examined decade between FLFPR and GDP per capita underscores the pivotal role of women in propelling economic development. As participants in the labor force, women contribute essential skills, knowledge, and perspectives that are critical for innovation and productivity enhancement across various sectors of the economy.

In context of India's economic landscape, where gender disparities in labour force participation persist, enhancing FLFPR emerges as a strategic imperative. Increasing women's participation in economic activities can lead to broader economic benefits, including higher household incomes, improved living standards, and overall economic stability. This aligns with global research highlighting that economies, where women are more actively engaged in the workforce, tend to experience higher levels of economic growth and resilience.

Moreover, the study highlights the detrimental impact of high adolescent fertility rates on economic progress. The inverse relationship between GDP per capita and adolescent fertility rates underscores how early motherhood can disrupt educational attainment, limit career opportunities for young women, and perpetuate cycles of poverty. Addressing these challenges requires comprehensive policies that promote reproductive health education, provide access to affordable and quality healthcare services, and empower young women with the knowledge and resources to make informed decisions about their reproductive choices.

Looking ahead, effective policymaking in India must prioritize gender-inclusive strategies that dismantle barriers to women's participation in the labor market. This includes implementing supportive policies such as maternity leave benefits, childcare facilities, flexible work arrangements, and initiatives to combat gender-based discrimination in hiring and promotions. By creating an enabling environment for women to fully utilize their potential in economic activities, India can harness demographic dividends and accelerate its path towards sustainable development goals.

In this way, advocating for gender equality in the labour market is not just a matter of social justice but also an economic imperative. Investing in women's education, skills development, and entrepreneurship can unleash significant economic potential and contribute to building a more inclusive and resilient economy. By fostering an environment where women can thrive professionally and personally, India can achieve sustainable economic growth that benefits all segments of society.

Hence, the study underscores the interconnectedness between female labour force participation, adolescent fertility rates, and economic growth in India. By advancing gender equality, promoting women's economic empowerment, and investing in reproductive health and education, policymakers can lay the foundation for a prosperous future where every individual, regardless of gender, has the opportunity to contribute to and benefit from India's economic advancement.

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The authors declare no competing interests.

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Women at Work: Unveiling the Impact of FLFPR and Adolescent Fertility on India's Economic Landscape

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