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Gender Equality

in the Labor Force

BACHELOR

THESIS WITHIN: Economics NUMBER OF CREDITS: 15

PROGRAMME OF STUDY: International Economics AUTHOR: Clara Bergman & Hui Zhang

JÖNKÖPING May 2021

How is the proportion of seats held by women in the

national parliament related to the female education level?

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Bachelor Thesis in Economics

Title: Gender equality in the labor force: How is the proportion of seats held by women in the national parliament related to the female education level?

Authors: Clara Bergman & Hui Zhang Tutor: Mikaela Backman

Date: 2021-05-24

Key terms: education, parliament participation, labor force participation, gender differences

Abstract

This study aims to examine the relationship between the ratio of seats held by women in parliament and the years of female education. The study is a cross-national study across 91 countries that uses the average value of data from 2014 to 2018. The findings show no significant relationship between the two variables, and based on the theoretical background, different areas are explored to clarify what caused this result. It is believed that patriarchy, cultural attitudes towards women, income level of individuals, and differing majors in higher education between men and women are why we see this correlation. The study also tests if labor force participation of women and female parliament seats are correlated, and it is found that there is a positive relationship between the two. The interest in this topic comes from looking closer at if women have the same opportunities in politics and generally in the labor force. It is essential since diversity in organizations and the labor market can have significant economic benefits. The results from previous studies into female seats in parliament and education have varied, so this study adds national income to see if that affects the variables.

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Table of Contents

1.

Introduction ... 1

2.

Theoretical Framework ... 5

2.1 Human capital ... 5

2.2 Patriarchy theory ... 7

2.3 Role Model Theory ... 8

2.4 The effect of diversity on productivity ... 9

2.5 Income and political participation ... 10

3.

Literature Review ... 12

4.

Hypothesis ... 14

5.

Method ... 16

5.1 Data Collection ... 16 5.2 Variables Description ... 16 5.3 Regression Model ... 21

6.

Empirical Results ... 23

7.

Discussion ... 25

8.

Conclusion ... 29

8.1 Limitations ... 31

Reference list ... 32

Appendix... 41

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Figures

Figure 1 Women head of state or government (197 countries in total) ... 2

Figure 2 Government ministers (worldwide) ... 2

Figure 3 Gender ratio in the national parliament (worldwide) ... 2

Tables Table 1 Expected sign of variables (female) ... 19

Table 2 Expected sign of variables (male) ... 19

Table 3 Descriptive Statistics ... 20

Table 4 Correlation Matrix ... 21

Table 5 Effects of independent variables on dependent variables (female) ... 23

Table 6 Effects of independent variables on dependent variables (male) ... 24

Table 7 Correlation method ... 25

Appendix Appendix 1 ... 41

Appendix 2 ... 42

Appendix 3 ... 43

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1. Introduction

In 1893 New Zealand was the first self-governing country to change its legislation to allow women to vote. No less than thirteen years later, Finland followed suit, and a further nine years after that, Denmark did the same (Miller, 2020). The same year that women were allowed to vote in the UK, in 1918, the first women were also allowed to run in elections (UK Parliament, 2021). The first woman in the British Parliament was Nancy Astor from America, who was elected in 1919, just one year after the law was passed (The History Press). Despite their early reform, the first parliament member selected in New Zealand was Elizabeth McCombs as late as 1933 (NZ History, 2018). Saudi Arabia had the first election where women were allowed to vote in 2015, one of the more recent breakthroughs in women gaining voting rights (BBC, 2015). The last place in the world to not allow women to vote is the Vatican City; however, neither can men since this is an absolute monarchy. That means that women now have voting rights worldwide. However, not all countries have female participation in parliament. The Pacific islands region is home to four of six countries worldwide with no women in their lower house of parliament. There are restrictions that cause it to be more difficult for women to run for office. For example, in Tonga, there are seats for nobles that only men can occupy. In Samoa, only people with Matai titles can run for seats in parliament, and far fewer women hold this title (Baker, 2015). Throughout history, women have had a much more limited role in society than men and have been more restricted in their financial, political, and labor-related opportunities (UN Women, 2021).

The UN Women’s survey found that only 22 countries have women as heads of government, and in as many as 119 countries, no woman has ever held such a high position. In 1995, only 11% of females in parliament rose to a still-low 25% globally today. In 27 countries, there is less than 10% female representation in lower or single parliament houses, some of which have no women at all represented. Nineteen countries have over 40% representation. In two-thirds of those countries, there is some gender quota applied, which opens up for further female participation in national parliament, such as a reserved number of seats for women to hold. We will have to wait until 2063 to see gender parity in the federal parliament when progressing at the current rate (UN Women, 2021).

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Figure 1 Women head of state or government (197 countries in total)

Figure 2 Government ministers (worldwide)

Figure 3 Gender ratio in the national parliament (worldwide)

In the workforce in general, there have existed barriers for women, which have included legal restrictions, quotas, and administrative regulations, and there is an overall lower representation of women in managerial positions. National census data by Parker (2015) reveals that women would most often obtain a degree in already female-dominated fields such as teaching, nursing, and social work. These facts show that this disparity might be due to policy, history, and choice (Parker, 2015). Under this circumstance, although women’s education level is getting higher, it seems to have little effect on their political participation since politics is not the subjectively chosen field of work by most women. However, there is no clear educational path for working in the political field, making it harder to identify which degrees to observe. However, it has been found that individuals with higher income will be more likely to be politically active (Paletz et al., 2011). It

11.17%

60.41%

28.43% Countries that women serve asHeads of State or Government Countries never have a woman leader

Countries used to have a woman leader

21%

79%

Women government ministers Men government ministers

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Women Men

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means that those who obtain higher-paying jobs would have it easier to move into the political field.

Representation of women in higher education is lower than for men in many places, and it likely has historical and social factors to blame. In some countries, though, like the United States, more women than men enrolled in tertiary education, and the same goes for Sweden (Duffin, 2021; SCB, 2021). Looking at data collected from the World Bank (Appendix 1) used in this study, however, we can see that when we look at some countries with lower income than the two aforementioned, we see a drop in the years of schooling. While these two high-income countries have an average of 13.36 years of education for women in the United States and 12.49 years in Sweden, in for example Burkina Faso, Cambodia, and Mali, there is only on average 0.93, 2.87, and 1.67 years of education for women, respectively which is a huge difference. When seeing these differences, it introduces the idea that income level in a country also could affect what abilities women have of continuing their education.

This study is a cross-national study that intends to analyze the relationship between the years of schooling of women and women’s representation in the national parliament. In a workplace setting, it is found that gender diversity can lead to better decision making and higher productivity (Dunn, 2015) which means that more diversity in politics could have the same outcome making it essential to study. It has been studied that gender diversity in organizations contributes to greater productivity due to different perspectives and greater knowledge exchange. It will be expanded on further in the theory section by discussing diversity in the labor market and human capital and its impact on productivity.

In the labor market, there have always been gender differences in the supply and demand of labor. The labor participation of men and women in different fields and occupations is also diverse. Many factors cause these differences, such as women’s fertility, childcare and family policies, social and cultural factors (Tzvetkova & Ortiz-Ospina, 2017). This thesis will revolve around gender economics, focusing on how women's seats in various countries' parliaments are affected by years of schooling of women. Whether the changing trend of women's seats in parliament is similar to the changing direction of women's

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participation in the labor market will also be presented in the thesis. Thus, the following research question is posed:

How is the proportion of seats held by women in the national parliament related to the female education level?

The research question will be supported by country-level data and women's seats in parliaments and women's enrollment rates in different education levels in 91 countries to study the possible relationship between them. These countries are also divided into two different income groups to study if the income level impacts female political participation. The contribution of this study is that no studies have focused on an income level perspective to the issue of gender inequality in politics on a cross-national level. There are previous studies on female education and parliament participation, but there are differing results and none of them bring in the income perspective to gender equality. Some of them claim that there is a positive relationship (Bravo-Ortega et al., 2020; Simon & Palmer, 2016; Khelghat-Doost & Sibly, 2020; Mlambo & Kampingura, 2019; Nechemias, 1987), and some that there are inconclusive results or varying between countries (Goetz, 2003). Therefore, we want to extend the research by adding the income element, which has not previously been done on a national level. There are studies on individual income and income inequality between individuals on the topic but, not on a national level.

The study is aimed towards policymakers, and it can hopefully answer if more resources and investments made in female education can reduce gender inequality in national parliaments. Education could be a pivotal aspect to increases in female parliamentary participation because, as found, individuals in general with education are more likely to be politically active (Winters, 2011). The education level is higher for men than for women in many countries, suggesting that political participation would also increase with a higher female level of education.

The remaining thesis is divided as follows: Section 2 explains the theoretical framework used in this thesis. Section 3 reviews the survey of previous literature on similar topics. Section 4 puts forward our hypotheses. Section 5 describes the sample selection and the econometric model used. Section 6 presents findings and the results of the thesis's

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empirical test and analyzes the results. Section 7 discusses the empirical results. Section 8 concludes, including the limitations of the research and future research opportunities in this topic.

2. Theoretical Framework

2.1 Human capital

Human capital refers to the skills and the knowledge that workers acquire. According to the Cambridge dictionary, the definition of human capital is “all of the knowledge, skills, experience that employees have, which makes them valuable to a company or economy” (Cambridge Business English Dictionary, 2021). For example, human capital investment is work training, apprenticeships, benefits, and family assistance. For employees, the most apparent investment in human capital is to obtain an education. The main methods of human capital investments, according to Chen (2020), are work training, migration, and of course, education. Schiller (2008) states that investing in human capital is learning by doing, explicitly training at your chosen trade, and your payoff is then the increased earnings that follow when you join the labor force. Increased human capital leads to spillover effects like higher income in the region, even for workers with lower education, which leads to higher economic growth in the area. Higher education not only increases earnings but also lowers unemployment (Schiller, 2008). With more human capital, there is knowledge passed between workers and businesses, increasing their productivity (Moretti, 2004). The positive externalities of higher education on human capital are increased productivity and technological progress. There are other spillovers seen when there is increased human capital from lower levels of education, such as lower crime rate and less welfare participation (Krueger & Lindahl, 1998).

Khan (2016) discusses how better education for women and more opportunities in the labor market will promote economic growth and uplift for society since women are in some parts of the world underutilized in the labor market, thereby not contributing to the worldwide growth process. Not engaging everyone in the population in the workforce, both men and women, leads to lower efficiency in the labor market (Khan, 2016). One major hindrance to developing countries is gender equality. The gender inequality index is generally lower due to less focus on developing policies that aim to improve women’s

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opportunities in society than in developed countries (Morrison et al., 2007). Khan’s study (2016) shows that economic growth contributes to both female and male human capital and that long-term planning through policy is necessary to form human capital.

Winters (2011) reports that research suggests that human capital levels are essential for economic outcomes. The study states that universities play a vital role in increasing human capital and that the presence of universities in an area is essential to the human capital level. The increased productivity that comes from increasing human capital will also make more people want to move to that area which will increase, for example, housing prices which will increase the value of an area's consumption (Winters, 2011). Higher educated individuals tend to use local public goods more than less-educated individuals. Moreover, examples of such public goods are museums, parks and theatres. Because of this, there will be more amenities in areas with more educated individuals, which improves the quality of life for all residents. Having a higher education institution in an area will both attract local students but also migrating students who may stay in the area after their education is complete, which is why we can see that areas with easier access to higher education institutions tend to have higher human capital levels (Winters, 2011).

Winters (2011) finally states that educated people are more likely to be active in politics but do not expand further. However, Kam & Palmer (2008) try to explain the relationship between higher education level and higher political activity. Through education, people develop skills such as communication and civic skills that are beneficial to participate in politics and help them gain a more favorable socioeconomic position that will help take political action. Further, the development of comprehension of political content is simply because people with interest in higher education generally have a more considerable interest in higher status jobs. They might be increasingly interested in pursuing a political career or have the financial ability to volunteer in political campaigns (Kam & Palmer, 2008). Milligan et al. (2004) expands on this and states that education has social benefits that transcend the benefits of individual economic return. Educated individuals are far more engaged in civic matters in general, which economists commonly argue (Milligan et al. 2004).

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Further, the study states that educated individuals have a better ability to select appropriate leaders. They can better understand political issues and recognize corruption or corrupt leaders. They have increased interest and knowledge in general about politics, and their participation is more effective (Milligan et al. 2004). Based on this knowledge, it would be fair to assume that with increased education and human capital levels regardless of gender, there will be increased individual economic profits and social benefits with increased political participation.

Chen (2020) looks at how human capital is affected by the parents' education level in the household, and it finds that with the higher education level of the parents, there is also a higher human capital investment in the family. The study recommends that governments improve the education policy to increase public education investment and ensure compulsory primary education. Also, higher education provides tuition reductions, grants and provides lower interest rates for student loans to provide better opportunities for students with limited economic ability (Chen, 2020).

2.2 Patriarchy theory

In countries worldwide, women have less representation in politics than men in parliament, even though there are limited legal obstacles for women to participate. So why is the climate unequal when women, in theory, should have the same legal opportunities as men to be politically active? When translated from the Greek word patriarkhēs, the word patriarchy means the rule of the father. It concerns division of labor in the home, participation for women in the workforce, religion, and politics (Khelghat-Doost & Sibly. 2020). The paper by Khelghat-(Khelghat-Doost & Sibly (2020) summarizes how patriarchy has been studied, and a power structure has in research been identified in the family, in the workplace, and at home where women are subordinate to men. By focusing on patriarchy as one of the obstacles to women's participation, perhaps one can get closer to answering why there is a disparity between women and men in politics and the labor force.

Women's places have been seen to be in the private arena rather than the public, focusing on home and the family, which has developed a global political model that is male-centered and male-dominated. Taking South Asia as an example, a study by Chuki & Turner (2017) states that there are both structural and cultural factors underlying women's

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position in society. The economic dependence women have on men in parts of the world makes it difficult for them to move into the public domain on their own in those places. Their study looks at Bhutan, where there has previously been a bias towards male enrolment in education, suggesting a patriarchal mindset. The mentality exists in politics and education in South Asia (Chuki & Turner, 2017).

The patriarchal model is also evident when looking at women's roles who have made it into the top of the political sphere. There is a significantly lower number of women dealing with foreign affairs, economy, and defense than social affairs, gender equality, and environmental issues, according to Khelgat-Doost and Sibly (2020). A pattern that can be spotted is that usually right-wing parties and conservative parties tend to have a more patriarchal view of women. Usually, these parties have fewer female candidate nominees, and the opposite is seen for liberal parties. Further, with women increasing their education level, they expand their role in the labor market, which questions traditional patriarchal values, showing that women are eligible for high-status decision-making positions as men. With increased socio-economic status, women will have more opportunities to decrease inequality in politics with more financial resources (Khelgat-Doost & Sibly, 2020).

Looking at patriarchy in relation to the research question of this thesis is that it is a good way of getting the complete picture as to how the relationship between education level and female parliamentary participation works. If a low correlation is found, then patriarchy may well be why there are still barriers from women who want to enter parliament. Not all women want to enter, and that those barriers turn out to be a hindrance.

2.3 Role Model Theory

Priyanka (2020) found that it can be significant with female representation in politics and for the labor force to stimulate further engagement by women in this field which can mean significant economic spillover effects that the study refers to as the role model effect. The study looks at the effect of political female role models on education, labor participation, and the aspiration of young girls in India.

The study's hypothesis in the study by Campbell & Wolbrecht (2006) is that female role models in politics make young women increasingly likely to express interest in

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participating in political activity later on in life. Moreover, other previous studies support this claim (Atkeson, 2003; Verba et al., 1997). The same study by Campbell and Wolbrecht explains that not only being parliamentarians, women are also less inclined to engage in small-scale political activism, such as making phone calls or sending letters to public officials, than men are. Different experiences in the home's labor market and power structure influence political gender disparity (Campbell & Wolbrecht 2006). Some scholars will state that the lack of prominent role models for women in politics encourages the idea that women may be unfit for political activity and that masculine traits are more suitable to politics (Huddy & Terkildsen, 1993). That can be connected to the previous discussion of the prevailing patriarchy structure in politics today. With fewer female role models, the stereotypes cannot be broken. The study by Campbell & Wolbrecht (2006) finds evidence for the role model effect as well. With more visible political role models who are female, younger women report being politically active. The study suggests that this is because it opens up for political discussion in the home. If there are more female role models in politics, women will be more inclined to pursue a political career, which may also positively affect education. Suppose women are not seen succeeding in leadership positions. In that case, it is natural to assume that those roles will be chased by young women who are getting ready to enter the labor market and who are contemplating their education choice to a minor degree.

2.4 The effect of diversity on productivity

A study by McKinsey Global Institute from 2015 claims that if the labor force participation were equal between men and women, the overall economic output in the world would increase by 26% (McKinsey Global Institute, 2015). Multiple studies have looked at what relationship exists between performance and gender diversity, but with mixed results. Some theories suggest a positive impact of diversity on performance, both organizational productivity and economic profit (Nguyen, Locke, & Reddy, 2015; Post & Byron, 2015; Terjesen, Couto, & Francisco, 2016). However, some have also shown a negative relationship between gender diversity and financial performance (Wellalage & Locke, 2013; Holgersson, 2013; Chapple & Humphrey, 2014). The study by Wellalage & Locke (2013) suggests that training and education of female employees would increase their representation in executive boards and increase their positive contribution. Chapple and Humpfrey (2014) write about how it is riskier to have diverse boards. Therefore, only

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larger firms can afford to have them. There may be intergroup conflict due to increased diversity, which can negatively impact productivity and overall performance. However, the knowledge expansion and competitiveness at higher organizational diversity can positively impact performance outcomes due to increased information exchange that would otherwise not be achieved (Kwang & Skaggs, 2019). Research has shown that mixed teams increase and expand the information that is beneficial to organizational performance (Van Knippenberg et al. 2004).

Looking specifically at efficiency in parliament, a study by Jayasurya & Burke (2013) finds that democracies with a higher number of females in parliament also have faster economic growth over the past decades, which suggests higher efficiency of diversified parliaments as already argued for other organizations previously. It means that in nations located in the Middle East and the Pacific, where the representation is very low for females in parliament. It could be beneficial not only for female empowerment in those places but also for the overall population since it could lead to faster economic growth. There is also evidence presented by Klasen (2002) that gender inequality in education shows the same pattern that it reduces economic growth and Dollar et al. (2001) states that higher female parliamentary representation reduces corruption. In general, there are not many studies specifically on how increased female representation in parliament affects the productivity of decision-making. The European Commission reports that women are underrepresented in the labor market by approximately 12% worldwide. 67% of women are employed while about 79% of men are (European Commission, n.d.). There is a 16% gender pay gap in Europe due to different reasons such as the varying work pattern like ending a career early to take care of children or relatives. Women are also more likely to have part-time employment than men. The European Commission also states that women are underrepresented as managers as well as in politics.

2.5 Income and political participation

An individual's socioeconomic status is influenced by factors such as level of income, education, and what occupation they have. It is observed that people with better educational backgrounds and who hold more wealth are more inclined to participate in a range of political activities, both voting and participation in party activities and donating money. People with more wealth can finance political activity such as campaigning when running for office. The connection can also be seen when looking at which occupations

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individuals hold. People in professional positions are more politically active than laborers. The least likely to take part are the unemployed (Paletz et al. 2011). There are not many studies to be found about the income level across countries and its impact on female political participation or labor market participation, which is surprising. The existing literature focuses on individual income and income inequality within countries. Bergh & Fink (2008) found that increasing GDP per capita is the most extensive explanation for increased educational enrolment, but the mechanism behind this relationship is not examined further.

To summarize the theoretical framework, the most central aspects are gathered to get a good base to stand on before starting the empirical analysis. The five aspects included in this thesis are human capital, patriarchy theory, role model theory, the effect of diversity on productivity, and how income affects political participation, as just discussed. Human capital is highly central to the thesis since it is deemed the basis of why it is important to study. Education contributes to human capital, and the conclusion should be that increased education for women increases workforce participation, but perhaps that is not always the case. It is why the next section discusses patriarchy and role model effects. These can be why women have a more challenging time getting themselves involved in politics and why education may not have the expected impact. It explains why it is essential that we see equality in the labor force and politics by looking at the positive effects of gender diversity. Finally, to include the income perspective, the research is extended, and an interesting aspect of the topic is examined.

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3. Literature Review

Ramachadran (2010) summarizes how there is research and literature on basic or primary education related to gender inequality in the labor market but not on secondary and tertiary education and its gender equality. The study further discusses what can affect the ability to extend primary education into higher education for women. Several factors are suggested to impact the households' economic situation and their ability to pay tuition fees, the previous academic performance of members of the family, and the individual themselves. Also, government policy, scholarship programs, and geographical implications such as distance to academic institutions play a part. Women attending higher education can also be influenced by pressures of having a family or getting married at a younger age with historical and cultural connections in many parts of the world (Ramachadran, 2010).

There are some conflicts in the literature regarding the effect of education on political participation. Burns et al. (2003) identify a positive relationship and some effects that education has on political participation, such as communication skills, direct training in analysis of political content, exercising leadership, and getting organizational skills that are useful when engaging in political activity (Burns et al., 2003). Several other studies have found a strong relationship between education and political participation, looking at engagement in political activity and political knowledge in general (Wolfinger & Rosenstone, 1980; Nie et al., 1996; Hillygus, 2005; Milligan et al., 2003). A study by Kinge & Oluwasanumi (2014) looks at the same issue but specifically to female education in Cameroon and finds a positive relationship between the two variables. These results are supported by some other studies (Dee, 2004; Milbrath & Goel, 1977).

However, there appears to be a variation between countries in the relationship between women's education and participation in political activity. Goetz (2003) shows that the United States, which outran most other democracies in terms of their numbers of women in higher education and the workforce, actually has seen a low number of women in formal politics. The study also explains that in some of the poorest countries in the world, Uganda, Mozambique, and Rwanda, which have a low literacy rate of only 41, 28, and 60 percent respectively, there are as many as around 30 percent of women in legislative positions. In Kerala in India, women's social status is high, but their political participation

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is meager. It tells us that the mechanisms behind political participation are not always fully observable (Goetz, 2003).

Given what we have seen, it is difficult to conclusively say that higher levels of education will make women more active in politics based on previous research. In some countries, the opposite has been found, and we can see educated women are indifferent towards engaging in politics (CENWOR, 1994). It has been found that higher educated people feel more pressure to participate in what is seen as desirable social behavior, such as engaging in politics (Silver et al., 1986; Bernstein et al., 2001).

Heath and Jayachandran (2016) explore the rise of women's labor force participation in developing countries and closing gender gaps in education. Increased education has made more women join the labor force, which gives better labor market opportunities. There is a relationship between higher education and labor force participation of women and their political participation, according to Khelghat-Doost and Sibly (2020). There is also a positive correlation between education and more political participation in a study by Nechemias (1987), which shows that a 1% increase in the proportion of women with a degree increased the seats held by women in political institutions more than 1% in 1983 and 1984. The exact correlation in a more recent study by Simon & Palmer in 2016 further strengthens the hypothesis that increased enrolment of women in higher education will also increase female political participation. Bravo-Ortega et al. (2020) find that if secondary education enrollment is increased, it would positively impact the increasing percentage of female parliament seats. With higher education and higher participation in the labor force, women can compete with men on the political scene and strive towards an equal distribution of men and women in politics (Simon & Palmer, 2016).

Mlambo's research from 2019 finds that countries with a well-functioning government have higher female political participation levels, which is consistent with other empirical literature. The study also identifies a negative relationship between the human development index and female political representation. It is surprising, but it shows that other factors than economic ones may impact women's political involvement. However, there is little further empirical data on this relationship between HDI and female political participation. Finally, it offers a positive relationship between female labor participation and political participation (Mlambo & Kampingura, 2019).

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4. Hypothesis

Based on the theoretical framework and the content described in the literature review, we put forward the following three hypotheses.

Through human capital theory, people with higher education are more likely to participate in political activities. Education can help people develop skills that are useful for participating in politics. People with higher education are usually more interested in higher-level positions, and they are more likely to pursue political careers or volunteer to participate in political campaigns. This theory applies to both men and women. Therefore, based on this theory, our first hypothesis can be divided as:

Hypothesis 1.1: The years of schooling for women have a positive relationship with the proportion of seats held by women in the national parliament.

Hypothesis 1.2: The years of schooling for men negatively affect the proportion of seats held by women in the national parliament.

According to the theory of income and political participation, a person's social status is affected by income level, education level, and occupation. People who are well-educated and those with more wealth are more inclined to participate in politics. Bergh & Fink (2008) found that the increase in per capita GDP is the most significant explanation for the increase in education enrollment, which shows that the country's economic status positively impacts education. Therefore, we propose the second hypothesis:

Hypothesis 2: The higher income level of countries will positively affect the impact of education on political participation.

According to role model theory, political female role models affect women’s desire for education, political participation, and labor participation. Unequal gender shares in the political sphere and the labor market are related to the weaker ambitions of young girls, stereotyped gender concepts, and women’s education levels. As more and more political women become role models, more young girls will be willing to participate in political activities or enter the labor market. Based on this theory, the third hypothesis we put forward is:

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Hypothesis 3: Women’s political participation is positively correlated with female labor force participation.

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5. Method

5.1 Data Collection

This empirical research uses cross-sectional data to capture the impact of women's education levels in different countries/regions on their political participation. All the data we used come from well-known and widely used data sources: female parliamentary seats, GDP growth rate, female population ratio, income levels of various countries, and female labor force participation are from the World Bank database. Women's average years of education originated from the UNESCO Institute for Statistics (UIS). The World Bank's database adopts internationally recognized standards and norms (The World Bank, n.d.) and is therefore deemed a reliable source of information. UIS is an official and trusted source of internationally comparable data on education, science, culture, and communication (UNESCO Institute for Statistics, n.d.). All the data use the average value from 2014 to 2018 in order to avoid fluctuations and highlight differences in space rather than changes in the period. We looked at which countries have consistent data for the selected years. Some countries/regions lack data for one or more variables for a given year, so we exclude them. In the end, we were able to gather complete information for 91 countries. Appendix 1 will show the data we used. Moreover, the selected countries (grouped in different income levels) are presented in the Appendix 2 based on the World Bank's definition of high-income (2019 GNI per capita was $12,536 or more), upper-middle-income (2019 GNI per capita was between $4,046 and $12,535), lower-middle-income (2019 GNI per capita was between $1,036 and $4,045), and low-income countries

(2019 GNI per capita was $1,035 or less).

5.2 Variables Description

This paper uses the proportion of seats for women in parliament as the dependent variable, the mean years of schooling for women as the explanatory variable, GDP growth rate and female population ratio as control variables, and countries' income level as the categorical variable to verify our hypothesis. The following variables are measured as the average value from 2014 to 2018 across 91 selected countries.

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Seats in parliament held by women

Parliament plays an essential role in the political life of a country. Therefore, female seats in the national parliament can show women's status and the political field situation to some extent. Stolt (2013) used the proportion of female parliamentary seats as an explanatory variable and several variables such as expected years of education and democratic index as control variables to study their economic growth impact. In this empirical research, we use the proportion of female seats in the national parliament as the dependent variable. It is the percentage of female seats in the selected countries' federal parliament's total number of seats.

Years of schooling

Education is one of the critical factors for evaluating economic growth and social development. It creates human capital by enhancing personal skills, competencies, and abilities (Lanzi, 2004). This research mainly explores the influence of women's education level on their participation in parliament. Therefore, female education level will be the focus variable in the estimation. Years of schooling refer to the number of years of education, which can measure the country's human capital stock. Since 2010, the average years of education have been used as an education indicator for calculating the Human Development Index (HDI) (UNDP, 2010). Therefore, we use mean years of schooling for women as the main variable of interest. Similarly, men's education level may also affect their political participation. If the number of seats held by men in parliament increases, it will have a crowding-out effect on the seats held by women in parliament, which will affect the proportion of seats held by women in parliament. Therefore, we take mean years of education for men as an independent variable and observe its impact on male parliamentary seats. By comparing the effect of men's and women's education levels on their political participation, we can enrich our research and get more comprehensive conclusions.

Gross Domestic Product (GDP) growth rate

The GDP growth rate measures the speed of economic growth by comparing the year-on-year changes in a country's economic output. A study using panel data regression models, focusing on the relationship between female political participation and economic growth,

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shows some influences between women's political participation and economic growth (Xu, 2015). There is also a study that shows economic development has had a positive impact on women’s status and equality (Clark et al., 1991). Therefore, the GDP growth rate is used as a control variable in the regression model.

Female population ratio

In different countries, the proportion of the female population in the total population varies. It would be inaccurate to ignore the proportion of women in the population and compare female parliamentary seats. Xu (2015) used the female population ratio as an independent variable to study how women’s political participation is affected. Therefore, we use the proportion of the female population as a control variable.

Income level

According to the human capital model, changes in human capital's growth rate depend on the degree of political stability and institutions' operation. Countries with lower income levels usually have unstable economic environments, and human capital will also show an unsustainable growth trend (Lucas, 1988). Therefore, we take the national income level as a categorical variable and divide the selected 91 countries into two groups according to the definition of income level by the World Bank. We put high-income and upper-middle-income countries (HIC) into one group (66 countries in total) and put lower-middle-income and low-income countries (LIC) into the other group (25 countries in total). In order to introduce it into the regression model, we use HIC as the base (value 0) and LIC as the comparison (value 1).

Female labor force participation

We want to study whether female seats in the national parliament are positively correlated with female labor force participation. The data we use refers to the proportion of women aged 15 and over engaged in economic activities. Since what we want to study is the closeness between the two variables, not the influence of female labor participation on their political participation. Therefore, female labor force participation will not be run as an independent variable in the regression model but will be used separately to do a correlation analysis with the proportion of female parliamentary seats.

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The expected sign of each variable shows as follows.

Table 1 Expected sign of variables (female)

Symbols Description Source Expected Sign

SEATfemale Proportion of seats held by women in

national parliaments World Bank

dependent variable EDUfemale Mean years of schooling for women,

population 25+ years UIS +

GDPgrowth

Annual percentage growth rate of GDP at market prices based on constant local currency (Aggregates are based on constant 2010 U.S. dollars)

World Bank +/-

POP Percentage of the population that is

female World Bank +

INCOME

High-income countries & Upper-middle-income countries = 0; Lower-middle-income countries & Low-income countries = 1

World Bank -

The data of all variables (except for INCOME) are the average value from 2014 to 2018

Table 2 Expected sign of variables (male)

Symbols Description Source Expected Sign

SEATmale Proportion of seats held by men in

national parliaments World Bank

dependent variable EDUmale Mean years of schooling for men,

population 25+ years UIS +

GDPgrowth

Annual percentage growth rate of GDP at market prices based on constant local currency (Aggregates are based on constant 2010 U.S. dollars)

World Bank +/-

POP Percentage of the population that is

female World Bank -

INCOME

High-income countries & Upper-middle-income countries = 0; Lower-middle-income countries & Low-income countries = 1

World Bank -

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Table 3 shows the descriptive statistics, including the observed value, minimum, maximum, mean, and standard deviation of each variable to observe the central tendency and dispersion of the data set we use. The mean value reflects the average level of each variable. In the selected countries, the average level of female parliamentary seats is 23.7%, years of education for women is 9.4 years, GDP growth rate is 3.4% per year, female population ratio is 49.6%, and female labor force participation rate is 51.1 %. We can find that the average proportion of female parliamentary seats in HIC and LIC is almost equal, while the average years of education for women in HIC are nearly twice that in LIC. It is an interesting finding, which seems to mean that women's education level has little influence on their political participation. The standard deviation is used to describe the degree of dispersion of the data. It can be seen from the table below that, except for the categorical variable of income level, the degree of dispersion of the data of other variables is not very high.

Table 3 Descriptive Statistics

HIC: High-income countries & Upper-middle-income countries (N: 66) LIC: Lower-middle-income countries & Low-income countries (N: 25) ALL: All countries selected for this research (N: 91)

Minimum Maximum Mean Standard Deviation

Variables HIC LIC ALL HIC LIC ALL HIC LIC ALL HIC LIC ALL SEATfemale 0.012 0.056 0.012 0.443 0.531 0.531 0.237 0.236 0.237 0.110 0.116 0.111 SEATmale 0.557 0.469 0.469 0.988 0.944 0.988 0.763 0.764 0.763 0.110 0.116 0.111 EDUfemale 6.428 0.925 0.925 13.780 11.812 13.780 10.883 5.556 9.419 1.896 3.451 3.390 EDUmale 6.695 1.844 1.844 14.459 12.005 14.459 11.063 6.604 9.838 1.887 3.019 3.001 GDPgrowth -0.007 0.002 -0.007 0.107 0.078 0.107 0.029 0.047 0.034 0.017 0.021 0.020 POP 0.242 0.472 0.242 0.541 0.530 0.541 0.493 0.504 0.496 0.051 0.013 0.044 INCOME 0.000 1.000 0.000 0.000 1.000 1.000 0.000 1.000 0.275 0.000 0.000 0.449 LABOR 0.161 0.218 0.161 0.691 0.802 0.802 0.514 0.503 0.511 0.095 0.180 0.123

In the correlation matrix, if the absolute value of the correlation coefficient is between 0 and 0.3, there is a weak linear relationship between the two variables. If the absolute value of the correlation coefficient is between 0.3 and 0.7, it means that there is a certain degree of the linear relationship between the two variables. If the absolute value of the correlation coefficient is between 0.7 and 1.0, there is a robust linear relationship between the two variables (Ratner, 2009). It can be seen from Table 4 that the correlation coefficient between the dependent variable and the focus variable is 0.106 but it is not significant,

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indicating that female parliamentary seats and female education years are not significantly correlated.

In addition, we found a robust linear relationship between the national income level and the focus variable (the absolute value of the correlation coefficient 0.705 > 0.7), so we need to consider whether there is a multicollinearity problem in the regression model. We use the variance inflation factor (VIF) to test whether there is multicollinearity between the selected variables. If the VIF value exceeds 4.0, or the tolerance is less than 0.2, there is a problem with multicollinearity (Hair et al., 2010). From Appendix 3, we can see that the VIF of all variables is less than 4.0 and the tolerance is more than 0.2, indicating that our model does not have the problem of multicollinearity.

Table 4 Correlation Matrix

Variables SEATfemale SEATmale EDUfemale EDUmale GDPgrowth POP INCOME

SEATfemale 1 SEATmale -1.000** 1 EDUfemale 0.106 -0.106 1 EDUmale 0.158 -0.158 0.977** 1 GDPgrowth -0.265* 0.265* -0.297** -0.267* 1 POP 0.333** -0.333** -0.018 0.035 0.050 1 INCOME -0.004 0.004 -0.705** -0.667** 0.406** 0.108 1

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

5.3 Regression Model

In order to study how women’s parliamentary seats are affected by women’s years of education, we use a linear regression model to test them empirically. In addition, we enriched our empirical test by establishing a regression model with male parliamentary seats as the dependent variable and male years of education as the independent variable. The equations are as follows:

𝑆𝐸𝐴𝑇𝑓𝑒𝑚𝑎𝑙𝑒𝑖 = 𝛼 + 𝛽1𝐸𝐷𝑈𝑓𝑒𝑚𝑎𝑙𝑒𝑖+ 𝛽2𝐺𝐷𝑃𝑔𝑟𝑜𝑤𝑡ℎ𝑖+ 𝛽3𝑃𝑂𝑃𝑖+ 𝛽4𝐼𝑁𝐶𝑂𝑀𝐸𝑖+ 𝜀𝑖

𝑆𝐸𝐴𝑇𝑚𝑎𝑙𝑒𝑖 = 𝛼 + 𝛽1𝐸𝐷𝑈𝑚𝑎𝑙𝑒𝑖+ 𝛽2𝐺𝐷𝑃𝑔𝑟𝑜𝑤𝑡ℎ𝑖+ 𝛽3𝑃𝑂𝑃𝑖+ 𝛽4𝐼𝑁𝐶𝑂𝑀𝐸𝑖+ 𝜀𝑖

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𝛼 = Intercept; 𝛽𝑛 = Estimate of coefficient; 𝜀𝑖 = Error term; Each cross-sectional observation is “i”

𝑆𝐸𝐴𝑇𝑓𝑒𝑚𝑎𝑙𝑒𝑖 = Proportion of seats held by women in national parliament, average value from 2014 to 2018

𝑆𝐸𝐴𝑇𝑚𝑎𝑙𝑒𝑖 = Proportion of seats held by men in national parliament, average value from 2014 to 2018

𝐸𝐷𝑈𝑓𝑒𝑚𝑎𝑙𝑒𝑖 = Mean years of schooling for women, average value from 2014 to 2018

𝐸𝐷𝑈𝑚𝑎𝑙𝑒𝑖 = Mean years of schooling for men, average value from 2014 to 2018

𝐺𝐷𝑃𝑔𝑟𝑜𝑤𝑡ℎ𝑖 = GDP growth rate, average value from 2014 to 2018

𝑃𝑂𝑃𝑖 = Female population ratio, average value from 2014 to 2018

𝐼𝑁𝐶𝑂𝑀𝐸𝑖 : High-income countries & Upper-middle-income countries = 0; Lower-middle countries & Low-income countries = 1

On this basis, we study further whether income level will affect education's influence on women's parliamentary seats, so we add the interaction term of schooling years and income level. The equations after adding the interaction term are as follows:

𝑆𝐸𝐴𝑇𝑓𝑒𝑚𝑎𝑙𝑒𝑖 = 𝛼 + 𝛽1𝐸𝐷𝑈𝑓𝑒𝑚𝑎𝑙𝑒𝑖 + 𝛽2𝐺𝐷𝑃𝑔𝑟𝑜𝑤𝑡ℎ𝑖+ 𝛽3𝑃𝑂𝑃𝑖 + 𝛽4𝐼𝑁𝐶𝑂𝑀𝐸𝑖 + 𝛽5(𝐸𝐷𝑈𝑓𝑒𝑚𝑎𝑙𝑒𝑖× 𝐼𝑁𝐶𝑂𝑀𝐸𝑖) + 𝜀𝑖

𝑆𝐸𝐴𝑇𝑚𝑎𝑙𝑒𝑖 = 𝛼 + 𝛽1𝐸𝐷𝑈𝑚𝑎𝑙𝑒𝑖+ 𝛽2𝐺𝐷𝑃𝑔𝑟𝑜𝑤𝑡ℎ𝑖 + 𝛽3𝑃𝑂𝑃𝑖+ 𝛽4𝐼𝑁𝐶𝑂𝑀𝐸𝑖 + 𝛽5(𝐸𝐷𝑈𝑚𝑎𝑙𝑒𝑖× 𝐼𝑁𝐶𝑂𝑀𝐸𝑖) + 𝜀𝑖

After adding the interaction term, multicollinearity may occur because the interaction term contains other independent variables. Centering the variable (standardizing the variable by subtracting the mean) is a simple way to reduce multicollinearity (Frost, 2017).

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6. Empirical Results

Table 5 shows the regression results. In Model 1, we input all independent variables into the regression model, and the focus variable is not significant. The GDP growth rate is negatively significant at a significant level of 1%. The proportion of the female population is positively significant at a significant level of 1%. The lower level of income is not significant. Model 2 shows the output results obtained after centralized processing of the interaction term of female education years and income level. We observe that in Model 2, the significance of the focus variable has changed, being positively significant at the 5% significance level, and the interaction term itself is negatively significant at the 5% significance level.

These results show that the impact of women's years of education on women's parliamentary seats has no explanatory significance. However, the impact of women's education level on women's parliamentary seats will be affected by income levels. From the output of Model 2, we can observe that in HIC, the proportion of women's parliamentary seats increases by 1.1% for each year of increase in women's years of schooling. In comparison, in LIC, the proportion of female parliamentary seats will decrease by 0.8% for each year of increase in women's years of schooling.

Table 5 Effects of independent variables on dependent variables (female)

Dependent variable: SEATfemale (N:91) Interactive: EDUfemale * INCOME

Coefficient

Independent variables Model 1 Model 2

(Constant) -0.180 -0.225* (0.128) (0.127) EDUfemale 0.005 0.011** (0.004) (0.005) GDPgrowth -1.784*** -1.818*** (0.593) (0.581) POP 0.834*** 0.799*** (0.245) (0.240)

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INCOME 0.050 0.034

(0.035) (0.035)

Interactive -0.019**

(0.009)

Standard error in parenthesis

*, **, *** refer to 10%, 5%, 1% significance levels, respectively

Then we observe how male education level affects the proportion of male parliamentary seats. From Table 6, we can find that the influence of men’s schooling years on the proportion of seats held by men in the parliament is negatively significant at the significance level of 10%. Income level can also affect the impact of men's years of education on men's parliamentary seats. In HIC, the proportion of men's parliamentary seats decreases by 1.2% for every year's increase in men's schooling years. In contrast, in LIC, the proportion of men's parliamentary seats increases by 0.6% for every year's increase in men's schooling years. It is also worth noting that the interaction term is only marginally significant at the 10% significance level in this model.

Table 6 Effects of independent variables on dependent variables (male)

Dependent variable: SEATmale (N:91) Interactive: EDUmale * INCOME

Coefficient

Independent variables Model 1 Model 2

(Constant) 1.194*** 1.215*** (0.126) (0.125) EDUmale -0.008* -0.012** (0.005) (0.005) GDPgrowth 1.801*** 1.828*** (0.587) (0.579) POP -0.797*** -0.740*** (0.244) (0.243) INCOME -0.059* -0.042 (0.034) (0.035) Interactive 0.018* (0.009)

Standard error in parenthesis

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We can see a positive correlation between female parliamentary seats and female labor force participation from the correlation scatter diagram (Appendix 4). We observed the Pearson correlation coefficient (r-value), which is used to measure the linear correlation between variables, and found a significant correlation between the two variables at a 1% significance level (Table 7). From the correlation coefficient (0.278), we can see a weak positive correlation between the two variables: female parliamentary seats and female labor force participation will slightly increase as each other increases. They have the same trend of change, but the magnitude of the change is not apparent. The empirical evidence supports our hypothesis that the share of women’s seats in the national parliament is positively correlated with women’s labor force participation in the labor market.

Table 7 Correlation method

Variables SEAT

r-value p-value

LABOR 0.278 <0.01

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The goal set out for this thesis is to determine whether there is a relationship between the number of years of education for women and the number of seats women hold in the national parliament. The hypothesis, as stated previously, is that more years of education will lead to higher national political activism among women. The results show no significant relationship between female education level and the female seats in parliament. It would be expected that with more education, more women would be politically active and that the value would be higher since higher levels of education have been seen to be beneficial for moving into the political field. It is an unexpected result, and we will try to explain why this could have happened.

It has been mentioned in the theoretical review that patriarchy and a lack of female role models in politics can be reasons for why, despite increasing levels of higher education of women, parliamentary participation does not increase. As previously mentioned, a patriarchal structure where women are expected to stay in the private sphere and focus on caring for a family and the household is still central to many cultures, contributing to these barriers for women to enter higher-level politics. Kenworthy & Malami (1999) suggest a few reasons why inequality in politics is unrelated to education levels in different countries. They suggest several reasons: when women gained suffrage, cultural attitude towards women, the number of women in professional occupations, and the electoral system. Andersson's (2020) research showed that the type of election system has a decisive impact on women's political representation. The proportional election system is more conducive to women's political representation. However, this result was also affected by the country's economic development level, level of democracy, gender quotas, and the number of parties. Since our research is cross-national, including countries from different regions and different cultural situations, it is affected by many of the above factors, which may cause the empirical results we obtained to be insignificant. Uopn adding factors such as democracy index, GII and HDI we noticed that these were highly multicollinear and gave insignificant results so we decided to exclude them from the results. By professional occupation, we mean an occupation that requires special education to practice in that field.

Another possible reason for the low correlation between seats in parliament and education level is that women and men differ in their preferred major when attending higher education. It means that even with an increasing number of women in higher education,

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it does not necessarily mean that more women enter fields that are currently male-dominated, such as politics, business, and economics. Women are more likely to choose to study humanities, languages, sociology, education, and psychology. Men tend to go towards business, economics, engineering, and social sciences (Kugler et al., 2021). Out of these majors mentioned, College Consensus ranks schools, education, and student reviews, rate economics, and business degrees to be the most beneficial to pursue a career in politics (College Consensus, n.d). In general, women tend to sign in areas that lead to lower-paying jobs than men. One reason why an increase in female enrollment in universities does not significantly affect the existing inequality in wages between women and men (Grogger & Eide, 1995).

It is also important to note that the results found that income does affect the number of seats held by women. For the higher-income countries, there was increasing political participation with each increasing year of education. Though there is lacking literature on national income level and its effect on political participation and education, the literature finds that individuals with higher income levels are more likely to pursue a political career. It makes it the result that was found to be expected. In lower-income countries, the number of seats held by women decreases as the years of education increase. Considering that better-off individuals are also more inclined to engage in political activities, it could also be assumed that economic inequality is smaller in wealthier nations. There will be more political participation by women since their socio-economic status is higher, which makes it easier to engage in political activity. We have not located any previous literature on income levels of whole countries and women's political participation specifically, which makes it difficult to argue for this with literature backing. It could be looked into further to see why there is no varying female political participation based on income level.

Dawn et al. (2018) propose three reasons women might be underrepresented in politics despite increasing education and increasing professional attainment. The paper suggests hostility towards female candidates, double standards between men and women, and what they call the double bind. Their research, which was conducted in the United States, found evidence of the double bind but not of the other two proposed reasons. The double bind suggests that voters favor candidates married with children, which creates a tricky balance for candidates to keep between family life and a successful political career. For example,

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in American politics, motherhood and family life have become increasingly important (Deason et al., 2015) to display a traditional family role at the same time as running for office can create this double bind. It may penalize women more than men because of the more significant burden on women when raising children. Another paper performing the same tests in Malawi showed the same results (Clayton et al., 2019). Another study of Latin America could see this preference in voters (Schwindt-Bayer, 2010). However, there are examples of childless female politicians that are highly successful, for example, German Chancellor Angela Merkel. However, it would be untrue to say that the numbers of elected women are not rising, but perhaps due to the short period of our research, we are unable to see this change.

When looking at male education level and male seats in parliament, we see a marginally significant impact of men's schooling years on their parliamentary seats. However, the income level's impact on the influence of male education on male parliamentary seats is opposite to that of females. It is easy to explain. The ratio of male and female parliamentary seats has a crowding-out effect on each other.

Labor participation and female parliamentary seats have a positive correlation which is expected, meaning that the two variables move together and as female labor participation increases, so do female parliamentary seats. There may also be the case of reverse causality here that they both influence each other. A study by Zhike & Rudai (2018) shows that the improvement of the status for women worldwide has a positive impact on female employment opportunities. They also explain how women tend to focus on different issues as politicians. Swamy et al. (2001) found that countries had less corruption when there were higher levels of female political participation. Ergas & York (2012) saw that air pollution is lower where women have a higher political status. It could signify those women are more interested in human social concerns, which can benefit increased female labor force participation (Zhike & Rudai, 2018). Rosenbluth and Iversen (2008) also try to explain why we can see that there is also a lower level of female representation in politics with lower labor force participation for women. Over the past three decades, female political representation and their representation in the labor force has risen in tandem. The paper by the authors mentioned above suggests that more women in the workforce make voters more accustomed to women in leadership roles and makes them more open to seeing women in political roles (Rosenbluth & Iversen, 2008).

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Analysis shows that the electoral system substantially impacts how much female labor participation affects their political participation. In some political systems, it is more critical with seniority, and women can be hurt more than men by this since their career can be interrupted by, for example, childcare. Where the country is located also plays a part. It has been seen that in wealthy democracies, women have been more successful at entering male-dominated fields, politics included (Rosenbluth & Iversen, 2008).

Kenworthy & Malami (1999) has found a strong correlation between women in professional occupations and seats in parliament held by women. They argue that women’s professional careers and relevant work experience have a more substantial influence than just higher labor force participation in general. However, it could be argued that these go hand in hand. However, to return to the paper by Rosenbluth and Iversen (2008), women are at a disadvantage when jobs require uninterrupted tenure, inflexible hours, and potentially long hours, which can inhibit women in both political and other professional careers.

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This thesis aims to study the influence of women's education on women's political participation and observe whether women's participation in the labor force and women's political participation in various countries show similar trends. Previous literature has no conclusive answer to the proposed research question. Positive relationships have been found since education gives people more excellent communication skills, leadership training, analysis skills, and organizational skills, which can be helpful in a political career. However, some countries see that female education positively impacts women's political participation, while others do not see the same results. The US has a high enrolment of women but a relatively low female political participation rate in parliament. In contrast, countries with low literacy rate and low income such as Uganda have a relatively high participation rate in parliament. Some studies argue that education is essential for political participation, while some find no relationship.

Empirical results from this study show that the relationship between women's parliamentary seats and women's years of education is not significant. They will not affect each other, and the country's economic level does not significantly impact women's political participation. This result caused us to have to consider possible explanations as to why this is. The prevailing patriarchal structure in politics causes women to have barriers to entering this field. There is also the fact that women tend to choose university majors which are not directly connected to a political profession such as psychology, education, and languages, and that generally leads to lower-paying jobs. It can also be related to something as simple: women have less interest in pursuing a political career than men. Moreover, the double bind can inhibit women to a more considerable extent than men since women are expected to carry a heavier burden of child care. Despite no legal restrictions to women in parliament, the cultural attitude towards women and their presence in the labor force in some countries can cause fewer women to be elected for office.

The results also show a significant relationship between women's seats in parliament and the country's income level. There has not been enough research in this area to know for sure why this is. However, previous research shows that individuals with higher household incomes are more likely to start a political career. It would be expected that more high-income individuals in a high-income country would then be an expected relationship to see. For policymakers, merely increasing education investment will not

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significantly help reduce gender inequality in the political area or even the entire labor market. It requires better economic development as a prerequisite.

8.1 Limitations

There are limitations to this study which we discussed in this section. Conclusions are drawn across many countries located worldwide, which means that we assume that they are all in the same situation politically and culturally, which they are not. These differences may affect either of the measured variables. The difference in income and tuition fees for those who go on to attend the university might also be relevant, there may be different situations in different countries. Further, not all countries have sufficient data on either year of education for women, labor market, or parliament participation for women which means that a selection has taken place where not all countries have been included. 91 countries are included in the study, but more would give an even better result and make conclusions drawn more reliable. The smaller sample size may be a limitation. The study will use studies on human capital, education, women's role in politics, and what affects these variables. The data is only regarding women's ratio to men in education, but it does not specify what they are studying or how many graduates from higher education institutions. It also does not consider at what level the individuals are studying at their university. Since we are looking at all levels of schooling, perhaps the change is more significant as the education level increases, which cannot be seen here. For example, if someone has one, two, or three years of schooling, perhaps it would not make much of a difference in the political field. However, perhaps the more significant change lies when we get to tertiary education, meaning up to over 12 years in school.

For further research countries could be divided by other indicators than income, such as HDI, degree of democracy or gender equality to see if it has a larger impact on women's political participation and labor participation. From the current regression the results show that even with an interaction effect the impact is small. This would be interesting in order to see what other factors impact gender equality in politics and in the labor force.

References

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