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Influences to Equal Gender Representation in Democracies

Honors Thesis

International Studies: Diplomacy

Political Science

Hanna K. M. Franck-Larsson

Committee: Dr. Staci Rhine (chair), Dr. James Allan and Dr. Lori Askeland

Wittenberg University, Spring 2012

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Introduction and History of Women in Politics

In 1893, New Zealand became the first country to grant women the right to vote. Since

then, the great majority of countries in the world have begun allowing women to vote, as well

as running for political office. In New Zealand, it was not until 1919 that women were

allowed to run for office, but most countries have granted the two rights at the same time. In

the last few years, the number of women that have made their way to political office

worldwide has increased, in some places more dramatically than others. However, not all

countries allow women to participate in politics, and in some places the percentage of women

in political office has been standing still for over 50 years. On the positive side, the general

trend is that the number of women in politics is increasing, but unfortunately at a painfully

slow rate. In some countries, there has even been a decrease in percentage of female

politicians in recent years.

The United States, Norway, and Japan have never had a woman as the head of state or

government, but less developed countries such as Chile, Liberia and India have already passed

this stepping-stone. In general, many less stable or even underdeveloped countries have a

higher number of female political leaders in the highest office than more developed countries.

Sometimes the countries are not stable enough to keep an executive leader for their full term,

but they have at least elected women as leaders. However, this research will not focus on

whether or not a country has had a woman as a head of state or government, but rather on the

percentage of women in legislative office or parliament, both in the upper and lower house.

The reason for this focus is that even though the head of the state makes a statement about the

tolerance, equality and progress in a country, it can sometimes be an isolated event and not

reoccur again for many years. The percentage of women in parliament, on the other hand,

shows a clearer picture of the trends and tendencies of a country, and can also be measured

easier from election to election. The percentage of women in parliament offers a broader base

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of examples to compare and contrast, and the larger number of countries makes the potential

result of the data analysis more reliable as an index for gender equality in politician life. It is

still important to pay attention to the women that are executive leaders, especially as they

become role models for other women politicians to follow.

Many developed countries have a high percentage of women in national legislature,

which may seem natural. An unexpected fact is that some countries that are usually seen as

lacking in equality actually have almost as high of a percentage of women elected that some

of the developed countries have. Another surprising piece of information is that some

developed countries have such a low percentage of women in office that they can be

compared to some of the poorer and less developed countries in the world. This observation

may seem unforeseen, especially since some countries have drastically increased their

percentage of female representatives during the past few years, sometime without any

apparent change in political, social, economic, or cultural variables.

The following question will be explored in this paper: What are the reasons that

some countries have a higher percentage of female representatives in their national

legislature than others? The dependent variable is Percent Women Politicians in Legislature

(Upper and Lower House). The independent variables that will be analyzed and discussed

include the existence of quotas, type of quotas, level of education for women, level of women

in the workforce, type of political system, and level of development. These variables will be

looked with both in univariate, bivariate and multivariate analysis. In the end, only a higher

level of women in the workforce and a more pluralistic political system proved to have a

statistically significant relationship with higher percent women politicians. The reasons as to

why these variables are the only ones with a stronger relationship to the dependent variable

will be discussed at the end of the paper.

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Literature Review

In order to set up a reliable data analysis system and to choose factors and variables

that may be influential in predicting a higher level of women politicians, it is crucial to look at

the variables that have been used in past research on this topic. Although this paper cannot

evaluate all of the below mentioned factors, it is important to be aware of the ones at hand and

their possible relationships with each other. Looking at research over the past few years paves

the way to finding the variables most influential in the current situation for women politicians

in the world.

Education

Education is one of the most crucial keys to development, because through the impact

of knowledge more doors are opened for both men and women in the workforce and in

politics. Education is necessary for the development of a country and leads to the

empowerment of women, awareness of opportunities given and developing new skills.

Realizing these options can lead people to take an interest and involvement in politics as a

way to change the current situation. A more educated population is often considered an

important factor influencing a more equal level of representation between men and women in

politics. Generally, it also leads to a higher percentage of workers in skilled labor, who tends

to have children at an older age (Krook 2010). Both these two reasons make it more likely for

women to run for office because they have more resources and spend less time at home taking

care of fewer children. There is a strong correlation between women’s overall rates of

education, labor force participation, national development and more influence in politics for

women, according to Krook (2010). Krook has found that in order to successfully analyze

today’s situation, there is a need for a comparison between women and men, not just a study

of the reality for women. If a country generally lacks resources for the improvement of both

women’s and men’s social balance, the situation is different than if there is a lack only in

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resources for women. When looking at the education levels or workforce participation for

women, there can also be clues to the development in the country when looking at similar

research for the men.

Jalalzai and Krook (2010) agree that a higher level of women’s education in a country

will produce more female candidates to run for political office. They also found that even

though women in executive positions come from a variety of geographic locations, women

elected for office are usually more privileged financially and more highly educated than the

ordinary population. Not just any education makes women more likely to run for office, but

having the monetary resources is a crucial element when considering a political campaign. To

possess the resources to attain a higher level of education requires financial means in most

countries, and those who do are more likely to also have access to sponsors and attaining the

financial means needed to run a political campaign.

One example of a case study is Burrell (1994), who has looked at female candidates

for seats in the United States’ House of Representatives between 1968 and 1992. She

compared their experiences, as well as presence and performance to those of their male

colleagues. In past research, she found that women usually lacked specific education, skills

and resources, such as a law degree, that would advance a political career. As a politician,

there is a certain expectation to have a law degree or some other kind of graduate degree.

Having the detriment of belonging to the minority gender in politics, women that lack a law

degree, further education, or experience in business or politics, are even more disadvantaged.

Political System

The most common way to measure types of political system is by looking at whether it

is majoritarian or proportional. There are many different systems out there, and most of them

are not strictly majoritarian or strictly proportional. Rather, there is a variety of systems. What

one usually does is to divide the different systems into a scale that ranges from most

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majoritarian to most proportional. A majoritarian system is a so-called “winner takes all”

system, where the party with the most votes wins the seat. A proportional system uses the

percent votes received to divide up the seats between the parties proportionally. In countries

with a so-called Proportional Representation (PR) system, there are generally higher

percentages of female politicians as the system opens up for the possibility of more candidates

that otherwise may not have had the opportunity to run (Inglehart and Norris 2003). In an

election with a system of proportional representation, parties receive the percent seats in the

office that is equal to the percent votes it received in the election. In a country with a more

majoritarian system, the party that gets the majority of the votes wins the seat. In a country

with a PR (proportional representation) system, greater party competition may increase the

access points for female candidates, but it does not guarantee that they are elected. Krook

(2010) has looked at how the political elections systems influence representation. She reports

that the percentage of women in politics is in general higher in countries with a PR system, in

agreement with Inglehart and Norris’ research. Krook argues that PR systems are not the only

factor influencing female political participation, but she does agree that the variable is a

reliable indicator.

Jalalzai and Krook (2010) found that women are more likely to serve in parliamentary

systems, and more often as prime ministers than as presidents when serving in executive

positions. Women are more likely to hold a prime minister position than the position of

president. This could be because it tends to be easier to overthrow a prime minister since they

are not directly elected, while presidents are. As an appointed official, it is not guaranteed that

the prime minister will have the support of the people. Like Inglehart and Norris, these

authors also found that countries with PR systems have much higher levels of female

politicians than others. In addition, Jalalzai and Krook found that left-wing parties tend to

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have more female politicians than right-wing parties, based on the traditional gender roles

typically espoused by more conservative parties.

Furthermore, Paxton (2010) has looked at past research of Proportional Representation

(PR) systems that has shown that this particular political system is associated with higher

numbers of female politicians. In her own research, she has found that PR systems’ positive

impact on women’s political representation is steady and stable over time. She speculates that

it could be because with a PR system, party lists are used, leading to an increased chance for

the candidates on the list to win political office. If a candidate is on the list, the voters can

choose to mark the person’s name themselves and to make an active choice of what candidate

to vote for. In a majoritarian system there is no party list, and since the general view is that

men have stronger chances to become elected, the parties tend to name male candidates. Here,

the party will themselves decide on which candidate to put on the list and not leave it to the

voters to decide. Paxton’s research also shows that democracy as a political system does

affect women’s political representation over time, although there may not be an immediate

effect. She argues that democracy is still a good indicator for a higher percentage of women in

politics as it proves to be influential in the long-run.

Krook (2010) argues that both the PR system and the need for education, higher levels

of work opportunities and the level of national development is crucial to encourage the

participation of women in politics. In her research, she has found that one cannot look at one

isolated variable, but rather it is necessary to compare and contrast them all as they are

influencing each other. Krook argues that all of the variables are interrelated, but when

looking at political systems only, PR (proportional representation) systems are more

beneficial to women politicians.

There are, according to Matland, some PR systems that are superior to others. He

claims that PR systems that use so-called Higher District Magnitude “the parties have the

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chance to compete for and win several seats, [which] allow[s] them to go further down the

party list, where women are usually listed” (Matland, 2005, 103). Where High Electoral

Thresholds are used, the system “discourage[s] the creation of ‘mini-parties’ which often elect

only one or two representatives, usually male” (Matland, 2005, 103). Threshold is a minimum

limit of how many percent of the votes that a party has to receive to receive any seats at all. It

depends on the country, but some use a 3 or 4% minimum threshold. Using thresholds limits

the chances for parties that are very small to become elected, and instead more women from

the larger parties usually win more seats.

Caul considers the electoral system “an integral component in explaining women’s

representation … Party-list PR systems produce more women in parliament than plurality

systems [as] they are more likely to add women to the list in order to broaden their appeal and

balance the ticket” (Caul, 2010, 161). He has found that the perceived electoral risk with a

woman politician decreases when she is part of a group rather than as a sole candidate (161).

The most important way to improve the situation is, according to Caul, to work on bettering

the work the parties do to increase gender parity in seats in legislature.

A specific example of how political systems can change the situation for women is in

South Africa, where there was a large increase in women politicians after changes were made

in the political system. Hassim argues that “electoral systems have been shown to have the

most significant impact on the proportion of women elected … PR List system[s] … allows

progressive party leadership to override traditional sentiments against women’s election”

(Hassim, 1999, 206). She found that when South Africa changed from a majoritarian system

to a more PR system there was a substantial increase in the percent women candidates and

politicians elected.

Labor Force Participation

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Most women that run for political office are, or have been, involved with different

kinds of political work in the workforce. Research suggests that women in the official work

force are more likely to become interested in, and enter, political life because they are

subjected to many more opportunities and possibilities for doing so. In a systematic review of

the research, Lawless (2005) found that even though women and men are today more

similarly situated professionally, economically and politically, women are less likely to run

for office, mostly because women still do not participate as much as men in the labor force.

Jalalzai and Krook (2010) highlight that higher levels of education and labor force

participation for women also lead to a higher level of female representatives.

Norris (2001) found that for both men and women, family and work situation play a

big role in the decision to run for office. If a potential candidate’s family includes younger

children, the wife may be expected to stay at home with them, providing the opportunity for

the husband to run for office. Women themselves are more likely to run for office after their

children have grown up and they have returned to the full-time workforce. Lawless (2005)

found that women are less likely to run in areas with a traditional culture, such as the

American southern states. In these regions, the expectations are often higher on the woman to

take care of the life at home, the house and children.

Burns and his fellow authors (2001) have studied the origins and solutions of gender

inequalities worldwide. Among the variables they found that influence women’s access to

political involvement are unequal access to education, differences in income and disparities in

occupational level. All of these factors play a large role in influencing women’s access to

political office. The research of both Burns and Lawless show that countries with a higher

percentage of women in the work force are more likely to have a higher percentage of female

members of parliament. Prejudice against women means a larger challenge to win office,

which can, according to Niven, be related to the fact that “women are more likely to pursue

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home-based or low-status work than are men and because women officeholders are

comparatively rare” (Niven, 2010, 152). Lacking the experience from the professional sphere

certainly influences women’s opportunities to seek to become elected for public office.

In conclusion, women in many countries often hold lower levels of occupations than

men do, which does them a disservice when it comes to the opportunity to run for office. The

expectation that women should first and foremost take care of the private sphere before they

go out in the public life will often make women stay outside of the workforce, and because of

that not become subject to opportunities of different kinds of political positions, leadership

positions and advancement in the workplace. Because this prejudice, women are as a group

seen as less experienced in the political life, which can hinder their likelihood of running for a

political position.

Level of National Development

In general, researchers have found a positive relationship between the levels of

national development and the percentage of women in political office (UN 2005).

Development can be measured in a number of ways, but the one used in this paper is

constructed by the United Nations and is a combination of education (main years of schooling

and expected years of schooling), health (life expectancy at birth), and living standards (Gross

National Income per capita). All of these variables add to a more stable and prosperous

society, which in general will aid in the process of helping women develop their skills in a

number of areas, such as through workforce participation and access to higher education.

There seem to be limitations to this theory, however. Inglehart and Norris (2003) have found

that some of the least developed countries in the world, such as South Africa, Mozambique

and Venezuela have a higher percentage of female politicians than some of the more

developed countries, such as the United States, Japan, and France. The authors argue that

even though education and professional statues serve as a facilitator for women´s

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empowerment, structures in some societies will hinder their way in to political office. These

structures can exist in any part of the world, not just in less developed countries. Krook (2010)

agrees with Inglehart and Norris and points out that even though national development can

prove to be influential for female representation, there are quite a few countries with a low

level of national development, and a high level of females in political office. As examples,

Krook mentions Sweden and Rwanda, both with almost fifty percent female representatives,

but on completely opposite sides of the development scale.

Research generally suggests that gender inequality, including unequal political

representation, is greatest in the countries with larger economic inequality. Where there are

fewer resources to provide for equal economic opportunities for men and women, there are

typically also fewer options to increase equality of access to the political process. Jalazai and

Krook (2010) studied and found a positive relationship between the presence of a female head

of state in any given country and lower levels of parity of women to men in education, life

expectancy, education, and income. It seems that if a woman is elected to head a country, an

increase in women running for office will follow, as well as an improvement in opportunities

for education, income and health care. Having an example of a woman executive leader can

inspire other women in various ways, as well as increasing the acceptance of female

leadership.

Quotas and Affirmative Action

There has been a growing discussion of quotas as a political question over the past few

years. Paxton (2010) argues that national quotas, where a number of women are guaranteed a

seat in the parliament, positively affect women’s presence in politics. However, earlier

research, for example Krook (2003), argued that not all quotas may increase the percentage of

women in office. Paxton agrees, but says that it is still an important tool to gender equality in

politics. Jalalzai and Krook (2010) mentions the quotas for women in the parties’ nomination

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lists as a factor that has been influential in promoting female politicians. When there is a

quota in place, parties have to put a certain number of females on their lists, and by doing so,

they increase the theoretical chances of them becoming elected. Many countries reserve seats

for women politicians to increase gender parity, often between 20 and 30%. These reserved

seats are called quotas and could possibly positively lead to a higher level of women

politicians in parliament.

The United Nations (2005) showed in their report that most countries with measures in

place to promote women’s presence in national parliaments have similar measures at the local

level. They are usually used in countries where there are close to no women in parliament to

begin with. Since, as earlier argued, proportional representation also produces stronger female

participation in politics, combining quotas with PR seems to provide the best chance of

achieving more equal levels of women and men politicians

One example of quota use is in Rwanda, where the country was left after the genocide

of 1994 with a 70% female population. The country uses quotas on all levels of the political

spectrum, due to the fact that “gender equality has been has been imposed as part of a top-

down policy rather than through popular protest and mobilization” (Wallace, Haerpfer and

Abbott, 2009, 112). In other words, the quota systems were implemented when the country

attempted to rebuild itself after the genocide, and those in charge decided on the quotas. One

has yet to see if there will be protests or acceptance of the quota system.

In Latin America, the use of quotas is widespread. According to Jones (1997), there

are two types of quotas, Rules for allocating slots within parties and National laws for the

allocation of slots. Del Campo explains that the latter ones are “shown to be much more

effective than the former ones mainly because of two reasons: in the first place, they are

applicable to all parties, and not just a few; and in the second place, laws for the allocation of

slots are being reinforced by the bureaucracy or the judicature, while the deployment of the

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parties rules depends on the interest, capacity and juncture of leaders of the same parties” (Del

Campo, 2005, 1707). The different quota systems are controlled by the government, which

makes it easier to get support for their actual implementation.

In his chapter on quotas in the book Women in Parliament: Beyond Numbers, Richard

E. Matland argues that for women, “bureaucratically-based systems that have incorporated

rules to guarantee women representation – that is, quotas – are a significant advantage”

(Matland 2005, 95). Especially in countries such as the Nordic ones, parties have adopted

quotas that guarantee 40 or 50% of their candidates to be women. These countries have, partly

because of their quotas, some of the highest levels of women politicians in the world.

Dahlerup, however, asserts that the reason that Scandinavian countries are so strong in this

area is not just because of the quotas, but that “for the most part the increase can be attributed

to sustained pressure by women’s groups within parties as well as the women’s movement in

general” (Dahlerup 2005, 147), although most parties have adopted their own quotas.

Other Factors

Many other factors have been found to influence women’s representation in

parliament, according to previous research, in particular, religion, which will be briefly

summarized here even though it will not be analyzed because of data challenges. Earlier

research done by Norris (2001) has found that Protestant-dominated countries tend to have a

higher percentage of female politicians than countries with another dominant religion. More

recent research, by Inglehart and Norris (2003), however, suggests that Protestant and

Catholic countries have predominantly higher levels of female politicians than countries with

all other kinds of religions. Jalalzai and Krook (2010) have looked at the past research arguing

that Christian countries tend to have more women in politics and found it to be true. The type

of culture and the most prominent religion in a country seem to play a role in influencing

women to run for office.

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Burns (2001) has found that especially in developing countries, women have greater

involvement in religious life and men have greater involvement in political life, which

suggests that cultural inequalities between genders shape their different focus. This may be

because women are often given less space in political life and then turn to religion to channel

their interest and energy.

Another variable that, will not be discussed due to of lack of data, is openness to

women in higher positions. However, scholars have previously found that there is a positive

relationship between openness to women in higher positions and a higher level of women in

parliament. Therefore, it is an important variable to mention in this context. The judgment as

to whether a country is open to women in high positions is a complicated one to make, as it is

not easy to determine what factors into it. Sanbonmatsu (2006) chose to look at a variety of

factors, such as the numbers of women politicians in the United States, the representation in

parties, how candidates are recruited, barriers for female politicians and the general pattern of

women in politics over the country, among others. Her research showed that the lack of

women politicians is not due to lack of support, but because there are few candidates, which is

why there is a need for more women politicians as role models and inspiration.

Sabbonmatsu’s research also proves that women are not disproportionately likely to lose their

political races, contrary to previous research. But Sanbonmatsu did find that voter stereotypes

about gender are widespread. As an example, women are mostly seen to be interested in

typical “female” issues, such as questions considering children and the home.

Dolan (2004) found that there are stereotypes about female candidates for political

office, including the notion that women are better suited to deal with education, environment,

and issues related to children. Women are generally seen as unable to handle crime, foreign

affairs, and economic problems. This makes the challenge to portray themselves as reliable

candidates harder.

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Thomas (2011) studied the strategies used by Michelle Bachelet and her opponents in

the Chilean elections of 2005/2006. Bachelet was described by her opponents as “too

feminine” and “not strong enough” in her leadership. Bachelet turned this to her favor by

arguing that this showed the Chilean prejudice against female leaders. Chile is known to be a

very sexist (“machista”) country, and the fact that Bachelet won the election says something

about her powerful leadership style and the way she portrayed herself during the campaign.

She showed that a woman can successfully be both “feminine” and “masculine” in her

leadership style. Bachelet was the first woman president in Latin American history who was

not a wife, widow or daughter of powerful male politicians. But she had earlier served as the

Minister of Defense, which was necessary as an experience in order to be able to win the

election.

Niven discusses the assumptions made by some party leaders about women, and

argues that their lack of support for women candidates is “not because they view women as

inherently incapable, but because their understanding of the political landscape (the

distribution of gender among professionals and officeholders) leads them to believe men are

more likely to succeed” (Niven, 2010, 152). Many women politicians have experienced

prejudicial treatment because of their sex, such as comments about not being in the right place

in the public sphere, and to go back home to the private sphere (152). Such prejudice hinders

women from becoming selected for new responsibilities.

Finally, specific cultural differences are said to influence the equality of members of

parliament worldwide. Inglehart and Norris (2000) researched the World Value Surveys from

the early 1980´s, early 1990´s and mid-1990´s. They argue that, women and men´s lifestyles

and cultural attitudes have changed by the process of societal modernization, which has

started to influence their political preferences. These cultural changes have opened up space

for more women in politics, since traditional women’s chores do not exist to the same extent.

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When men and women divide up the responsibilities at home as well as in the workforce and

of providing for the family, the social systems are more prone to be beneficial to women

seeking leadership roles.

Jalalzai and Krook (2010) connect to the above mentioned reasons for fewer women in

office, looking at what is expected of women to run for office. They found that women are in

many cases more qualified than men, but must meet higher standards, both self-imposed and

external and therefore they are less likely to run for office. Hill (1981) has found that women

are less likely to get elected for office because of society’s expectations that they should take

care of their children and home rather than work. He argues that it is different from country to

country, but that there is a clear stereotype that women do not have the time required to hold

office, as they are in charge of the house. The situation has improved since this research was

done, but similar or the same opinions still exist in many countries.

Leadership styles may differ between men and women from culture to culture. One

example was found by Hassan and Silong (2008), who studied Malaysian women in

leadership positions. They found that the Malaysian male leaders are generally more goal-

oriented than the female leaders, while female leaders focus facilitating interactions more than

male leaders. This article portrays an example of a culture where political leadership is not

traditionally held by women, and as a result few women are involved with political life. This

kind of cultural difference tends to negatively influence women’s involvement in politics.

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Research Hypothesis

The level of education in a country is seen as an influential factor as to why a country

has a more equal level of men and women in politics. In order to find out if this assumption is

true, my first hypothesis is that there is a positive relationship between the percentage of

female representatives in national legislature and the percentage of women that obtain a

higher level of education.

Another variable that was important to take into consideration when looking at the

percent women politicians was based on the previous research done, type of election system.

Since countries with a Proportional Representation (PR) system are predicted to have more

female politicians, my goal was to see if that this argument proved true and held when

compared to the other factors. Using various different systems, some more majoritarian and

some more proportional, a scale was created that would aid in seeing if the assumption was

true. My hypothesis is that there is a positive relationship between more proportional

representational types of election systems and percent women in the upper and lower

houses.

Percent Women in the Labor Force was also seen as a reliable factor to influence the

existence of a higher level of female politicians. With more women in the official workforce,

the chance for more opportunities to become involved with political activities would

presumably be higher. By looking at both education and workforce participation, the chances

for women’s partaking in politics as candidates could increase. My hypothesis is that there

is a positive relationship between percent women in the labor force and percent women

in upper and lower houses.

By looking at the prevalence of quotas, my aim was to see if they did in fact have a

significant impact on the participation of women politicians. This research focuses on quotas

in the lower houses because there was a greater dataset to take advantage of than if looking at

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the upper houses. However, it is important to study not just the existence of quotas, but also

the types of quotas used by the different countries. I hoped that the variations between the

different countries would yield a clearer and more exact picture of the impact of quotas. The

hypothesis is that there would be a positive relationship between the use of quotas and a

higher level of women politicians in the lower and upper houses. The other hypothesis is

that there would be a positive relationship between stronger quotas and percent women

in parliament.

In order to control for other, overall influencing factors, attention was also paid to

level of democracy, using data provided by the United Nations. Looking at the different levels

of democracy could also potentially be crucial when determining the most influential factors

to a higher level of female politicians in the upper and lower houses of parliament in the

countries analyzed. The hypothesis is that there would be a positive relationship between

level of democracy and percent women politicians in lower and upper house.

The final factor taken into consideration in this paper was Level of Development, also

determined by the United Nations. Development consists of a number of factors, such as

education, economy and health care. Altogether they make up a diverse spectrum of factors

that contribute to one. The hypothesis is that there would be a positive relationship

between level of development and percent women politicians in the upper and lower

house.

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Body of Research

Data selection and Research Design

This research focuses on factors that influence a higher percentage of female

politicians in the lower and upper houses of legislature in countries worldwide. In order to

make a relevant database, I needed to narrow down the confounding factors and find the data

to transform them into variables. Initially, in fact, I had intended to use all countries for which

there was data, but after consideration the decision was made to focus only on recognized

democracies, for various reasons. First, having such a large number of countries to analyze

would make a more heterogeneous dataset, which would allow for other factors than the ones

chosen to influence the outcome. Second, countries without democratic rule also sometimes

have other suppressive laws that will undermine the chances for less privileged candidates,

such as uneducated, poor people and women to run for office. To instead focus on the

countries where there are at least some guarantees that women have rights and possibilities to

run for office was favorable. However, this is not to say that non-democratic countries always

lack female politicians. In fact, Rwanda, which is considered an autocracy, has one of the

highest levels of female politicians in the world. But the cut had to be made somewhere, and I

made the decision to only include countries that had scored a 4 (DEM) or a 3 (dem) on the 4th

democracy scale, Polity IV, released by the Political Instability Task Force (PITF) and funded

by the Central Intelligence Agency (CIA).

Number of Seats, Women Politicians and Percent Women Politicians

The first variable I took into consideration was the number of women politicians in the

upper and lower houses in countries. The dependent variable, percent women politicians,

came from data on total number of seats in the upper and lower houses, as well as the number

of women politicians. The data was taken from the Inter-Parliamentary Union (www.ipu.org),

an organization that “is the focal point for world-wide parliamentary dialogue and works for

Franck-Larsson 20

peace and co-operation among peoples and for the firm establishment of representative

democracy” (The Inter-Parliamentary Union). The Inter-Parliamentary Union cooperates with

parliaments around the world to collect data on their work and its work is closely related to

the United Nations. It is a globally recognized organization and the data is the most updated,

having current data up to the middle of 2011 at the time of this writing. As different countries

have election during different years, the data is from the last time that a country held an

election. In this paper, there is no distinction made between countries that appoint and those

that elect their upper house politicians, which is something to take into consideration when

analyzing the data.

Level of Democracy

There are various datasets that release information on the level of democracy for

countries worldwide. For this paper, Polity IV was chosen as the dataset to categorize

different levels of democracies. Polity IV bases their categorization on a number of factors,

eventually resulting in the different levels of democracy. A country that is very autocratic is

an “AUT,” less autocratic an “aut,” while the more democratic countries were labeled “dem”

for less democratic and “DEM” for the most democratic. The different levels were recoded

into 1, 2, 3 and 4 with 4 being the most democratic and 1 being the least democratic. In the

end, only 3 and 4 were used since the cutoff for the data was done based on the level of

democracy from this dataset.

Polity IV is the latest version of the dataset “Polity” that ranks countries based on their

political systems and other variables pertaining to the ways of ruling the country. The

conclusions about a country's level of democracy are based on an evaluation of that state's

elections for competitiveness, openness and level of participation. The measurements were

made in “mid-2011 … and an upper case ‘AUT’ indicates the country is governed by an

institutionalized autocratic regime (POLITY -6 to -10); a lower case ‘aut’ indicates that the

Franck-Larsson 21

country is governed by an uninstitutionalized, or ‘weak’ autocratic regime (other EXREC 1 to

5)” (Cole and Marshall, 2011, 37). For the more democratic countries, “an upper case ‘DEM’

indicates an institutionalized democracy (POLITY 6 to 10) and a lower case ‘dem’ indicates

an uninstitutionalized, or ‘weak’ democratic regime (other EXREC 6 to 8)” (Cole and

Marshall, 2011, 37). The researcher put together different variables into one categorization in

order to rank the different countries.

Type of Electoral System

The information on the different kinds of electoral systems came from the

International Institute for Democracy and Electoral Assistance (IDEA). This institute

produces information on different kinds of electoral systems and divided them into a number

of categories. The ones used in the dataset were List PR (List Proportional Representation),

Parallel (Parallel Systems), Alternative Vote (AV), FPTP (First Past The Post), MMP (Mixed

Member Proportional System), PBV (Party Block Vote), TRS (Two-Round System), STV

(Single Transferrable Vote) and BV (Block Vote). The different kinds of election systems

were divided into three different categories, ranging from more proportional, middle and more

majoritarian. The systems that fell under a proportional system and were recoded into a 3

were List PR, MMP and STV. For Parallel, recoded into a 2, was Parallel Systems. Finally,

the more majoritarian systems were recoded into a 1 and are the following: FPTV, AV, TRS

and PBV.

Level of Development

The data on level of development comes from the data that the United Nations

provides. The UN categorizes data on countries from Very High Development, High

Development, Medium Development and down to Low Development and Others. I

categorized this data into values from 1 to 4 where 4 was the highest (Very High Human

Development). The territories that did not have a level of development or where data was

Franck-Larsson 22

missing were categorized as missing data. The categorizations are influenced by education,

health and living standards, and are explained in more detail earlier in the paper.

Percent Women and Men in the Workforce

The data that described the percentage of women in the workforce and men in the

workforce also came from the data that the United Nations provide in their Human

Development Report annually. The male and females were divided into their own categories

and separated into columns. Both women and men’s participation in the workforce was

included originally, in order to see if a higher level of men in the workforce would influence

the result of women politicians in any way. The data was given in percent by the United

Nations.

Percent Women and Men with at least Secondary Education

In order to measure the level of education as a variable I decided to look at the

percentages of the population that had at least secondary education. This data came from the

United Nations Human Development Report, and was divided into levels separately for males

and females. The data on secondary education was chosen because a larger level of citizens

educated to the secondary level would provide more people with opportunities for the higher

education often needed to run for office. The data was given in percent by the United Nations.

Quotas in Lower House

The data for the quotas in the lower houses came from the Quota Project

(www.quotaproject.org), a project that partners with the International Institute for Democracy

and Electoral Assistance (IDEA), the University of Stockholm (Sweden), and the Inter-

Parliamentary Union (IPU). The data given was whether or not a country had quotas in their

lower house, to which they had responded by “yes” or “no.” Sometimes there was data

missing and in that case it was marked as missing in the dataset.

Type of Quota

Franck-Larsson 23

When looking at the types of quotas that were given in different countries, the

different ones were the following: Reserved Seats, Legislated Candidates Quota, Voluntary

Political Party Quota, and no quota or missing data. This data was also taken from the Quota

Project and their website. This data was re-coded into 2, 1 or 0 where 0 meant no quotas at all

or missing information. 1 meant Voluntary Political Party Quota and 2 meant Reserved Seats

and Legislated Candidates Quota. The higher the number was the stronger was the quota.

Reserved Seats and Legislated Candidates Quota are both strong because, as their names

imply, there are reserved seats or a percentage of the total number reserved for women

politicians. Voluntary Political Party Quota means that the parties will, if they so choose,

make half of their candidates on the ballot be women and half men. This practice is used

widely in the Nordic countries.

Franck-Larsson 24

Univariate Analysis

In order to understand the range and variety of data that has been found on the above

mentioned variables, the univariate analysis serve as a tool to describe these differences.

Lower House Data

The minimum number for percent female seats in the Lower House is 0%, at the

Solomon Islands. The countries with the highest percentages are South Africa and Sweden,

each with 45% female seats. The mean percent of female seats is 20, while the median is 19.

The mean and median are close to each other in this variable, suggesting that there are no

large outliers. This is probably due to the fact that the variable is measured in percentages.

The standard deviation is 11. Out of the maximum of 113 countries, 106 are represented in

this dataset, which is 93.8%. Table 1 shows all the descriptive statistics for my variables.

[Table 1 here]

Upper House Data

Looking at the descriptive statistics for the Upper House, one can see that less than

half of the countries have one. Only 47 out of the 113 countries have an Upper House, about

41.6%. In terms of the percentage of female seats, the minimum is 0% (in Liberia), and the

maximum is 47% (in Bolivia). The mean percent is 21, and the median is 19. Again, the

mean and the median are relatively close, as is often the case when studying the percentage.

The standard deviation is 11, and there is data on all of the 47 countries, which transcribes to

41.6%.

Education Data

On the percent of women who have completed at least secondary education, there is

data on 103 out of 113 countries, or 91.2% of the countries in this study. The minimum

percent is 1.50% which is Mozambique. The maximum is in Norway, with 99.30%. Hence,

not even 2% of the women in Mozambique have achieved secondary education while in

Franck-Larsson 25

Norway, almost all of the women have. The mean percent of women is 54.76%, and the

median is 57.60%, numbers that are relatively close, again suggesting that there are no large

outliers. The standard deviation is 27.75.

In the case of percent men with at least secondary education, the minimum is also in

the case of Mozambique, with a number of 6.00%. The maximum is also in Norway with

99.10%. The mean is 60.54% and the median is 65.60%, which are relatively close. The

standard deviation in males with at least secondary education is 25.58.

Workforce data

For the data on participation in the workforce, data was available on 109 countries out

of 113, or 92%. In the case of women in the workforce, the minimum is in Iraq, with 13.80%.

The maximum is held by Burundi, with 91.00%. The mean is 53.70% and the median is

53.50%, very closely aligned, suggesting few outliers. The standard deviation is 13.01.

For men in the workforce, the country with the lowest level of participating men is

Solomon Islands with 50.00%. The highest level is in Tanzania, with 90.60%. The mean is

74.32% and the median is 74.60%, two close percentages. The standard deviation in this case

is 8.25.

Level of Democracy

The level of democracy was either 3 or 4, as explained in the methodology section.

Level of Development

For level of development, countries are divided into four different groups by the

United Nations, ranging from Very High Human Development, High Human Development,

Medium Human Development, Low Human Development and Others. In order to make an

analysis, the levels of development were re-coded on a scale from 1 being the lowest level of

development, and 4 being the highest. Out of 113 countries there is data on 111, or 98.2%.

The median level of development is 3 (High Human Development), which could be expected

Franck-Larsson 26

since all of the countries selected for the dataset are at the top level of the democracy scale.

When looking at the quartiles, the 25th

quartile is 1, the 50th

quartile is 3 and the 75th

quartile

is 4.

Electoral System

In order to analyze the data on electoral system and its effect on the level of female

politicians, the different election systems were divided into three categories, where List PR,

MMP and STV were re-coded into 3, the most proportional systems. Parallel was re-coded

into 2 as it is halfway in between the proportional systems and majoritarian. FPTP, AV, TRS,

PBV and BV were re-coded into 1, being the most majoritarian of the systems. Out of the 113

potential countries data on 4 of them was missing, so in this dataset 96.5% of the countries

were present. The mode was 3.

[Graph 1 here]

[Graph 2 here]

Quota Lower House

The data on quotas in the lower house was recoded into 0 (no) and 1 (yes). Of the 113

countries, 73 had data, so 64.5% of the total level of countries were represented in the dataset.

The mode is 1 (yes).

[Graph 3 here]

Type of Quota

The types of quotas was recoded into three new variables, 2 (Strong: Reserved Seats

or Legislated Candidates Quota), 1 (Middle: Voluntary Political Party Quota), and 0 (Weak:

the rest of the data). The mode was 0.

[Graph 4 here]

[Graph 5 here]

Franck-Larsson 27

Bivariate Analysis for the Lower House

For all of the bivariate data run for this paper, 1-tailed significance was used. Either 2-

tailed or 1-tailed could have been used, but the 1-tailed was chosen. Where both variables

were Interval/Ratio, Pearson’s R Correlation was used, as well as a significance test (1-tailed).

Where the dependent variable was Interval/Ratio and the independent variable was either

Nominal or Ordinal, Eta Squared and a correlation was run. These are the ways to analyze this

type of data in SPSS that is commonly used.

When looking at the correlation between percent women in parliament and the percent

women with at least secondary education, the correlation was very weak at 0.090, and not

significant at 0.189. This was an unexpected result, as the literature suggested that there

would be a positive relationship between level of education and percent women politicians in

office.

[Table 2 and 3 here]

When looking at the correlation between percent women in parliament and the percent

men with at least secondary education, the correlation was very weak at 0.052, and not

significant at 0.304. This correlation was only analyzed because of an idea to see whether the

education of males in a country had any influence on the women politicians in office.

When looking at the correlation between percent women in parliament and the percent

women in the workforce the correlation was weak at 0.159 and close to, but not actually,

significant at 0.053. This result was unexpected, as the literature suggested a positive

relationship between the two variables.

The correlation between percent males in the workforce and percent females in the

lower house was very weak, -0.011 and not significant, 0.910. This correlation was also a test

to see if men in the workforce had any kind of relationship with women in the political life of

Franck-Larsson 28

the lower house. As shown, there was no relationship between the two variables, and it was

not statistically significant.

For the correlation between percent women in the lower house of legislature and level

of democracy, the independent variable explained 1.2% of the dependent variable. The result

was not significant.

For the correlation between percent women in the lower house of legislature and type

of electoral system, 15.0% of the dependent variable was explained by the independent

variable. The findings were significant at 0.01 level. This was unexpected, as it was not

consistent with what the literature suggested. Previous research had found that the

independent variable would explain a higher level of the dependent variable.

For the correlation between percent women in the lower house and quotas, 0.3% of the

dependent variable was explained by the independent variable and it was not significant since

the ANOVA turned out to be 0.648. The assumption had been that if a country had any type

of quota, there would be a higher percentage of women politicians in the national legislature.

When looking at the types of quotas and the correlation between them and the percent

of female seats in the lower house, the independent variable explained 7.3% of the dependent

variable, and it was significant at 0.05 level. This result was unexpected as the literature had

implied a positive relationship between quotas and a higher level of women politicians.

When looking at the correlation between level of development and the percent female

politicians in the lower house, the independent variable explained 11.1% of the dependent

variable, and it was significant at 0.05 level. This result was unexpected, as a higher level of

development suggest a more equal representation between women and men politicians.

However, development is put together by five different variables and therefore it can be

complicated to analyze.

Franck-Larsson 29

After the bivariate analysis, no relationships were found to be more than weak and

statistically significant at the same time. But one cannot be sure about the results without

controlling for the other variables as well. Hence, linear regression was conducted for all of

the variables.

Franck-Larsson 30

Bivariate Analysis for the Upper House

For the correlation between percent females in the upper house and percent females

with at least secondary education the relationship was found to be very weak (0.081) and not

significant (0.298). This did not align with what the literature said, as it suggested a positive

relationship between education and the percent of women in legislature.

[Table 4 and 5 here]

The correlation between percent females in the upper house and percent males with at

least secondary education was found to be very weak (0.009) and not significant (0.476).

Again, this analysis was conducted to see if percent males with secondary education was in

any way influential on the percent of women in legislature.

The correlation between Percent females in the upper house and Percent Females in

the workforce turned out to be moderately strong (0.278) and significant at the 0.05 level (1-

tailed). This was in line with what the literature had suggested; a positive relationship between

women in the workforce and percent women in legislature.

Concerning the correlation between percent females in the upper house and percent

males in the workforce, the result was very weak (0.069) and not significant (0.322). This

result showed that percent males in the workforce do not have a correlation with percent

female seats in legislature.

Looking at the correlation between percent females in the upper house and level of

democracy showed that the independent variable explains 8.7% of the dependent variable and

the result is significant at 0.05 level. The result is not consistent with the literature and

hypothesis because the independent variable explains a low level of the dependent variable,

even though it is significant.

When looking at percent female seats in the upper house and the level of development ,

it was found that the independent variable explains 6.0% of the dependent variable, and the

Franck-Larsson 31

result is not significant. This was not what was suggested by the literature, so the result was

not expected.

Looking at percent females in the upper house and electoral system the result was that

2.6% of the dependent variable was explained by the independent variable, and it was not

significant. The result was not in agreement with the previous research studied, and hence was

the opposite of the expected result.

When looking at percent females in the upper house and quotas for the lower house , it

turned out that the independent variable explained 1.3% of the dependent variable, and the

result was not significant (0.523). The assumption, based on the literature, was that quotas

would lead to a higher level of women politicians in the legislature, which was not shown to

be consistent here.

Studying percent female seats in lower house and type of quota in lower house the

independent variable explained 7.7% of the dependent variable, and was not significant

(0.170). This result was not consistent with the hypothesis or previous research done and

unexpected.

Franck-Larsson 32

Multivariate/Control Analysis

For the Multivariate or Control analysis the method used was linear regression,

because the dependent variable is an Interval/Ratio variable and Linear regression is the best

method to use in that case. All the previously used variables were part of the linear regression.

Lower house Regression

For the lower house regression, the independent variables used in the analysis were the

(recoded) quota lower house, (recoded) type of quota, level of democracy, percent female in

workforce, (recoded) electoral system, percent females with at least secondary education, and

level of development. I made these choices because the variables should preferably not be

similar as they could then influence the outcome of each other. For example, the data on

females with at least secondary education and males with at least secondary were not

analyzed together as the first would be the one I wanted to analyze, and the second one was

not the focus of this research.

The results from the multivariate analysis were somewhat in line with what the

literature has suggested. But there were also factors that proved to not be significant in

influencing a higher level of female politicians. Contrary to expectations, Percent females

with secondary education, Level of democracy, Level of development, Quota for the lower

house and Type of quota were not related to women in legislatures after controlling for the

other factors. On the other hand, two variables were significant, Percent females in the

workforce and Electoral system. Percent female in the workforce was found to have a positive

relationship with percent women in legislature of 0.200 and was significant at 0.038. This

means that if the percent women in the workforce increase by 1%, the percent women in

lower house legislature would increase with 0.200% and significant at 0.1 level. The Type of

electoral system had a relationship of 4.173 and was significant at 0.013, meaning that for

every step up on the scale of more proportional representation political system a country

Franck-Larsson 33

would take, the percent increase in women politicians would be 4.173% and significant at

0.05 level.

[Table 6 here]

Both of these two variables had been suggested in the previous research as to be

influential on the level of female politicians in the legislature. Other variables that had been

mentioned to be influential included quotas, education, democracy and development. But

those independent variables were shown to not be influential in increasing the percent of

female politicians in the lower house. The data for the variables that were correlated with

percent females in the lower house suggest that for every percent more of women in the

workforce, the percentage of women in legislature is increased by 0.200 percent. In the case

of electoral system, for one step up on the scale of more proportional system, the percent

women in legislature increases by 4.173 percent.

One can suspect that there were no findings of more robust relationships because of

the small number of cases. As seen in the table, the potential maximum number of cases is

113. If the data had been collected over longer time, there would have been more variation

and possibly a clearer pattern in the results.

Another reason as to why the analysis did not find more statistically relationships

could be because of why the policies were in place, and how they had been implemented. In

the case of quota, the hypothesis was that they would increase the percent females in

parliament, as the laws require a certain percent of the seats to be women. Many of the

countries with higher levels of women in parliament do have quotas, but there are also some

that do not. In some cases it is unclear whether the quotas resulted in higher levels of women

in parliament, or if a higher level of women politicians to begin with demanded the quotas.

Upper House Regression

Franck-Larsson 34

For the upper house regression the same variables were used as for the lower house

regression. Here, the only variable that was shown to be statistically significant was percent

females in the workforce at 0.015. The relationship was 0.460. This shows that in this case,

for every percent higher women in the workforce a country had, the percent women

politicians in the upper house would increase by 0.460%. and was significant at 0.05 level.

This result was following the arguments made by the literature, as a higher level of women in

the workforce was predicted to have an impact on the percent women politicians.

As a test to see whether or not the way that politicians won their seats in the upper

house, I also controlled for the way that they were elected here. The data was taken from the

Inter-Parliamentary Union, and showed to what extent each country with an upper house

appointed and/or elected their members. I recoded the variables to say that of all of the

members were selected (directly or indirectly), variable was 1. If all of them were appointed,

the variable was 0. If the country both appointed and elected their members of the upper

house, the percent elected turned into the variable, meaning that if 60% of the members were

elected the variable was 0.6. The type of election for the upper house was not significant.

[Table 7 here]

Discussion and Conclusions

The size of the dataset could be one of the overall reasons as to why there was a lack

of relationship and significance found between the variables. The choice was made to only

analyze the 113 countries that were considered democratic, as those countries have a specific

Franck-Larsson 35

set of characteristics. Using a larger dataset of either more countries or more data over time

could have influenced the finding of stronger and more significant results.

Past research suggested that there would be a positive relationship between a higher

level of education and more women politicians in parliament. But in the analysis made for this

paper, no strong or significant relationship was found for the hypothesis. The reasons for this

could be that most of the countries in the dataset already have relatively high levels of

education. Hence, there was no large difference in comparison between the countries that had

a higher level of women representatives in parliament.

The independent variable that proved to be influential in both the upper and lower

houses was Percent Women in the Workforce. As described in the literature review

previously, countries that have a higher level of women in the workforce are generally more

open to women in the public sphere and in the politics. Being a part of the official workforce

also provides women with skills that could later be used in political life, such as public

speaking and handling administrative work. Having a higher level of women in the workforce

expands the potential group of female politicians and increase the possibility for them to

become interested in politics. This variable proved to be influential enough presumably

because it is a variable that has a great impact on the possibilities for women to run for office

in various ways.

The relationship between the existence of quotas and a higher level of women

politicians was hypothesized to be positive and significant, as it seemed like a reliable way to

increase the percent women in parliament. Unfortunately, this hypothesis did not have strong

enough of a correlation or significance. As mentioned earlier, something that would shed

some light on this situation would be looking at whether the quotas or a higher number of

women in parliament was in place first. The reason behind is that sometimes the quotas are

put in place because the level of women politicians is so low, and sometimes they are

Franck-Larsson 36

implemented when pressure is put by women politicians. The history could possibly influence

the impact the quotas are making.

A more democratic country did not show to be an influential variable in increasing the

percent of women politicians. The research had suggested that democracies have higher levels

of women politicians in general, as democracies are more open to different kinds of people

serving as leaders. The reason as to why a higher level of democracies was not influential

could have been that all the countries were already considered more or less democratic to

begin with. The countries in the dataset were considered a 3 or a 4 on the scale of 1 through 4,

with the highest number being the most democratic.

Another variable that was not influential enough in the analysis of the data was

Development. The literature suggested that the more developed a country was in finance,

social politics and education, the higher level of women politicians it would have. The reason

why it did not prove to be influential could be that the countries were mostly democratic, and

therefore generally high in development. The measurement chosen to describe development

was a combination of health care, education and GDP per capita. This is a categorization that

is focused on five different variables, which is relatively limited. If the development data had

also contained data on women in the workforce, gender gap in salaries, or other variables, it

may have been able to show the influences more accurately.

Political System was found to be influential in the case of the lower house, but not in

the upper house. It was in line with what the research suggested, implying a hypothesis that

showed that countries with a more proportionally representative (PR) system would have a

higher percentage of women politicians. That it was not influential in the case of upper house

could be attributed to the fact that less than half of the countries actually had an upper house.

As the literature suggested, political systems that are more on the PR (proportional

representation) side of the spectrum make it easier for women politicians to become elected.

Franck-Larsson 37

With a party list, the chances to get elected are larger and the general voter decides what

candidate he or she wants to vote for, instead of just the politicians who have already attained

power in the party and have been appointed to make these decisions.

In the end, only two hypotheses were found to have proof of correlation. The Percent

Women in the Workforce and Type of Political System were the two independent variables

that were shown to influence the dependent variable, Percent Women in Legislature. With

more women in the workforce, the potential pool of women that could become elected is

larger. Professional experience is crucial to understanding the political world, and with the

work experience also comes more possibilities to network and becoming involved in political

life. The other variable, Political System, showed that the way that the election system is set

up makes an important influence in the question of more women elected. It is not just the

campaigning or the image that makes a difference, but also the way that the alternatives (if

any) are presented to the voters.

Understanding methods to increase the percent women politicians in the world is

important because “lack of women in political decision-making results in government that

ignores – even disdains – what women want and need. Until women achieve numbers in

legislature far nearer parity, all advances in equality between women and men must be viewed

as extremely fragile” (Abdela, 2000, 17). Without women in influential political positions,

reaching gender equality would become even more challenging. The logic behind this claim is

applicable to all groups that are underrepresented in political life today. Women do make up

roughly half of the population in the world, and by being underrepresented so gravely sets the

stage for discrimination in the policy world.

To understand the political system, and the factors, beyond specific political

campaigns, that influence the final results of elections, one must study structural and social

factors such as those included in this study. The factors will influence dissimilarly in all

Franck-Larsson 38

countries, but overall there are some trends that hold for most. By looking at those, policies

and action plans can be made to ensure that women and men will have equal access to the

political process. Beyond the prejudice against either sex as politicians, these factors do aid in

understanding how to better serve women politicians who are attempting to win public office.

All of the above mentioned factors are, in one way or another, aiding women in

learning the traits required for political office, and hopefully helping in eventually winning

office. They can be used in various ways to predict the level of women politicians in a country.

Having an overall high percentage of women in political office does not singlehandedly

produce more equal opportunities for men and women, but it is among the most important

factors, as having women elected as politicians will bring issues that women face to the table.

When a group is not represented where the important decisions are made, they will not be able

to influence that decision. Unfortunately, women are largely underrepresented in almost all

countries in the world. The United States currently has 17% female Members of Congress

even though women make up half of the population. The main reason for this research is to

understand the reasons why some countries have a much larger number of female politicians

than others, in order to see what can be done to improve the situation worldwide.

Franck-Larsson 39

For Future Research

For future research the possibilities to reach more significant results could be found if

using a larger base of data. In this analysis, only 113 countries were used, the ones that scored

high enough on the democracy scale. One way to increase the dataset could be to utilize all

the countries possible, even those that are not democratic. It could also be useful to look at the

changes in percent women politicians over time, and see if it possibly relates to different

policy implementations in the different countries. One example could be to focus on when

quotas were implemented in country and look at the trend in percent female politicians after

that.

There are also a few different ways that could be suggested that the hypothesis could

be interpreted and other data would be used. One example is the secondary education, chosen

to represent the variable of education. Instead, the percentage of women that receive a law

degree compared, either on its own or compared to the percentage of men could have been

Franck-Larsson 40

one option. Another way of showing the influence of education could be to compare the levels

of women in education to those of men. In this paper, the two were used separately, but it

could be useful to compare the two and see if a larger disparity between level of education for

men and women would more closely predict women’s participation in parliament.

The two variables that were found in the literature review but not discussed in this

paper could be influential, and therefore an idea to look at. For religion, one could look at the

majority religions in the countries studied, and study whether or not there was a relationship

between type of religion and percent women in legislature. As for openness to women in

higher positions, one could look at the World Value survey for various years and analyze the

results. The World Value survey looks at a limited number of countries though, which could

possibly make the analysis hard to conduct.

Looking at income disparities or difference in participation in the workforce and

education could also be possible variables to study in the future. There is a possibility that in

countries with larger disparities in salaries, education and labor force participation would

make it more challenging for women to break into the political life as they are discriminated

against in different ways.

Networking opportunities or political background is a variable that is hard to measure.

As in any career, both male and female politicians benefit from having experience in the area,

but also from contacts within the political system. With male politicians there is a larger pool

of examples to look at, but with female politicians it could be important to look at their

backgrounds and networks to provide a better picture of what is needed in order to succeed as

a politician. Many women in political life have a father, brother, husband or other male

relative that has been a part of the political system. Their contacts or influence can prove to be

a facilitator for them. It could be found to be a very important factor if there was a possibility

to study these kinds of relations and what type of networking possibilities it would lead to.

Franck-Larsson 41

One way to use the information found would be for women attempting to seek office to

improve the already existing networks.

Franck-Larsson 42

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Franck-Larsson 45

Tables and Graphs

Table 1

Table 2

Bivariate Correlation for the Lower House

DEPENDENT VARIABLE

% Females in lower house

INDEPENDENT VARIABLE

% Females with at least Pearson Correlation

secondary education Significance (1)

0.090

0.189

% Male with at least Pearson Correlation

secondary education Significance (1)

0.052

0.304

% Female in the workforce Pearson Correlation

Significance (1)

0.159

0.053

% Males in workforce Pearson Correlation

Significance (1)

-0.011

0.455

** p <0.01

* p <0.05

Percent

Females

Lower

House

Percent

Women

Seats

Upper

House

Percent

Females

with at

Least

Secondar

y

Educatio

n

Percent

Males

with at

Least

Secondar

y

Educatio

n

Percent

Females

in the

Workfor

ce

Percent

Males in

the

Workfor

ce

Level of

Develop

ment

Recoded

Electoral

System

Recoded

Quota

for

Lower

House

Recoded

Types of

Quota

Valid number of countries 106 47 103 103 109 109 111 109 73 113

Missing number of countries 7 66 10 10 4 4 2 4 40 0

Mean 19.85 21.17 54.7592 60.5388 53.7009 74.3294

Median 18.85 18.50 57.6000 65.6000 53.5000 74.6000 3.000

Standard Deviation 10.595 11.414 27.75450 25.57640 13.01421 8.25248

Minimum 0 0 1.50 6.00 13.80 50.00

Maximum 45

47 99.30 99.10 91.00 90.60

Percentile 25 1.000

Percentile 50 3.000

Percentile 75 4.000

Mode 3.00 1.00 0.00

Franck-Larsson 46

Table 3

Bivariate Correlation for the Lower House

DEPENDENT VARIABLE

% Females in lower house

Level of democracy Eta Squared

Significance ANOVA

0.012

0.266

Level of development Eta Squared

Significance ANOVA

0.111

0.007**

Electoral system Eta Squared

Significance ANOVA

0.150

0.000**

Quota lower house Eta Squared

Significance ANOVA

0.003

0.648

Type of quota Eta Squared

Significance ANOVA

0.073

0.020*

** p <0.01

* p <0.05

Table 4

Bivariate Correlation for the Upper House

DEPENDENT VARIABLE

% female seats upper house

INDEPENDENT VARIABLE

% Females with at least Pearson Correlation

Secondary education Significance (1)

0.081

0.298

% Male with at least Pearson Correlation

secondary education Significance (1)

0.009

0.476

% Female in workforce Pearson Correlation

Significance (1)

0.278

0.029*

% Males in the workforce Pearson Correlation

Significance (1)

1.069

0.322

** p <0.01

* p <0.05

Franck-Larsson 47

Table 5

Bivariate Correlation for the Upper House

DEPENDENT VARIABLE

% female seats upper house

Level of democracy Eta Squared

Significance ANOVA

0.087

0.044*

Level of development Eta Squared

Significance ANOVA

0.060

0.442

Electoral System Eta Squared

Significance ANOVA

0.026

0.576

Quota lower house Eta Squared

Significance ANOVA

0.013

0.523

Type of quota Eta Squared

Significance ANOVA

0.077

0.170

** p <0.01

* p <0.05

Table 6

Multivariate Analysis/Regression for Lower House

Independent Variables b Significance

(Constant) 18.897 0.242

% Females with at least secondary

education

0.034 0.672

% Females in the workforce 0.200 0.038*

Level of democracy -5.118 0.207

Level of development 0.884 0.631

Electoral system 4.173 0.013*

Quota lower house 6.255 0.257

Type of quota -3.542 0.340

Adjusted R-square: 0.095

** p <0.01

* p <0.05

Franck-Larsson 48

Table 7

Multivariate Analysis/Regression for Upper House

Independent Variables b Significance

(Constant) -10.127 0.815

% Females with at least secondary

education

0.004 0.983

% Females in the workforce 0.460 0.015*

Level of Democracy 3.102 0.766

Level of Development -0.025 0.994

Electoral System -2.221 0.413

Quota Lower House -6.344 0.561

Type of Quota 7.289 0.290

Election type upper house -6.233 0.351

Adjusted R Square: 0.336

** p <0.01

* p <0.05

Graph 1 _

Graph 2 _

Graph 3

_

Graph 4 _

Graph 5 _