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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 _
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