Natural resources and the position of women on the labour market

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Natural resources and the

position of women on the

labour market

Master Thesis

International Relations - Global Political Economy

25 October 2018

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Preface

This is the Master’s thesis for the International Relations – Global Political Economy program. The thesis is named ‘Natural resources and the position of women on the labour market’. This thesis has been written between February and October 2018. In the process of writing my thesis, I have encountered multiple difficulties, such as the use of the right analysis in SPSS and drawing the right conclusions from the output of these analyses. With the guidance and support of my supervisor, Ruben Gonzalez Vicente, I have been able to successfully write this thesis and conduct the research. For his advice during the process, I sincerely thank him.

The curse that natural resources can bring along has always interested me, as it is a strange paradoxical phenomenon. When I read Ross’ (2008) research, I was immediately interested. Even though it was known that women in the Middle East participated less in the labour market than in other parts of the world, I thought the connection between the production of oil and participation of women was

extremely interesting. When I dug deeper into the subject, I found Rørbæk’s (2016) counterarguments, which made a lot of sense. Then, I decided to conduct my own research and find out if the claims Ross (2008) made were true, and also generalizable worldwide, or if Rørbæk (2016) provided a better explanation worldwide. The results were not always satisfying, but that is what conducting an academic research sometimes entails. I hope you enjoy reading my thesis.

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Content

Abstract 4 Introduction 5 Literature Review 7 Hypotheses 11 Method 12 Limitations 15 Cases 16 Results 18 Analysis 34 Reflection 37 Conclusion 39 Bibliography 40

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Abstract

In this thesis, I argue that there is no connection between the amount of export of the natural resources oil and gas and the female participation on the labour market worldwide. This argument resolves an important debate in the literature. In Ross’ (2008) research, he claims that there is a correlation between the oil export and the female participation on the labour market in the Middle East. I counter his argument by analysing all countries with a major oil or gas export worldwide and the major exporters of oil in the Middle East separately. Another opponent of Ross’ (2008) theory is Rørbæk (2016), who argues that culture and religion in the Middle East is to blame for the lack of female participation on the labour market in the region. By analysing the difference in oil and gas export and compare this to the change in female participation between the years 2011 and 2015, I was able to draw a conclusion. The regression analysis of the data of all major gas or oil exporting countries shows us that there is no significant correlation between the two variables, meaning that no connection between the oil or gas export and the female participation on the labour market can be proven. Also in the analysis of the Middle East, no connection between the export of oil and the female participation can be found. Only in the analysis of Islamic countries, a significant correlation between oil and female participation could be found, but this was very minimal. This research therefore implies that Ross’ (2008) conclusions are not applicable to the whole world or the Middle East in the years between 2011 and 2015.

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Introduction

‘The paradox of plenty’, the resource curse is sometimes called (Melum, Moene & Torvik, 2006; Ross, 1999). It is called a curse, because according to the theory, a country with a large amount of natural resources often fails to make this work in favour of a major part of its population. Some argue that the cause lies in the lack of the right institutions, causing the wealth that can be created with the resources to be unfairly distributed (Ross, 1999). Critics argue that colonialism is the cause of this curse, as the relations with the previous colonial ruler may have caused a resource periphery, that resulted in weak institutions (Acemoglu et al., 2001; Stevens, 2003). An elite group will grab the wealth that the resources bring along, leaving nothing for the rest of the people. The economic and political consequences have been widely analysed by scholars. The social consequences have been analysed as well, but less than the economic and political consequences. It is argued that by Ross that an increase in oil supplies can indicate a lower female work rate (Ross, 2008). The increase in oil supply within a country and therefore in the state revenue, causes a higher household income. Also, the oil industry is mostly dominated by males, meaning that mostly male wages will rise. This will imply a decrease in female participation (Mammen & Paxson, 2000; Ross, 2008), which would mean that there is a connection between the oil export and the female participation in the labour force. However, one can wonder whether this can also be applied the other way around and worldwide. This brings me to my research question: “Has the number of exported oil and gas of a country affected the female participation in the labour force between 2011 and 2015?”

Women’s rights have developed immensely over the past century, starting with the right to vote all the way to close to equality with men. However, this is not the case everywhere. In many countries, women are still left behind and are not able to participate in the labour force like they should, even in developed countries. Female participation in the labour force can be beneficial in multiple ways. Firstly, it is argued that it increases the female representation in politics, as more women become politically active (Iversen & Rosenbluth, 2008). Secondly, women become less dependent on men and are more empowered with their own incomes (Psacharopoulos & Tzannatos, 1989). When women are able to participate in the labour force, they are more independent and are much better able to take care of themselves without having to rely on men within society. This is beneficial for society and will create more equality between men and women. One could argue however, that women are often still in charge of household labour even after joining the labour market. Nevertheless, increasing female participation is a positive effect. Many scholars have looked for reasons behind this inequality. Factors that are argued to have played a role vary from a patriarchal culture to low incomes per capita within a country. Interestingly enough, one of the most cited articles on the effects of the resource curse pointed out that a greater supply in resources affects the female participation in the labour force (Ross, 2008). I shall continue where this research left off, adding another piece to the research puzzle.

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Where many scholars have argued that having many resources within a country can have negative economic side effects, not as much attention has been given to the position of women in the countries that are affected by this curse and the type of natural resource that has an effect on this. The two different types of natural resources that I shall distinguish, are oil and gas. These resources are used extensively all over the world, in households and in transportation and are therefore also exported in great numbers. For this reason, I have decided to focus on these natural resources. For each country, an overview of natural resources can be found, combined with the female participation in the labour force according to the World Bank (2017a). Through a regression analysis, it will become clear whether a certain type of natural resource has a greater effect on the female participation in the labour force than another. For example, it is possible that oil-rich countries have a lower status concerning women’s rights than countries with a major gas supply do.

By conducting this research, more knowledge on the causes of low female participation in the labour force will become known. As I add a piece to the puzzle that this debate brings along, the answer to my research question may be policy relevant. Governments or NGO’s fighting for women’s rights can take the results into account when trying to improve the situation of women worldwide. The effect or the lack of effect that resources could have on the female participation can then be taken into account. In this research, I will argue that there is no significant correlation between the increase or decrease in the export of oil or gas and the female participation in a country. The analysis will prove that the claims of Ross (2008) are not generalisable for the whole world, in the period between 2011 and 2015, and are possibly just applicable to the Middle-Eastern region in a particular period of time. The conclusions are not replicable on both the oil, the gas and the combination of the two natural resources when looking for a correlation with the female participation in the labour force. In the next paragraphs, the literature background will be given and the arguments of the different authors will be analysed.

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Literature Review

In my literature review, I will discuss the two fields that my research touches upon. Firstly, I shall discuss the content of the literature on female participation in the labour force. Secondly, the literature on the resource curse will be discussed. Finally, the literature that is attached to both fields will be analysed.

As I just stated, I argue in this thesis that there is no correlation between the increase or decrease in the export of oil or gas and the female participation in the labour force. Nevertheless will I discuss authors who argue in favour and against this statement and their arguments will be discussed.

The female participation in the labour force

Many scholars have come up with different reasons for the low female participation in the labour force in society. Religious and cultural backgrounds, low income and the sex imbalance at birth

(Jayachandran, 2014) are all factors that are claimed to be important causes for the low female participation in the labour force in developing countries. A particularly unorthodox explanation is provided by Ross (2008), who claims that a boom in the resource supply is one of the reasons for the low female participation in the labour force. The political and economic aspects around the resource curse have been widely researched in the past two decades, to which I shall return in the next paragraphs. However, as stated earlier, other factors that can also be a cause of consequence of this curse, have been analysed less by scholars. Ross (2015) argues for a wider scope of the resource curse, including social and cultural aspects in the research. He also argues that the mechanisms and

conditions for the resource curse to arise should be analysed (Ross, 2015). Finally, he argues that a solution to the problem should be found by scholars (Ross, 2015). “The need for evidence-based policy advice is more necessary than ever” (Ross, 2015: 253).

On the position of women in countries, many scholars have conducted research. However, on the connection between the amount of resources a country possesses and the female participation in the labour force, very little research has been done. The relationship between trade and the female participation in the labour force has been analysed (Do, Levchenko & Raddatz, 2011). The authors argue that “gender equality is a source of comparative advantage when a country integrates into world markets” (Do, Levchenko & Raddatz, 2011: 22). They conclude that countries in which more female labour is required are more likely to have a smaller gender gap and a more expanding economy when these women are empowered (Do, Levchenko & Raddatz, 2011: 22). Assaad conducted a research on feminisation in Morocco and Egypt, in which he concluded that Morocco benefited from the inclusion of women in the labour force after the implementation of the economic liberalisation, where Egypt has defeminised (2004). Ross (2008) takes an interesting perspective on the issue of women’s status in the Middle East. He argues that not Islam, but oil is to blame for the low female participation in the labour

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force in the Middle Eastern region (Ross, 2008). This is an interesting argument for my own research, as I will also analyse the effects that resources have on the female participation in the labour force. In his research, he comes to the conclusion that oil exporting countries in the Middle East know less female participation in the labour force, women have less rights and women are less seated in the national parliament (Ross, 2008). Outside the Middle East however, he argues that there are some exceptions to the resource curse effect on the female participation in the labour force in the country. Norway, New Zealand and Australia are all three countries that are known for their oil export, but also have a very small gender gap in the labour force (Ross, 2008). Like the resource curse on the

economic and political factors, the social factor does not necessarily needs to worsen due to the boom in resource supplies. When the right institutions are not in place however, the resource curse can also affect the social factors within a country. Ross states the following in his conclusion: “This study suggests that the production of oil and gas - and potentially, other minerals - also influences a country’s social structure, a topic that has received little attention. Oil not only hinders democracy; it also hinders more equitable gender relations” (Ross, 2008: 121). He argues that an increase in the amount of oil, will decrease the women participation in the labour force. Women mostly work in the traded sector and men in the non-traded sector in developing countries (Ross, 2008). As workers in the non-traded sector mostly require more strength and physical skills than workers on the traded sectors do, this sector is mostly dominated by men. This is seen worldwide, also in Western countries such as Australia (Lozeva & Marinova, 2010). Some see this male dominance in the sector of the mining of natural resources as a sign of masculinity and dominance, also over women (Loveza & Marinova, 2010), but that is not the focus of this research. The point is that the traded sector is male dominated. The boom in oil supply makes the demand for male labour therefore much higher, as this is the non-traded sector. The higher demand in the non-non-traded sector means that male wages will rise and female wages in the traded sector will decline along with the sector itself. The higher male wages and the higher government transfers to households because of the new oil supply, cause women to be less inclined to join the workforce. The demand and supply of female labour declines, meaning that there will be less female participation when oil is found (Ross, 2008: 110). This makes his article the groundwork for my own research, in which a wider selection of natural resources will be analysed in a wider scope of countries.

A study contradicting these conclusions has been conducted by Rørbæk (2016), who disagreed with Ross (2008) in his article. He argued that the Islamic culture is still responsible for the lack of female participation in the labour force, not oil. In his research, he used the data of 166 countries in the period between 1999 and 2008. He came to the conclusion that women are participating less in the Middle East, but did not see the same effect in other resource rich countries (Rørbæk, 2016). Instead of oil, or any other type of natural resources, Rørbæk argues that culture and religion, in particular certain interpretations of the Islamic religion, is to blame. He claims that “even when factors such as oil,

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income, and democracy are accounted for, 20 Muslim countries still fall markedly short of the rights levels obtained by women in other countries” (Rørbæk, 2016: 19-20). This conclusion of his research clearly implies that the countries in which the Islam is the most dominant religion, the women’s rights are lacking. Oil is, according to Rørbæk (2016), not to blame for the difference in men and women in these particular countries.

In contrary to Ross’ article (2008), there are also other factors that could be responsible for the lower female participation in the labour force in countries. Where Ross argues that oil, gas and potentially also minerals are the blame for the lack of women’s participation in society (2008), others argue differently. To prevent a spurious relationship between the resource curse and the female participation in the labour force, I will take the factors that can play a role in the increase or decrease of women’s participation into account as well.

In this thesis, I also partly disagree with the statements made by Ross (2008), as I see no correlation between the oil and gas exports and the female participation in the labour force in the period between 2011 and 2015, worldwide. He however, focused on the Middle East, so I do not deny his conclusions. I only eliminate the generalizability of his research to the whole world and to the export of gas. The explanations of Rørbæk (2016) however, also have to be taken into account. The lack of correlation between the oil and gas export and the female participation in the labour force could also imply that other reasons lie behind the connection in the Middle Eastern region. Because of this lack of correlation, Rørbæk (2016) his argument that the Islamic culture could perhaps provide a better explanation for the lack of participation of women in the labour force.

The resource curse

Many scholars have conducted a research on the resource curse: how it comes to exist and what the consequences are. Few scholars however, have attempted to conduct a research on the consequences of this resource curse for the female participation in the labour force. In this paragraph, I shall give a description of how scholars argue what causes the resource curse and what the political and economic consequences are. After this, I shall analyse the existing literature on the social consequences of the resource curse.

A sudden discovery of national resources in a country or an increase in the price of a particular resource can have very different effect in different countries. More often, a boom of natural resources pose a curse than a blessing, due to the lack of or bad institutions in a country (Mehlum, Moene & Torvik, 2006; Papyrakis & Gerlagh, 2003; Ross, 2015). The resource curse is therefore also named ‘the paradox of plenty’ (Melum, Moene & Torvik, 2006: 1). It is argued that with the right institutions, the resource curse can be prevented. However, as many countries do not have the right institutions in the government, the new wealth will immediately be ‘grabbed’ by the elite (Melum, Moene & Torvik, 2006). With the ‘grabber-friendly’ institutions, the wealth cannot be equally distributed amongst the

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people of the country, leaving the economic benefits of the resources only to the elite. Such weak states “tend to generate authoritarian governments or undermine democratic governance” (Jensen & Wantchekon, 2004: 834). The government and elite in a country will ‘grab’ the profit and wealth that comes from the resources, especially in undemocratic regimes. “Higher levels of natural resources are associated with higher levels of government consumption and worse government performance” (Jensen & Wantchekon, 2004: 836).

Besides the ‘grabbing’ effect, meaning that the (political) elite will grab the wealth that comes from the new supply of natural resources, there are also other economic and political effects. A sudden boom in the national resource supply can also be the cause of a conflict, even a civil war. When more wealth suddenly becomes available, without the right institutions to guide this wealth to be distributed over the whole society, elites may fight over this wealth (Frankel, 2010). “Moderately high levels of petroleum wealth, and possibly other types of resource wealth, tend to trigger or sustain conflict when they are found in regions dominated by marginalized ethnic groups, particularly in low- and middle-income countries” (Ross, 2015: 252). The volatility of the resources is also high, imposing high risks on a country when being dependent on this national resource for its wealth (Frankel, 2010). The concept known as the ‘Dutch Disease’ can also play a role in the underdevelopment of resource-rich countries. This Dutch Disease means that the currency of a country appreciates in combination with increased government spending (Frankel, 2010). This affects the competitiveness of the export of these goods. If the commodity prices worldwide were to go down, the country in question would be in trouble (Frankel, 2010). If a country is very dependent on the export of a certain type of natural resource, a sudden drop of price of this particular natural resource can damage the country’s economy seriously and very rapidly. The Dutch Disease can bring a country into a deep crisis. An example of the Dutch Disease can be found in Russia in 2005. The export of oil was enormous, which led to the appreciation of the ruble compared to the dollar (Latsis, 2005). This led to a significantly smaller economic growth percentage compared with the years that preceded (Latsis, 2005). The manufacturing sector suffers most from the decline in economic growth (Latsis, 2005). It left a scar on the country’s economy. The resource curse and Dutch Disease can also be prevented, as seen in the case of Norway, where oil was found in the previous century (Larsen, 2006). The right institutions, like in Norway, can ensure that these curses can be stopped. Scholars, however, have not come with an actual solution to the problem that the resource curse brings along, but arguing in favour of ‘better’ institutions. This literature review has provided the most relevant information in the field of the resource curse in combination with women’s participation in the labour force. The limited research that has been

conducted on this issue forced me to analyse the two fields separately. Ross’ (2008) research will form the base of my research and I will conduct my research following up on his.

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Hypotheses

The results of the research will be interesting and contribute to the existing literature and theory on this subject, whether they are significant or not. I have certain expectations for this research and its results. The literature has given different arguments. Ross’ arguments are, according to his article, applicable to the Middle East. The Middle Eastern countries have exported great amounts of oil and are not known for their women’s rights, which left him to argue that the oil was responsible for the lack of female participation in the labour force in these countries. Rørbæk (2016) has countered the conclusions of Ross (2008), stating that culture is responsible for the lack of female participation in the labour force in the Middle East rather than oil. Firstly, I do not expect that the lack of female participation is caused by high oil (and gas) exports is applicable worldwide. My argument is that the arguments of Ross (2008) are not generalisable. Ross (2008) conclusions may be applicable in the Middle Eastern region, as his research points out, but I do not think that the same effect will be visible in the whole world. Secondly, I expect that the gas exporting countries will have a different result than the oil exporting countries. Where Ross (2008) concluded that because of the male-dominated oil industry, the female participation in the labour force in countries with a large oil export is lower than in other countries, this does not have to be the same for the gas industry. The oil and gas industry are quite alike, as they both require drilling into the earth to obtain the resource, but they are not

completely similar. Also, there are multiple countries that do export oil for example, but not gas. Therefore, a difference between the industries may be seen.

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Method

The research is of quantitative nature, as I will look at the data of all countries in terms of female participation in the labour force and the rise or decline in resources. The number of cases is too large to go into depth for each case, meaning that I will be drawing a general conclusions for all cases instead of an analysis per case. The research will therefore be an analysis of all cases combined. To be able to conduct this research, the following method has been thought of. Firstly, the data needs to be collected. The number of exported resources (oil and gas), which should portray the independent variable, the resource curse, will be collected with data from OPEC, in which the exported oil and gas supplies of the major oil and gas exporters worldwide are mentioned. In my analysis, I shall only include the countries that are said to be the major exporters of oil and gas in the OPEC report. With this data, I am able to make a distinction in what type of resources that certain countries have exported and in what numbers. After the resource export distinction can be made, the next necessary data is that of the female participation in the labour force. The World Bank (2017a) provides us the necessary data. This is the dependant variable, which will be tested for a connection with the independent variable, the amount of resources that have been exported. This list will give me the necessary data on the female participation in the labour force in countries all over the world. The combination of these reports will give us the data we need to answer our research question. All of these reports will be used of the two years mentioned in the research question, so I will be able to compare them to each other. The first year is 2011 and the last is 2015. Both reports use the year in which the report is published in their titles, but the data is on the years before. I have selected the year of 2015, because in January 2016, the price of oil was the lowest in years. To be able to analyse a certain development in both the amount of resources and the female participation in the labour force, a gap of at least five years is necessary. Between 2011 and 2015, a major decrease in the price of many resources is known, in particular oil. To be able to determine what effects a decrease in resource prices has on the women’s participation in the labour force, these years can be used best. For example, in May 2011, the oil price was $113.03 per barrel. By January 2016, the oil price had dropped to $26.55 per barrel (Macrotrends, 2017). This drop had great economic effects on the countries that are dependent on the export of oil. In this research, I will find out whether there have also been social consequences.

The price drop between 2011 and the beginning of 2016 of resources can be of significant influence to this research. Due to weak economic activity, the demand has decreased in that period of time (The Economist, 2014). The US has become a major exporter of one of the most important resources: oil. The increased supply drives the prices down (The Economist, 2014). Furthermore, countries such as Saudi-Arabia have decided not to limit their exports to increase the price, as other countries would benefit extremely (The Economist, 2014). The factors mentioned in this paragraph mean that the

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exports of resources were declining in this period. If Ross’ (2008) theory was correct, then the female participation in the labour force should increase, as the export of resources is likely to decrease. I shall look at the cases differently when comparing the research to Ross (2008). Where Ross analysed a boom in the resource supply and focused on the Middle Eastern region, I will compare the data of the whole world between the years of 2011 and 2015, whether this amount has increased or decreased. I have chosen to look at five years, as this gives enough room for countries to have potentially found new resources. I will not focus on the Middle East, as Ross (2008) has already conducted a similar research. I shall focus on the whole world and make a distinction between natural resources. I will look at a new type of natural resources: gas. Where Ross (2008) focused on oil in his research, I will also include gas to analyse whether a rise in these natural resources within a country also have a certain impact on the female participation in the labour force.

As is argued in the literature review, there are also other factors that might play a role in the lower female participation in the labour force within a country. For this reason, I shall also include other factors in the research to prevent a spurious relationship. Ross included the following variables in his research for the same reason: income, income squared, Middle-East, Islam, communist, working age and proportional representation (2008: 112). As I shall not focus on the Middle-East and based on the other literature on this issue, I will include the following control variables to prevent a spurious relationship. Firstly, there is the income per capita of the country, that can play a role in the increase or decrease of the female participation in the labour force. I will obtain the data of all countries from the World Bank (2017), and I will add this control variable to the dataset. The income is the number of the year 2015 in current US dollars. Secondly, there is the cultural and religious background of countries. This is harder to measure than the income of countries, as these are not numbers. Jayachandran argues that the Middle East, North-Africa and India place most value on a woman’s ‘purity’, meaning that this could decrease the female participation in the labour force in these countries (2014: 15). The countries she mentioned are mostly Muslim, and India is mostly Hindu. I shall include the dominant religion in each country, also including other religions such as Christianity and Buddhism. With the CIA Factbook (2018), I am able to determine what religion is most dominant in each country. The next factor that is mentioned in the literature on the causes of a low female participation in the labour force, is the sex imbalance at birth. The higher number of sons are born in comparison to daughters, the more likely that women’s participation in that particular country is lower, as is argued by Jayachandran (2014). For this reason, I shall take the male/female ration at birth from the CIA Factbook (2018a), and create a new control variable using this data. I shall also include the control variables of the working age (CIA Factbook, 2018b) and democracy level (The Economist Intelligence Unit, 2017), that Ross (2008) uses as well in his research. Because of the use of these control

variables, I am able to rule out a spurious relationship between the rise in resource supply of a country and the decline of female participation in the labour force.

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When the data is collected and placed into SPSS, the regression analysis can be done. By comparing the amount of supply of a particular resource of a country with the female participation in the labour force, a table will come out that will give us the answer to the question whether there is a significant causal relationship these factors. The results will then be widely analysed and discussed. The

mechanism that the female participation in the labour force is affected by the amount of resources that a country exports will be tested by the hand of this method. I will test empirically whether this

mechanism is indeed significantly evident. By applying this method, I am able to conduct this research.

In this research, the correlation between female participation in the labour force and the supplies and prices of resources are analysed. In the literature, there is a recent research from Ross (2008) that argued that female participation is not influenced by culture or religion, but because of oil. Others however, disagreed. In my research, I shall test Ross’ assumptions and expand the research to a worldwide basis on different resources. Through this, I hope to conclude whether female participation is indeed influenced by resources.

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Limitations

The research is analysing whether the causal connection that Ross (2008) argues to be true for the Middle East can also be applied to the whole world in the period between 2011 and 2015, in which the natural resource prices and in particular the oil price have dropped significantly. I have attempted to be as accurate as possible, to have a valid and reliable research method and to limit the mistakes as much as possible. However, some things could not be excluded due to the operationalisation of the research. In the model, I have included control variables to prevent a spurious relationship. However, one can never exclude this with a 100 percent certainty. I have included religion, income per capita, sex ratio at birth, percentage of the people between 16 and 65 and the democracy index. With these variables included, I limited the chance of a spurious relationship. However, the operationalisation is never ideal. The religion variable enabled me to include a part of a country’s culture. However, I was only able to take the most dominant religion. If a country was split between two religions, I was not able to include the other religion as well. Besides this, a religion also does not fully cover all the cultural aspects of a country. Because of the fact that it was impossible to do so, I had to limit myself to the religion variable.

Time was also an issue during the process of writing the thesis. Due to the lack of time, I was unable to include minerals and other resources, which was initially my intention. If I would have had more time, I would have widened the scope of the research and would have been able to give an even better portrayal of the effects that resources have on the female participation in the labour force.

The cases have been selected by the hand of the OPEC annual statistical bulletin, in which the major oil and gas exporters per region were mentioned. This means that the countries with smaller export numbers are not included in the dataset. The number of cases is limited to 55. The smaller number of cases means that the results will be less generalizable, as it only includes major exporters and not small oil or gas exporting countries. The results are, on the other hand, generalizable for the larger oil or gas exporters in this world. The limited number of cases for each region also means that the question whether the hypothesis is valid for the Middle Eastern region cannot be answered with certainty, as only nine countries from the Middle East are included in the dataset. I can however, give an answer for the largest oil exporters in the Middle East, meaning that I can partially find out whether Ross’ (2008) conclusions can also be applied to the 2011 – 2015 period.

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Cases

As is already mentioned shortly in the previous paragraphs, the case selection is based upon the OPEC Statistical Bulletin (2016), which shows the major oil and gas exporting countries in each separate region. For the oil export, the cases are as follows.

North America Latin America Eastern Europe and Eurasia Western Europe Middle East

Africa Asia and Pacific

Canada Brazil Romania Belgium Bahrain Algeria Australia

US Colombia Russia France Iran Angola China

Ecuador Germany Iraq Congo

(Republic of)

India

Mexico Italy Kuwait Egypt Indonesia

Trinidad & Tobago

Netherlands Oman Gabon Japan

Venezuela Norway Qatar Libya Malaysia

UK Saudi

Arabia

Nigeria Singapore

UAE Sudans South

Korea Vietnam

For the gas exporting countries, the following cases were mentioned in the OPEC Statistical Bulletin (2016). Some of the countries have also been mentioned in the oil export table, but will of course not be put into SPSS twice.

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North America Latin America Eastern Europe and Eurasia Western Europe Middle East

Africa Asia and Pacific

Canada Argentina Azerbaijan Austria Iran Algeria Australia

US Bolivia Kazakhstan Belgium Oman Angola Indonesia

Colombia Russia Denmark Qatar Egypt Malaysia

Mexico Turkmeni-stan

France UAE Equatorial

Guinea

Myanmar Trinidad &

Tobago

Uzbekistan Germany Yemen Libya

Italy Mozam-bique Netherlands Nigeria Norway Spain UK

In the case selection, that was based on the OPEC Statistical Bulletin (2016), one case was left out. Brunei was not mentioned in the democracy index, meaning that this case was always left out in the SPSS models, as it was labelled as a missing case. For this reason, I have decided to leave the case of Brunei out of the dataset. The consequences are limited, because it is only one out of 56 cases.

Besides, Brunei is a small country with a limited number of people and resources. The conclusions are therefore still the same and generalizable for major gas or oil exporting countries.

In the cases of Sudan and South Sudan, some of the data combined the two states, while other data sources separated the countries. I have combined the data in my research, as the data cannot be separated. To combine the data from the sources in which they were separated, I have taken the average number, proportionally divided over the number of people in each country (UN, 2017), and used the average in my dataset.

With this case selection, I will be able to answer my research question and label the hypotheses as true or false. The female participation in the labour force of countries worldwide will be analysed in their religion, democracy index, income per capita, percentage of people between the ages of 16 and 65 and of course the oil and gas exports of these countries.

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Results

In the next paragraphs, I will show to the results of the tests that have been conducted through SPSS and give a short explanation of the results that are shown. In the analysis, I will extensively cover the backgrounds and reasons for the results of the tests run in SPSS. Firstly, the tables will be shown for the gas export regression analysis, followed by the oil export regression analysis. The rest of the variables are included in both cases. This is followed by a regression analysis for the oil export. Thirdly, all the countries that export both oil and gas will be analysed. And finally, a regression analysis of countries that lie within the Middle Eastern region and export oil is executed.

As I have argued in the previous paragraphs, there is no correlation between the oil and gas export of countries and the female participation in the labour force in these particular countries during the period between 2011 and 2015. The results of the regression analysis, which are shown in the tables below, will provide the evidence for my claims. With Table 4, in which the countries from the Middle East are analysed, I will even be able to counter the conclusions that Ross (2008) had drawn in his research for the period that I have analysed. Table 6 shows that there is a significant correlation between the two variables in Islamic countries, but very minimal.

Table 1 – Gas Export and Female Participation changes between 2011 and 2015

Descriptive Statistics

Mean Standard Deviation N

Female Participation Change (FPC)

-,0057 1,02257 37

Gas Export Change (GEC)

-9148,527 59679,4769 37

Religion (REL) 1,81 1,151 37

Income per Capita (IPC)

22812,58 21697,854 37

Sex Ratio (SER) 1,0459 ,02374 37

Working Age Percentage (WAP) 66,0400 5,84529 37 Democracy Index (DEI) 5,5738 2,69133 37

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Correlations

FPC GEC REL IPC SER WAP DEI

Pearson’s Correlation FPC 1,000 ,156 ,056 ,266 ,153 ,289 ,297 GEC ,156 1,000 ,008 ,207 ,023 -,027 -,022 REL ,056 ,008 1,000 ,079 ,042 ,113 ,001 IPC ,266 ,207 ,079 1,000 ,030 ,281 ,666 SER ,153 ,023 ,042 ,030 1,000 ,045 ,200 WAP ,289 -,027 ,113 ,281 ,045 1,000 -,140 DEI ,297 -,022 ,001 ,666 ,200 -,140 1,000 Significance FPC . ,179 ,372 ,056 ,183 ,042 ,037 GEC ,179 . ,481 ,110 ,446 ,438 ,448 REL ,372 ,481 . ,321 ,402 ,253 ,499 IPC ,056 ,110 ,321 . ,429 ,046 ,000 SER ,183 ,446 ,402 ,429 . ,396 ,117 WAP ,042 ,438 ,253 ,046 ,396 . ,204 DEI ,037 ,448 ,499 ,000 ,117 ,204 . N = 37 Model Summary

R R square Adjusted R square Standard Error of the

Estimate

.507 ,257 ,109 ,96546

ANOVA

Sum of Squares

Df Mean Square F Significance

Regression 9,680 6 1,613 1,731 ,148

Residual 27,963 30 ,932

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Coefficients Unstandardized Coefficients Stnd. Coeffic-ients t Sig. 95% Confidence Interval for B Correlations B Stnd. Error Beta Lower Bound Upper Bound Zero-Order Partial Part (Con-stant) -7,185 7,318 -,982 ,334 -22,130 7,761 GEC 3,994E-6 ,000 ,233 1,370 ,181 ,000 ,000 ,156 ,243 ,216 REL ,021 ,141 ,023 ,148 ,884 -,267 ,309 ,056 ,027 ,023 IPC -1,245E-5 ,000 -,264 -,976 ,337 ,000 ,000 ,266 -,175 -,154 SER 1,195 7,150 ,028 ,167 ,868 -13,408 15,798 ,153 ,031 ,026 WAP ,077 ,034 ,440 2,281 ,030 ,008 ,146 ,289 ,384 ,359 DEI ,203 ,099 ,534 2,044 ,050 ,000 ,406 ,297 ,350 ,322

In Table 1, the results of the model that only includes the gas exporting countries are shown.

In the Descriptive Statistics, one can see the mean of the variables in question. Most importantly, there is the female participation in the labour force between 2011 and 2015. It is visible that the female participation has known a slight decline on average in the world in important gas exporting countries. On the other hand, the gas export has known a major decline as well over the five years. In my hypothesis, I argued that I suspected that the female participation would not have a negative connection with the gas export, countering Ross’ (2008) research on oil in the Middle East. This hypothesis appears to be correct, following the mean statistics in Table 1.

In the Correlations in Table 1, it is visible that there is a small positive correlation between the female participation and the gas export variables. However, the correlation has a significance of 0.179, meaning that it does not meet the requirements of significance (<0.05). This means that the correlation between the two is not statistically significant, which implies that no conclusions can be drawn from this correlation, as it is unable to explain a potential connection.

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The Model Summary shows us the R square, which is the percentage that the model explains the decline in the female participation. This is 0.257 in the model in Table 1. This implies that the variables in this model can explain difference in female participation for 25.7 percent.

The ANOVA gives us a perspective on whether the model is significant. The significance is 0.148, meaning that requirements for significance of the model are not met. Unfortunately, the model is therefore not able to explain the change in female participation in the labour force.

In the Coefficients in Table 1, the individual effect that each variable has on the female participation is shown. The first variables appear to be insignificant, including the gas export per country. The

democracy level and working age variables however, are significant. The working age percentage has a small positive influence on the female participation of 0.077, with a significance of 0.030. The democracy level appears to have a large effect on the female participation of 0.203 with a significance of 0.050. The significance of these variables implies that there is a connection between the working age and democracy level in gas exporting countries and the female participation in these countries. The influences however, are only small, meaning that, even though the connection is significant, the effects are not large.

Table 2 – Oil Export and Female Participation changes between 2011 and 2015

,3037 ,75177 42

Oil Export Change (OEC)

83,271 408,2354 42

Religion (REL) 2,12 1,400 42

22023,56 20428,586 42

Sex Ratio (SER) 1,0521 ,02301 42

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Correlations

FPC OEC REL IPC SER WAP DEI

Pearson’s Correlation FPC 1,000 -,028 ,070 ,150 -,110 ,094 ,071 OEC -,028 1,000 -,068 ,229 ,003 -,057 ,219 REL ,070 -,068 1,000 ,159 ,484 ,217 ,104 IPC ,150 ,229 ,159 1,000 -,128 ,354 ,552 SER -,110 ,003 ,484 -,128 1,000 ,199 ,062 WAP ,094 -,057 ,217 ,354 ,199 1,000 -,079 DEI ,071 ,219 ,104 ,552 ,062 -,079 1,000 Significance FPC . ,429 ,329 ,171 ,245 ,276 ,329 OEC ,429 . ,334 ,072 ,492 ,360 ,082 REL ,329 ,334 . ,157 ,001 ,083 ,257 IPC ,171 ,072 ,157 . ,210 ,011 ,000 SER ,245 ,492 ,001 ,210 . ,104 ,349 WAP ,276 ,360 ,083 ,011 ,104 . ,310 DEI ,329 ,082 ,257 ,000 ,349 ,310 .

N = 42

Model Summary

Estimate

,224 ,050 -,113 ,79303

ANOVA

Sum of Squares

Regression 1,160 6 ,193 ,307 ,929

Residual 22,012 35 ,629

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Coefficients Unstandardized Coefficients Stnd. Coeffic-ients t Sig. 95% Confidence Interval for B Correlations B Stnd. Error Beta Lower Bound Upper Bound Zero-Order Partial Part (Con-stant) 5,668 6,710 ,845 ,404 -7,955 19,290 OEC -7,252E-5 ,000 -,039 -,227 ,822 -,001 ,001 -,028 -,038 -,037 REL ,066 ,106 ,122 ,621 ,538 -,149 ,281 ,070 ,104 ,102 IPC 2,117E-6 ,000 ,058 ,230 ,819 ,000 ,000 ,150 ,039 ,038 SER -5,933 6,776 -,182 -,876 ,387 -19,688 7,822 -,110 -,146 -,144 WAP ,009 ,022 ,085 ,421 ,676 -,035 ,053 ,094 ,071 ,069 DEI ,016 ,068 ,053 ,239 ,812 -,123 ,155 ,071 ,040 ,039

In Table 2, the model that includes the difference in oil export between 2011 and 2015 of major oil exporting countries can be seen. The countries that export gas and not oil are left out of this model. In the Descriptive Statistics, we can see an interesting development. In the oil exporting countries, the female participation in the labour force has grown with 0.3037 between 2011 and 2015, where there was a slight decline in gas exporting countries. The oil export has also increased on average in those years, as is visible in the table, where the gas export declined. This means that there is again a high chance of a positive correlation between the two variables.

In the Correlations, we surprisingly see a small negative correlation between change in the oil export and female participation between 2011 and 2015, where the means of the countries combined showed a positive connection. The number, however, is so small (-0.028) that there barely appears to be a correlation between the two. Looking down in the Correlations, it is clear that none of the variables have a significant correlation with the female participation in this model.

In the Model Summary, the R square is extremely low. Only five percent of the model explains the rise of female participation in the labour force. This would imply that the change in oil export is not able to explain the change in female participation, contrary to what Ross (2008) has argued in his research.

In the ANOVA, we can see the significance of the model. This leaves us with a surprising result, compared to the R square in the Model Summary. The significance is 0.929, which is not significant

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enough for <0.05, but is surprisingly close and would meet the requirements of <0.1 significance. It implies that we can be 90 percent sure that the model explains a correlation.

The Coefficients in Table 2 tell us that the individual effect that the change in oil export has had on the female participation was extremely minimal. All of the variables all have met no significance,

meaning that no connection or correlation between any of the variables and the female participation can statistically be proven to be significant. This implies that, contrary to what Ross (2008) has stated in his research for the Middle Eastern region to be true, oil export does not have a linear connection with the female participation in the labour force worldwide.

Table 3 – Oil and Gas Export and Female Participation changes between 2011 and 2015

,2403 ,87293 24

-14843,121 73959,8194 24

76,046 511,1493 24

Religion (REL) 1,92 1,283 24

27753,99 22638,211 24

Sex Ratio (SER) 1,0496 ,00999 24

Working Age Percentage (WAP) 67,0129 5,80393 24 Democracy Index (DEI) 6,1229 2,54666 24 Correlations

FPC GEC OEC REL IPC SER WAP DEI

Pearson’s Correlation FPC 1,000 ,283 -,033 ,070 ,088 ,115 ,138 ,097 GEC ,283 1,000 -,004 ,022 ,306 ,142 -,010 ,025 OEC -,033 -,004 1,000 -,127 ,321 ,030 -,041 ,302 REL ,070 ,022 -,127 1,000 ,173 -,003 -,018 ,128 IPC ,088 ,306 ,321 ,173 1,000 -,307 ,258 ,570 SER ,115 ,142 ,030 -,003 -,307 1,000 -,538 ,083 WAP ,138 -,010 -,041 -,018 ,258 -,538 1,000 -,375 DEI ,097 ,025 ,302 ,128 ,570 ,083 -,375 1,000 Significance FPC . ,091 ,440 ,373 ,341 ,296 ,260 ,326 GEC ,091 . ,493 ,459 ,073 ,254 ,482 ,454 OEC ,440 ,493 . ,277 ,063 ,445 ,425 ,076 REL ,373 ,459 ,277 . ,210 ,495 ,466 ,275 IPC ,341 ,073 ,063 ,210 . ,072 ,112 ,002 SER ,296 ,254 ,445 ,495 ,072 . ,003 ,350 WAP ,260 ,482 ,425 ,466 ,112 ,003 . ,035 DEI ,326 ,454 ,076 ,275 ,002 ,350 ,035 .

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Model Summary

Estimate

,464 ,216 -,127 ,92691

ANOVA

Sum of Squares

Regression 3,780 7 ,540 ,628 ,726 Residual 13,747 16 ,859 Total 17,526 23 Coefficients Unstandardized Coefficients Stnd. Coeffic-ients t Sig. 95% Confidence Interval for B Correlations B Stnd. Error Beta Lower Bound Upper Bound Zero-Order Partial Part (Con-stant) -23,148 27,105 -,854 ,406 -80,609 34,313 GEC 4,263E-6 ,000 ,361 1,387 ,185 ,000 ,000 ,283 ,328 ,307 OEC -5,526E-5 ,000 -,032 -,132 ,897 -,001 ,001 -,033 -,033 -,029 REL ,048 ,157 ,071 ,305 ,764 -,286 ,382 ,070 ,076 ,068 IPC -1,444E-5 ,000 -,374 -,902 ,381 ,000 ,000 ,088 -,220 -,200 SER 16,670 24,540 ,191 ,679 ,507 -35,352 68,692 ,115 ,167 ,150 WAP ,078 ,051 ,521 1,542 ,143 -,029 ,186 ,138 ,360 ,341 DEI ,165 ,131 ,482 1,262 ,225 -,112 ,443 ,097 ,301 ,279

In Table 3, the results are shown for a model that includes the gas and oil exporting countries are shown. The countries that do not export one of the two are left out of this model, limiting the model to 24 cases.

The Descriptive Statistics show that also in the countries that are major oil and gas exporters, the gas export went down and the oil export went up between 2011 and 2015. This is similar to the models in which the countries that exported gas or oil were analysed. On average, the female participation in the

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labour force has risen over the years in the countries that were selected in this model. This means that, when looking at the means, there is a positive connection with the oil export and a negative one with the gas export of these countries.

In the Correlations, we see a negative correlation with the oil export and a positive correlation with the gas export, contradicting with the means of the variables. The oil export variable has, like in Table 2, a very limited correlation (-0.033). The gas export variable however, has a stronger correlation with the female participation (0.283). This could be explained by an outlier case, Russia, in which the gas export has decreased drastically. None of the variables have reached the <0.05 significance mark, but the gas export variable has gotten close with a significance of 0.091. This implies that the strong positive correlation between the gas export and the female participation has almost reached

significance. Even though the limit was not reached, some speculation on its implications can be done. The Model Summary gives us the R square, which is 0.216 in this model. This implies that the model explains 21.6 percent of the change in female participation in the cases that are selected for the model. The ANOVA gives us the significance of the model. The model that includes the gas and oil exporting countries is not significant, as it is 0.726. This is not enough to claim that the model is even close to significance, meaning that the model is not able to explain the rise in female participation between 2011 and 2015.

The Coefficients of Table 3 give us the information on the individual effect that the variables have on the female participation variable. None of the variables seem to have reached significance. The oil and gas export variables both individually have an extremely small effect on the female participation. Again, this model favours the arguments that were made against Ross (2008) by Rørbæk (2016), arguing that resources are not responsible for the change in female participation in the labour force. On the other hand, the ‘religion’ variable does not reach significance either. One does have to keep in mind that religion is not the whole culture, as described in the limitations.

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Table 4 – Oil Export and Female Participation changes between 2011 and 2015 in the Middle

East

,2160 1,21239 8

10,950 633,7452 8

Religion (REL) 2,00 ,000 8

25545,39 20084,828 8

Sex Ratio (SER) 1,0425 ,01165 8

Working Age Percentage (WAP) 72,3900 8,73752 8 Democracy Index (DEI) 2,9938 ,71470 8 Correlations

FPC OEC REL IPC SER WAP DEI

Pearson’s Correlation FPC 1,000 ,120 . ,509 -,523 ,515 -,040 OEC ,120 1,000 . ,125 -,105 -,267 ,463 REL . . 1,000 . . . . IPC ,509 ,125 . 1,000 -,587 ,852 ,012 SER -,523 -,105 . -,587 1,000 -,530 -,192 WAP ,515 -,267 . ,852 -,530 1,000 -,331 DEI -,040 ,463 . ,012 -,192 -,331 1,000 Significance FPC . ,389 ,000 ,099 ,092 ,096 ,462 OEC ,389 . ,000 ,384 ,402 ,261 ,124 REL ,000 ,000 . ,000 ,000 ,000 ,000 IPC ,099 ,384 ,000 . ,063 ,004 ,488 SER ,092 ,402 ,000 ,063 . ,088 ,325 WAP ,096 ,261 ,000 ,004 ,088 . ,212 DEI ,462 ,124 ,000 ,488 ,325 ,212 .

N = 8

Model Summary

Estimate

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ANOVA

Sum of Squares

Regression 4,093 5 ,819 ,264 ,900b Residual 6,196 2 3,098 Total 10,289 7 Coefficients Unstandardized Coefficients Stnd. Coeffic-ients t Sig. 95% Confidence Interval for B Correlations B Stnd. Error Beta Lower Bound Upper Bound Zero-Order Partial Part (Con-stant) 26,980 88,850 ,304 ,790 -355,312 409,272 OEC ,001 ,002 ,304 ,379 ,741 -,006 ,007 ,120 ,259 ,208 IPC -1,590E-5 ,000 -,263 -,159 ,889 ,000 ,000 ,509 -,111 -,087 SER -31,490 76,628 -,303 -,411 ,721 -361,196 298,215 -,523 -,279 -,225 WAP ,091 ,257 ,654 ,353 ,758 -1,016 1,197 ,515 ,242 ,193 DEI -,033 1,318 -,020 -,025 ,982 -5,703 5,636 -,040 -,018 -,014

In Table 4, only the cases that are located in the Middle East and export oil have been selected. I have chosen to specifically look at the Middle East, as this is where Ross (2008) focussed on in his research when he came to the conclusion that oil was responsible for the female participation in the labour force. It needs to be said that my case selection is smaller, as I have only included the major oil and gas exporters in the region. The religion variable is not taken into account in this model, as it is constant. All the countries have a majority Muslim population.

In the Descriptive Statistics, we can see that both the female participation and the oil export has known a rise in the Middle East between 2011 and 2015. This shows a positive connection between the two, as both have risen in the selected period.

In the Correlations table, we see a correlation of 0.120 between the female participation and the oil export variables. This connection is positive, as expected due to the means in the Descriptive Statistics table. The correlation however, is not significant (0.389).

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In the Model Summary, it is visible that the R square is 0.398. This means that the model is able to explain 39.8 percent of the rise in female participation between 2011 and 2015.

In the ANOVA, we see that the significance of the model is 0.900, which does not fit in the <0.05 significance, but we can say that the model is 90 percent sure that it can explain a correlation. Finally, in the Coefficients table, the individual influence per variable is shown. Again, the influence of oil export seems to be very small. The variable also has not reached significance in this table. A variable that has reached significance, is the democracy index. The democracy index also had an influence in gas exporting countries worldwide. The democracy index has a small negative influence on the female participation, which is surprising to say the least. In Table 1, the influence was larger and positive. This would mean that in the oil-exporting countries in the Middle East, the lower the democracy index is, the higher the female participation is.

Table 5 – Oil and Gas Export and Female Participation changes between 2011 and 2015 in

the Middle East

-,1682 1,61692 9

1877,980 8556,1324 5

10,950 633,7452 8

22862,78 20438,758 9

Sex Ratio (SER) 1,0422 ,01093 9

Working Age Percentage (WAP) 70,7267 9,57608 9 Democracy Index (DEI) 2,8911 ,73604 9

The number of cases of countries in the Middle East that export gas, or gas and oil, is too low in the dataset that I have used in this research to be able to make a proper regression analysis. As can be visible in Table 5, there are only 5 countries in the Middle East that export gas and 4 that export both gas and oil. We can however, obtain some numbers from the Descriptive Statistics table.

The female participation in the labour force has, in contrary to the countries that only export oil located in the Middle East, declined between 2011 and 2015. This decline can be almost solely be blamed on Yemen, which is the only country in the Middle East in my dataset that does not export oil but does export a significant amount of gas. Yemen is in a state of civil war since 2015 (Bazzi, 2018).

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This has resulted in a completely failed state, meaning that there is no place for female participation in the labour force, if one can speak of any labour force at all. The consequences are that Yemen has a major effect on the dataset of Middle Eastern countries, as only their data is already able to push the numbers of female participation in the labour force to a negative number. Besides the female

participation numbers, Yemen has also known a major decline in gas export, likely caused by the civil war, meaning that the gas exports in the Middle East are also affected by the negative numbers of Yemen. This number however, as can be seen in the descriptive statistics, is still positive. The

democracy index has also dropped one decimal, compared to the Descriptive Statistics in Table 4, also likely to be caused by the situation in Yemen.

Not many conclusions can be drawn from this table, due to the lack of cases. Yemen can be seen as an outlier, as it’s data is drastically different compared to the other cases in the Middle East. Yemen is the only country that is only exporting gas and not oil in the Middle East in my dataset, which means that the oil exporting countries, which have already been discussed in Table 4, make up the rest of the region. This means that the conclusions can be drawn from Table 4.

Table 6 – Oil and Gas Export and Female Participation changes between 2011 and 2015 in

Islamic countries

,0798 1,22865 20

-23059,313 93081,8206 15

-11,933 462,2534 15

13067,79 16213,089 20

Sex Ratio (SER) 1,0425 ,03007 20

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Correlations

FPC GEC OEC REL IPC SER WAP DEI

Pearson’s Correlation FPC 1,000 ,307 ,142 . ,277 ,105 ,180 ,260 GEC ,307 1,000 -,120 . ,251 ,207 ,069 -,591 OEC ,142 -,120 1,000 . ,228 ,112 ,055 ,332 REL . . . . . . . . IPC ,277 ,251 ,228 . 1,000 -,674* _,861** _-,266 SER ,105 ,207 ,112 . -,674* _1,000 _-,637* _,241 WAP ,180 ,069 ,055 . ,861** _-,637* _1,000 _-,320 DEI ,260 -,591 ,332 . -,266 ,241 -,320 1,000 Significance FPC . ,389 ,696 . ,439 ,772 ,619 ,468 GEC ,389 . ,740 . ,485 ,566 ,849 ,072 OEC ,696 ,740 . . ,526 ,758 ,881 ,349 REL . . . . . . IPC ,439 ,485 ,526 . . ,033 ,001 ,458 SER ,772 ,566 ,758 . ,033 . ,048 ,502 WAP ,619 ,849 ,881 . ,001 ,048 . ,368 DEI ,468 ,072 ,349 . ,458 ,502 ,368 .

N = 20

Model Summary

Estimate

,739 ,547 -,360 1,52600

ANOVA

Sum of Squares

Regression 8,426 6 1,404 ,603 ,726

Residual 6,986 3 2,329

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Coefficients Unstandardized Coefficients Stnd. Coeffic-ients t Sig. 95% Confidence Interval for B Correlations B Stnd. Error Beta Lower Bound Upper Bound Zero-Order Partial Part (Con-stant) 12,264 97,522 ,126 ,908 -298,096 322,624 GEC 1,137E-5 ,000 ,989 1,047 ,372 ,000 ,000 ,307 ,517 ,407 OEC 2,996E-5 ,002 ,011 ,020 ,986 -,005 ,005 ,142 ,011 ,008 IPC - 2,485E-5 ,000 -,399 -,253 ,817 ,000 ,000 ,277 -,145 -,098 SER -20,136 97,601 -,198 -,206 ,850 -330,747 290,475 ,105 -,118 -,080 WAP ,098 ,162 ,644 ,603 ,589 -,417 ,612 ,180 ,329 ,235 DEI ,846 ,597 ,989 1,416 ,252 -1,055 2,746 ,260 ,633 ,550

In Table 6, only the cases in which Islam is the dominant religion are analysed. Rørbæk (2016) argued that the culture within Islamic culture is to blame for the lack of female participation in the labour force of these countries. However, in this research, the connection with oil and gas export and the female participation is analysed, following Ross’ (2008) arguments. As the religion variable has become constant in this model, it is automatically excluded. The other variables are included. In the Descriptive Statistics, one can see that the oil and gas export has known a relatively small decline in these countries, while the female participation has risen between 2011 and 2015. The decline in export can be explained by the decline in the price of the resources. The Descriptive Statistics implies that there is a negative connection between the export and female participation variables, like Ross (2008) implies in his research.

In the Correlations table, we surprisingly see a positive connection between the gas and oil export and the female participation in the labour force of respectively 0.307 and 0.120, but both are not

significant.

The Model Summery tells us that the model of the regression analysis can provide an explanation for the correlation for 54,8%, which is quite a high number.

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The ANOVA table says that the model has a significance of 0.726, which is not enough to reach significance. It does mean that the model can be argued to be correct for 72.6%.

In the Coefficients table, the individual influence per variable is shown. This provides an interesting outcome. The variable of the oil export has reached significance in this model (0.986), meaning that in Islamic countries, there is a connection between the oil export and the female participation in the labour force. However, when looking at the first column of this table, it can be seen that the correlation is extremely small. So concluding on this table, a connection between the oil export and female

participation is proven in Islamic countries, but the correlation is only minimal and not even negative. Again, the influence of oil export seems to be very small. The variable also has not reached

significance in this table. A variable that has reached significance, is the democracy index. The democracy index also had an influence in gas exporting countries worldwide. The democracy index has a small negative influence on the female participation, which is surprising to say the least. In Table 1, the influence was larger and positive. This would mean that in the oil-exporting countries in the Middle East, the lower the democracy index is, the higher the female participation is.

All of these results show us that both oil and gas export are, according to the models, not able to explain the change in female participation in the labour force. According to my analysis, the conclusion that Ross drew in his research in 2008 is wrong and is potentially based on a spurious relationship. In the analysis, I shall extensively discuss the results and its implications

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Analysis

In this analysis, the results that were shown in the previous paragraphs will be widely discussed. The meanings of the numbers in the tables and its implications will be analysed and explained in the next paragraphs. Through the analysis, the research question can be answered and the hypotheses can be labelled as true or false.

In the Descriptive Statistics in Table 1 and 2, we can see the average development of the gas and oil export between 2011 and 2015 and the female participation in oil and gas exporting countries. The gas export has declined with a staggering 9148.527 cubic meters, while the oil export has risen with 83271 barrels per day on average per country. When looking at the averages, it appears that the majority of the countries therefore did not alter their oil export strategy when the price dropped in the selected years. Interestingly enough, the US even rose their oil export with over 50 percent. The gas export did see a decline, partially because of Russia limiting their export 35573.1 cubic meters, which is just below the average gas export in the major gas exporting countries used in my dataset. For the female participation in the labour force, there is a slight rise in the selected period. Between 2011 and 2015, there was an average rise of 0.1232 per country. When looking at gas and oil exporting countries on the female participation in the labour force, an interesting result can be seen. In the major gas exporting countries, there is a small decline in the female participation in gas exporting countries of 0.0057. The drop in the gas exporting countries is countered by the rise in female participation of a staggering 0.3037 in oil exporting countries, which is quite a big change when comparing this to the change of female participation in gas exporting countries. This large difference is an interesting result and needs an explanation. This difference is interesting, as it implies a major difference in gas and oil exporting countries in terms of female participation in the labour market in the years between 2011 and 2015. Where it is possible to speculate at this moment to find an explanation for this difference, I argue that new research is necessary to analyse the reasons behind this difference in the data.

As can be seen in Table 1, 2 and 3, we can conclude that there is no significant connection between the oil and gas export of a country and the female participation in this particular country. Only in Table 3, the correlation between the gas export and the female participation of oil and gas exporting countries was close to significance. The connection was positive, implying that a higher gas export would result in a higher female participation in the labour force, contrary to Ross’ (2008) conclusions on the oil export in the Middle East. However, because significance was not reached, this conclusion cannot be officially drawn. As is just discussed in the results, the significance is not between the boundaries and therefore, the hypothesis is rejected. This implies that the research that Ross (2008) has conducted, is at least not applicable for the whole world. Where he came to the conclusion that resources are responsible for the lack of female participation in the labour force, I have found that this is not

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accurate for the whole world. Female participation is not significantly affected by the oil and gas export of a country. This result answers an important part of my research question.

Where an important part of the research question is answered, the world can still be divided in regions and religions to see whether the hypothesis is true for a particular region or religion of the world. In Table 4, the results for the Middle Eastern region can be found. It can be seen that for the Middle-Eastern region, the oil export is not significantly correlating with the female participation as Ross (2008) described it in his research. However, as stated before, I only analysed the major oil or gas exporting countries in the world, meaning that I have less cases in the region than Ross (2008) had included. In Table 6 however, one of the variables did reach significance. The oil export variable was significant for Islamic countries. The influence however, was so minimal, that one could not speak of a major effect on the female participation in the labour force of Islamic countries. The religion variable could not be included in this model, as this was constant. This means that I am not able to see if Rørbæk’s (2016) conclusions are correct. It is interesting to see however, that the one model that only included Islamic countries, has reached significance in the oil export variable.

According to the different models that I have created within the dataset, the explanation should either be sought within the democracy index or the working age variables. The democracy index was significant in both the gas export model (Table 1) and the oil export in the Middle East model (Table 4). Surprisingly, the B is positive in the first model and negative in the last model. This means that in major gas exporting countries worldwide, the higher the democracy index is, the higher the female participation is. In the oil exporting countries in the Middle East, the higher the democracy index, the lower the female participation is. One must keep in mind however, that only eight cases were included in the model, meaning that a single outlier can have a major impact on the results. In the case of Oman for example, there was a major decrease in female participation between 2011 and 2015 of 2.53 percent, while the democracy index for Oman is average for the region. Iraq, the country with the highest democracy index in the region (4.09), knew a rise in female participation in that particular period. This is likely how the Middle Eastern results were formed. The working age variable was also significant in the worldwide gas export model, implying that a higher percentage of people within the working age (16-65) would also indicate a higher female participation rate in the labour force. The B is rather small (0.077), meaning that the influence of the working age variable is not very large. Due to its significance however, we do have to take it into account.

The results show us that the conclusions that were drawn by Ross in his research, are at least not applicable to the major gas and oil exporters worldwide between 2011 and 2015. The price drop that the oil price primarily has experienced in the time frame selected for my research, is an interesting factor. The oil export from the major exporters in number of barrels increased slightly in the time frame, despite the price drop. This means that the production was not limited, but increased instead.