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GENDER EQUALITY AND GROWTH

What is the effect of gender equality on the economic growth in the

OECD countries?

Bachelor Thesis

University of Amsterdam

Bachelor Thesis: Juliette van der Werf Nr.: 6165796

Supervisor: Thomas Buser August 2014

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INDEX  

1. INTRODUCTION  ...  3  

2. LITERATURE REVIEW  ...  4  

3. METHODOLOGY AND DATA  ...  9  

4. RESULTS  ...  13  

5. CONCLUSION AND RECOMMENDATIONS  ...  18  

6. REFERENCE LIST  ...  20  

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1. INTRODUCTION

This bachelor thesis examines the effect of gender equality on the economic growth in the OECD countries.

“In the aftermath of the Great Recession, there is an urgent need to focus on the economic case for gender equality and on how changes in the labor market might provide better economic opportunities for both men and women.”

- OECD report 2012, Closing the Gender Gap: Act Now

These are the exact words in the introduction to the OECD’s Closing the Gender Gap Report of 2012. This report points out that gender equality is relevant for the economy and its development, both in developing and developed countries.

According to the OECD report, during the last two decades many countries worldwide have made significant changes with respect to gender equality, and it can be said that gender equality has made huge progress, both in education and employment. Many OECD countries experienced an exemplary rise in the female education and employment rates in the 70s and 80s, and the gender wage gap was starting to close. As you can see in Figure 1 (OECD, 2012) in the Appendix, the gender gap of the labor force across the OECD countries narrowed in the period of 1980-2010. Notice the variation of the gender gap levels in the labor force across the OECD countries. However, women continue to experience gender discrimination. For example, women still earn less than men, they face higher barriers to achieve high-level positions in business than men, and it is more common for women to spend their final years in poverty (OECD, 2012).

Economists and other analysts have actively investigated the relationship between growth and gender equality, but mostly in developing countries. Therefore the literature review of this thesis will mostly include literature on the effect of gender equality on the development and growth in developing countries.

The purpose of this thesis is to investigate whether there is a significant effect of gender equality on the economic growth in the OECD countries. The central question will be “What is the effect of gender equality on the economic growth in the OECD countries?”

To answer this question, an OLS panel data regression analysis with country fixed-effects is used to investigate the effect of gender equality on the economic growth in the OECD countries during 15 years.

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This paper is laid out as follows: Section two will provide a literature review based on documented empirical evidence of the effects of gender inequality on growth and human development. This literature is mostly based on developing countries. In addition, this section also presents the various channels via which gender equality in education and employment tends to increase growth. Section three provides the data and the definitions of the variables that are used, followed by the description of the methodology. The main results of this investigation are highlighted in section four. In section five the main conclusions and recommendations are discussed.

2. LITERATURE REVIEW

This section will provide an overview of the existing literature on gender equality, economic growth, and empirical evidence that gender equality tends to exert effects on the economic growth. The majority of the literature relates to developing countries. This is because in countries where poverty is a primary issue, for example in parts of Africa, there is an even greater and more urgent need for gender equality and its ensuing effect on human development and growth (OECD, 2012). Also the possible and various channels in which gender equality could affect growth will be explained in the second part of this section.

Based on neo-classical production function and exogenous savings and population growth, Solow (1956) created a model for economic growth. He suggested that the savings rate and the population growth have effects on the steady-state level of income per capita. Later on, Mankiw, Romer and Weil (1992) expanded Solow’s growth model by the inclusion of human capital (which has an indirect effect on the level of technology) as an extra measurement in the traditional Solow model. This model emphasizes the importance of human capital for economic growth.

Mankiw et al. (1992) found that education has a significant effect on growth. They explained that knowledge and production are a part of the growth process, and thus the effect of education on growth is of great importance.

There are a few models that have explicitly investigated the impact of gender equality in education on economic growth and development. Micro literature, such as (Gertler and Alderman, 1989) on gender points out the different reasons for why parents invest more in the education and health of their sons than in that of their daughters. Because male and female are imperfect substitutes in the labor force, investing more in boys’ education seems to be a more

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beneficial choice for the parents. Parents also have a direct benefit of investing in their son, because they expect to be supported by him in their old age. Daughters tend to leave the family and become part of another family.

One of the arguments suggested by theoretical literature (Klasen, 1999) is that gender inequality in developing countries is preventing a reduction of child mortality, fertility, and the expansion of the education of the next generation. Thus, gender bias in education and employment has a reducing effect on human capital in a society and therefore an indirect impact on economic performance.

Barro and Lee (1994) found in their cross-section growth regression study that female education has a significantly negative effect on the economic growth. They found that the initial level of female secondary education had a negative effect on their growth equation. Klasen (1999, 2002) however arrived at the opposite conclusion in his work. With his cross-country regression study on developing countries (South Asia, Middle East, and Sub-Saharan Africa) he showed that through lowering the average quality of human capital, gender inequality in education has a direct effect on the economic growth. And through the impact of gender inequality on investments in human capital and population growth there is an indirect effect on economic growth. He concluded that if the developing countries as South Asia, Middle East, and Sub-Saharan Africa would have achieved gender equality in schooling between 1960 to 1992 as rapidly as the countries in East Asia did, they would have enjoyed an additional growth of income per capita of 0.5 to 0.9 percentage points per year.

Hill and King (1995) also studied the effect of gender equality in secondary education on income. They only used a different indicator for growth. Instead of GDP growth, they related gender equality to the GDP levels. They found an association between the low female-male enrollment rate and a lower GDP per capita.

Dollar and Gatti (1999) focused more on the endogeneity of gender differentials. They proved in their study that gender inequality in education is bad for the economic growth and that it is not an efficient economic choice to refrain from investing low in women. They found that the level of female education has to increase considerably to have a minor effect on economic growth. Moreover, if there is a high level of female education, even a small further increase of it will boosts the economy drastically.

Several studies link gender equality to fertility rates and child mortality. Summers (1992) investigated and found that on average women in Africa with more than seven years of education have two fewer children than women with no education at all.

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Lagerlof (1999) investigated the impact of gender inequality in education on fertility and economic growth. He found that a continued gender inequality rate will lead to higher fertility and a lower level of economic growth.

In 2005 The World bank investigated the annual GDP growth in Northern Africa and in the Middle East in the year 1990. They concluded that if women participated more actively in the labor force, the annual GDP growth would be 0.9 percent higher (Lehmijoki & Palokangas, 2006).

According to the OECD’s Closing Gender Gap Report of 2012, it is also necessary to continue focusing on solving the gender inequality issue in developed countries. The report mentions that greater gender equality in economic opportunities contributes to a stronger, more sustainable economic growth for both developed and developing countries. Also according to the OECD report in 2012, gender equality is one of the key drivers in happiness and life satisfaction, which contribute to sustaining economic growth.

So in sum, there are several studies that have shown support for a positive impact of gender equality (and in particular in education and employment) on economic performance and development. But the reasons for these positive effects of gender equality on economic growth and development are still disputed. However, in the many papers of Klasen (1999, 2002), he speculates about the various channels via which gender equality in education and employment could have a positive effect on economic growth. These possible channels are the selection distortion factor, the environment effect and the demographic transition effect and are explained below.

The Selection-Distortion Factor

The two assumptions are: 1) boys and girls have a very similar distribution of innate abilities and 2) it is more likely that children with higher innate abilities will receive education. With these assumptions in mind and assuming the capacity of schools to be constant, Klasen suggests that gender inequality in education must imply that the less talented boys are more able to receive education than (more highly talented) girls, and so the average level of innate abilities of those who become educated is lower than it would be if girls had the same access to education as boys. Hence, when boys and girls with the same innate abilities receive equal opportunities in education (which means gender equality) the average level of innate ability of the educated children will rise. This higher average will result in a higher average of productivity of human capital, and in turn this rise in human capital productivity would result

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in a higher rate of economic growth. As mentioned above, Dollar and Gatti (1999) found a similar result, i.e. that a rise in female education would have a positive impact on economic growth.

In addition, Klasen (2002) also mentioned that the higher level of human capital tends to have an indirect effect on economic growth by increasing the total rate of return to capital, which will lead to a higher investment rate and thus further the increase of economic growth.

According to Klasen (2002), the gender equality in employment will have a similar effect that operates at the level of the labor force. Gender equality will lead to a higher average of productivity in the labor force than a gender gap would. Higher labor force productivity tends to improve economic growth, both directly and indirectly (via a lower investment rate).

The Environment Effect

Klasen (2002) suggests that female education tends to have positive external effects on both the quality and quantity of the education for children. The children of educated mothers are more motivated towards education via the support system and general environment provided by an educated mother and this will lead to a rise in the human capital of the next generation. This higher level of next generation human capital will stimulate the economic growth. This could be backed up by the study of Stevenson and Baker (1987). They found that the educational status of the mother is related to the degree of parental involvement in the education of the child, and this degree of involvement is related to the school performance of the child.

In addition Klasen (1999) mentions some evidence that indicates if the level of education is similar in the household, this will promote the positive external effects on the quality and quantity of education. For instance, siblings who are equally educated can support and inspire each other in both their educational success and activities. In the same way, life partners with a similar level of education may stimulate and support each other in life-long learning. So, according to Klasen (2002), having more educated women will improve the intellectual environment in households, which will also improve the human capital.

The Demographic Transition Effect

As discussed above, it has been documented that a higher level of female education (the result of gender equality in education) has a significant causal effect on a decline in fertility (Lagerlof, 1999). This is because women who have received education tend to marry and have children at a later age. Also the time interval between pregnancies tends to increase. In

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consequence, they give birth to a fewer number of children. Galor and Weil (1996) found in their paper of gender gaps, fertility and growth that the household fertility rate is subject to male and female wages. Improvement of female education leads to women’s work becoming more expensive and thus it is likely this will lead to the reduction of fertility.

In addition, Galor and Weil (1996) concluded that an increase of women’s wages would lead to an increase of the costs of having children relative to the household income, which also leads to fertility reduction.

As discussed by Klasen (2002), this reduced level of fertility affects the economic growth in four ways:

1. The reduced level of fertility lowers the youth dependency burden, which is the ratio of number of youth to the number of people in the working age population. The decrease in number of youth tends to lower the total dependency burden, which is the ratio of the number of youth and the elderly to the number of people in the working age population. This leads to an increase in the aggregate supply savings within the economy.

2. The reduced levels of fertility lower the population growth. This means the capital investments increase, because there is more capital available per worker. This leads to an increase in the economic growth.

3. There will be a boost in investment demand for a limited period because of the increase in working population.

The upsurge of workers entering the labor force due to the previously high population growth means that there will be an increase in the demand for investments in capital equipment. This higher investment demand, together with the increased supply in savings, will result in a higher investment rate, which should increase the economic growth.

4. After some years, when the growth in the labor force is absorbed, these reduced levels of fertility will lead to be a “demographic gift” as referred by David E. Bloom and Jeffrey G. Williamson (1998). The working-age population would grow faster than the overall population. Because of the fact that there are more workers who have to share their income with fewer dependents, they are boosting the average income per capita and hence have a positive impact on economic growth. According to the OECD gender gap report of 2012, Korean economic transformation is an example of this. One of the reasons for this transformation was the Korean family-planning policy in the 1960s (to curb the birth rate) that stimulated the investments per child.

However, Klasen mentions that “the demographic gift” and its impact on the average income per capita is a temporary effect. After a few decades the working age population will decline

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and the inactive working population will increase. In other words, the total dependency burden will start to increase and thus, the average income per capita will begin to decline. This could be seen in the Korean example. The OECD report mentioned that in Korea from 2018 the working age population will start to decline (as demonstrated in figure 2 in the appendix). The figure shows the impact of the Korean family planning policy; after 1960 there is an increase in the working age population, but it is expected to decline after 2018. Still, according to Bloom and Willliamson (1998), this temporary effect tends to have made a considerable contribution to the rapid growth in East and Southeast Asia.

So in sum, a lower fertility rate will have both direct and indirect effects (due to savings and investment) on growth.

3. METHODOLOGY AND DATA

This section provides the econometric analyses of the effects of gender equality in education and gender equality in employment on the economic growth in the OECD countries. OECD promotes policies that will improve the economic and social well-being of people around the world. The organization includes 31 of the world’s most advanced countries, but also three emerging countries (Mexico, Chile and Turkey). (Source: OECD) 1

This section starts by presenting the definitions and the sources of the variables used in this paper. The second part will describe the methodology used to analyze the data.

Definitions of variables and sources of data

The main data in this paper are provided by the data of the World Bank Group and the OECD group. The data provide information from all of the 34 OECD countries for a period of 15 years (1999-2013).

Dependent variable

To fully understand the relationship between economic growth and gender equality, one measure of economic growth has been selected. The average growth rate of GDP is used to measure the economic growth.

The annual GDP growth rate (GDP) is the annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2005 U.S. dollars. GDP is the sum of gross value added by all resident producers in

                                                                                                               

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the economy plus any product taxes, minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. (Source: World Development Indicators)2

Independent Variables: Gender equality variables

There are four different indicators of gender equality used to investigate the effects of gender equality on the economic growth of the OECD countries. According to the Global Gender Gap report 2013, these gender equality indicators represent three different fundamental categories that examine the gap between men and women. The categories are economic participation, political empowerment and educational attainment.

• Female share in labor force participation (FLF) is the proportion of females in the

labor force participation rate. (Source: World Development Indicators)3

• Gender Wage Gap (WAG) is unadjusted and defined as the difference between male and female median wages divided by the male median wages. Data refer to full-time employees. (Source: OECD Employment database)4

Proportion of seats held by women in national parliaments (%) (PAR). Women in

parliaments are the percentage of parliamentary seats in a single or lower chamber held by women. (Source: World Development Indicators)5

Ratio of female to male tertiary enrollment (%) (EDU) is the percentage of men to

women enrolled at tertiary level in public and private schools. (Source: World Development Indicators)6

Independent Variables: Control variables

Based on the literature, there are different control variables used to measure the population growth, labor force growth and the investment growth to see the effects on economic growth in the OECD countries.

Unemployment, total (% of total labor force)(UMPL) refers to the share of the labor

force that is without work but available for and seeking employment. (Source: World Development Indicators)7                                                                                                                 2  http://databank.worldbank.org/data/views/reports/tableview.aspx?isshared=true   3  http://databank.worldbank.org/data/views/reports/tableview.aspx   4  http://stats.oecd.org/index.aspx?queryid=54751   5  http://databank.worldbank.org/data/views/reports/tableview.aspx   6  http://databank.worldbank.org/data/views/reports/tableview.aspx  

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Population Total (POP GR) is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship - except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. The values shown are midyear estimates. (Source: World Development Indicators)8

S&P Global Equity Indices (S&P) measures the U.S. dollar price change in the stock markets covered by the S&P/IFCI and S&P/Frontier BMI country indices. (Source: World Development Indicators)9

Domestic credit to private sector (DCPS) refers to financial resources provided to the

private sector by financial corporations, such as through loans, purchases of non-equity securities, and trade credits and other accounts receivable that establish a claim for repayment. Financial corporations include monetary authorities and deposit money banks, as well as other financial corporations where data are available (including corporations that do not accept transferable deposits but do incur such liabilities as time and savings deposits). (Source: World Development Indicators)10

Methodology

To estimate the effect of gender equality in education and employment on the economic growth in the OECD countries, the OLS panel regressions with country fixed-effects were used. In testing the effect of gender equality on growth, it was obvious that the endogeneity issue would arise. Figure 3 (OECD, 2012) in the appendix demonstrates that gender equality in education and growth are related. Rich countries have a higher level of gender equality than poorer countries. But this leaves us with the question: do women need to live in a rich country to experience a higher level of gender equality, or does gender equality stimulate the growth? This reverse causality is one of the sources of the endogeneity issue. The other source of the endogeneity issue is the possibility of unobserved or omitted variables in the regression model. These unobserved or omitted factors could correlate with one or more of the variables, and thus makes the estimates of the 𝛽′𝑠 biased (Wooldridge 2002). The endogeneity issue could partly be solved by using the fixed effect method. The fixed effects approach is an efficient way to control for these unobserved, omitted and time-invariant factors, because they

                                                                                                                                                                                                                                                                                                                                                          7  http://databank.worldbank.org/data/views/reports/tableview.aspx  

8  http://databank.worldbank.org/data/views/reports/tableview.aspx   9  http://databank.worldbank.org/data/views/reports/tableview.aspx   10  http://databank.worldbank.org/data/views/reports/tableview.aspx  

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all drop out when estimating the equation (Wooldridge, 2002). For example, the basic linear specification of the effect gender equality on economic growth could be as follows:

(1) 𝐺𝐷𝑃!" = 𝛽!  + 𝛽!𝐺𝐸𝐼!"+ 𝛽!𝑋!" + 𝛽!𝑆!"+ 𝑢!  + 𝑒!"

Where 𝐺𝐷𝑃!" is the measure of the economic growth of country i at time t, 𝐺𝐸𝐼 is the measure of the gender equality, 𝑋 measures independent control variables, 𝑆 is a vector of state dummies, 𝑢!  represents unobserved factors that do not vary over time, 𝑒!" is the random

time-varying error, and 𝛽′𝑠 are the coefficients to be estimated.

If there are no unmeasured or unobserved variables that are significantly correlated with the economic growth measure and the gender equality indicator variables, Equation (1) provides consistent coefficient estimates. But if 𝑢!is correlated with one of the variables, results will be invalid (Wooldridge 2002). A common way to control for the potential endogeneity is the fixed effect approach. By averaging Equation (1) over time for each i country, the fixed effects model is obtained as you can see in Equation (2):

(2)      𝐺𝐷𝑃!= 𝛽!  + 𝛽!𝐺𝐸𝐼!+ 𝛽!𝑋!+ 𝛽!𝑆!+ 𝑢!  + 𝑒!

Next, subtracting Equation (1) from Equation (2) for each t gives:

(3) 𝐺𝐷𝑃!"−  𝐺𝐷𝑃!   = 𝛽!  + 𝛽! 𝐺𝐸𝐼!"− 𝐺𝐸𝐼! + 𝛽!(𝑋!"− 𝑋!) + (𝑒!"− 𝑒!)

The unobserved heterogeneity, which was included in 𝑢!  , drops out of the final equation along with all time-invariant variables. The final equation generates consistent coefficient estimates for the variables (Wooldridge 2002).

1. Ordinary Least Squares Estimation

Again the variable that measures growth is used as dependent variable, and the other variables, both gender equality variables and/maybe the control variables as independent variables.

The regression specification, which investigates the effect of the gender equality of the economic growth, is estimated in two ways. First, Equation (4) provides the direct effect of one of the four gender equality indicators on the economic growth. Equation (5) calculates the indirect effect of one of the four gender equality indicators on the economic growth:

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(5) 𝐺𝐷𝑃  𝑔𝑟𝑜𝑤𝑡ℎ = 𝛽!  + 𝛽!𝑈𝑀𝑃𝐿 + 𝛽!𝑃𝑂𝑃  𝐺𝑅 + 𝛽!𝑆&𝑃 + 𝛽!𝐷𝐶𝑃𝑆 +      𝛽!𝐺𝑒𝑛𝑑𝑒𝑟  𝐸𝑞𝑢𝑎𝑙𝑖𝑡𝑦  𝑖𝑛𝑑𝑖𝑐𝑎𝑡𝑜𝑟

4. RESULTS

Descriptive statistics

Table 1a represents the acronyms of the variables. Table 1b represents a summary of the descriptive statistics for the variables used in the analysis. As you can see, the observations are different among the variables. This is because of some missing information among the data that are collected across the OECD countries. Further, the descriptive statistics provide the mean, standard deviation, and the minimum and maximum of the data values of the variables. The most important descriptive statistics are detailed below.

Table 1a Variable names

EDU Ratio of female to male tertiary enrollment

PAR Proportion of seats held by women in national parliaments

FLF Female share in labor force participation WAG Gender Wage Gap

UNEM Unemployment, total

POP Population Total

SP S&P Global Equity Indices

DPS Domestic credit to private sector

GDP The annual GDP growth rate

Table 1b Descriptive Statistics

 

Variable Obs Mean Std. Dev. Min Max EDU 432 124.5516 25.38075 60.127 191.182

PAR 502 23.16474 10.58002 3.7 47.3

FLF 476 51.31155 8.554067 23.4 71.7

WAG 307 16.90808 7.780594 0.384 40.394

UNEM 476 7.286134 3.709143 1.8 25.2

POP 476 3.54E+07 5.58E+07 277381 3.14E+08 SP 454 9.788983 33.57639 -69.9427 138.5755 DPS 457 108.9181 54.67333 13.28584 319.4609 GDP 476 2.412004 3.134115 -14.0983 10.97129

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As described above, the ratio of female to male tertiary enrollment is the percentage of men to women enrolled at tertiary level. As shown in table 1, the mean of the enrollment of men to women in tertiary educational levels is around 124.6%. This corresponds with the results of the OECD report of 2006 as you can see in figure 4 (OECD, 2006) in the appendix, which shows the percentage of men and women with tertiary education in 2004 across the OECD countries. As mentioned in this report, and as shown in figure 4, in over half of the OECD countries the female attainment rates exceed those of men. Especially in Canada, Finland, Sweden and New Zealand the rates are significantly higher. This is in contrast to the substantially higher percentages of male attainment rates in Korea and Switzerland.

Across the OECD countries in the period 1999-2013, the average proportion of seats held by women in national parliaments are around 23% (see table 1). This is almost the same result as in the OECD report of 2006. As shown in figure 5 (OECD 2006) in the appendix, the OECD average percentage was just below 25 in 2005. According to the OECD 2006 report, the parliamentary seats held by women amount to at least one-third of the total seats in nine OECD countries. The Nordic countries and the Netherlands are the only exceptions; here female representation stands out with more than 35%. In most other OECD countries, the seats held by women are below 25%.

The mean of the female share in labor force participation is just above 51%, as indicated in table 1. This result also corresponds with the results of the OECD report of 2006. Figure 6 shows the percentage of men and women in employment in 2004. The report of 2006 mentioned that in each OECD country a higher level of men than women is employed.

As described above, the difference between male and female median wages divided by the male median wages is defined as Gender Wage Gap. So, as shown in table 1, the gender wage gap in median earnings is around 17 across OECD countries.

This result also corresponds with the result of OECD 2006 report, which states that in 2004 the gender wage gap in median earnings was below 20. Figure 7 in the appendix shows this amount. The report also indicates that the gender wage gap increases for the high wage earners.

Estimated  results  

Table 2 (next page) represents the OLS panel regressions with country fixed effects results including the estimated coefficient of the female share in the labor force. In Equation 4, you can see the direct effect of the female share in the labor force on the GDP growth levels. The estimated coefficient of the FLF is significant at 1% and includes a negative sign, which

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means raising the female share of the labor force leads to a decrease of the GDP growth rates according to this collected data. After adding all the independent control variables and eliminating the insignificant ones, the estimated coefficient of the FLF is still negative. Compared to the coefficient of FLF in equation 5, the coefficient of the FLF variable is higher in equation 4. This is probably because the estimated coefficient in equation 4 includes some effects of FLF which influences the GDP growth rate via the other control variables. So, in conclusion the female share in the labor force has a negative effect on the economic growth according to this data.

Table 2. Tests of GDP growth with FLF gender variable (fixed effects panel models) Fixed effects GDP Eq. 4 Eq. 5 Constant 22.65435*** 16.10478*** (3.556.115) (3.787.646) FLF -.3944987*** -.162233** (.0692546) (.0802458) UNEM -.3624184*** (.0608665) DPS -.0250858*** (.0059049) R squared (within) 0.0685 0.1866 Number of obs. 476 457 Number of countries 34 34 Avg. Years 14 13.4

Notes: *, **, and *** denote significance at 10%, 5%, and 1% levels respectively.

Again, the ratio of female to male tertiary enrollment (EDU) is the percentage of men to women enrolled at tertiary level in public and private schools. As demonstrated in the descriptive statistics (table 1), the average percentage is 124.55% in OECD countries for the period 1999-2013. When testing the direct effect of the EDU as gender equality indicator on GDP growth, it emerges that this gender equality indicator has a negative effect on growth. This could be seen in table 3 (next page), which represents the results of testing GDP with the fixed effects panel model. The estimated coefficient of EDU in equation 4 is significant at 10% level. When the proportion of men vs. women increases, the GDP growth rates will decrease according to table 3, equation 4. In equation 5, after including the significant

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independent control variables the EDU estimator becomes insignificant. So according to this data, the direct effect of achieving a higher level of gender equality in tertiary educational levels (thus the percentage men to women starts to decrease) will have a positive effect on the GDP growth rates at a 10% significance level in the OECD countries.

Table 3. Tests of GDP growth with EDU gender variable (fixed effects panel models) Fixed effects GDP Eq. 4 Eq. 5 Constant 7.04173*** 10.75865*** (2.520329) (2.772494) EDU -.0367874* -.0197133 (.0202019) (.0221531) UNEM -.3926267*** (.0691668) DPS -.0277592*** (.0056792) R squared (within) 0.0083 0.1665 Number of obs. 432 419 Number of countries 34 34 Avg. Years 12.7 12.3

Notes: *, **, and *** denote significance at 10%, 5%, and 1% levels respectively.

Table 4 shows the estimated results of regressing the GDP growth variable on the proportion of seats held by women in national parliaments (PAR) variable in this fixed effect panel analysis. As shown in the table in equation 4, the direct effect of the percentage of seats held by women in the parliament on the GDP growth rate is negative at a 1% significance level. So an increase of women in the national parliaments of the OECD countries would, according to this data, lead to a decrease in GDP growth. The result becomes insignificant when the independent control variables are included as seen in equation 5 of table 4. This means that when only looking at this variable, which represents the gender equality indicator, gender equality does not stimulate the GDP growth rate in the OECD countries.

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Table 4. Tests of GDP growth with PAR gender variable (fixed effects panel models) Fixed effects GDP Eq. 4 Eq. 5 Constant 8.388336*** 11.0092*** (.9648409) (.9768689) PAR -.2620254*** -.1490573 (.0417585) (.0436723) UNEM -.3472348*** (.0611617) DPS -.0243555*** (.0054543) R squared (within) 0.0834 0.1994 Number of obs. 468 449 Number of countries 34 34 Avg. Years 13.8 13.2

Notes: *, **, and *** denote significance at 10%, 5%, and 1% levels respectively.

Finally, the last tests results of GDP growth with the Gender Wage Gap (WAG) variable as gender equality indicator are represented below in table 5.. As made visible in table 5, equation 4, the direct effect of the gender wage gap on the GDP growth rates is positive at a 5% significance level. Hence, according to this data, the wage difference between males and females is exactly promoting GDP growth. After adding the significant control variables, this estimated coefficient becomes insignificant.

However, in all tested GDP growth tables, the R squared in both equation 4 and equation 5 are very low. According to Wooldridge (2002) this means the variable variation that is explained by the linear model (in other words, how close are the data fitted in the regression line) is low. Wooldridge (2002) mentioned that, regardless of the low R squared values, it is still possible to draw important conclusions about how changes in the GDP growth rates are associated with the gender equality indicators when they are statistically significant.

In conclusion, when testing the GDP growth with the fixed effects model on the different gender equality indicators, the ratio of female to male tertiary education enrollment is the only positive gender indicator affecting economic growth. According to these data the other gender equality indicators stimulate the economic growth negatively.

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Table 5. Tests of GDP growth with WAG gender variable (fixed effects panel models) Fixed effects GDP Eq. 4 Eq. 5 Constant -2.69104** 7.598086*** (1.321791) (1.925301) WAG .2903675** .0771112 (.0775569) (.0782389) UNEM -.4533952*** (.0917862) DPS -.0295348*** (.0065492) R squared (within) 0.0488 0.1829 Number of obs. 307 294 Number of countries 33 33 Avg. Years 9.3 8.9

Notes: *, **, and *** denote significance at 10%, 5%, and 1% levels respectively.

5. CONCLUSION

In sum, according to the OECD report of 2012 a higher level of gender equality is relevant for the economy, both for developing and developed countries. Because of this relevance, this thesis investigates the effect of gender equality on the economic growth in the OECD countries.

As provided in the literature review, there is empirical and theoretical evidence that gender equality in education and in employment has a significant influence on the economic growth in developing countries. Especially in accordance with Klasen (2000, 2002), gender equality matters for development and achieving a higher growth in developing countries in different ways. Klasen (2000, 2002) suggests the different channels via which gender equality affects growth are the selection-distortion factor, the environment effect, and the demographic transition effect.

To investigate the effect of gender equality on the economic growth in the OECD countries, the OLS panel regression with fixed effects is used. With different gender equality indicators, important conclusions are drawn about how changes in the GDP growth rates are associated with the effect of gender equality. Data collected provide information about the selected variables of all 34 OECD countries in the period 1999-2013.

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To conclude: according to the results of the data panel analysis, stimulation of the female share of the labor force and the proportion of seats held by women in the national parliaments will lead to a decrease of the GDP growth rates. Also this panel data model suggests that the Gender Wage Gap variable has a negative effect on growth, because increasing the gap will lead a higher rate of GDP growth. Finally, according to the results, only the female share of tertiary education enrollment will stimulate the economic growth positively.

So, the answer to the question whether gender equality affects the economic growth in OECD countries is yes, but mainly in negative ways. Testing the GDP growth with the fixed effects model on the different gender equality indicators, the ratio of female to male tertiary education enrollment is the only positive gender indicator affecting the economic growth. The other gender equality indicators stimulate the economic growth negatively, according to this data.

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6. REFERENCE LIST

Barro, R. J. And Lee, J. (1994) Sources of Economic Growth. Carnegie-Rochester Conference Series on Public Policy. (40), 1-46.

Bloom, D. and Williamson, J. (1998). Demographic Transition and Economic Miracles in Emerging Asia. The World Bank Economic Review. Vol. 12, No. 3, 419-55.

Chen, D. H. C. (2004). Gender Equality and Economic Development: the Rol for Information and Communication Technologies. World Bank Policy Research Working Paper 3285, April 2004

Dollar, D. and Gatti, R. (1999). Gender Inequality, Income, and Growth: Are Good Times good for Women? Policy Research Report on Gender and Development Working Paper Series, No. 1., The World Bank, May.

Galor, O. and D.N. Weil, (1996).The gender gap, fertility, and growth, American Economic Review, 86 374-387

Hill, A. And King, E. (1995). Women’s education and economic well-being. Feminist Economics, 1 (2), 21- 46.

Klasen, S. (1999). Does Gender Inequality Reduce Growth and Development? Evidence from Cross-Country Regressions. Policy Research Report on Gender and Development Working Paper Series, No. 7, The World Bank, November.

Klasen, S. (2002). Low Schooling for Girls, Slower Growth for All? Cross-Country Evidence on the Effect of Gender Inequality in Education in Economic Development. The World Bank Economic Review, 16(3), 345-373.

Lagerlof, N. (1999). Gender Inequality, Fertility, and Growth. Mimeographed. Department of Economics, University of Sydney.

Lehmijoki, U. and Palokangas, T. (2006). Political Instability, Gender Discrimination, and Population Growth in Developing Countries. Journal of Population Economics, 19(2), 431-446.

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Mankiw, G. N., Romer, D., & Weil, D.N. (1992) A Contribution to the Empirics of Economical Growth. The Quarterly Journal of Economics, 107(2), 407-437.

Solow, R. M. (1956). A Contribution to the Theory of Economic Growth. The Quarterly Journal of Economics, 70(1), 65-94.

Summers, L. H. (1992). Investing in all the People. The World Bank Working Paper Series, No. 905, The World Bank, Washington, DC.

Stevenson, David L. and Baker, David P. (1987). Family-School Relation and the Child’s School Performance. The Society of Research in Child Development. 58, 1348-1357.

OECD reports

The OECD (2012.) Closing the Gender Gap: Act Now. OECD Publishing. http://dx.doi.org/10.1787/9789264179370-en

The OECD (2006). Women and Men in OECD countries. OECD Publications. Paris, France 00 2006 3B 1 P) – No. 83841 2006.

The Global Gender Gap report 2013. World Economic Forum. The result of collaboration with faculty at Harvard University and the University of California, Berkeley.

Websites www.oecd.org www.worldbank.org

Books

Wooldridge, Jeffrey M. 2002. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: the MIT Press.

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APPENDIX  

Figure 1 In the OECD, Gender gaps in labor force participation vary widely accross countries

(Source: OECD, 2012. Closing the Gender Gap Report)

Figure 2 Korean population by broad age-group, 1950-2050

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Figure 3 Richer countries have higher and more gender-equal educational attainments

(Source: OECD, 2012. Closing the Gender Gap Report)

Figure 4 Percentage of men and women with tertiary education 2004

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Figure 5 Percentage of parliamentary seats held by women in OECD countries in 2005

(Source: OECD, 2006. Women and Men in OECD countries.)

Figure 6 Percentage of men and women of working age in employment in 2004

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Figure 7 Gender Wage Gender 2004

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