What is the trend of the gender wage gap in Germany during the period 1990-2010?

What is the trend of the gender wage gap in

Germany during the period 1990-2010?

Name: Jessica Wagenvoord

Student number: 10244387

Specialization: Economics

Field: Labour Economics

Number of credits thesis: 12

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Outline

2.1THE GENDER WAGE GAP ... 6

2.2HISTORICAL BACKGROUND ... 6

2.2.1 Germany………....……… 6

2.2.2 The transition ... 7

2.2.3 Characteristics of labour markets under communism ... 7

2.2.4 Women in the communistic labour market ... 8

2.2.5 The transition years for East Germany ... 9

3. LITERATURE REVIEW--- 10

3.1REVIEW ... 10

3.1.1 The classical research method ... 11

3.1.2 Other research methods ... 12

3.1.3 The worldwide position of Germany ... 12

3.1.4 The public and private sector ... 13

3.1.5 East and West Germany ... 13

3.2HYPOTHESES ... 14

4. EMPIRICAL PART --- 15

4.1DATA SOURCES ... 15

4.1.1 Structure of earnings survey ... 15

4.1.2 Statistisches Bundesamt... 16

4.1.3 Eurostat ... 17

4.2OUTCOME VARIABLE ... 18

5. RESULTS --- 19

5.1EMPIRICAL PART ... 19

5.1.1 Back to the research question ... 19

5.1.2 East and West Germany ... 19

5.1.3 The public and private sector ... 19

5.1.4 The worldwide position of Germany ... 20

5.2POSSIBLE EXPLANATIONS... 20

5.2.1 Explanatioins in the literature………..………..20

5.2.2 Possible explanations for Germany ... 21

6. DISCUSSION AND CONCLUSION --- 24

6.1CONCLUSION ... 24

6.2DISCUSSION ... 24

7. REFERENCE LIST --- 26

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1. Introduction

1.1 Motivation

The gender pay gap is generally defined as the difference between the wages

earned by women and by men in gross hourly wages (Plantenga and Remery 2006). Wage inequality based on gender is a topic which has been widely discussed in literature. It is now even more relevant for Germany as it is has been discussed in the recent negotiations to form a coalition. Moreover, the gender wage gap has been an important topic on the European political agenda. Since 1999 it has been part of the European Employment Strategy and Policy, and so countries are more focused on it. Member states had to formulate targets in 2003 to achieve a substantial reduction in the gender pay gap by 2010 in each state through a multi-faceted approach addressing the underlying factors of the gender pay gap (Plantenga and Remery, 2006). Also social partners are interested in the wage gap as

UNICE/UEAPME/CEEP and ETUC agreed in 2005 to reduce the gender pay gap within their ‘framework of actions on gender equality’ (Plantenga and Remery 2006).

I will fill the gap in the existing literature by observing and analysing the situation of the gender wage gap in the labour market in Germany across the period 1990-2010. Since the aim of the paper is to provide an overview, to be observing and to pay less attention to explaining the gap the research question is; what is the trend of the gender wage gap in Germany during the period 1990-2010? For the overview of the gender wage gap to be more specific a distinction will be made between West and East Germany, the public and private sector and comparisons will be made across different geographic levels.

1.2 Related literature

The wide written national and international literature (Blau and Kahn 1997, 2000, European Commission 2006 among others) shows a disadvantage gender wage gap for women. Hinz and Gartner (2005) researched the gender wage gap in Germany in general using an employer-employee dataset of the Instituts für Arbeitsmarkt- und Berufsforschung der Bundesagentur für Arbeit. They used the mean wages of men and women, and concluded a stable trend of women’s wage being on average 16 percent lower than men’s wages, between 1993 and 2001 in Germany. Also Melly (2005) evaluated her research for Germany over the years 1984 – 2001 and found

3 no trend or cycle. There are several ways to determine the gender wage gap. The classical methodology used in the literature is the human capital approach of Oaxaca (1973). It typically estimates the Ordinary Least Square estimations of the wage equations of men en women separately. The method is limited by only using the mean wage gap (Del Rio et al. 2011).

Later, researchers aimed to include the distribution of the gender wage gap across different characteristics e.g. income and age. According to the Organization for Economic Co-operation and Development (2012), also known as OECD, the gender wage gap in Germany is second highest across all OECD countries.

Plantenga and Remery (2006) report the German trend to be rather stable over the period 1994-2004. And their results show a percentage of 26% for 1991 and 29% in 2004 for West Germany only. Hinz and Gartner (2005) researched the gap in

Germany over 1993-2001, they found the gap to be stable over the years with wages of women to be 75% of those of men. After controlling for human capital, the gender wage gap turned out to be 16%. Hunt (1997) found the wages of women relative to men in East Germany rose from 74% in 1990 to 84% in 1994 and so concludes that the unification of East Germany with West Germany has been extremely beneficial to women in the East. In his research Melly (2005) concludes that the gender wage gap in the public sector is smaller than in the private sector.

1.3 Hypotheses

As discussed in the previous paragraph, Hinz and Gartner (2005) and Melly (2005) found a gender wage gap of 15% for the first decade. Taking this into account, it can be expected that a stable trend around a gap of 15% will be found for 1990-2010.

With respect to East and West Germany, taking Hunt (1997) into account, it can be expected a smaller gender wage gap in East Germany than West Germany will be found.

After taking into account Melly (2005), it can also be expected to find a wider gender wage gap in the private sector in Germany than in the public sector.

1.4 Research method

To apply the research methods used in the literature it is necessary to have access to a database with data on all characteristics which may influence the gender wage

4 gap, e.g. education, work experience, marital status, age and sector. As there is no such public database available with respect to Germany this paper will focus on the unadjusted gender wage gap, defined as the relative average wage of women to men.

Next to the overall gender wage gap in Germany, special attention will be paid to three other sub subjects, which the gap in West and East Germany, the gap in the public and private sector and the position of the gap of Germany within the world.

The paper will start with a chapter which contains background information about Germany and historical background information. The historical background will elaborate on the political situation in Germany around 1990 by reviewing the

economic, social, and political dimensions of the transformation process in East Germany. This will benefit the understanding of the labour market during that period. Further, this paper contains a literature review and an empirical research, both

complement each other and so a clear overview of the situation can be given. With respect to the literature review, key papers and other researches will described. For the empirical research databases from the Statistisches Bundesamt, Eurostat and the OECD will be used to gather the data.

After the literature review and the empirical part a chapter with the results will follow. This chapter will also contain some possible explanations of the gender wage gap as it is found for Germany.

The results of the empirical part show a decreasing gender wage gap in Germany between 1990 and 2010. Next, the gap in East Germany appeared to be halve of the gap in West Germany. Moreover, it shows the gender wage gap in the public sector to be smaller than the gap in the private sector. Within Europe,

Germany has one of the greatest gender wage gaps (Eurostat 2013) but on a global level the gap in Germany is more moderate (OECD 2014).

The paper suggest the increasing female educational level and the decreasing difference in duration of working life between men and women in Germany contribute to the decreasing gender wage gap.

To summarize, this paper will start with a chapter with background information about the gender wage gap and historical background information about Germany. Then, a chapter with the literature review and a chapter with the empirical research will follow. The chapter with the results will mainly contain results from the empirical

5 research, but will also describe possible explanations of the wage gap. The paper will be concluded with the conclusion and the discussion. The figures and tables are attached after the reference list.

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2. Background information

This chapter will provide background information for the sub questions in this paper. After introducing the gender wage gap, Germany and its economy will be shortly discussed. Thereafter the situation around the transition of East Germany will be described, which will help to compare the situation in East and West Germany.

2.1 The gender wage gap

Currently, inequalities in earnings is an important factor for social inequality. The gender wage gap refers to the difference between the wages earned by men and by women. The unadjusted gap is usually calculated by (one minus) the average wage of women divided by the average wage of men or the difference between men’s average wages and women’s average wages as a percentage of men’s average wage (Plantenga and Remery 2006). The literature and data discussed in this paper show the existence of the gender wage gap, mainly as a disadvantage for women. Remarkable is the fact that in the European Union gender differences in wage in case of equal work is forbidden by law (Hinz and Gartner 2005).

2.2 Historical background

2.2.1 Germany

The central country in this paper is Germany, which has the fourth-largest national economy and industry in the world. Only the United States have more trade with foreign countries than Germany. Most of the trade is done with other European countries. The economy is characterized by many small and medium-sized firms (European Commission 2013). The GDP in 1990 was 1,79 billion dollar and grew to 2,4 billion dollar in 2010, with constant prices (IMF 2013). The employment and unemployment rates are shown in figure 1 and 2 (Eurostat 2013a), where we can see an increasing employment rate for women and a fluctuating unemployment rate over the period 1990-2010. Eurostat defines an employed person as someone with age equal or higher as 15 who has a job or business or worked a minimum of one hour at the moment when the research was done. An unemployed person is by Eurostat defined as a person with age of 15 till 75 and who either is without work, but

7 available for work and is actively seeking or is without work at the moment of

research but who had found a job starting within 3 months. According to the European Commission (2013) the unemployment rate in Germany is one of the lowest in Europe. Underemployment, excluding short-time working, has recently been shown to be 8,9% (European Commission, 2013). Figure 3 shows the active population over the researched period 1990-2010. According to Eurostat (2013b) the active population consist of all unemployed and employed persons, as defined

before.

2.2.2 The transition

From 1949 till 1990 East Germany was controlled by the Soviet Union, and so automatically had an economy based on central planning (Brainerd, 2000). In the night of 30 July 1990 the formal monetary unification between East and West

Germany took place. The entire economy had to change from a planned economy to a market based economy. In the East, both the goods and labour market were

centralized. The allocation of input factors was planned, as well as prices and the distribution of output. Moreover, all firms were owned by the government (Krueger and Pischke 1992). Wages were converted to West Germans currency (Deutsch Mark) and tax, legal and social insurance systems were harmonized. Moreover, there was trade liberalization, price liberalization and firms owned by the state had to privatize (Brainerd 2000). The first years after the reform, transitional economies typically experience a decline in GDP, a decline in real wages, high inflation rates and increasing unemployment. The transition of East Germany has occurred

relatively quick compared to other former East bloc countries who were experiencing the same development in their economies. West Germany has been of great

financial and technical assistance to their eastern neighbours (Krueger and Pischke 1992).

2.2.3 Characteristics of labour markets under communism

Communism is in favour of uniformity in outcomes, independent of the efforts made and the ability of the individual (Krueger and Pischke 1992). Typically for

communism was the compressing nature of the wages at the labour market

8 scale consisted of 6 levels of compensation, all a multiple of the lowest level. The actual height of the wages per scale differed per industry. Despite this centralization, the system did allow for some harmonization with the Western system by giving firms some freedom in setting wages for their workers. If an industry experienced

disadvantages by the plans made by the government, firms were allowed to diverge from the plans (Krueger and Pischke 1992). Other characteristics of the labour market were relatively high minimal wages, open excess demand for labour, low wage levels, low growth of wages and limited labour mobility (Brainerd, 2000).

2.2.4 Women in the communistic labour market

During communism women were doing relatively well in the labour market (Brainerd, 2000). Women participation rate in the labour force, around 80%, was amongst the highest in the world. The industrialization of transitional countries required a high female labour force participation. The government provided circumstances to attract women to contribute to the work force.

Firstly the government guaranteed the right of equal pay for work. Secondly there were generous maternity benefits, like mothers who were entitled to take up three years of maternity leave per child. Thirdly, excellent and low-cost day care facilities for children were provided. And furthermore, the average wages were low, with the consequence women had to work to supplement family income to be able to feed a family (Brainerd, 2000).

Despite the high participation rate of women, they were still mainly

responsible for the children and family. This made mothers less interested in any form of promotion. Moreover, promotion would not mean a significant increase in wage, due to the flat wage scale system.

Traditionally women work in service sectors as health and education and men in heavy industry sectors. Many of the service sectors shrunk less or even grew compared to the industrial sectors which shrunk with their decreasing output, during the period of transition. The high presence of women in the service sectors appeared to be an advantage, and job opportunities grew during and after the transition

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2.2.5 The transition years for East Germany

Just before monetary unification the GDP of East Germany was only 10% of West Germany’s GDP. This can mostly be explained by the size of the population, East Germany is in terms of population only one fourth of West Germany. One month after the reunion East Germanys economy was in a deep depression (Krueger and Pischke 1992). Output fell to half of the level in 1989 (Akerlof et al., 1991)

Employment fell from 9,2 million in 1989 to 7,1 million in 1991. Unemployment increased form 1% to 10% of the total labour force (Krueger and Pischke 1992). Under communism unemployment was unrecognized and could even result in imprisonment (Brainerd 2000). Economic recovery between 1995 and 2000 improved the overall situation on the labour market, but in some countries employment was still decreasing. And especially female employment was still decreasing.

According to Akerlof et al. (1991) this depression can partly be explained by the extreme growth in wages in the years 1989 – 1991. In other transition economies in Eastern Europe the increase in nominal wages was tempered by enormous

inflation rates, but this was not the case in East Germany. This is an example of the cushioning role the West German economy played for the East. Despite the growth in nominal wages, the wage rates were still only 40% of the West German wage rates (Krueger and Pischke 1992). The same paper of Krueger and Pischke shows East Germans gender wage gap of 23,4% in 1988 is decreasing to a value of 19,8% in 1991.

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3. Literature review

3.1 Review

Wage discrimination has been of great interest in the literature of labour markets. Gender wage discrimination can be indicated by the adjusted gender wage gap. The unadjusted gender wage gap, also called the observed raw gap, needs to be

corrected for the differences in distinctive gender patterns to obtain the adjusted gender wage gap (Kunze 2000). A substantial part of the written literature about the gender wage gap concerns the methodology to determine the adjusted gender gap.

This paper concerns the unadjusted gender wage gap, due to a lack of an individual-level dataset containing information about all characteristics influencing the wage and productivity for every participant of the survey. The unadjusted gender wage gap is also called a standard measure of the gender gap (Selezneva & Van Kerm, 2013).

Corley et al. (2005) define it to be one of the most important structural

indicators in the analysis of the discrepancy between the position of men and women in the labour market. It is generally defined as (one minus) the average gross hourly wage rates of women divided by the average gross hourly wage rates of men. This method is limited as it focuses only on the mean wages, and does not indicate any explanations of the observed gap, in contrast to the adjusted gender wage gap.

Selezneva and Van Kerm (2013) conclude in one of the most recent papers on the gender wage gap in Germany that the situation of women in appears to be worse than estimated by the unadjusted gender wage gap on the mean wages. This suggest an underestimation of the adjusted gender wage gap compared to the method using the mean wages.

Kunze (2000) addresses three points which summarizes the fundamental methodological issues in the literature.

To start with, to be able to compare wages of men and women, precise measures of individual human capital characteristics are needed. Moreover, in order to compare wages, the derivation of consistent estimates of the coefficients of the human capital characteristics in the regression model are required. And to conclude, a general method of decomposition of the unadjusted gender wage gap is needed.

11 The point made by Kunze (2000) concerning the extensive data availability is also the main issue for this research as can be recognized in the next chapter. The second point, which addresses the consistency of the estimates is widely discussed in the literature. The third point, the general decomposition method, will easily follow from the first two.

3.1.1 The classical research method

The classical methodology used to determine the discrimination on gender in wages is the Oaxaca-Blinder decomposition. The first prominent study on wage

discrimination was done by Oaxaca in 1973. Even though this research focused on wage discrimination between black and white men and women in the US, the proposed methodology has been widely used and discussed in the literature. The method is based on Ordinary Least Square estimations of wage equations. It quantifies the wage discrimination by comparing the mean female worker with the mean male worker.

Oaxaca and Blinder (1973) divided the observed unadjusted gender wage gap in two components (Del Rio et al. 2011). The first one, A, which is explained by the differences in human capital endowments, reflects productivity differences (Kunze 2000). The second component, B, shows the difference between the labour market reward for the human capital endowments, and estimates discrimination. The intermezzo below shows the derivation from the Mincerian log wage equations, which is a way to model wage equations based on human capital, leading to the two components A and B.

Intermezzo:

Where m refers to males, f to females ,yi stands for the ith worker hourly wage, ωi is

the natural logarithm of yi, Zi is the vector of characteristics, β are the characteristics’

12 Component B would state the wage penalty the mean women get, given that they have a different remuneration of attributes compared to men.

3.1.2 Other research methods

Later, researchers aimed to include the distribution of the gender wage gap across different characteristics e.g. income and age. There are two different trends in the literature with respect to the distributional approach. Reilly (1999), Garcia et al. (2001) and Gardeazabal and Ugidos (2005) among others proposed to use quantile

regression to estimate the wage equations in order to increase the number of points in the distribution which can be evaluated. However, others proposed a variety of techniques to estimate earning distribution functions to be able to quantify the effects of wage differentials across the whole distribution. Both trends contributed to the literature as more information from the observed wage distribution is obtained than by using the Oaxaca blinder classical methodology.

However, these approaches are still not optimal as the individual dimension of discrimination is not taken into account, to solve this problem Del Rio et al. (2011) made a proposal with a normative framework based on poverty and deprivation literature. They conclude as well that the distributional approaches proposed as a reaction on the classical methodology which uses the mean, show greater gender discrimination than the classical approach. Kunze (2000) acknowledges other limitations of the existing approaches. According to her, the estimated parameters lack econometric and economic reasoning and robustness.

3.1.3 The worldwide position of Germany

The OECD recognizes with their report in 2012 the German gender wage gap of 22% to be the second across the OECD countries. Plantenga and Remery (2006) report the German trend to be rather stable over the period 1994-2004. And their results show a percentage of 26% for 1991 and 29% in 2004 for West Germany only. Hinz and Gartner (2005) researched the gap in Germany over 1993-2001, they found the gap to be stable over the years with wages of women to be 75% of those of men. After controlling for human capital, the gender wage gap turned out to be 16%.

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3.1.4 The public and private sector

The government is by far the biggest employer in Germany, employing 4,8 million people in 2001, which was then 13,1% of the total labour force. Melly (2005) researched the pay gap between the public and private sector in Germany in the period 1984-2001. The sectors differ the most in their objectives, being subject to political constraints or profit constraints. Besides, both fulfil a different role as an employer. The government is supposed to be a model employer, who does not pay low wages to low skilled employees. But too high public wages will attract employees out of the private sector into the public sector which will increase taxes and budget deficits. Moreover, Melly found higher average hourly earnings, higher educated employees, more labour market experience and a greater concentration of professionals and technicians in the public sector than in the private sector. The differences in education and work experience might explain why the wages in the public sector are higher than in the private sector, as found by Smith (1976) and Melly (2005). In his research Melly concludes that the gender wage gap in the public sector is smaller than in the private sector. This is contradicting with what can be expected from economic theory, as Becker (1957) concluded profit maximization cannot be accompanied by discrimination. Even though the gender wage gap is greater in the public than in the private sector, Melly found parallel movements of the two sectors during the years 1984-2001. This can mainly be explained by the

indirectly linked wages in both sectors, as the negotiated results of large private sector unions are often taken as a benchmark for the public sector.

3.1.5 East and West Germany

According to Selezneva and Van Kerm (2013) in all cases where the differences between the gender wage gap in East and West Germany has been researched, the gap turns out to be greater in West Germany than in East Germany.

14 3.2 Hypotheses

Following from the literature discussed in the previous paragraph it can be expected to find, in the empirical chapter, a more or less stable gender wage gap around 20% over the years 1990-2010. Next, it can be expected that the gender wage gap in the private sector is higher but parallel to the gap in the public sector for the years 1990-2010. With respect to East and West Germany, after reviewing the literature and taking the historical background into account it can be expected to find a greater gender wage gap in the West Germany than in the East Germany.

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4. Empirical part

The second part of this research consist of an empirical research where online available data from public databases are used to gather data on earnings and the unadjusted gender wage gap. This chapter focusses on the description of the data and the databases, which are used in this paper. Also the outcome variable will be discussed in this chapter. Ultimately the data will be manipulated and turned into several clear diagrams, which are shown in the chapter of the results following up this chapter. These diagrams give an graphical overview of the situation of the gender wage gap in Germany.

4.1 Data sources

4.1.1 Structure of earnings survey

This is a returning survey on European level which provides harmonized structural data on earnings and labour cost, and which is the most important and reliable data source available for this research. The objective of this survey is to provide accurate and harmonised data on earnings in all states in the European Union for policy-making and research purposes (Eurostat 2013b). The data are collected every four years under the council regulation of the European Committee, since 2006 for Germany. Important to note here is these data do not contain data for the public sector, this may influence the results substantially as women are, relative to men, overrepresented in the public sector. Employees is here defined as everyone who has a direct employment contract with an enterprise or local unit and receives remuneration, independently of the type of work and the number of hours worked. The definition of mean hourly gross earnings is the gross monthly earnings divided by the number of hours paid of that month. Number of hours paid includes paid overtime hours and paid hours when the employee did not work. Mean gross monthly earnings in this case is defined as all remuneration paid in cash before the deduction of tax and social contributions.

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4.1.2 Statistisches Bundesamt

There are a couple of databases with data available for calculating the unadjusted gender wage gap. The first to mention here is the Statistisches Bundesamt, which can be translated to Federal Statistical Office. It is an institute that gathers data on all kinds of topics in Germany. Their mission is to provide objective, independent and high quality statistical information which is available for everybody. The Statistisches Bundesamt is also actively involved in gathering data on international levels (source: destatis.de). Their responsibilities and duties are set in federal law on statistics of Germany. According to this information this database is considered to be relevant and trustable for this research.

The information provided for this theme consist amongst others firstly of data of long-time series of average gross monthly earnings on ‘Former territory of the Federal Republic’, ‘New Länder’ and Germany in total. According to their website, the relative standard error of the sample of the average gross monthly earnings is 0% - 2% for a full-time employee and is decreasing in the size of the economic branch, which is measured by the number of employees. By using the formula in the last chapter, the gender wage gap can be calculated for East and West Germany for the relevant period. The data of ‘Former territory of the Federal Republic’ are used for West Germany and data for ‘New Länder’ for East Germany. For the ‘New

Länder’ there are no data available for 1990 and so for both Germany in total as East Germany the trend line starts from 1991. The results are shown in figure 4 and will be discussed in the chapter ‘results’.

Secondly the Statistisches Bundesamt provides data about the unadjusted gender wage gap in the public service and private sector for the years 2006-2012. The source of the data is the Structure of Earnings Survey of 2006 and 2010. For the survey, the public sector consists of the economic sectors including public

administration, defence, compulsory social security and education. Even though the data about the public and private sector do not cover the entire period researched here, it gives a useful insight in the distribution of the gender wage gap across these two. Figures 5,6,7 show the results of the analysis of the public en private sector.

Thirdly the Statistisches Bundesamt provides data about the 16 different states (Ländern) in Germany. This information is shown in figure 8 where the five East German states are marked red in the legend.

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4.1.3 Eurostat

As well as the Statistisches Bundesamt, also the statistical office of the European Union provides relevant data for this research. Their main task is to provide the European Union with statistics at European level to facilitate better comparisons within the EU (Eurostat 2013b). Eurostat uses the gross hourly earnings where in this research the gross monthly earnings are used. Since Eurostat uses a common definition for gender wage gap, there is comparison between countries possible. The dataset consist of 25 countries over the period 2002-2011, based on the Structure of Earnings Survey of 2006 and 2010.

To ensure to give a clear impression of the gender wage gap in Europe, the average of the European Union, Germany, the countries with the highest and lowest gender wage gap in 2006, Sweden and Italy respectively, are compared. In addition six members of the European Union are added to this comparison, three countries former controlled by the Soviet Union and three countries which have not been controlled by the Soviet Union. The trends can be found in figure 10. Eurostat also provides data on how the gender wage gap is spread over the population with respect to age, this is shown in figure 9 (Eurostat 2013a,b).

4.1.4 Organization for Economic Co-operation and Development

Lastly the OECD (2014) is used as a source for data. Important to mention here is the difference in definition of the gender wage gap between the OECD and this paper. The OECD defines the gender wage gap as the difference between median earnings of men and women relative to median earnings of men (OECD 2014). This explains the differences in results with respect to the gender wage gap in Germany. With the data available figure 11 is made which shows the trends in Germany and Non-European OECD countries.

18 4.2 Outcome variable

The gender wage gap as researched here is defined as unadjusted because its goal is to give a general impression of gender inequalities in terms of wages. It gives an overall picture of the gender inequalities in terms of wage, and may indicate the position of women in the labour market. Most of the data used in this paper was originally in the form of gross mean hourly wage. To turn this into the uniformly used definition of the gender wage gap in this paper formula 1 as shown here is used.

Formula 1:

is the average gross monthly earnings for women for the years t. is the average gross monthly earnings for men for the year’s t.

A gap of 0 presents wage equality between men and women. When the gap increases between 0 and 1, the less are female average wages relative to male average wages. When the gap becomes negative, female average wages are higher than male average wages.

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5. Results

This chapter will first briefly discuss the observations from the figures made by the author of the empirical part for every sub subject. Afterwards a section will follow which will consist of explanations of the gap as discussed in the literature and possible explanations for the gap in Germany.

5.1 Empirical part

5.1.1 Back to the research question

The main result of the empirical part is figure 4, which shows the trend of the gender wage gap in Germany for the period 1990-2010. This is directly linked to the

research question of the paper, which addresses the trend in the overall gender wage gap in Germany from 1990 to 2010. It shows a decreasing trend starting at a percentage of 28% in 1991 and decreasing to 18% in 2010.

5.1.2 East and West Germany

A striking observation is a halving gender wage gap in East Germany between 1990 and 2000, from 12 to 4 percent points. This is in contrast with a relatively extremely high, but also decreasing, gender wage gap in West Germany. Figure 4 shows three similar trends for East, West and whole Germany, with rising and declining

movements simultaneously. This is simply explained by the fact the West and East German trends are combined in the German trend. The German trend is

substantially more influenced by the trend of West Germany because of the relative size of West compared to East.

5.1.3 The public and private sector

Figures 5,6 and 7 show the situation in the public and private sector during the period 2006-2012 for East and West Germany and Germany in total.

Remarkable is the gender wage gap in the private sector in West Germany, which is twice the gap the private sector in East Germany. It shows also that the gender wage gap in Germany is mainly caused by the private sector.

With respect to the public sector, figure 6 shows the striking result of a negative gender wage gap in East Germany from 2007 on, which means that on

20 average women earn more than men. Since the private sector is larger in Germany than the public sector, the overall trend is similar to the trend of the private sector with upward and downward movements simultaneously.

5.1.4 The worldwide position of Germany

Figure 8 shows the distribution of the gender wage gap over the different states, which are called Ländern in Germany. The most important result here is that all individual states in East Germany have a lower gender wage gap than all individual West Germany states. Berlin, the state belonging to both East and West, is exactly between the other Western and Eastern states.

Figure 9 illustrates the gathered data by the structural earnings survey in 2006 and 2010 on the distribution of the gender wage gap in age of the employee. It

shows the gender wage gap is increasing in age. Ultimately, Figure 10 and 11 show the position of Germany within the world. Figure 10 shows that in Europe, Germany has the greatest gender wage gap with 25%, compared to a European average of 15%. Figure 11 shows the position of Germany on a global level. Surprisingly, this figure shows a moderate situation. So within Europe

Germany has a wide gender wage gap, but compared to countries outside of Europe it has an average gap.

5.2 Possible explanations

5.2.1 Explanations in literature

In general, studies have shown that the gender wage gap is mainly caused by labour market characteristics of males and females.

The European Commission came up in 2006 with three specific

characteristics in particular. First, the difference in labour force participation rates of women and men, also called the composition effect. Corley et al. (2005) complement this argument as they found a very clear negative relationship between female

labour force participation rates and the gender wage gap.

Second, the differences in pay among men and women of similar characteristics, which is also called the remuneration effect and may signal discrimination.

21 And third, the selection effect, the difference in the labour market participation behaviour between men and women.

Corley et al. (2005) also came up with a positive relationship between the gender wage gap and the female unemployment rate. According to them, this can exist due to the weaker bargaining position of women relative to men. When the female unemployment rate is even weaker, the gap will be even greater because the bargaining position will shrink.

According to Selezneva and Van Kerm (2013) the higher wage inequality among women conditional on human capital characteristics is caused by greater prevalence of low paid part-time employment, strong variations in years of actual experience, and possibly greater dispersion of occupational choices.

The OECD (2012) dedicates half of the gender wage gap in Germany to the differences in working hours between men en women. Besides, the German

tax/benefit system is the only one within the OECD which favours a single breadwinner over dual-earning families with children.

Plantenga & Remery (2006) as well as Hinz and Gartner (2005) conclude that the gender wage gap in Germany is mainly caused by both horizontal and vertical segregation and differences in personal characteristics play a minor role. Plantenga and Remery came in their report for the European Commission in 2006 with a surprising conclusion.

Firstly, evidence suggest the gender wage gap is mainly related to the level of occupational segregation and the wage structure. Women are penalized for the occupations and industries they are working in.

Secondly, a compressed wage structure, as in the Soviet Union, is likely to diminish the gender wage gap (Plantenga & Remery 2006). On one hand there are developments to an individual wage setting system, which hurt the position of women. On the other hand, there is a trend to women with higher education and fewer children and shorter career breaks. Both outweigh each other and the gender wage gap stays more or less the same (Blau and Kahn 1997).

5.2.2 Possible explanations for Germany

To research if the negative relationship between the gender wage gap and the female labour force participation rate holds for Germany in the relevant period, new

22 data (Eurostat 2013a) is related with the gender wage gap.

The employment growth for women is used as a proxy for the labour force participation rates of women. Figure 13 shows this negative relationship only holds for half of the years during 1992-2010. To conclude, this statement of Corley et al. (2005) and the European Commission (2003) cannot be automatically applied for Germany.

To see if the positive relationship holds for Germany, data of the female unemployment rate from the Statistisches Bundesamt are related to the already present data of the gender wage gap. Shown is that this positive relationship holds for 10 out of 15 years during the period 1995-2010. This is shown in figure 12. To conclude, this relation holds in general, but not always.

It has also been researched if it holds that a higher educational level of

women decreases the gender wage gap simultaneously during the period 1990-2010 in Germany. Figure 14 shows an increasing educational level of women and a

decreasing gender wage gap. More specifically, for 12 out of 17 years the negative relation holds so this suggest, educational level of women is a contributing factor of the closing gender wage gap.

In addition, the differences in duration of working life between men and women are related to the gender wage gap. This indicator measures the number of year’s 15 aged men and women expect to be active in the labour market throughout his/her life (Eurostat 2014). This can be used as a proxy for the differences in

working hours between men and women as it indicates the differences in labour market behaviour. The data show for both men and women an increasing duration of working life, but for women the growth is stronger and so the differences between men and women is decreasing. This trend, simultaneously with the decreasing gender wage gap between 2000 and 2010 suggest that decreasing differences in duration of working life decreases the gender wage gap.

Ultimately the fertility rate is related with the gender wage gap. There is no clear decreasing number of children per women observed, even though the gender wage gap is decreasing in Germany. So there is no reason to assume a decreasing number of children per woman contributes to a decreasing gender wage gap.

To conclude, the literature came up with different explanations for the gender wage gap. After applying some of these indicators on the relevant timeframe in Germany we can conclude that indeed some of those explain or contribute to the

23 decreasing gender wage gap in Germany during the period 1990-2010.

There is no direct positive relation found between the fertility rate and the gender wage gap.

The contribution of female labour force participation and the female

unemployment rate are ambiguous. There is reason to assume this contributes to the gender wage gap, but as the results were not convincing, it should be

researched further if and how much these indicators contribute to the gender wage gap.

The results do suggest the female educational level contributes to the gender wage gap, as well as the differences in length of working life between men and women.

24

6. Discussion and Conclusion

6.1 Conclusion

This paper observed the situation of the gender wage gap in Germany during 1990-2010. By both using widely written literature and an empirical research, a clear overview of the developments on the labour market have been given. The

hypotheses stated after the literature review were all confirmed in the empirical part, except for the expectation of the overall trend to be stable.

The overall gender wage gap in Germany decreased form 28% in 1990 to 18% in 2010. This means women earn on average between 28% and 18% less than men between 1990 and 2010.

Striking is, the gap in West Germany is more than double the gap in East Germany. And both gaps decreased between 1990 and 2010. This suggest more wage inequality in West Germany than in East Germany.

The gender wage gap in the private sector is greater than in the public sector in both East and West Germany. Another striking result from this research is that the gap in the public sector in East Germany is negative, which means women earn on average more than men.

The gender wage gap in Germany is the highest within Europe, but when observed on a global level, Germany’s gender wage gap is more average.

According to the literature the gender wage gap can be explained by the female unemployment rate, female labour participation, discrimination, the wage structure and horizontal and vertical occupational segregation.

From this research can be concluded that the increasing female educational level and the decreasing differences in duration of working life cause the decreasing gender wage gap in Germany between 1990 and 2010.

6.2 Discussion

This paper is limited because of a lack of public available individual-level data for the labour market in Germany. Consequently, only the mean wages have been taken into account, this illustrates the situation limited. Further research based on this kind of datasets can increase the shared knowledge about the gender wage gap in Germany fairly. With this new data more attention can be paid to the explanations

25 and the factors contributing to the gender wage gap by doing regressions. Most of the data in the empirical part of this paper is based on only one source, the Structure of Earnings survey. This helps to make numbers across countries and time periods harmonized and comparable, but may hurt the reliability of the whole paper. Further research should also address if and to what extent female labour force participation and the female unemployment rate contribute to the existence of the gender wage gap.

26

7. Reference list

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Becker, G. (1957). The economics of discrimination. Chicago: University of Chicago press.

Blau, F. and L. Kahn (1997). Swimming Upstream: Trends in the gender wage differential in the 1980s. Journal of Labor Economics, 1, 1-42.

Blau, F. and L. Kahn (2000).Gender differences in pay. Journal of economic perspectives, 14, (4), 75-99.

Brainerd, E. (2000). Women in transition: changes in gender wage differentials in Eastern Europe and the former Soviet Union. Industrial and Labor Relations Review, 54, (1), 138-162.

Corley, M., Y. Perardel and K. Popova (2005). Wage inequality by gender and occupation: A cross-country analysis. International Labour Organization. Del Rio, C., C. Gradín and O. Cantó (2011). The measurement of gender wage

discrimination: the distributional approach revisited. Journal of Economic Inequalities, 9, 57-86.

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(http://epp.eurostat.ec.europa.eu/portal/page/portal/labour_market/earnings/main_ta bles), 1 December.

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(http://epp.eurostat.ec.europa.eu/cache/ITY_SDDS/EN/earn_gr_gpg_esms.htm), 4 December.

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(http://epp.eurostat.ec.europa.eu/cache/ITY_SDDS/en/tsdde420_esmsip.htm), 15 January.

Gardeazabal, J. and A. Ugidos (2005). Gender wage discrimination at quantiles. Journal of population economics, 18, 165-179.

Hinz, T. and H. Gartner (2005). Lohnunterschiede zwischen Frauen und Männern in Branchen, Berufen und Betrieben. Discussion paper, Institute for Employment Research.

Hunt, J. (2002). The transition in East Germany: When is a ten point fall in gender wage gap bad news? Journal of Labor Economics, 20, 148-169.

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27 Kunze, A. (2005). The evolution of the gender wage gap. Labour economics, 12, (1), 73-97.

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28

8. Tables and figures

Formula:

is the average gross monthly earnings for women for the year’s t. is the average gross monthly earnings for men for the year’s t.

29 Figure 2: The employment rate in the period 1992-2010 (Eurostat 2013b).

Figure 3: The active population in Germany in the period 1992-2010.

0 5.000 10.000 15.000 20.000 25.000 30.000 35.000 40.000 45.000 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 N u m b er o f p ers o n s in t h o u sa n d s Years

Active population

30

Figure 4: Trends of Gender wage gap in East and West Germany and Germany in total for the years 1990-2010.

Figure 5: The gender wage gap in public and private sector in Germany for the years 2006-2012 0 5 10 15 20 25 30 35 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 G en d er w age ga p Years

Gender wage gap in Germany

West-Germany East-Germany Germany 0 5 10 15 20 25 30 2006 2007 2008 2009 2010 2011 2012 G en d e r w age ga p in %

Public and private sector in Germany

Public service Private sector Total

31

Figure 6: The gender wage gap in the public sector in Germany for the years 2006-2012.

Figure 7: The gender wage gap in the private sector in Germany for the years 2006-2012. -4 -2 0 2 4 6 8 10 12 2006 2007 2008 2009 2010 2011 2012 G en d er w age ga p in %

Public sector in Germany

West-Germany East-Germany Germany 0 5 10 15 20 25 30 2006 2007 2008 2009 2010 2011 2012 G e n d er w age ga p in %

Private sector in Germany

West-Germany East-Germany Germany

32

Figure 8: The trend of the gender wage gap in the 16 different states of Germany for the years 2006- 2011.

Figure 9: The gender wage gap with respect to age for the years 2006 and 2010. 0 5 10 15 20 25 30 2005 2006 2007 2008 2009 2010 2011 2012 2013 G e n d er w age ga p in % Years

Gender wage gap in all Ländern

Schleswig-Holstein Hamburg Niedersachsen Bremen Nordrhein-Westfalen Hessen Rheinland-Pfalz Baden-Württemberg Bayern Saarland Berlin Brandenburg Mecklenburg-Vorpommern Sachsen Sachsen-Anhalt 0 5 10 15 20 25 30 35 <30 30-39 40-49 50-59 60>

Gender wage gap in %

A ge in Y ea rs

Gender wage gap to age

33

Figure 10: An impression of the trend of the gender wage gap in Europe for the years 2006-2011.

Figure 11: The gender wage gap in Germany compared with Non-European OECD countries for the period 1990-2010.

0 5 10 15 20 25 30 2006 2007 2008 2009 2010 2011 G en d er w age ga p in % Years

Gender wage gap in Europe

EU Germany France Italia Netherlands Poland Romania Sweden Hungary United Kingdom 0 5 10 15 20 25 30 35 40 45 50 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 G e n d e r w age ga p in % Years

Gender wage gap comparison with

Non-European OECD countries

Australia Germany Japan Korea New Zealand United States

34

Figure 12: Female unemployment rate in relation with the gender wage gap (Eurostat 2014). Female unemployment rate Gender wage gap 1995 10,6 24,8 1996 11,2 23,9 1997 12,2 23,1 1998 11,8 22,7 1999 11,2 22,4 2000 10,0 21,3 2001 9,5 20,9 2002 9,5 20,9 2003 10,0 20,6 2004 10,1 20,2 2005 11,8 19,9 2006 11,1 19,6 2007 9,6 19,3 2008 8,2 19,2 2009 7,9 17,8 2010 7,5 18,3 0 5 10 15 20 25 30 P erc en ta ge Year

Female unemployment rate and the gender

wage gap

Female

unemployment rate

35 Figure 13: Female employment growth related to the gender wage gap (Eurostat 2014). Female employment growth Gender wage gap 1992 -1,8 26,8 1993 -1,2 25,3 1994 0,5 25,1 1995 1,1 24,8 1996 0,9 23,9 1997 0,3 23,1 1998 1,7 22,7 1999 2,5 22,4 2000 2,4 21,3 2001 0,9 20,9 2002 0,5 20,9 2003 -0,3 20,6 2004 0,5 20,2 2005 0,1 19,9 2006 1,0 19,6 2007 1,9 19,3 2008 1,3 19,2 2009 1,1 17,8 2010 0,9 18,3 -5 0 5 10 15 20 25 30 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 P erc en ta ge Year

Female employment growth and the

gender wage gap

Female employment growth

Gender wage gap

36

Figure 14: Level of female education related to the gender wage gap (Eurostat 2014)

Females with upper secondary or tertiary education Gender wage gap 1992 70,4 26,8 1993 69,9 25,3 1994 73,6 25,1 1995 71,8 24,8 1996 67,7 23,9 1997 69,3 23,1 1998 22,7 1999 73,1 22,4 2000 74,6 21,3 2001 71,8 20,9 2002 72,5 20,9 2003 72,9 20,6 2004 73,6 20,2 2005 72,7 19,9 2006 73,1 19,6 2007 74,5 19,3 2008 75,9 19,2 2009 76,3 17,8 2010 77,0 18,3 0 10 20 30 40 50 60 70 80 90 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 P erc en ta ge Year

Female education and the gender

wage gap

37 Figure 15: Duration of working life of men and women in Germany (Eurostat 2014)

Year Men Women Difference

2000 37,70 30,80 6,90 2001 37,70 31,20 6,50 2002 37,70 31,50 6,20 2003 37,90 31,80 6,10 2004 37,90 31,80 6,10 2005 38,60 32,40 6,20 2006 38,90 33,10 5,80 2007 39,20 33,40 5,80 2008 39,30 33,60 5,70 2009 39,30 33,80 5,50 2010 39,40 34,10 5,30 2011 39,80 34,80 5,00 2012 39,90 34,90 5,00

Figure 16: Average number of children per woman (Statistisches Bundesamt 2013)

1,1 1,15 1,2 1,25 1,3 1,35 1,4 1,45 1,5 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 P e rc e n ta ge Year

Number of children per woman