Content

• Foreword
• Marzena Grzesiak, Anita Richert-Kaźmierska

• Part I Women’ entrepreneurship

• Activity and discrimination against women in the labour market in the countries of the Baltic Sea Region
• Magdalena Olczyk, Marzena Starnawska
• Developmental barriers to women’s entrepreneurship
• Bogusław Plawgo
• Myths and Facts About Women aged 50+
• Anita Richert-Kaźmierska
• Selected aspects of women holding managerial positions
• Alina Szepelska
• The situation of women on the labor market as a determinant of the development of their entrepreneurship
• Adam Tomanek
• Gender differences in entrepreneurship myths
• Beata Krawczyk-Bryłka
• Economic aspects of reproductive decisions in the Baltic Sea Region in years 2002-2012
• Anetta Waśniewska
• The convergence of gender wage differences – myth or fact – multi country multi sector analysis
• Joanna Wolszczak-Derlacz

• Part II Ageing society in the context of companies’ competitiveness

• The digital divide and the issue of participation of persons aged 50+ in the Polish labour market
• Anita Richert-Kaźmierska, Katarzyna Stankiewicz
• Modern tools of using elderly persons’ potential in an enterprise
• Maciej Muczyński
• Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
• Marzena Grzesiak
• The concept of intergenerational cooperation network – the transfer of knowledge and skills
• Katarzyna Tubielewicz

• Part III Determinants of competitiveness and innovation of modern enterprises in BSR

• Poverty and social exclusion in the transition Baltic States during the implementation of the European Union Lisbon Strategy - comparative analysis
• Izabela Borucińska- Dereszkiewicz
• Competitiveness of the enterprises in the light of the sustainable development principles
• Hanna Kruk
• Socio-economic exclusion as a hindrance of economic development. A comparative study for European countries
• Ewa Lechman
• Social development – a multidimensional approach to social development analysis. Country level evidence
• Ewa Lechman
• Social enterprises as a fertile ground for reducing social and economic exclusion – good practice examples from Poland
• Marzena Starnawska
• Knowledge management in SMEs – selected issues
• Małgorzata Zięba
• Innovative management of IT projects with the use of the agent-based approach on the basis of intelligent agents
• Artur Ziółkowski
• Risk Management in "Agile" methodologies using the example of Scrum and the IBM Rational Team Concert tool
• Bartosz Chrabski, Artur Ziółkowski

Foreword

The issue of competitiveness and innovation has been a subject of theorist discussions and debates since the beginnings of the modern economy, as well as a challenge that business practitioners face every day. Over time, only the factors indicated as determinants of such competitiveness change: the key role played by land, capital and labour in the nineteenth and early twentieth century has now been taken over by new technologies, entrepreneurship and knowledge.

The competitiveness of modern enterprises is largely affected by their ability to deal with threats that occur in the environment and the effective use of opportunities, related to e.g. the socio-economic globalization, the technological and ICT revolution and finally the depopulation and ageing of the population of most European countries and the United States of America.

This publication relates to the subject of shaping and maintaining high competitiveness and innovation by businesses, with particular emphasis on the SME sector in the Baltic Sea Region. It was divided into three parts. The first part includes the discussion of women's economic activity and their participation in the creation and strengthening of the competitive position of companies. The second part is devoted to problems related to the ageing of population in the Baltic Sea Region countries and the potential socio-economic impact of this process. The deliberations contained in the second part refer also to the possibilities and conditions for realizing the potential of seniors in the development of competitiveness and innovation of enterprises. The third part is a fragmentary overview of achievements related to the factors of competitiveness and innovation of modern enterprises. The authors of individual sections have related both to endogenous and exogenous elements.

Marzena Grzesiak, Anita Richert-Kaźmierska

Part I

Women’ entrepreneurship

Activity and discrimination against women in the labour market in the countries of the Baltic Sea Region¹

Magdalena Olczyk, Marzena Starnawska²

Introduction

The European Union, which includes most of the countries of the Baltic Sea Region is currently the only region in the world, where unemployment is not falling. The unemployment rate in the EU-27 is currently at the level of 10.9% and of 12.0% in the euro area (the highest level of unemployment in the euro area, since the monetary union was established). Differences between EU countries when it comes to situation the labour market are very significant: the best the situation is in Austria, Germany, Luxembourg, the worst in Spain, Portugal and Greece.

The reasons for this are several. Of course, the weakening of economic activity in the countries around the Baltic Sea region is the direct cause of the decline in employment in most European countries. However, a bad situation on the European labour market has structural causes. They are: a low degree of flexibility of labour markets in many EU countries, a significant mismatch structure of supply and demand in the labour market especially among the New EU Members and the low level of entrepreneurship among the citizens of our continent. The most difficult situation on the labour market touch the very young people, just entering the labour market, people have been unemployed for a long period of time, and women [Labour Markets 2012].

Women's activity on the labour market is crucial to overcome the problems in the EU labour market and to achieve the objectives of the Europe 2020 strategy. To achieve an average employment rate of 75%, it is necessary to "attract" women to the labour market. In addition, to realize the desired level of development conducive to social exclusion (target Europe 2020), it implies a strategy to increase the participation of women on the labour market. On the labour market is seen the greatest discrimination on grounds of sex, and women's difficulties in returning to work after maternity leave, often contributing to their exclusion from a group of people actively trade for many years [Barwińska-Małajowicz 2009, p. 211].

Therefore, the aim of the study is to identify differences in the situation of women in the labour market in selected countries specially those in the Baltic Sea region, which is due to its diversity provides an excellent sample. In year 2004 the European has expanded to include 10 new countries (mainly from the region of the Baltic Sea), which are very diverse in terms of economic development, macrocompetitiveness and the degree of labour market development. This article aims to verify the hypothesis of the existence of direct and indirect discrimination against women in the labour market in the countries of the Baltic Sea region. Participation of women in the labour market will be compared with the activity of men in these markets. The authors analyze selected nine countries surrounding the Baltic Sea, i.e. Denmark, Germany, Estonia, Latvia, Lithuania, Poland, Finland, Sweden and Norway (the only country outside of the EU). Research period covers the years 2000-2011.

Labour force participation of women in BSR region

Firstly, the author analyzes the participation rate of women in selected countries. The participation rate means the percentage of people of working age, who are currently employed or looking for a job. In the analyzed period, in most of the countries strongly increase the labour force participation of women. Both, at the beginning and at the end of the reporting period the Scandinavian countries are the leaders, because the share of economic active women in the population of women of working age are around 75% (table 1). By far, the most effective policies, which allow to increase a female participation in labour market in the decade studied, was introduced in Germany, Estonia and Latvia. It allows to achieve a 70 percent of participation rate of women in the labour market in these countries. The worst, quite alarmingly situation represents the activity of women in the Polish labour market. The rate of participation of women remains at very low level, virtually unchanged throughout the period considered. This is due primarily to very low activity Polish women aged 35-44 [Kobiety i mężczyźni 2012, p. 3].

Table 1. Activity rate of women in selected BSR countries

Source: Own calculation on Eurostat data.

The increased economic activity in most countries affect the growing rate of employment among women (table 2).

Table 2. Employment rate of women in selected BSR countries

Source: Own calculation on Eurostat data.

By the employment rate, we mean the proportion of working age women employed. Countries with a high rate of female participation (Denmark, Sweden, Norway), also record the highest levels of employment rates among the surveyed countries. Interestingly, the level of employment rate of women at the level of 71-73% seems to be the maximum level, which is confirmed by a negative growth rate of employment in Denmark and Norway in the period 2000-2011. Among the "catching-up" countries such as Germany, Estonia, Latvia significant increase in women's economic activity is reflected in the double-digit growth in the employment rate over the period. The worst is the situation of women in the Polish labour market. Although the employment rate increases by 8% during the period 2000-2011, in terms of the level in the employment rate by women, Poland has a gap of almost 20 percentage points to the country-leader (Norway).

In addition, we examine the change in employment rates in the countries in the cross-section of age, by education level and by sector, in which women are employed. Analysis of table 3 confirm a similar trends in all countries. First, the increasing employment of women in the age group 55-64, which probably is a result of a large number of programs aimed to increasing labour force participation of women in this age group. Secondly, education (higher) is the best protection of women in the labour market, guaranteeing them employment. Thirdly, the service sector is the best market for women looking for work, because only in this sector in all countries the increasing employment among women is observed.

Table 3. Growth of employment rate of women between years 2000-2011 in selected BSR countries – criteria of age, education and sector of employment

Source: Own calculation on Eurostat data.

In addition to increasing the participation of women in the labour market, and hence the employment rate of women, an important issue is to reduce the gender employment gap in the Baltic Sea region. Overall, the employment gender gap, measured by gender gap in employment rate, decreases in all analyzed counties, in with the exception of Polish and Swedish economies (Figure 1). This is due to the fact that the employment rate for women rose faster between 2000 and 2010 than the employment rate for men (with the exception of Polish and Swedish labour market).

This phenomenon allowed to effectively reduce the gap between male and female employment rate in analyzed period.

Figure 1. Gender gap in employment rate 2000-20011³

Source: Own calculation on Eurostat data.

Analyzing the gender gap in employment gap by different age classes, is clear that the largest difference in employment rates between men and women in a group of people aged 55-64 (table 4).

Table 4. Gender gap in employment rates by age class, 2000 versus 2011

Source: Own calculation on Eurostat data.

The difference in this age group can be up to 20.5 percentage points in case of Poland and up to 14 percentage points in case of Germany (in 2011). It is interesting that the largest reduction (if we take into account the average gender gap in employment rates by age groups for the analyzed countries) occurred in the age group of 15-24 and 55-64 age group. The situation in the group aged 25-54 remained virtually unchanged between years 2000 and 2011.

Analysis of absolute numbers of people trained at various levels of education shows that the labour force in analyzed countries from year to year is becoming better educated. Generally, women are higher educated than men. In addition, the negative gender gap in employment rates at highest level of education (level 5-6) increased significantly between 2000 and 2011 in most analyzed countries (table 5). Because a significant number of women enroll in higher level education, gender gap in employment rates at the medium level of education is growing.

Table 5. Gender gap in employment rates by level of education attained, 2000 and 2011

Source: Own calculation on Eurostat data.

In turn, the distribution of employment rates by sector provides a clear picture of the very different composition of female and male employment. Industry is still the main work place for men, the services sector now provides the majority of female jobs (table 6). Men in all analyzed countries are more likely than women to work in agriculture and this situation almost didn’t change over the last decade.

Table 6. Gender gap in employment by sector of activity, 2000 and 2011

Source: Own calculation on Eurostat data.

To better illustrate the situation of women in the labour market, it is worth analyzing the changes in unemployment rates in the countries (table 7).

Table 7. Unemployment rate and growth of unemployment rate of women between years 2000-2011 in selected BSR countries – criteria of age and education

Source: Own calculation on Eurostat data.

By far the lowest single-digit levels of unemployment we note in the Nordic countries (Sweden, Norway, Denmark) and in Germany. Unfortunately, the New Member States (Estonia, Latvia, Lithuania) are characterized by a high, double-digit unemployment rate among women at the beginning and end of the period considered. The exception, surprisingly, is Poland, which during the decade studied reduce the unemployment rate among women from 14.8 to 9.1%. This shows the high efficiency of the implemented programs that reduce unemployment in Poland, especially among young and poorly educated. Among the countries that are most able to reduce unemployment among women in the period considered (like Poland and Finland), it is worth noting that this decline most often affects women well or very well educated. This allows you to once again confirm the idea that education is the best protection against unemployment among women. A worrying phenomenon is quite a significant increase in the unemployment rate among women in Denmark and Sweden, regardless of their age or level of education, despite the fact that the unemployment rate in these countries remains at a relatively low level.

It is interesting to compare the unemployment rates among women and men in the analyzed countries. Overall, there is not a significant difference between the sexes, when it comes to unemployment rates. In 2011 the male rate is consistently slightly higher than the female i.e. in year 2011 male rates exceeds female rate no more than by 2 percentage points in seven out of nine analyzed counties (figure 2). Exception are Latvia and Lithuania, where gender gap in unemployment rate reaches a level of almost 5 pp. In year 2011, compared to year 2000 men are more often than women threaten with unemployment, which is confirmed by positive gender gap in unemployment rate in year 2011 in 8 of 9 analyzed country. So, in the surveyed countries, the situation of women is much better than that a position of average woman in the European Union (where female unemployment slightly rate is higher than the male one).

Figure 2. Gender gap in unemployment rate 2000-20011⁴

Source: Own calculation on Eurostat data.

Analysis of the gender gap in unemployment rates by age classes allows us to confirm the above mentioned thesis about the better position of unemployed women compared to men in almost all age groups. The exception is the group of the unemployed aged 25-54, which is the most feminized. In year 2011 a female unemployment rate in this group was higher than the male unemployment rate in four of nine countries. This is probably due to fact, that women aged 25-54 are more likely than men to exit and re-enter the workforce for family reasons (there is a general 'crowding' of females into occupations fewer than men).

Table 8. Gender gap in unemployment rates by age class, 2000 versus 2011

Source: Own calculation on Eurostat data.

The gender gap based on differences in unemployment rates tend to be higher among the less educated workers in the majority of countries, and tend to be lower among the more educated workers (table 9). This allows to conclude that education in analyzed countries protect against unemployment better women than men. This conclusion is confirmed by the negative gender gap between unemployment rates for the men's and women in five of the nine surveyed countries in year 2011.

Table 9. Gender gap in unemployment rates by level of education attained, 2000 and 2011

Source: Own calculation on Eurostat data.

When it comes to duration of working life, both women and men work from year to year more. However, during 2000-2011 in seven of the nine analyzed countries the duration of active working life increased more rapidly for females than for men. This causes that the gender gap in duration of working life (men versus women) significantly decreased during the period considered in most countries. The exceptions are Poland and Sweden, where the duration of working life grown more slowly for women than for men.

Figure 3. Gender gap in duration of working life, 2000 and 20011

Source: Own calculation on Eurostat data.

We should also look at average exit age from the labour force⁵. Most workers (men and women) in majority analyzed countries leave the labour market before the standard pension eligibility age. The country, where people leave the labour market significantly earlier than normal pensionable age, is Poland. Analysis of table 10 shows that the average retirement age for men and women differ little. The gap (men versus women) relating to the average exit age from the labour force increased, but no significantly over the period.

Table 10. Average exit age from the labour force, 2000 and 2011

Source: Own calculation on Eurostat data.

Occupations and the wages – discrimination of women on the labour market or not?

Low participation of women in the labour market is often explained by the discrimination in this market. Discrimination can take two forms. The first is direct discrimination (wage), where the woman does not receive a market's wage corresponding to a given profession and specific qualifications, only because she is a woman. The second form is called indirect discrimination and occurs when, despite the use of universal criteria, they can not be met by a large social group. It manifests itself in disparities in the forms/conditions of employment to the detriment of large groups of workers (such as women.)

The author is going to make the empirical verification of the hypothesis of the existence of direct and indirect discrimination against women in the countries of the Baltic Sea. Firstly, the analysis will concern standard forms of employment for both women and men.

Self-employment⁶ is in literature considered as the evidence of entrepreneurship or lack of opportunities to work as an employee. However, in view of economy and the situation on labour market this phenomenon is highly desired due to the evidence of the resilience of self-employment to the crisis, compared with paid employment [Self-employment 2010]. Generally, in the analyzed group of countries on average, about 13% men among all employed workers works as self-employed and only 7% of women prefer this form of work (table 7). Over all these years, this situation hardly changed. Against this background two countries are outstanding. Lithuania, where the share of self-employed people, both men and women, decreased significantly during this period. Poland, which for the whole period had a very high participation of both men and women in self-employment (almost double than the average for all countries).

Table 11. Self-employed in % of total employment, gender gap in 2000 and in 2011

Source: Own calculation on Eurostat data.

Recent decades is characterized by a growing trend towards non-standard forms of work, with more part time and temporary employment in developed economies and more informal employment in developing countries. Temporary contracts belong to one of the most widespread flexible forms of employment on EU's labour market. This type of contract being somewhat more common amongst women than amongst men (table 12). Among the nine countries, in five of them i.e. in Denmark, Germany, Finland, Sweden, Norway, both in 2000 and 2011 years, women were employed with temporary contracts often than men. On the other hand, among the new EU member states, i.e. in Estonia, Latvia, Lithuania and Poland, this form of employment was in the whole period more popular among men than among women, although it is worth noting that the gender gap in this area was slightly reduced.

Table 12. Employees with temporary contracts in % of total employment, gender gap in 2000 and 2011

Source: Own calculation on Eurostat data.

Another very popular flexible form of employment is a job on part-time. In literature, flexible working time arrangement (which includes a job in part-time) is one of the possibilities, how to open the labour market to women. This thesis is also confirmed by the analysis among our countries, where shares of part-time's employees with temporary contracts in total employment were much higher for women than men (in years 2000 and 2011). However, the gender gap in use of work in part-time is much higher (on average 24 pp.) in Old Member States i.e. Denmark, Germany, Finland, Sweden, Norway than in new ones i.e. Estonia, Latvia, Lithuania and Poland (on average 4-5 pp).

Table 13. Part-time employees with temporary contracts in % of total employment, gender gap in 2000 and 2011

Source: Own calculation on Eurostat data.

Of course, the question whether the women’s preference for working in part-time, it is their conscious and voluntary choice or a lack of other alternatives? Based on ILC report on gender equality we can conclude that for many women family remains a top priority and a work in short hours allows them to care for children and also earn some income [ILC report 2009]. So a part-time job can not be treated as a negative phenomenon.

Then, the author verifies the hypothesis about existence of wage discrimination against women in the labour markets in the region BSR. Women’s wages are usually lower than men. According to analysis of wages in nine countries, women earned gross and per hour less (on average about 18,2% in year 2006; 17.2% in 2010) than men. The unadjusted Gender Pay Gap⁷ often varies between 15-22% in most countries. Poland is the exception due to the lowest GPG (5,3% in 2010), in turn, Estonia is known as a country with the highest GPG in Europe (27,6% in 2010). Generally, a very slow tendency to reduce the gap in salaries in all analyzed countries is observed.

Figure 4. Gender pay gap in unadjusted form in 2006 and 2010 (data for Estonia in 2010 were from 2008)

Source: Own calculation on Eurostat data.

Of course, it is reasonable to question, whether GPG varies with age. Generally, we would expect its growth with the increase of workers age. The idea is that on young people (aged 25-34) such factors as family, children, maternity leave haven't yet influenced, so GPG should be the smallest. Results of table 14 confirm this thesis. On average, in year 2010, the gender pay gap was 11.3% for those aged 25-34, this gap reached a level of 16.5% for those aged 35-44 and 45-54 and a GPG was 16.2% for people aged 55-64.

Table 14. Gender pay gap in unadjusted form by age in % - NACE Rev.2: B to S excluding O, year 2010

Lack of data for Germany, Estonia, Lithuania

Source: Own calculation on Eurostat data.

We have to notice an interesting phenomenon of reduction of the GPG in public sector in comparison to the private sector (table 15). Big successes in this field have Poland, Germany and Norway, what are probably related to the legal regulations in these countries.

Table 15. Gender pay gap in unadjusted form by economic control in % - NACE Rev.2: B to S excluding O, year 2010

Source: Own calculation on Eurostat data.

In addition, we should note the significant difference in the gender pay gap between workers employed in part-time and full-time jobs (table 16). On average, this gap is double higher in case of workers employed full-time than for employees in part-time. A lower GPG among part-time workers compared to full-time employees is probably related to a relatively high participation of women in this elastic form of employment (in part-time work).

Table 16. Gender pay gap in unadjusted form by working time in % - NACE Rev.2: B to S excluding O, year 2010

Lack of data for Estonia, Finland and Lithuania

Source: Own calculation on Eurostat data.

Finally, it is worth mentioning the relationship between the level of GPG and level of education. In most countries, wage differences between men and women are greater for highly educated workers than among low-skilled workers (i.e. those without upper secondary education). A possible explanation of these results could be a low share of low-or unskilled women in the workforce (table 17).

Table 17. Average annual earnings of females as a percentage of males by level of educational attainment and age-cohort, 2008

Lack of data for Latvia, Lithuania

Source: OECD Education at a Glance, 2010.

Conclusions

An increasing participation of women in the labour market seem to be a key to overcome the problems of the EU labour market and to achieve the objectives of Strategy Europe 2020. Therefore, the objective of this paper is to identify differences in the situation of women in the labour market in selected countries such as those in the Baltic Sea region and to attempt to verify the hypothesis of the existence of discrimination against women in the labour market in the analyzed region. Analysis of economic activity and employment indicate the increase in labour force participation and in employment among women in all countries in the period 2000-2011. Although, it remains a high diversity in levels of the analyzed indicators between the "old" EU-15 countries (a high level of activity and employment) and the New Members of the EU (a low level of activity and employment). The determinants of high activity and employment among women are: high education, work in the service sector and the age between 55-64 years. These conclusions are confirmed by the analysis of unemployment rates in selected countries, where the falling rates of unemployment are recorded in most countries especially among women with higher education. Furthermore, the analysis of gender employment gap indicates that the gap between the employment rate of men and women quickly reduces among workers with higher education and in the age group 55-64.

Trying to answer the question, whether we are dealing with a discrimination against women in the labour market, the answer must be the affirmative and the negative. Surely, on the European labour market exists a direct price discrimination, because an unadjusted gender pay gap varies between 15-22% in most analyzed countries. In addition, there is observed only a very slow tendency to reduce the gap in salaries, mainly in the public sector. However, the author can not confirm the hypothesis of the existence of an indirect discrimination against women in the European labour market. Choice of flexible forms of employment, such as job on part-time, temporary employment or self-employment is not determined by gender, but rather depends on the legal and cultural conditions in individual countries.

References

1. Barwińska-Małajowicz A., Próby rozwiązania problemu dyskryminacji i nierówności na rynku pracy Unii Europejskiej. Zeszyty Naukowe Uniwersytetu Rzeszowski, nr 15, 2009.
2. Budnik K., Migration Flows and Labour Market in Poland. National Bank of Poland, Working Paper No. 44, 2008.
3. Ciponne A, Patacchini E., Vallanti G., Women’s Labour Market Performance in Europe: Trends and Shaping Factors. Centre for European Policy Studies Perpers, No 7329, 2012.
4. Corral M., Isusi I., Part-time Work in Europe. European Foundation for the Improvement of Living and Working Conditions, Dublin, 2007.
5. Employment in Europe 2004. European Commission, DG ECOFIN.
6. Employment in Europe 2005. European Commission, DG ECOFIN.
7. Employment in Europe 2007, European Commission, DG ECOFIN.
8. Ferreira M., New Member States contribute to reducing unemployment in Europe. Statistics in Focus, 124/2007.
9. Garibaldi P., Wasmer E., Raising Female Employment: Reflections and Policy Tools. “Journal of the European Economic Association”, MIT Press, vol. 2(2-3), 2004.
10. Jurajda S., Gender Wage Gap and Segregation in Late Transition. CERGE-EI Working Papers nr 182, Prague, 2001.
11. ILC report on gender equality, 2009, www.ilo.org
12. Kluve J. (eds.), Active Labour Market Policies in Europe. Performance and Perspectives. Springer, 2007.
13. Kobiety i mężczyźni na rynku pracy, GUS, Warszawa, 2012.
14. Labour Market Development in Europe. European Commission, DG ECOFIN 2012.
15. OECD Education at a Glance, 2010, www.oecd.eu
16. Paas T., Eamets R. et al., Labour Market Flexibility, Flexicurity and Employment: Lessons of the Baltic States. Nova Science, Hauppauge NY, 2006.
17. Self-employment in Europe, European Employment Observatory Review, 2010.
18. Statistic datebase in Eurostat, www.eurostat.eu.
19. Tijdens K., Gender Roles and Labour Use Strategies: Women's Part-Time Work in the European Union, “Feminist Economics”, Taylor and Francis Journals, vol. 8(1), 2002.

________________________

¹ The article was prepared as a part of the project Quick IGA, part-financed by European Union (European Regional Development Fund) in Baltic Sea Region Programme 2007-2013. Research paper financed from the funds for science 2012-2013 for co-financed international projects.

² Gdańsk University of Technology, Faculty of Management and Economics.

³ Gender gap is defined as difference between male and female rate of employment.

⁴ Gender gap is defined as difference between male and female rate of employment.

⁵ Average exit age from the labour force - is the exit age weighted by the probability of withdrawal from the labour market. The indicator gives the average age at which active persons definitely withdraw from the labour market. It is based on a probability model considering the relative changes of activity rates from one year to another at a specific age. The activity rate represents the labour force (employed and unemployed population) as a percentage of the total population for a given age. The indicator is based on the EU Labour Force Survey.

⁶ A self-employed person is the sole or joint owner of the unincorporated enterprise (one that has not been incorporated i.e. formed into a legal corporation) in which he/she works, unless they are also in paid employment which is their main activity (in that case, they are considered to be employees). Self-employed people also include: unpaid family workers; outworkers (who work outside the usual workplace, such as at home); workers engaged in production done entirely for their own final use or own capital formation, either individually or collectively.

⁷ The unadjusted Gender Pay Gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees.

Developmental barriers to women’s entrepreneurship

Bogusław Plawgo⁸

Introduction

Women commencing and conducting business activity undoubtedly encounter a range of universal entrepreneurial barriers. Nevertheless, a general lower level of women’s entrepreneurship than men’s entrepreneurship is the evidence of existence of some additional specific barriers to women’s entrepreneurship. This paper focuses on these barriers. The objective is to analyze, on the basis of reference literature, specific barriers to entrepreneurship among women in comparison with men. Identification of these barriers may constitute a starting point for detailed empirical studies verifying individual barriers in a specified social-economic context. On the other hand, such an analysis of a set of some characteristic developmental barriers to women’s entrepreneurship may constitute a constructive starting point for planning activities of public intervention aiming at neutralizing or at least limiting their influence. In this paper, the fundamental subject matter considering developmental barriers to women’s entrepreneurship has been preceded by considerations on the level of women’s entrepreneurship that indicate the objective character of occurrence of specific barriers to entrepreneurship development among women.

The level of entrepreneurship among women in comparison to men

The state of women’s entrepreneurship should be analyzed in a longer perspective of time in regard to world experiences. Researchers from the USA remark that women’s entrepreneurship rapidly developed not before than within the last three decades [Brush and Gatewood 2008, p. 175-179]. They estimate that enterprises owned by women constituted less than 5% of all enterprises in the USA in 1970. In 1978 their contribution equaled more than 30% and in 2006 they reached 40% of the whole population of enterprises and employ more than all the largest companies of the Fortune 500 list. A fast pace of contribution growth of enterprises run by women in the world has not yet led to the balance of proportionality of women’s and men’s entrepreneurship. Furthermore, the state of this disproportion, to a certain extent, seems to have become established in the last decade, i.e. in the period 2002-2010. It is confirmed by the data provided by the World Bank [Women in business 2012], which say that a little more than one third (35.3%) of enterprises worldwide are entities run by women. In the course of research based on GEM’s data and on the report Women in Enterprise: a different perspective, it was discovered that since the beginning of the 1970’s, the self-employment rate among women has consistently accounted for a half of the value of the same rate for men. Furthermore, in comparison with men, women usually start with establishing a smaller enterprise and usually they do not develop but remain on the level of a micro enterprise; they possess a lower level of capitalization and more rarely decide on expansion into foreign markets. The source of this status quo can be found in the fact that women in comparison with men on average perceive their own opportunities and their opportunities for success in business as worse; they are less motivated and more afraid of failure. These differences are most significant in developed countries.

Eurostat’s data also indicate a visible in the countries of the European Union predominance of enterprises run by men over enterprises owned by women. The analysis of the years 1998-2009 indicates some tendencies in the level of women’s entrepreneurship. In some countries the level of women’s entrepreneurship has remained during the last decade on a similar level without undergoing significant fluctuations. These countries include, e.g. Ireland (18.6%), Sweden (27.6%), Great Britain (28.8%), the Czech Republic (27.3%), Finland (32.7%), Poland (34.4%). In most European countries, women’s entrepreneurship was growing at the end of the 1990’s and in 2000 there was a decrease in women’s contribution in the number of persons owning their own business. Estonia was a remarkable case, because the women’s contribution significantly increased from 31.1% in 1998 to 38.5% in 2000, and a year later it decreased by nearly 10 percent points – to the value of 28.8%. It is the greatest decrease in the percentage of women among entrepreneurs. During the subsequent years (2001-2006) the percentage of women among the self-employed and employers, although in different countries and in different pace, revealed a growing tendency. The percentage grew most fast in Denmark, Luxemburg and Malta. Until 2006, there was an increase in the percentage of women owning their own business in 13 countries of the European Union. The subsequent years (until 2009) were a period of continuing, but slow (from 0.5 to 2%) growth and stabilization of the level of women’s entrepreneurship in the European Union. In 2009 the women’s contribution in the number of employers and the self-employed in EU-27 equaled 30.5%. In the examined year, the significant majority of entrepreneurs – 69% was constituted by men. The highest percentage of women in the general number of entrepreneurs⁹ was then reported in Portugal (40.35%), Austria (35.2%), Latvia (36.5%) and Lithuania (37.5%) [Balcerzak-Paradowska 2011].

The problem of women’s entrepreneurship is not only a relatively lower number of enterprises run by them, but also smaller sizes of these enterprises and the lower pace of growth. It was noticed in the USA that only a few companies owned by women report achieving a considerable size. In 2004 only 13% of enterprises run by women achieved sales value exceeding USD100,000 and only 15% employ more than 50 employees [Brush and Gatewood 2008, p. 175-179]. Almost in every research it is visible that enterprises run by women are of smaller sizes than enterprises run by men. It is emphasized that this regularity is present at every stage of enterprise development. Irrespective of the fact that the number of enterprises established and run by women is constantly growing, it does not change the aforementioned regularity. Particularly large discrepancies are characteristic of high-growth enterprises [Gatewood, Carted, Hart 2009, p. 129-144]. Some generalizations in this scope can be suggested in the form of some model regularities (figure 1).

Figure 1. Sizes and pace of growth of enterprises run by women and men

Source: based on [Gatewood, Carter, Hart 2009, p.129-144]

Polish data confirm that women gain a significantly lower income coming from business activity than men [Balcerzak-Paradowska 2011]. It is reasoned that this is connected with the fact that women are more often active in less profitable branches in comparison to men who undertake activity in more profitable branches such as building industry and IT [Trafiłek 2006, p.151-152]. It results from the examination of the structure of wages and salaries by occupation in Poland in 2010 that men gained profit by 8.1% higher than an average remuneration on a national scale, whereas women – lower by over 8.8%. Consequently, it means that an average remuneration of women was by 15.0% lower than an average remuneration of men [Aktywność ekonomiczna ludności 2012]. It is also confirmed by the surveys conducted by TaxCare which state that enterprises run by women are less profitable [Ślęzak-Matusiewicz 2011]. It is significant that the reason of this is, according to the research, the fact that women dedicate less time to their own business than men (maximally 8 hours a day), whereas 61% of men dedicate more than 8 hours. Furthermore, women more often choose such a form of employment, which will allow a more flexible time management and fulfill themselves as mothers.

The data on Polish economy also confirm that enterprises run by women are characterized by survivability on the market which is shorter than survivability of enterprises run by men. In 2010 the survivability rate of enterprises (established in 2006) run by women equaled 43% and by men – 50.6% [Balcerzak-Paradowska 2011].

The data concerning the state of women’s entrepreneurship both worldwide and in Poland confirm lower contribution of enterprises run by women, a slower pace of their growth and lower survivability. Undoubtedly, it is the evidence of the existence of specific barriers to women’s entrepreneurship development.

Types of barriers to women’s entrepreneurship

In the course of research conducted by the European Commission, three types of barriers have been identified. Firstly, contextual obstacles – defined as educational choices, traditional views and stereotypes about women, science and innovation. Secondly, economic obstacles – identified as innovation sector, which requires significant investment expenditures, whereas women are perceived as less financially reliable than men. Thirdly, soft obstacles – connected with absence of an access to scientific-technological and business networks, lack of business training, role models and the sense of entrepreneurship¹⁰. A very similar categorization of barriers to women’s entrepreneurship in the context of conditions existing in Poland is proposed by E. Lisowska and R. Kasprzak [2008]:

• –   Educational barriers, connected with lack of information and deeper knowledge how to establish, conduct and develop own company. Another problem is high cost of training connected with acquiring managerial skills, building a team and learning the ways of motivating employees, as well as with rational management of own psychophysical potential, effective management of the company’s development and information about financing sources for small and medium enterprises. Experiences of the Scandinavian countries, the USA and Canada prove that women more eagerly benefit from support within separate centers of women’s entrepreneurship.
• –   Traditional socialization – connected with preparing women mainly to the caring and educational functions, not to activeness in the professional sphere, independence and success. A barrier to running a business, resulting from this way of bringing up, is e.g. lack of self-confidence and trust in own skills or engaging in the company’s matters and subordinates’ personal problems too often.
• –   Barriers in the access to financing – barriers in gaining capital for establishing or developing a business by women. Enterprises run by women are granted loans of lower amount and with higher interest rate; and they finance their business activity with their own funds to a greater extent (80% of enterprises run by women in comparison to 65% of enterprises run by men). A similar problem is familiar to female business owners in Denmark, where the research revealed that female enterprises indeed have less initial capital than enterprises run by men. In Hungary, female owners report that the main barriers in the access to financing result from the difficulties in obtaining a credit; whereas, the relatively low percentage of women in the number of entrepreneurs in Sweden largely results from hindered access to bank loans, because banks are interested in granting loans to large enterprises.

With particular regard to the aspect of smaller-sized companies and slower pace of growth of companies owned by women, it seems that a modified categorization of barriers to female entrepreneurship embracing three main aspects can be proposed:

• -   social-cultural barriers
• -   barriers resulting from difficulties in the access to business networks, including networks connected with the sources of capital
• -   barriers resulting from a lower “entrepreneurial intensity” of women.

Social-cultural barriers

Europa dla kobiet