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FLOWS WORKING PAPER
SERIES
NO. 22/2014
Kairi Kasearu, Avo Trumm and Dagmar Kutsar Local Production Systems in Tartu, Estonia FLOWS: Impact of local welfare systems on female labour force participation and social cohesion
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FLOWS Working Paper Editor: Per H. Jensen E-mail: [email protected] www.flows-eu.eu Working papers may be ordered from: Inge Merete Ejsing-Duun Fibigerstræde 1 9220 Aalborg Ø E-mail: [email protected] Tlf: (+45) 99 40 82 18 Fax: (+45) 98 15 53 46 Aalborg 2014 ISSN 2246-4840
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About the FLOWS project: The FLOWS project has been funded under the EU FP7 program, grant Agreement no: 266806. The project started January 1 2011 and ended April 30 2014. The FLOWS project analyses the causes and effects of women’s labour market integration, which is an issue that represents a major challenge for the European Union and its member states, and is supposedly also a precondition for the sustainability of the European social model. The overall aim is to analyse (1) how local welfare systems support women’s labour market participation, as well as (2) the extent to which (and under which conditions) female labour market integration has contributed to the strengthening social cohesion. The project focuses on how public and private welfare services such as care and lifelong learning intended to support women’s labour market integration have been designed; on how women of different classes, qualifications, ethnicities, and geographical locations have grasped and made use of such policies, and on how the increase in women’s labour market integration has affected structures of inequality and social cohesion. The study is based on in-depth analysis of eleven cities, i.e. one city in eleven different countries. The cities/countries are: Brno/Czech Republic, Aalborg/Denmark, Tartu/Estonia, Jyväskylä/Finland, Nantes/France, Hamburg/Germany, Székesfehérvar/Hungary, Dublin/Ireland, Bologna/Italy, Terrassa/Spain, and Leeds/UK. The FLOWS project is composed by 6 academic work packages: WP 1: Degree and structures of women's labour market integration WP 2: Local production systems WP 3: The local welfare system WP 4: Local policy formation/local political actors WP 5: Survey questionnaire WP 6: Women’s decision making WP 7: Social structures: cohesion or cleavages and segregation This working paper series reports work conducted in the seven work packages.
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Introduction
The aim of the current country report is to contribute to comparative analysis with data and analysis of the employment opportunities of women in Estonia with a special focus on the second largest city Tartu – in the frames of the (local) production system and the labour demand. The objective of the analysis is to describe and interpret particular patterns of economic development that may facilitate or weaken the integration of women into the labour market of the sample city.
First, we presume that the economic competitiveness of the city may affect inactivity and unemployment rates of women as well as their inactivity or concentration in the informal economy may affect the economic growth of this area. Secondly, we are interested in, whether the economic specialization of the local production system may affect the presence and quality of the female participation in the labour market.
The data are drawn from the database of the Statistics Estonia as the first priority (national/county/city level), EUROSTAT (no city-level data available here) and micro data from the Estonian Labour Force Survey from different rounds, and the 2010 data as the most recent (in case the Statistics Estonia does not offer the needed data). The report will reflect its weaknesses: due to some problems with data availability, by some items we will stop on the country level even if the city-level was preferred; by some issues county-level data are presented instead of the city-level for the same reason; by some issues there are no data disaggregated by gender on the local level and the micro-data from the LFS are not reliable (too small sample) however, also desk research of grey literature is applied as an additional resource to fill the blanks. The Labour Force Survey is principally rich source of data however it is not regionally representative, thus while using these data we can give only the tendencies and estimates, not representative numbers. Specifically this concerns the estimates about Tartu city. Another problem is the smallness of Estonia (1.3 million of population) – by Eurostat classification the whole country is dealt as NUTS-1 and NUTS-2. The NUTS-3 level is not often used. In the current report we use national (Estonia), county (Tartu County) as well as city-level (Tartu city) data.
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1. Urban pattern of development and structure of the labour market
The change in the local production system during last 15 years
Estonia has gone through a tremendous economic development – the economic growth in the 2000s has been the highest in the Estonian history. According to the analysis of Tiit41, for the 4th quarter of 2007 the gross domestic product had grown more than 2.5 times compared to the same quarter of 2000. This means on an average 14% annual growth during seven years. The employment rate among persons aged 15–74 grew from 54–55% in 2000 to 63% in 2007, and the unemployment rate decreased to 5%. The number of taxpayers grew by 14.5% for December 2007 compared to December 2002, thus the number of persons receiving taxable income grew on an average 2.7% a year. There was still a slight increase in 2008 followed by drop due to the economic recession impacted by the global economic and financial crisis. The increase in the GDP per capita has been even more rapid in the Tartu city if compared to the Tartu County or the national level (Figure 1).
Figure 1. GDP per capita in Estonia, Tartu County and Tartu city (EUR), 1995–2010. Source: Database of Statistics Estonia
Next, we will concentrate more precisely on the change in local production system in ten years. According to the survey “Entrepreneurship in Tartu 2010” almost two thirds of enterprises have been established since 2000 (Murakas, 2011)42.
41 Tiit, E.-M. (2010) The role of macroeconomic development in shaping welfare possibilities. In: Kutsar, D. (Ed) Poverty in Estonia. Tallinn: Statistics Estonia, p.22–47. 42 Murakas, R., toim (2011) Tartu ettevõtlus 2010: sotsioloogilise uuringu kokkuvõte [Entrepreneurship in Tartu 2010]. Tartu: TÜ SHSS.
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Figure 2 demonstrates the division of economic units in the statistical profile in the Central Commercial Register. Analyzing these data we have to take into account that the entrepreneurs have been distributed by counties according to their legal address. This means that the legal address and the activity place may not always coincide.
The most spread unit type in Estonia is private limited company followed by non-profit associations and foundations and sole proprietors. Regarding the sole proprietors, since January 1st, 2010 all sole proprietors have an obligation to be registered in the Central Commercial Register, therefore compared to the year 2004, we can witness a significant increase in the proportion of the sole proprietors (Figure 3).
Figure 2. The division of economic units in Estonia and Tartu. Source: Central Commercial Register database
Compared to the year 2004 the number of registered units has increased in Tartu from 6,356 to 10,101, most explained by the registration of sole proprietors, but also the number of other types of organizations has increased, this concerns for instance the private limited companies and non-profit associations. However, compared to 2004 the number of government and local government institutions has decreased both in Estonia as well as in Tartu about 12%.
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Figure 3. The change of economic units compared to the year 2004, N (year 2004 is a baseline). Source: Central Commercial Register database
The number of enterprises has increased both in the country as well as in Tartu city. Compared to 2000 by 2010 the number of enterprises has doubled, and the new enterprises have been mostly established in the tertiary sector. Also the peculiarity of Tartu is coming from the production system of the city, namely compared to the whole country in Tartu the tertiary sector is domineering (Figure 4).
100% 90% 80% 70% 60% 50% 40% 30% 20% 10%
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Prim ary Secondary Tertiary Enterprises growth
Figure 4. The increase of the number of enterprises compared to year 2000 and proportion of enterprises by sector in Estonia and Tartu city (%). Source: Statistics Estonia
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The proportion of the primary sector has declined over the years: in 2010 approximately 3% of enterprises were active in the primary sector. According to Murakas (2011) nearly a third of the enterprises are currently active in retail trade, the share of construction industry has decreased considerably, as compared to 2006 when this was the largest branch of economic activity. Moreover, looking at the distribution of enterprises within the tertiary sector, the number of enterprises dealing with arts, entertainment and recreation; transportation and storage; construction; information and communication has gone through the most rapid increase in Tartu (Table 1 in Appendix). Murakas (2011) with colleagues from the entrepreneurship survey in Tartu claim that during last ten years also the number of enterprises in education, health care and social care, where mostly the women are occupied, has doubled.
In the context of a noticeable increase in the number of enterprises, the increase mostly concerns small- seized ones where less than 10 people are employed (table 1). According to data of the Statistics Estonia, in Tartu city the proportion of enterprises, where less than 10 people are employed, has increased from 85.5% in year 2004 to 92.4% in year 2010. In year 2010 in Tartu, there were only seven enterprises with more than 250 people employed forming approximately 0.1% only of all enterprises.
Table 1. Enterprises by the number of employees in Estonia and Tartu city in 2011 (N; %) 2005 2006 2007 2008 2009 2010 Whole country
N 60898 65362 71012 76159 77948 81909 100216 % of N
Less than 10 87,3 87,8 88,2 88,5 88,8 90,5 93,2 10-49 10,3 10,0 9,7 9,4 9,2 7,8 5,5 50-249 2,1 2,0 1,9 1,8 1,8 1,5 1,1 250 and more 0,3 0,3 0,3 0,2 0,3 0,2 0,1
Tartu city
N 4274 4665 5194 5723 5816 6064 7354 % of N
Less than 10 85,5 86,3 86,4 86,6 87,3 89,2 92,4 10-49 12,4 11,7 11,8 11,8 11,1 9,5 6,6 50-249 1,8 1,7 1,5 1,4 1,4 1,2 0,9 250 and more 0,3 0,2 0,2 0,2 0,3 0,2 0,1
Source: Statistics Estonia 2011
One important indicator of the production system is its location. Characteristically for Tartu city, in recent years some big firms and companies have moved outside the city. This is reflected also in the numbers of people who are living in the city but working in another municipality. As an example, in 1998, 88% of inhabitants worked in the city compared to 82% in 2008 (Aro, 2008)43. However, according to the data of Estonian Labour Force Survey (data from 2010), 13% of inhabitants of Tartu did not work
43 Aro, K. (2008) Ankeet Tartu ja Tartlased 2008 Tartu: Tartu Linnavalitsus Linnaplaneerimise ja maakorralduse osakond (http://info.raad.tartu.ee/uurimused.nsf/236552664d75f727c2256c4b00207453/ba81a8f4667e5c24c22574f300499d06/$FILE/ Arvamusaruanne.pdf
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in the local municipality. On the other hand, the suburban areas, which by official definition locate in other municipalities, provide with labour force the enterprises in Tartu city, e.g in the municipality Ülenurme (a neighbouring parish) 37% of employed persons are working in Tartu.
Next, we will elaborate the reconstruction of the production system on the basis of changes in the numbers of employed persons in different sectors. Since 1997, a visible reconstruction of the production system has taken place (Table 2 in Annex). The share of the employed persons in the primary sector (agriculture, forestry and fishing) shrank from 34.4% in 1995 to 4.2% in 2010. This sector has been male- dominated with the proportion of around one third formed by women, i.e. the drop of this sector impacted both women and men proportionally (Table 3 in Annex). In case of Tartu, the primary sector has played a minor role in the production system and its dynamics and thus we can conclude that it has relatively week impact on women’s employment (Table 1 in Annex).
The secondary sector, which is male-dominated, decreased in total as well over the years but the drop has been smaller than in the primary sector (from 34.4% in 199544 to 30.5% in 2010). The developments inside the sector have been diverse. More specifically, the construction had a remarkable increase in 2006-2009 occupying 10-12% of the labour force, and then went to a sharp decline from 2009. The decline of this particular sector is one of the unemployment pumps for men but even though the percentage of women in this sub-sector decreased from 17.1% in 1995 to 6.9% in 2010. The change of the secondary sector in total has disfavoured men keeping the unemployment rate for men higher than that of women and decreasing the employment gap between men and women. The sub-sector that lost female labour over the years has been manufacturing: the percentage of females employed here decreased from 26.8% to 15.7% (eleven percentage points). Regarding the secondary sector in Tartu city, although the number of enterprises has increased the proportion has stayed relatively stable.
Over the years, the tertiary sector has gained power in Estonia (see figure 5): it increased from 54.2% in 1995 to 63.3% in 2010. The tertiary sector is female-dominated with three exclusions: administrative and support service activities (42.3%); information and communication (33.9%) and transportation and storage (28.4%) of female labour. The highest female dominance is in the case of education, and human health and social work activities (83.85 and 86.7% accordingly). This domination has been typical over the years with increasing trend. A slight decrease of the percentage of females in the labour force has taken place in accommodation and food service activities and wholesale and retail trade as well as repair of motor vehicles and motorcycles (74.2% and 62.1% respectively). In Tartu city the share of the employed in the tertiary sector has been higher than that in Estonia in general over the years, and there is even a noticeable increase from 2008 while the employment rate in the age group 15-64 went noticeably down (Figure 7). This indicates that in Tartu the tertiary sector was less influenced by increasing unemployment rate.
Also the most recent survey among enterprises in Tartu city (Murakas 2011) confirmed, that 10% (in 2006 it was 72%) of enterprises claimed having problems with finding workforce. Especially this
44 The year 1995 is taken as the launching point for two reasons: in 1990 it would have reflected the structure of the former economic system and 1995 is the year when the main social, political and economic system got reconstructed and therefore is better basis for comparison.
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concerns the enterprises in the fields of hotels, restaurants, industry, energy, gas and water supply and education, health care and social work thus indicating to potentials of further increase of the tertiary sector that is traditionally more female-dominated.
Figure 5. Employment in tertiary sector, 1995–2010. Source: Database of Statistics Estonia
Comparing men and women among blue- and white-collar employees, the data show female domination among the white-collar workers (legislators, senior officials and managers; professionals; technicians and associate professionals clerks). This is typical for Estonia and even more represented in the case of Tartu city over the years. In 1995, this proportion was in Tartu 64%, slightly fluctuating between 56 and 59% early 2000s and stabilising on 60-64% late 2000s. The blue-collar workers (service workers and shop and market sales workers; skilled agricultural and fishery workers; craft and related trade workers; plant and machine operators and assemblers; elementary occupations; armed forces) are less among men in Tartu compared to Estonia. To conclude, Tartu is better white than blue-collar city in case of both genders (Figure 6).
The survey among entrepreneurs in Tartu city (Murakas 2011) indicated that the share of women among managers has grown. As an example, 24% of managers were women in 2000; in 2010 the proportion is 33%. It is important to emphasize that the female managers had significantly more likely obtained a university degree in management/business compared to male managers (53% of women and only 16% of men)
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Figure 6: Proportion of white-collar employed, 1995–2010 Source: Database of Statistics Estonia
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2. Main impacts of the transformations on the employment opportunities for women
Female employment rate
The female employment rate in Estonia in the age group of 15–74 years has gone through an increasing trend from 1997 until 2008, with a dropping line during the economic recession late 2000s (Figure 7). Even though the employment gap between men and women became narrower, still the female unemployment rate has stayed lower than the male employment rate over the years. In Tartu (the county-level data) the female employment rate has been notably higher during the period of intensive economic growth from the mid-2000s compared to female population in Estonia and during the economic decline it reached both the national average and the male employment rate by 2010.
In international comparison, according to EUROSTAT, the employment of Estonian women is one of the highest in the EU. The employment rate of women in Estonia aged 20–64 has been over the EU average during the whole last decade. In 2009, the employment rate of women in Estonia aged 20–64 was 68.8%, which is 6.3 percentage points higher compared to the EU-27 average.
Figure 7: Employment rate of men and women (15-74 years of age) in Estonia and Tartu county, 1997–2010, %. Source: Database of Statistics of Estonia
Estonia has a tradition of people in working age working full-time. The data show that there is only a slight increase in those employed part-time over the years for both men and women (Figure 8). In 2010, the impacts of the economic decline can be noticed for both genders, and thus 62.6 thousand of the employed persons were working part-time basis in Estonia. From them 31.1% were males and 68.9% were women. On the basis of the data of Estonian Labour Force Survey (2010) in Tartu city
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approximately 17% of women and 11% of men are working part-time basis. It suggests that the situation of women in Tartu compared to whole country is similar, but in case of men, the differences emerge, namely the share of part-time workers among men is higher in Tartu.
Reasons for working part-time
The reasons for working part-time basis vary by gender. Women more often than men connect part- time working with family reasons (17.5% for women against 11.5% of men), personal preference (17.8% of women against 10.9% of men) or incapacity of finding full-time job (21.7% of women against 17.3% of men). Men in their turn connect working part-time more often with studies (20.4% of men against 15.7% of women) and bring the reasons related to the employer (40% of men against 27.4% of women). Important to note, that the reasons connected to the employer were most often reported by both genders (Figure 9).
Figure 8: Proportion of employed persons working part-time or are underemployed by gender in Estonia, 2010. Source: Database of Statistics of Estonia
Underemployment
Underemployment has not been a serious problem in Estonia according to self-reported data of the respondents of the Labour Force Survey. It has been varying from 3.3% for women in 1995 to 2.3% in 2010 and 2.4% to 1.6% for men accordingly – both in decreasing trend (Figure 9). Because of the low share of underemployed persons, it is impossible to find any data on the situation in Tartu city.
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Figure 9: Employed persons working part-time in main job by reason of part-time job, 2010. Source: Database of Statistics of Estonia
Informal work
According to Leetmaa and Võrk (2007: 2–3)45 the focus is on wholly undeclared work (both the employment status and earnings are concealed), under-declared work (where employers pay taxes only on the minimum wage, paying the remaining salary “under the table”) and tax evasion on the earnings of the self-employed. With reference to Renoy, et al (2004) Leetmaa and Võrk state that in comparison with the new EU members, Estonia (together with the Czech Republic and Slovakia) belongs to the group of countries where the share of undeclared economy is the lowest (around 8-13% of GDP). With reference to estimate made by Purju et al 2004, Leetmaa and Võrk bring the differences by economic sub-sectors varying from 9% in agriculture, hunting and forestry; real estate, renting and business activities (13%); wholesale and retail trade; repair of motor vehicles, motorcycles and personal and household goods (16%) up to one fifth (21%) in community, social and personal service activities. The informal work carries the pattern of gender segregation between economic sectors: males dominate in agriculture, hunting and forestry and construction, while females are mostly concentrated in health and social work, hotels and restaurants and education. However, the share of males and females engaged in undeclared work is equal (Purju et al 2004 as referred by Leetmaa and Võrk, 2007).
45 Leetmaa, R., Võrk, A. (2007) Article on Undeclared Work from SYSDEM Correspondent. (Update of EEO Review: Autumn 2004) European Employment Observatory , May 2007.
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Unemployment
The unemployment rate has been significantly lower in Tartu compared to the national average (Figure 10). It decreased with the economic growth and reached its lowest level in 2007 (3.1% in Tartu compared to 4.7% as the national average). The unemployment rate in Tartu increased to 11.7% (10.8% for women); the national average accordingly 13.8% (10.6% for women) during the economic recession – data from 2009. The unemployment for women and men continued to increase after the economic recession and reached 17.3% in 2010.
Figure 10. Unemployment rate, national and city level and by gender, age group 15-69, %. Source: Database of Statistics Estonia
According to Statistics Estonia, the number of long-term unemployed persons increased rapidly in 2010. In 2009, 26,000 unemployed had been looking for job for one year or longer, but two times more in 2010 – 53,000 unemployed persons. The number of discouraged persons did not change during the year. 9,000 persons had stopped seeking a job because they did not expect to find one. According to the estimations based on the data of Estonian Labor Force Survey (2010) the share of discouraged persons is higher among men (3.1% of men in working age) than among women (1.7%). In case of Tartu city, the discouraged persons are mainly women, but the share is almost twice lower than that on the country level – 0.8% of women in working age in Tartu city can be identified as discouraged persons.
Temporary work
According to data of the Statistics Estonia, there were 4.2 thousand enterprises in Estonia with at least one employee having a temporary /fixed contract (24% of the enterprises) – slightly more women (7%) than men (6.3%) in 2009 (Table 2). More often (61%) they were the state and local governmental agencies (61%) and non-profit associations and foundations (34%).
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Table 2. The enterprises by contract type, Estonia (N; %)
At least 1 employee has temporary/ fixed date /oral contract
No employees with temporary/ fixed-date / oral contract
Number of enterprises in thousands 4.2 13.1 Proportion in different companies (%)
Companies 19.3 80.7 Non-profit associations and foundations 34.1 65.9 State and local government agencies 61.4 38.6
Source: Statistics Estonia database
Self-employment
One specific group of self-employed persons are entrepreneurs, according to the data of Statistics Estonia in year 2004 about 54,300 persons have identified themselves as self-employed, out of them 31% were women.
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3. Most important transformations affecting the supply of female employment over last two decades
Changes on educational levels
Over the years a slight trend towards feminisation of the tertiary education can be mentioned in Estonia while men choose more often the after-compulsory vocational education or training (among the graduates 53% were males in 2007 – Leetmaa, 200846). According to Statistics Estonia (Figure 11), there are more women than men admitted to all levels of the tertiary studies. The success rate of completion of the tertiary education for women has increased by about ten percentage points for the bachelor’s and master’s level and a remarkable increase has taken place on the doctoral level (from 11.5% in 1995 to 46.3% in 2009). The latter shows the widening choices for women in their professional horizons and higher resistance to economic shocks in the society. The studies have confirmed that higher educated people are more resistant to unemployment, or the duration of unemployment is shorter than for those with lower levels of education.
Figure 11. Percentage of female students admitted to the tertiary education, 1995–2009 Source: Database of Statistics Estonia
The educational choices in Estonia have been clearly gender stereotyped however, there are slight changes towards desegregation, at least on the tertiary level. For example, women more often than earlier choose traditional males’ specialities, e.g. natural sciences, ITC, finance while the female dominated specialities are unchangeably still humanities and social sciences.
46 Leetmaa, R. (M. Karu and K. Nurmela research assistance) (2008). Gender segregation in the labour market: root causes, implications and policy responses in Estonia. http://www.fgb-egge.it/
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Transformations in cultural attitudes
The distribution of housework in families in Estonia is traditional: women do the majority of the daily, routine and time-consuming housework in families with two parents and children under 18 years. Men are mostly responsible for activities related to car and repair works, which are not everyday activities, and these works are often purchased as services. However, the Monitoring reported changes in traditional gender stereotypes, e.g. it revealed that compared to the previous Gender equality monitoring in 200547, the attitudes of the respondents have become more positive concerning men’s participation in traditional female-dominated sectors, like health and social affairs, and also men being more active in child rising and childcare. The change of attitudes allows assuming that the informal family work of women has taken a decreasing trend. The men’s involvement in child care has also increased – the share of men among parents, who have stayed on parental leave and receive the parental benefit, has increased from 1.6% in 2005 to 7.3% in 2010 (Social Insurance Board 2011)48. Also general attitude towards men’s and women’s equal opportunities on labour market has increased (Kasearu 2011)49
Changes in the family structure
In Estonia, among younger age groups the proportion of unmarried unions has increased quite rapidly since the independence was regained in 1991 (Kasearu 2010). In Estonia the cohabitation unions are more marriage-like: cohabiting couples have more likely children compared to the other European countries (Kasearu & Kutsar 2011). This is illustrated also by the fact that in 2010 only about 41% of children were born to married parents (see Figure 12).
47 Soolise võrdõiguslikkuse monitooring 2009. Sotsiaalministeeriumi toimetised nr 1/2010 48 Estonian National Social Insurance Board (2011) http://www.ensib.ee/vanemahuvitised/ 49 Kasearu, K. (2011). Meeste ja naiste võrdne õigus tööle – põlvkondade erinevad hoiakud Euroopa riikides. In Sooline ebavõrdsus tööelus: arengud Eestis ja rahvusvaheline võrdlus. O. Toomet, M. Ainsaar (Eds.). Tartu Ülikool working paper: http://www.sh.ut.ee/orb.aw/class=file/action=preview/id=1001899/Innove+Raport+I_kogumik.pdf
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Tota
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1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Total fertility rate Marital births, %
Figure 12 Total fertility rate and the percentage of births within marriage, 1990-2010. Source: Database of Statistics Estonia
In the beginning of the 1990s the fertility rate decreased quite rapidly and reached its lowest position in 1998. This trend can be explained as a postponement effect and as a reaction to the changing societal system50. Since 2003 we can witness an increase in the number of births. The postponement of giving babies to birth is clearly visible also in the mean age of mothers at childbirth. In 1990 the mean age of mothers at the first childbirth was 22.7 years; in 2010 it had increased to 26.3 years. This means, that mostly the women have some employment experience before the birth of the first child. In case of Tartu city, during the last decade the number of births has increased very rapidly; compared to 2000 the number of births increased 1.3 times by the year 2010. This has caused a shortage of places in the public child care institutions and put the decision-makers to look for solutions. As a policy response, the Tartu municipality supports diversification of preschool institutions (see the last paragraph of the report).
Estonia is a country, where the proportion of single-mother families has been one of the highest in Europe - according to the census data from 2000. In the age group 20–44, 29% of women were single parents (e.g. in Finland 17.9%)51. However, on the basis of the Estonian Household Budget Survey, the number of lone-parent households has decreased from 32 thousand in 2001 to 24 thousand in 2007.
50 Klesment, M., Puur, A., Valge, J. (2010). Childbearing and macro-economic trends in Estonia in the 20th century. Tallinn: Eesti Kõrgkoolidevaheline Demouuringute Keskus 51 Sobotka, T., Toulemon, L. (2008). Changing family and partnership behaviour: common trends and persistent diversity across Europe. Demographic Research, 19, 85-138.
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Hous
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In 2007 the proportion of lone-parent families among households with children was 14% (Sinisaar & Tammpuu 2009)52.
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Figure 13. The number of households and the proportion of households with children, 2000-2007 and 2010.
52 Sinisaar, E., Tammpuu, P. (2009). Ühe vanemage pered: probleemid, vajadused ja poliitikameetmed. Poliitikaanalüüs. Sotsiaalministeeriumi toimetised nr 4/2009.
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1. Impact of the economic-financial crisis on female and male a) employment; b) unemployment; c) participation in the labour
market
The report “Minifacts about Estonia 2011” of Statistics Estonia states that due to the economic crisis the situation on the labour market has changed rapidly. The financial crisis reached to Estonia in 2008, and generally saying it impacted more men than women. The situation on the labor market improved since the 2nd quarter 2010. The number of unemployed persons, which rose to record high 137,000 persons in the 1st quarter 2010, decreased in the following quarters. In the 4th quarter, the unemployed persons numbered less than 100,000 and the unemployment decreased compared both to the previous quarter as well as to the same quarter of the previous year. During the year the unemployment declined, but in 2010 the annual average number of the unemployed was still the largest during the period after the restoration of independence in Estonia (Statistics Estonia 2011).
Men have been more vulnerable than women
To be more precise, in situation of economic crises, the men were more vulnerable than women facing the unemployment risks. For instance, the labour force participation of men decreased and unemployment increased by 2009 2nd quarter being 6.9 percent points higher than that of women. Unemployment has hit the male-dominated sector activities (e.g. construction – 91% of workers were men in 2009) more than the female dominated sector activities (e.g. education and public administration where over 80% are female labour force). The construction was also the activity that went through the biggest increase during the economic growth in the 2000s with the highest number of the created male work places. In the top of the economy in 2007 and 2008, 22% of male labour force had concentrated in the construction sub-sector while only 2.4% of the female labour force. By 2010, the drop in the construction was six percentage points for males and around one for females (Table 3 in Annex).
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Figure 12. Labour force participation rate by gender, 1995–2010 Source: Database of Statistics Estonia
To explain the described trends above, the specific feature for Estonia has been the average education level of men not exceeding the average level of women. During the economic shock, namely lower educated people were put to test. Besides the educational factor, the reactions of the economic structures such as construction and manufactirung being male-dominated and now loosing the labour demand impacted the male employment. Moreover, the decrease of the male labour force demand has decreased also due to the overall structural changes (e.g. the tertiary sector coming to the forth) and development of technologies freeing the human hands. New technologies have not invaded that strongly to the sectors that traditionally are female dominated like the public and services sectors thus the loss in female labour force cannot be the issue here.
According to Tartu county data, the labour force participation rate of women dropped by 3.1 percentage points from 2006 to 2010 (Figure 12). The same trend started in case of men in 2008 and the decline was by 2.7 percentage points. If the latter can be related to the financial-economic crisis, this cannot be said about women, and other factors can be found here. We are not able to give the alternative explanations because of the smallness of the ELF sample.
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2. Impact of economic transformations on the income gap between men and women
The economic growth in Estonia has been accompanied by increasing levels of gross incomes of the population. In the nominal value this was impressive and concerned all income groups. According to calculations of Tiit (2010), during the seven years from the last quarter of 2000 to the last quarter of 2007 the average gross wages and salaries rose 2.3 times in nominal value (about 13% per year). The average real wages and salaries grew about 7% a year during the six years (from the 4th quarter of 2001 to the 4th quarter of 2007). The incomes continued growing also in 2008 and due to the economic recession, dropped in 2009 by 4.4% as the Estonian average. In Tartu city the income decrease was by 5% for men (for EE-males – 5.4%) and 2.5% for women (for EE-females – 2.5%) (Figure). According to data, the incomes dropped in case of both genders but it was smaller in women.
Fi gure 13. Average monthly gross income per employer in euros, 2003-2009. Source: Database of Statistics Estonia
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The gross monthly income levels of men and women are compared with the national average on the Figure 13. Over the years, the gross income of women has been lower than that of men. Logically, it has been lower of the national average, as well. The gender pay-gap widened over the years and reached the top in 2008 together with the flourishing economy. Paradoxically, referring to Masso (2010)53, already in 2005, gender pay-gap in the top income decile had remarkably widened: if the female salaries formed 74.6% of the male ones as an average in 2005, and in the lowest decile the respective percentage was 87.3, then in the top decile this formed only 69.8%. In Tartu similar pattern can be noticed however, the pay-gap is not that wide.
The monthly gross income in Tartu city has been slightly higher than the national average over the years, and this concerns both genders (Figure 14). The economic backlash produced a decrease in the incomes for both genders thus also making the pay-gap narrower. If the gender pay-gap for Estonia was 251 euros and 228 euros for Tartu city in 2008, then the respective numbers in 2010 were 217 euros and 199 euros respectively. The pay-gap shortened by 14% on the national level and by 13% in case of Tartu city.
Figure 14. Differences between average monthly gross incomes of men and women, 2003–2009, EUR Source: Database of Statistics Estonia
Estonia shows stably the highest gender pay gap among the EU-27. The gender pay gap is caused by several factors, e.g., horizontal and vertical segregation of jobs; paternalistic mindset of the population supported by traditional stereotypes of men and women; self-censorship of women in political and career aspirations, etc.. The critical analyses have shown that started from early education, boys and girls are directed towards separate choices which feed the occupational segregation. (The explanation is based on Estonian Gender Equality Monitoring 2005; 2009).
53 Masso, M. (2010). Mehed ja naised tööelus [Men and women in work life]. Teel tasakaalustatud ühiskonna poole. Naised ja mehed Eestis II. Tallinn: Sotsiaalministeerium: 26–39.
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3. Horizontal and vertical sex segregation Horizontal segregation
Horizontal segregation refers to the extent to which men and women are concentrated in different occupations and in different sectors. Similarly to the other developed countries, men and women in Estonia are also employed in different sectors and fields of activity and occupations. The EU report “Gender segregation in the labour market: root causes, implications and policy responses in the EU” (15/10/2009) refers to Estonia as to the highest horizontally gender-segregated country in the EU, where the IP index54 has a value of 32.2.
Although the labour force is formed by men and women quite equally, both the occupational choices as well as the labour demand are gender-typed and the labour market is horizontally and vertically clearly segregated. As said before, female labour force is more concentrated in the tertiary economic sector and the sector itself has grown since 1995. According to 2010, the female labour forms over 80% in education, and in health and social work services; over 70% in accommodation and goods services; over 60% in arts, entertainment and recreation, financial and insurance activities, real estate activities, wholesale and retail trade; repair of motor vehicles and motorcycles, and over 50% in public administration and defence, compulsory social security; professional, scientific and technical activities. The female labour has a low representation in some economic activities of the secondary sector that in general has gone through a slight decline since 1995. Namely the female labour forms 43% in manufacturing, 25% in electricity, gas, steam and air conditioning supply and less represented in the rest activities. Female labour covers stably about a third in the primary sector over the years (Table 3 in Annex).
There are very few occupations which can be said to be more or less equal in terms of gender segregation. There are also no signs of significant feminization or masculinization of economic sectors. Instead, in relative terms several fields have gained more female labour force, e.g. in financial and insurance activities, real estate activities, professional, scientific and technical activities, administrative and support service activities, public administration and defence, compulsory social security (15, 10, 10, 8 and 6 percentage points accordingly in 2005–2010) while in education and human health and social work activities it has stabilised on a high level and these fields are the most feminized. (Table 3 in Annex).
54 IP index (standardised or Karmel and MacLachlan index) ranges from 0 in the case of complete equality to twice the male share of employment multiplied by the female share in the case of complete dissimilarity. In percentage terms, the absolute maximum for the index is 50 and it is reached when there are as many women as men in employment working in completely segregated occupations/ sectors.
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Vertical segregation
Vertical segregation is the most acknowledged gender specific problem in Estonia. The main reason for that is the significant difference in the wages of men and women resulting in the widest gender pay gap in Europe. There are several studies and research reports about gender pay gap and vertical segregation in Estonia available from the recent years (Rõõm, Kallaste 200455; Viies 200656; Vöörmann 200857, Gender Equality Monitoring 200958, etc). The studies have revealed the differences in gross salaries of men and women, especially concerning the youngest categories of employed, and also in the case of employed with the tertiary education. The factors related to different human and social capital of men and women (different education level, difference in working hours, different length of the career) explain only about one third of the gender pay gap and the rest still needs more clarification, according to estimates of Kallaste and Rõõm (2004).
Vöörmann (2005) basing on data of a longitudinal survey claimed that in the beginning of the 1990s males were slightly more overrepresented among managers (14% of males and 11% of females in 1993). By late 2000s the proportion of females in the highest level occupations has decreased and the proportion of males has increased. In 2007 (Leetmaa 2008) only 37.5% of legislators, senior officials and managers were females and the gender division differs across the management levels. The Statistics of Estonia (2006) shows that the share of females in age range 25–64 years was lower among directors and chief executives (only above 20%) and the highest among other department managers (47%) which include human resource managers, sales managers, marketing managers, etc, in 2005.
According to calculations of Leetmaa (2008), only 11.4% of craft and related trade workers were female. This is an occupation which occupies 30% of males and only 3.6% of females and the gender gap in this occupation has significantly increased over the years as in 1997 the share of females in the occupation was 24%. Although the share of female plant and machine operators and assemblers has increased in 10 years significantly to a one third in 2007 compared to 16% in 1997, it is still one of the most masculine occupations in Estonia. The most feminized occupation in 2007 was service workers as 82% of employees in this occupation were female. The next most feminized occupations were clerks and professionals with 77.6% and 71.5% of females. (p.6).
According to Murakas (2011)59, the share of women among managers in Tartu city has grown, being one of the most significant changes in the overall picture of managers here.
55 Ka lla ste , E., Rõõm, T. (2004) Naised-mehed Eesti tööturul: palgaerinevuste hinnang [Men and women on the labour market: estimation of the wage gap]. - Poliitikauuringute Keskus PRAXIS, Poliitikaanalüüs, 200 4, nr 8 56 Viies, M. (2006) Gender pay gap. In: Women and Men. Tallinn: Statistics Estonia, 2006: 88-91. 57 V öörma n n , Rein (2008). Horizontal and vertical gender segregation in the Estonian labour market. Irina Novikova (Ed.). Gender Matters in the Baltics. University of Latvia Press: 93-108 58 Soolise võrdõiguslikkuse monitooring 2009. Sotsiaalministeeriumi toimetised nr 1/2010 59 Murakas, R., toim (2011) Tartu ettevõtlus 2010: sotsioloogilise uuringu kokkuvõte [Entrepreneurship in Tartu 2010]. Tartu: TÜ SHSS.
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Public and private sector
The proportion of women in the public sector has decreased over the years, being 44.1% in 1995 and 36.9% in 2010. In Tartu county, over the years women saved slightly higher representation in the public sector compared to the national level, being 57.3% in 1995 and 43.5% in 2010 (Figure 15).
Figure 16. Proportion of employed in the public sector, 1995–2010 Source: Database of Statistics Estonia
Earnings in comparison
Interestingly if the gross salaries of males and females serving in different sectors are compared with the national average gross salary level then in all activities where males form over 50% of the labour force the average salaries by sectors exceed the national average while in case of women, only three activity fields where females are overrepresented overreached the average level in 2009. These were financial and insurance activities – by 679 euros (68% are females in this activity sector); professional, scientific and technical activities – by 131 euros (59% are females); public administration and defence, compulsory social security – by 197 euros (59% are females). From the total female labour force they form one fifth.
In human health and social work activities the salaries are just above the national average by 43 euros and in education 79 euros below the average while the female overrepresentation here is the highest forming one fourth of the whole female population in labour force. In the female-dominated accommodation and food service activities the salaries depart from the average the most being 270 euros less than the national average.
On Figure 16 gross hourly earnings of full-time and part-time employees by gender, national and Tartu county in 2007 are presented. The picture is quite complicated for one-way explanation as being
29
impacted by the occupational structure especially in Tallinn (the capital with higher concentration of high officials dominated by men and representing the high income group) and Tartu (with higher concentration of professionals again male dominated with not that high level of the hourly rates). Another problem is that data for Tartu are given on the county level which may following the economic structure differences between the county and the city make the bias in the hourly rates.
Figure 16. Gross hourly earnings of full-time and part-time employees, by gender, national and Tartu county, 2007. Source: Database of Statistics Estonia.
Explanations of horizontal and vertical segregation
Horizontal segregation lays on different factors: gender stereotypes concerning ‘suitable’ occupations and/ or educational standards for men and women, access to education and education system in general, prospects for reconciliation of work and family life, etc. The Estonia gender equality monitoring in 2005 gives evidence about traditional perceptions of ‘men’s and women’s occupations’. First of all, occupations requiring physical strength and technical capacity – transport worker, plumber, taxi-driver, and salesperson in building material store – are associated with men. Being a manager was also assessed as masculine work, but definitely in a production company but not in ‘soft’ economic activity (e.g. head of the basic school). A woman, on another hand, is a person taking care of somebody (e.g., kindergarten teacher), creating or dealing with beauty (florist, hairdresser).
Estonia is doing well with access to education of women, and the average educational level is higher for women compared to men. Even if women are not as many as men among the PhD holders and university professors and men start dropping out of the educational system on the general compulsory level, women’s potentials that their high human capital uncovers are not adequately applied here and
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one can witness horizontal segregation of the labour market by gender (women dominate in lower paid sectors and men in the higher paid ones).
The EU report “Gender segregation in the labour market: root causes, implications and policy responses in the EU” (15/10/2009) gives evidence about interconnections between horizontal segregation on the labour market and educational segregation. The report declares (p.42): “Over time, and for EU-15 countries only, de-segregation of education clearly associates with de-segregation in employment (and conversely). While this finding conforms to expectations, it is not repeated for central and east European countries, where the distribution of women and men across fields of education has recently become more balanced – with the exception of Romania, Estonia and the Czech Republic – without this showing up in the distribution in employment. Moreover, inspection of levels of segregation across countries does not reveal a clear tendency for more dissimilar educational choices to be matched by more dissimilar occupational structures. Perhaps the main reason for this patchy evidence is that the choice of field matters for a limited number of occupations and is therefore easily obscured by other factors at aggregate level”.
The study (RISC 2008) has revealed that 86% of the population believe that ensuring economic security of the family is the obligation of a father and 71% of respondents consider that women are happier if they can dedicate themselves entirely on family and children. The Gender Equality Monitoring 2009 reveals that only 48% of women and 40% of men find women as suitable for the position of top managers.
The issue of horizontal segregation in Estonia is less acknowledged compared with the vertical segregation. The low interest towards this topic could be explained by above described gender stereotypes (it is natural that men and women are occupied in different and for them ‘most suitable’ fields) and/ or belief that occupational segregation is less harmful compared to widespread differences in pay. The occupations constructed as masculine or feminine are determined by the masculine normative values that are deeply seated in people’s minds, including women. However, the authorities accept that horizontal and vertical segregation are interrelated and gendered segmentation of the labour market leads to unequal opportunities and differences in outcomes.
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4. Forms of local coordination of the labour market (approx 2000 words) Typology of employment contracts
The employment relationship is governed by the Employment Contracts Act in the private sector and the Public Service Act in the public sector. On 1 July 2009, a new Employment Contracts Act was due to take effect, which is expected to modernize the legal context of employment relations.
The employment contract is regularly made for an unspecified period. A fixed-term employment contract may be made for up to five years if it is justified by good reasons arising from the temporary fixed-term characteristics of the work, especially a temporary increase in work volume or performance of seasonal work.
In general there are three types of employment contracts: the employment contract (included in public service and regulated by the Public Service Act); contract of agreement (fixed-term); and the verbal contract.
According to Statistics Estonia in 2010, majority of the labour was employed by the employment contract (97.2% of men and 98.6% of women), and this has been an increasing trend from 2003 when the respective proportions were 94.9% and 97.2%. Working on contract of agreement is slightly more spread among women (0.8%) than men (0.7%) in 2010 while women working on verbal contracts are less (0.6% against 2.2% for men in 2010) compared to men.
Regarding the work regulation in the public administration and in the private companies, the slight differences emerge, namely in state and local government agencies about 8.8% of employees work by temporary or fixed-date contract compared to 6% in private companies. However, the highest proportions of employees working on temporary contracts are in the non-profit associations and foundations. According to the occupation, 10% of senior officials and professionals work by temporary or fixed-date contracts. (Table 3)
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Table 3. Employees by type of contracts (total number of employees and %) in 2009.
Number of employees, thousands
Work by termless contract, contract of service (incl. public service), %
Work by temporary or fixed-date contract or by oral contract or agreement, %
Employees total 484,2 93,3 6,7 Type of employer Employees of companies 375,2 94 6 Employees of non-profit associations and foundations
22,6
89,9
10,1
Employees of state and local government agencies 86,4 91,2 8,8 Type of sector Employees of enterprises of primary sector 11 96,6 .. Employees of enterprises of secondary sector 155,5 97,6 2,4 Employees of enterprises of tertiary sector 317,7 91,1 8,9 Group of occupation Senior officials and professionals 125,4 89,8 10,2 Associate professionals and clerks 105,6 93,9 6,1 Service workers and shop and market sales workers 65 93,8 .. Skilled agricultural and fishery workers, and other craft and related trades workers
65,2
95,5
4,5
Plant and machine operators and assemblers 72,4 98,9 .. Elementary occupations, armed forces 50,6 89,3 10,7 By age groups Employees aged 15-24 47,5 91,6 8,4 Employees aged 25-49 279,2 93,3 6,7 Employees aged 50-64 134,3 94,9 5,1 Employees aged 65-74 and older By NUTS2 Employees of enterprises of Southern Estonia
23,1
98,9
88,6
97
11,4
3 Source: Database of Statistics Estonia.
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Unionization
According to Eurostat, the trade union density (union members as percentage of all employees in dependent employment) was 7.6% in Estonia(LFS-2007). The employer organisation density (percentage of employees employed by companies who are members of an employer organisation) was 25% (estimate of the Estonian Employers’ Confederation *Eesti Tööandjate Keskliit, ETK+. ETK is the only employer organisation recognised for the purpose of tripartite consultations. Thus, only its membership data are taken into account here.)
This is also reflected in the membership data of the largest trade union confederations. There are two nationally recognized trade unions in Estonia, which in broad terms are divided between blue-collar and white-collar workers. Although a notable membership increase is found among some occupations, such as seafarers, the general trend is still declining. This is mostly explained by the mass redundancies in some economic sectors with high trade union membership, particularly manufacturing.
The Estonian Employees’ Unions’ Confederation *Teenistujate Ametiliitude Keskorganisatsioon, TALO+ is the second largest trade union organization in Estonia. TALO mostly represents educational and cultural workers and public servants, with 11 affiliates and 13,009 members in 2007, compared with 16,536 members in 2005.
In general, trade union density has shown a continuously decreasing trend in Estonia. According to the Labour Force Survey trade union membership has declined from 11.1% in 2003 to 7.6% in 2007, but the data from year 2009 show a minor increase again – 10.7%. This increase could be the result of economic crisis, which highlighted the importance of belonging to the trade union. According to the data from 2009, there is no difference between men and women in unionization, but the share of members has increases by age (see Table 4). Belonging to the trade union is related to the type of employer, namely one third of employees working in non-profit associations and foundations are the members of trade union, compared to 8% of employees of private companies and 17% of the state and local government agencies. Regarding the occupational groups, the proportion of trade union members is the highest among skilled agricultural workers and plant and machine operators and assemblers.
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Table 4. Groups of employees by membership of trade union (N and %) in 2009
Belongs to a trade unions
Does not belong to trade unions
Number of employees in thousands
Share of employees (total=100), % 10,7 89,3 484,2 Type of employer Employees of companies 8,1 91,9 375,2 Employees of non-profit associations and foundations 31,4 68,6 22,6 Employees of state and local government agencies 16,7 83,3 86,4 Type of sector Employees of enterprises of primary sector .. 95,2 11 Employees of enterprises of secondary sector 7,5 92,5 155,5 Employees of enterprises of tertiary sector 12,5 87,5 317,7 Group of occupation Senior officials and professionals 14 86 125,4 Associate professionals and clerks 8 92 105,6 Service workers and shop and market sales workers 8,2 91,8 65 Skilled agricultural and fishery workers, and other craft and related trades workers
10,4
89,6
65,2
Plant and machine operators and assemblers 14,2 85,8 72,4 Elementary occupations, armed forces 6,9 93,1 50,6 By gender Male employees 10,2 89,8 226,2 Female employees 11,2 88,8 258 By age groups Employees aged 15-24 .. 96,1 47,5 Employees aged 25-49 9,3 90,7 279,2 Employees aged 50-64 15,7 84,3 134,3 Employees aged 65-74 and older 12,4 87,6 23,1 By NUTS2 Employees of enterprises of Southern Estonia 10,3 89,7 98,9
Source: Database of Statistics Estonia
Social protection
We do not have the employment-specific measures addressed to different employee categories. According to social status there are universal measures (e.g. family benefits, benefits for disabled, etc), no exclusion by gender.
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Minimum wage or salary
Minimum wage or salary in 2011 is 1.73 euros per hour and if working full-time, the minimum wage is 278.02 euros per month that has stayed unchanged from 2008.Together with Latvia, Lithuania, Romania, Bulgaria and Hungary, Estonia belongs to country group with the lowest minimum wage in the EU. However, if compared to 1999, the minumim wage has gone through a tremendous increase when it was 80.32 euros per month, according to Statistics Estonia.
Parental benefit
The parental benefit, instituted on 1 January 2004, is a type of benefit that depends on the recipient’s income and declared taxes in the preceding year (not the current level of income) and is governed by the Parental Benefit Act. The aim of the Parental Benefit Act is to retain the previous level of income of the parent whose income would otherwise decrease due to raising children and, to support parents in balancing their work and family lives. Consequently, the parental benefit is a substitute for income in case of forced absence from work. However, it is important to note that a parent will receive the parental benefit even if he or she continues to work, but in this case the amount of the parental benefit is reduced in proportion to the income earned by the particular recipient of the parental benefit. As the parental benefit is also paid to parents who have never been employed before, it cannot be seen as a substitute for income in their case but rather as a measure for securing a certain level of income, thus not being employment-related. (Kreitzberg et al, 2010).
Other aspects that are related to the working conditions
According to Labour Force Survey, the average number of working hours has decreased for both genders. With reference to calculations made by Masso (2010)60, the average number of working hours in 2001 was 42.9 for men and 41 for women; in 2008 the respective numbers were 41.6 and 40.2 accordingly. Although the difference between the genders is not big (1 hr and 24 min in 2008), men are used to longer working weeks than women: 7.4% of men and 1.9% women worked more than 49 hours per week in 2008. Also the working strain is higher for men than for women and is related to gender occupational segregation (e.g the work strain in women is more related to communication activities (with clients, patients, travellers, students, etc) while in case of men this is more connected to organisation of work, like production aims, control, and management activities, specific aspects of working with machines, etc. (Masso, 2010).
During last ten years working on irregular times has generally decreased however, still women more often than men work in the evenings (after 6 p.m.) and on weekends. In 2008 15.2% of men and 17.6% of women worked at least half of the days in the evenings (from 6–12 p.m.); 15% of men and 18.4% of women worked on Saturdays; 10% of men and 12% of women worked on Sundays. In case of night shifts there are more men than women working – 10% against 12% of females (data from 2008, see: Masso, 2010). Masso also adds that gender differences in organisation of work are impacted by social and
60 Masso, M. (2010). Mehed ja naised tööelus [Men and women in work life]. Teel tasakaalustatud ühiskonna poole. Naised ja mehed Eestis II. Tallinn: Sotsiaalministeerium: 26–39.
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power relations in work relations. According to him and basing on working conditions survey, 59% of men and 66% of women in 2005 claimed missing opportunity to change the working time. This is related to gender occupational segregation – women are employed in the sectors where they have less to say by regulation of the working time and the work schedule is declared by the employer and also with gender stereotypes (men working longer hours; on high posts, etc); and reconciliation of family and work in case of women (working less hours, at irregular time, etc).
From the point of view of the occupational health, men and women take different positions as well. According to Masso (2010) and basing on data from 2005, men more often suffer from occupational accidents while women fall ill caused by work conditions: 42% of men and 34% of women declared dangers putting their health at risk at work, and 21% of men and 52% of women by their self- assessments never meet physical, chemical or biological dangers at their work place. To conclude, men face direct dangers to their health, women have to cope with more hidden health risks.
Unemployment benefit
Social protection associated with unemployment is secured through unemployment insurance and through labour market services and benefits. While unemployment insurance creates social security for persons who have previously been employed and have recently left employment for some reason, the labour market services and benefits are designed to help people who have been away from the labour market for a shorter or longer period, as well as those entering the labour market for the first time (incl. young people who have recently finished their studies as a separate risk group).
Persons who have been employed or engaged in an activity equal to work for at least 180 days during the twelve months prior to registration as unemployed and who have no income in the extent of the unemployment allowance have the right to receive the unemployment benefit. The unemployment benefit is payable for up to 270 calendar days and it is not paid concurrently with the unemployment insurance benefit. The amount of the unemployment benefit was very low (25.56 euros per month) for many years, but it was increased to 63.91 euros per month in 2007. However, this amount is subject to income tax 21% (58.79 euros after the income tax) (Kreitzberg et al 2010)61.
Unemployment insurance benefit
Unemployment insurance is a type of compulsory insurance, based on the principle of solidarity, the purpose of which is to provide, upon unemployment, partial compensation for the lost income to insured persons for the time of search for work. The Unemployment Insurance Act entered into force on 1 January 2002.
The purpose of the unemployment insurance benefit is to compensate the unemployed persons for the loss of income to the extent specified by the law. The amount of the benefit depends on the previous remuneration of the recipient. For the first hundred days, the amount is 50% of previous remuneration
61 Kreitzberg, M., Mäe, Ü., Reinomägi, A. (2010). Social protection as a means to alleviate poverty in Estonia. In: Kutsar, D., ed. Poverty in Estonia. Tallinn: Statistics Estonia: 172–191.
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and then, from day 101 to day 360, it is 40% of previous remuneration. Period, for how long the benefit is paid, depends on the insurance period.
During the time of unemployment, the substitute income is low. Payment of unemployment insurance benefit in case of unemployment (the average unemployment insurance benefit is 22–24% of the maximum amount of the benefit) does not constitute a significant contribution towards reduction of poverty associated with unemployment; it only offers some relief. For the reason of women’s lower average salaries’ level, they also receive proportionally less of the unemployment insurance benefit. (Kreitzberg et al 2010).
Maternal / care leaves
Maternity leave: at 100% of earnings with no ceiling. If the leave is taken less than 30 days before the expected birth the leave is shortened accordingly. Taking leave is obligatory.
Paternity leave: 10 working days of unpaid leave.
Parental leave: until 3 years after childbirth paid at 100% of earnings for 62 weeks with a ceiling of 3 times average earnings (1,965 euros per month in 2009). A low flat-rate payment (38.50 euros per month) as a childcare benefit is paid from the end of the parental benefit until the child reaches 3 years of age to all parents, whether on leave, employed or neither.
Leave to care for sick children: 14 days of leave can be taken by either parent for each episode of sickness of a child under 12 years at 100% of pay
Other: Mother with a child under 18 months can take feeding breaks every 3 hours at 100% of pay but this is not paid to mothers who receive parental benefit. (Excerpt from short overview of Karu & Pall 200962).
Actions supporting female employment in Tartu city
Basing on personal communication with a current candidate to the vice-major of Tartu on social issues, the major support addressed to women employment concerns activities helping them by reconciliation of work and home responsibilities. In the situation of a shortage of places in municipal pre-school institutions, the political decision has made to support diversity of pre-school institutions and cover partly (in the county region fully) the difference in price. Also parents with low income are supported partly or fully by paying for the kindergarten place.
62 Karu, M., Pall, K. (2009). Estonia: halfway from the Soviet Union to the Nordic countries. – S. B. Kamerman, P. Moss (eds). The Politics of Parental Leave Policies. Bristol: The Policy Press, pp 69–85.
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CONCLUSION
In general, the changes in the production system in Tartu city have been in favour of women however have been cementing the gender occupational segregation. The tertiary sector has been spreading in Tartu (traditionally where women are employed) and this particular sector has been less vulnerable to the economic recession (the recession hit more the masculine sectors like construction). Women profit from their higher educational levels compared to men that helps them to bolster the impacts of the economic reconstruction.
The main economic sectors in a good shape in Tartu city, according to the survey of enterprises (Murakas 2011)63, are education and research (52% of the survey respondents agreed), medicine (47%), and culture (36%) – all these uncovering positive employment challenges for women. Concerning the vertical segregation, there are positive changes towards women increasing the numbers as female managers.
In terms of the equal pay, women are disfavoured and receive less than men on the national as well as on the city level. They also have less to say by determining the working conditions.
63 Murakas, R., toim (2011) Tartu ettevõtlus 2010: sotsioloogilise uuringu kokkuvõte [Entrepreneurship in Tartu 2010]. Tartu: TÜ SHSS.
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ANNEX
List of tables:
Table 1. Enterprises by economic activity, 2000-2010, N (Tartu city) Table 2. Change of economic activity, 1995–2010, % (national) Table 3. Change of economic activity by gender, 1990–2010, % (national) Table 4. Average monthly gross wages (salaries), euros Table 5. Average monthly gross wages (salaries), euros
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Table 5. Enterprises by economic activity, 2000-2010, N (Tartu city)
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Economic activities total 3470 3749 3802 3992 4275 4665 5194 5723 5816 6064 7354
Agriculture, forestry and fishing 248 271 127 116 125 139 124 117 131 148 232
Mining and quarrying 2 3 3 3 2 5 5 6 8 8 10
Manufacturing 368 388 354 376 389 439 458 485 447 440 504
Electricity, gas, steam and air conditioning supply 3 4 6 5 6 7 7 8 6 9 11
Water supply; sewerage, waste management and remediation activities
7
7
6
8
13
11
14
16
20
18
24
Construction 196 210 240 259 352 462 606 891 774 736 742
Wholesale and retail trade; repair of motor vehicles and motorcycles
1352
1347
1305
1381
1420
1408
1506
1299
1265
1305
1446
Transportation and storage 151 228 484 485 504 554 591 703 699 690 674
Accommodation and food service activities 109 121 132 128 137 139 140 142 163 174 203
Information and communication 96 132 135 146 160 183 198 225 262 296 367
Financial and insurance activities 32 31 32 29 35 41 44 60 78 68 79
Real estate activities 244 265 263 261 271 312 377 405 462 496 594
Professional, scientific and technical activities 342 396 382 415 452 522 614 730 814 878 1101
Administrative and support service activities 97 98 106 111 131 146 176 245 253 282 342
Public administration and defence; compulsory social security
0
0
0
0
0
0
0
0
0
0
0
Education 55 51 39 39 44 49 61 71 74 77 150
Human health and social work activities 61 62 71 87 93 97 106 117 134 142 206
Arts, entertainment and recreation 26 31 27 36 35 39 43 56 71 85 245
Other service activities 81 104 90 107 106 112 124 147 155 212 424
Activities of households as employers; goods and services production for own use
0
0
0
0
0
0
0
0
0
0
0
Activities of extraterritorial organisations and bodies 0 0 0 0 0 0 0 0 0 0 0
Source: Database of Statistics Estonia
41
Table 6. Change of economic activity, 1995–2010, % (national)
1995 1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Agriculture, forestry and fishing
10,3
9,9
9,4
9
8,1
7,1
6,9
6,9
6,2
5,8
5,2
4,8
4,6
3,9
4
4,2
Mining and quarrying
1,6
1,5
1,1
1,2
1,4
1,3
1
1
1
1,3
1
0,8
0,8
0,9
1,1
1,2 Manufacturing
24,9
23,9
21,7
21,5
21,2
22,3
22,5
21,5
22
23,1
22,3
20,6
20
20,6
19,1
19
Electricity, gas, steam and air conditioning supply
1,8
1,9
2,2
2,2
2,2
2
1,5
1,3
1,3
1,6
1,8
1,7
1,3
1,2
1,3
1,5
Water supply; sewerage, waste management and remediation activities
0,5
0,6
0,7
0,6
0,7
0,7
0,6
0,6
0,8
0,9
0,7
0,3
0,3
0,4
0,4
0,4
Construction
5,6
5,9
7,5
7,6
7
7,1
6,7
6,8
7,4
8
8
9,8
12,5
12,3
9,8
8,4 Wholesale and retail trade; repair of motor vehicles and motorcycles
12,5
13,2
13,6
13,7
13,6
13,5
14,3
14,4
13,4
13,2
13,2
13,6
13,3
14,1
14
14
Transportation and storage
9,1
9,1
8,3
8,3
9,4
9
8,4
8,9
8,9
7,8
8,1
8,7
8,1
7,6
8,3
7,6
Accommodation and food service activities
2,6
2,7
2,3
2,3
2,3
3,5
3,1
3,1
3
2,7
3,4
3,4
3,4
3,6
3,4
3,4
Information and communication
1,7
1,8
1,9
1,8
1,7
2,1
2,4
2,1
1,8
2,2
2,4
2,4
2,1
2,3
2,4
2,2
Financial and insurance activities
1,1
1,1
1,2
1,4
1,5
1,4
1,3
1,4
1,3
1,3
1,1
1,2
1,4
1,6
1,9
1,7
Real estate activities
1,8
1,7
1,5
1,9
1,9
1,9
1,8
2,3
2,1
1,7
1,7
1,6
1,5
1,6
1,5
1,8 Professional, scientific and technical activities
2,2
2,2
2,6
2,7
2,8
3,1
2,3
1,8
2,6
2,3
2,6
2,7
2,7
3,1
3,4
3,7
Administrative and support service activities
1,2
1,3
1,4
1,6
1,9
2
2,3
2,6
2,5
2,4
2,9
2,4
2,8
2,6
2,8
3,3
Public administration and defence, compulsory social security
5,4
5,3
5,5
5,9
6,1
6,2
6,3
5,9
6
6,3
6,2
6,2
6
5,8
6,2
7,1
Education
8,7
8,9
9,4
9,1
8,9
8,1
9
9,7
9,5
9,2
9,1
9,1
8,4
9,1
10,5
9,8
Human health and social work activities
5,4
5,5
5,7
5,5
5,2
4,8
5,2
5,3
5,8
6
5,5
5,6
5,5
4,7
5,5
6,1 Arts, entertainment and recreation
2,5
2,4
2,4
2,3
2,5
2,5
2,5
2,6
2,8
2,5
2,5
2,8
2,7
2,3
2,4
2,6
Other activities
1,2
1,3
1,5
1,5
1,6
1,6
1,8
1,6
1,6
1,8
2,3
2,3
2,6
2,3
1,9
2,1
Source: Database of Statistics Estonia
42
Table 7. Change of economic activity by gender, 1990–2010, % (national) % of males occupied in a sector % of females occupied in a sector % of females in a sector
1990 1995 2000 2005 2010 1990 1995 2000 2005 2010 1990 1995 2000 2005 2010 Economic activities total 100 100 100 100 100 100 100 100 100 100 48,4 48,3 49,2 50,5 51,8 Agriculture, forestry and fishing 24,7 12,7 9,7 7,1 5,8 14,1 7,7 4,5 3,3 2,8 34,8 36,3 30,8 32,3 34,0 Mining and quarrying 2,1 2,6 2 1,8 2 0,6 .. 0,6 .. .. 20,7 .. 21,6 .. … Manufacturing 24,5 27 24,5 23,6 22,5 26,8 22,5 19,9 21 15,7 50,6 43,7 44,0 47,6 42,8 Electricity, gas, steam and air conditioning supply
2,1
2,3
2,9
2,8
2,4
1,2
..
1
0,8
0,8
34,3
…
24,8
22,4
25,3
Water supply; sewerage, waste management and remediation activities
..
..
0,7
0,9
0,6
..
..
0,6
..
..
…
…
44,7
…
…
Construction 13,4 9,3 12,7 14,8 16,2 3 1,6 1,3 1,4 1,1 17,1 13,9 9,1 8,8 6,9 Wholesale and retail trade; repair of motor vehicles and motorcycles
4
10
11,2
10,7
11
11,5
15,2
15,9
15,5
16,8
72,9
58,7
57,9
59,7
62,1
Transportation and storage 11,2 12 12,3 12 11,3 4,1 6 5,6 4,3 4,2 25,5 31,8 30,6 27,0 28,4 Accommodation and food service activities
1,3
..
1,5
1,5
1,8
3,6
4,1
5,6
5,3
4,9
72,0
…
78,5
78,5
74,2
Information and communication 1,5 1,8 2 2,9 3 1,3 1,7 2,1 2 1,4 45,7 46,8 50,0 41,6 33,9 Financial and insurance activities .. .. 1,3 .. 1,1 1 .. 1,5 1,9 2,2 … … 53,8 … 68,4 Real estate activities 0,7 1,7 1,8 1,6 1,4 1,1 1,8 1,9 1,7 2,1 58,9 49,5 51,4 51,5 61,0 Professional, scientific and technical activities
2,3
2
2,6
2,7
3,2
2,8
2,3
3,5
2,6
4,2
53,4
51,8
56,0
49,1
59,0
Administrative and support service activities
..
1,5
2,4
3,8
3,9
0,7
..
1,6
1,9
2,7
…
…
38,6
34,5
42,3
Public administration and defence, compulsory social security
3,3
6,3
5,8
5,8
6
3,8
4,4
6,6
6,6
8,1
52,1
39,5
52,7
53,7
59,4
Education 3,2 3,5 2,7 3,1 3,3 13 14,2 13,6 15 15,9 79,2 79,2 82,7 83,2 83,8 Human health and social work activities 1,4 1,6 1 1,5 1,7 7 9,5 8,6 9,5 10,1 82,8 84,5 89,0 86,8 86,7 Arts, entertainment and recreation 1,2 2,3 1,8 1,6 1,8 2 2,7 3,2 3,3 3,3 60,4 53,2 63,6 67,3 66,0 Other activities 1,9 .. 1 1,4 1,1 2,3 1,9 2,3 3,2 3 53,8 … 68,1 69,5 75,6
Source: Database of Statistics Estonia
43
Table 8. Average monthly gross wages (salaries), euros
2009 Average monthly gross wages (salaries), euros
Average of economic activities 783,81 Agriculture, forestry and fishing 633,36 Mining and quarrying 881,85 Manufacturing 716,71 Electricity, gas, steam and air conditioning supply 1058,12 Water supply; sewerage, waste management and remediation activities
818,07
Construction 773,59 Wholesale and retail trade; Repair of motor vehicles and motorcycles 734,47 Transportation and storage 801,52 Accommodation and food service activities 514,42 Information and communication 1282,20 Financial and insurance activities 1462,36 Real estate activities 631,96 Professional, scientific and technical activities 915,09 Administrative and support service activities 713,70 Public administration and defence;compulsory social security 980,85 Education 704,82 Human health and social work activities 827,02 Arts, entertainment and recreation 613,23 Other service activities 553,92
Source: Database of Statistics Estonia
Table 9. Average monthly gross wages (salaries), euros Average monthly gross wages
(salaries), euros Average monthly net wages (salaries), euros
Whole country Tartu county Whole country Tartu county 2000 313,6 266,3 245,5 209,4 2001 352,2 303,3 276,7 240,5 2002 392,7 346,6 304,8 270,7 2003 429,7 384,7 330,8 297,6 2004 465,7 426,9 362,7 332,9 2005 516,0 487,3 411,0 388,3 2006 601,2 580,8 484,0 466,9 2007 724,5 715,3 583,1 575,5 2008 825,2 810,1 670,0 657,4 2009 783,8 749,4 636,9 608,4 Note: Employees with an employment contract, a service contract and working under the Public Service Act are included. Source: Database of Statistics Estonia
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