75443 State Planning Organization of the Republic of Turkey and World Bank Welfare and Social Policy Analytical Work Program Working Paper Number 2: Recent Trends in Female Labor Force Participation in Turkey Arzu Uraz The World Bank Meltem Aran Oxford University & The World Bank Müşerref Hüsamoğlu State Planning Organization, Republic of Turkey Dilek Okkalı Şanalmış State Planning Organization, Republic of Turkey Sinem Çapar State Planning Organization, Republic of Turkey Ankara, March 2010 State Planning Organization of the Republic of Turkey and World Bank Welfare and Social Policy Analytical Work Program Working Paper Number 2: Recent Trends in Female Labor Force Participation in Turkey Arzu Uraz The World Bank Meltem Aran Oxford University & The World Bank Müşerref Hüsamoğlu State Planning Organization, Republic of Turkey Dilek Okkalı Şanalmış State Planning Organization, Republic of Turkey Sinem Çapar State Planning Organization, Republic of Turkey Ankara, March 2010 Recent Trends in Female Labor Force Participation in Turkey iii Recent Trends in Female Labor Force Participation in Turkey Table of Contents Abstract..................................................................................................................................................................... v 1. Introduction......................................................................................................................................................... 1 2. Data and Methodology........................................................................................................................................ 2 3. Overall Levels of Female Labor Force Participation in Turkey......................................................................... 3 4. “Life Events� and Participation in the Labor Market......................................................................................... 7 5. Multivariate Analysis on the Probability of Working for Women...................................................................... 9 6. Conclusion. .......................................................................................................................................................... 13 Annex-Tables............................................................................................................................................................ 15 Annex-1. .................................................................................................................................................................... 18 Annex-2. .................................................................................................................................................................... 20 References................................................................................................................................................................. 22 Recent Trends in Female Labor Force Participation in Turkey v Abstract The female labor force participation level in Turkey is currently very low at 27% compared with the OECD and EU-19 averages of 61 and 64% respectively. This rate has been declining in the last 30 years from a level of 48% in 1980. This paper looks at the most recent trends and profiles of labor force participation of women in Turkey using three different household level data sources in available Turkey (HBS, LFS and TDHS) for the period 2003-2006. The paper also reports a multivatiate analysis on the probability of working for women, controlling for various characteristics. This paper constitutes part of a collaborative analytical work program between the World Bank and the Turkey State Planning Organization. The findings of this paper have been previously presented at the Welfare and Social Policy Conference organized these institutions in Ankara on October 22, 2008. The findings and statements in this research paper are the responsibility of the authors and do not reflect the official views of their respective institutions. The authors would like to thank Jesko Hentschel, Diego Angel-Urdinola, Francisco Ferreira, Maria Beatriz Orlando and Maria Laura Sanchez Puerta for their valuable comments during the conference and in the process of writing this paper. Recent Trends in Female Labor Force Participation in Turkey 1 1. Introduction Figure 1: Female Labor Force Participation in Turkey has Declined Significantly Over Time (Changes between 1980 – 2006) 1. Turkey has low and declining levels of female labor force participation with only about one-in- four women in the working age population being active in the labor market as of 2006. With 26.7% participation rate, Turkey has the lowest female labor force participation among OECD and EU-19 countries, where the averages are 61% and 64% respectively as 1980 of 2007. When Turkey is compared to a sample of 62 countries from the World Development Indicators, that includes many comparable developing countries, the result stays the same: Turkey has the 5th lowest level of female labor force participation: there are only 4 countries in the WDI data that have lower levels of female participation than Turkey and these are: Saudi Arabia, Egypt, Oman and Morocco. Even countries that historically report low levels of participation such as the Islamic Republic of Iran, Pakistan, Syria and Libya are currently reporting higher levels on this indicator when compared to Turkey. Again, according to the WDI 2008, female labor force participation rate (28%) for Turkey in 2006 was recorded below the 2006 averages of the Latin America and Caribbean (53%) and East Asia and Pacific (66%) regions. 2. Turkey did not have such low levels of participation for women 30 years ago. In 1980, Turkey was comparable in terms of its female labor force participation rate with the Netherlands, Austria, Australia and Switzerland (in the same WDI sample Source: WDI 2008 and Authors’ calculations of 62 countries) with 48.3% of women in working age group participating in the labor force. Figure 1 4. Previously, there have been a number of studies provides a scatter plot of female and male labor force on female labor force participation in Turkey. In participation rates for all countries available in the some studies (See Kasnakoglu and Dayioglu, 2002), WDI dataset for 1980 and 2006. The horizontal lines the main driving force for women to participate is on Figure 1 show the levels of participation for women stated as the market wage level being below the in Turkey. The countries below the horizontal line are reservation wage level of women in Turkey, which the ones that have lower rates of female labor force corresponds to the total value of home production participation in the sample when compared to Turkey. for women. Some of these economic studies (See Kasnakoglu and Dayioglu, 1997) have also argued 3. Understanding the falling trend in female labor that wage differences among genders are keeping participation requires looking at the recent trends women out of the labor market. Some other studies and changes in the labor profiles of women in (See Alkan, 1995; Ozar and Günlük-Şenesen, 1998; Turkey. This paper considers the most recent profile Eyuboglu et al, 2000; Erman, 2001; Kasnakoglu and of female labor force using available datasets at the Dayioglu, 2002; Gunduz-Hosgor and Smits, 2006; household level between the years 2003 and 2006. Pancaroglu, 2006) have focused on the social roles The current profiles and changes for the given period of women in determining women’s decision on labor are identified for various groups by education level, market participation. A considerable number of papers work status, type and sector of employment. (See Erman, 1998; Kocak, 1999; World Bank, 2000, Recent Trends in Female Labor Force Participation in Turkey 2 2004; Gunduz-Hosgor and Smits, 2006; SPO, 2007; Survey (LFS) 2003-2006 (ii) Turkey Household Turkonfed, 2007) have emphasized that migration Budget Survey (HBS) 2003-2006 and (iii) Turkey from rural to urban areas has been a determinant in the Demographic and Health Survey (2003). declining trend in female labor force participation in Turkey. Among the new urban migrants, women from 7. The Labor Force Survey provides information rural areas who worked previously as unpaid family on the structure of the labor force in the country. In workers, become unemployed or unable to participate this paper, the LFS is used for reporting changes in in the urban labor market. Other important factors that participation rates as well as the profiles by sector and determine women’s labor force participation are found type of employment. The quarterly sample size for the as early exit, child care (See Ozar and Günlük-Şenesen, LFS is 37,000 households and yearly estimates for 1998; Dayioglu, 2000; Pancaroglu, 2006). Dayioglu Turkey are provided at the rural-urban, NUTS 1 levels (2000) has evidenced that especially the presence of making this the largest and most reliable dataset for young children negatively affects the participation reporting labor force statistics in Turkey. In this paper decision of women. we use 4 years of the LFS dataset: between 2003 and 2006. 5. This paper aims to look at the changing profiles of women’s labor force participation between 2003 8. Household Budget Survey (HBS) is the data and 2006 in light of the literature presented. The source used for the measurement of consumption and contributions of this paper are the comprehensive poverty statistics in Turkey. In 2003, HBS had 25,764 look at trends over several consecutive years; and the households in the sample and provided regional multivariate structural analysis over several years. The estimations at the NUTS-1 level. In the following years, data available from household level surveys is analyzed the survey size was reduced to 8,640 households and for levels and trends in female labor force participation provided estimations at the national as well as urban in this time period taking a closer look at the profiles and rural levels in Turkey.1 The earnings data collected of women’s activity in the labor market over time. by HBS is more detailed and more reliable than the Following the introduction, Section-2 provides the LFS. Therefore, for the analyses related to earnings in data sources for the paper. Section-3 analyzes changes this paper we use HBS,2 whereas for employment and in labor force participation of women (between 2003 labor force statistics we revert to LFS datasets. The and 2006) and considers profiles of participation by HBS data set is also used in this paper for the 4 years education levels, employment categories and sectors. of data available: 2003-2006. This section also briefly analyzes earnings differentials between men and women in Turkey by education levels. 9. The Turkey Demographic Health Survey (TDHS), Section-4 focuses on the potential effects of various conducted by Hacettepe University Institute for “life events� such as marriage, pregnancy, childbirth Population Studies, is used as the third data source in and migration on labor force participation. This is this paper. We use the most recent data available from followed in Section-5 by a more detailed multivariate this survey at the time of publication, which comes from analysis, where the probability of a woman working is 2003. The reason why we utilize the TDHS survey is interacted with explanatory variables in the previous that it not only provides one cross-section of data but sections. Finally, Section-6 concludes by stating the has very rich information (in the ever-married women main findings of the paper. module) on background variables for the women 2. Data and Methodology ‘interviewed such as fertility, husband’s background, region and place of birth, migration as well as some 6. The paper builds on three different household social and cultural values proxy variables. We use this level data sources: (i) Turkey Household Labor Force data set in Section 5 and 6 of this paper. 1 TUİK, Official Statistics Program 2007-2011, pp.24 2 Since the main purpose of the HLFS is to provide labor force statistics, income and wage statistics will be derived from the HBS as it is specifically designed to collect income and expenditure of households. The new series (ILO definition adopted) started with the October 1988 survey. In 2004, number of questions in the LFS increased from 47 to 98, but there was not any change regarding the definition of the variables used in this study. Sampling design of the HLFS includes a three-month period (quarters) and monthly field implementation. Sample design is contracted on yearly basis. Yearly estimates of the whole of Turkey, rural-urban, SRE (Classification of Statistical Region Units. SRE-1 level has 12 region units, SRE-2 has 26 sub-region units) level 1 (urban-rural) and SRE level 2 are provided. Recent Trends in Female Labor Force Participation in Turkey 3 10. The analyses regarding profiles and changes in accompanied in the same time period by an increase in female labor are produced through cross-tabulations the percentage of discouraged female workers in the derived from the “ADePT Labor3� software program, population from 0.6% to 4.6% (See Table 1). which creates standard tables and graphs of labor markets. In order to run the program successfully, Table 1: Hierarchical Decomposition of Working-Age Population by Gender (2003-2006) certain variables were used to produce the tables (For detailed definitions of each variable used in the software see Annex 1). 11. Two data constraints are important to note here in terms of the analysis: The first is that we limit our analysis to the years 2003 and 2006 as these are the years for which comparable household level data sets are available from TUIK. Secondly, all data used in this paper is cross-sectional nature as in Turkey there is not yet a panel data set available that would allow us to carry out a more dynamic analysis on the changes in the labor market for women. It is worthwhile to keep these data constraints in mind while reading through Source: ADePT Labor results, LFS 2003-2006 and Authors’ calculations the next sections. 14. Informality remains high in women’s 12. Regarding the compatibility of the TDHS and employment in Turkey with 66% of female LFS, we are aware that the employment question in employment being unregistered employment TDHS asks the women if she has worked in the last (compared to 34% for men). The proportion of month, whereas the reference period for the respective women employed informally has come down from question in LFS is the last week. For deriving labor 71% in 2003 to 66% in 2006, following closely the statistics we conducted all our analyses on LFS. We decline in the percentage of unpaid family workers conducted the multivariate analyses on the probability (See Table 2). As of 2003, 48.3% of women employed of women being active by using the TDHS, since the in Turkey were employed as unpaid family workers. In survey provided detailed information on women’s and 2006, this level has declined by 10 percentage points, husband background, and also socio-cultural values. down to 38.3%. In the same time period, the proportion 3. Overall Levels of Female Labor of women employed informally has also come down Force Participation in Turkey as a result of such a large reduction in the percentage of women working as unpaid family workers, and an 13. Only about 1-in-4 women in Turkey in the increase in registered workers that does not match up to working age population are currently active in this reduction in scale: The percentage of women who the labor market. As of 2006, 26.7% of women work as registered regular employees has increased in in the working age group were active in the labor this time period by 5 percentage points, from 27.4% market and only about 23.9% of them were actually to 31.9 %. The net effect of the reduction in the employed. The decline in the level of female number of unpaid family workers in the economy has participation, which was outlined in Figure 1 in been a reduction in the total proportion of informality the introduction, still continues to this day and the for female workers but an overall reduction in total detailed analysis of labor force data between 2003 employment has also followed this decrease. and 2006 show that the percentage of active female population in the labor market has declined from 15. Unpaid family workers, who are mostly employ- 28.1% in 2003 to 26.7% in 2006. This trend has been ed in agricultural enterprises of their households, 3 The program has been developed by Michael Lokshin, Sergiy Radyakin and Zurab Sajaia in the Development Economics Unit of the World Bank, under the guidance of Michael Ravallion. For more information on the ADEPT software please visit http://econ.worldbank.org/programs/poverty/ adept 4 Based on the International Labor Organization (ILO) definition. In addition to TUİK definitions please see ILO definitions on employment in Annex-2. Recent Trends in Female Labor Force Participation in Turkey 4 still make up the largest category of working women Table 3: Distribution of the Female Employed by Economic in Turkey and the agricultural sector remains the Sector largest employer of women. Of the women active in the labor force, 47% are employed in the agricultural sector and of these 74% are employed as unpaid family workers as of 2006. In fact, the trend in the percentage of women’s employment in the agricultural sector follows very closely the trend in the percentage of women who work as unpaid family workers. From 2003 to 2006, there is a 9.8 percentage point decline in the proportion of women in the agricultural sector going down from 57% of the labor force to about 47% (see Table 3). Services5 and manufacturing follow as the second (37.4%) and third (14.6%) largest sectors for employing women in 2006. Table 2: Employment Categories, Shares in Female Employment Source: ADePT Labor results, LFS 2003-2006 and Authors’ calculations 17. In fact, the reduction in the share of the labor force working in the agricultural sector (and also as unpaid family workers) in recent years, has gone hand in hand with the overall reduction of female labor force participation. Overall employment in the agricultural sector has shrunk in Turkey from 2003 to 2006 by 5.3 percent per annum. The proportion of Source: ADePT Labor results, LFS 2003-2006 and Authors’ calculations the labor force in agriculture is lower for men in 2003 (at around 23%) than for women (at 47%), therefore 16. Table 3 provides the distribution of the female the reduction in the proportion of men in agriculture employed by sector between 2003 and 2006 where as a result of the shrinking employment in the sector we observe the rapid reduction in female employment is much less pronounced. The net outflow of women in agriculture in these years and the 8.4% rise in away from agriculture in this time period is about employment (as a percentage of the total) in the 563,000 women while the number for men in the services sector. While it seems from the data below, same situation is about 400,000. The overall decline in that there may have been a shift in employment in female labor force participation in Turkey in this time agriculture into services, when we look at absolute period is 1.4% of the total working age population. The levels of employment and labor force participation, net outflow from agriculture is 3.2% of the total active we observe that those leaving the agricultural sector female population while there are slight increases are likely to not be fully absorbed into other sectors of observed in the employment proportion of the other employment.6 sectors (1.6% in services and 0.2% in manufacturing). 5 According to the 9 code division of sectors, services sector cover wholesale retail trade, restaurants and hotels, transportation, communication and storage, financial intermediation, real estate, renting and business activities, public and government services, education, health and social work, community services. 6 It is also important to note here that given the cross-sectional nature of the datasets, it is only possible to speak about the net changes in employment across sectors rather than flows from one sector to the other. Recent Trends in Female Labor Force Participation in Turkey 5 The differences in the net flow by sector signals that ages of 25-44) in urban areas who are illiterate or the female workers leaving the agricultural sector have have not completed primary school is less than 9% not been absorbed into other sectors in the same speed, while this level increases to 32% for those who have therefore reducing the level of total participation in the completed secondary school and to 80% for those who overall working age group. have completed university education. Those women in urban areas who are illiterate or have no formal 18. Low female labor force participation is the case schooling, also have the lowest levels of participation in urban areas more so than rural areas in Turkey. in the labor market. This may be a function of the Urban women at working age have lower labor jobs available for these women and the pay associated participation rates (21.4%) than rural women (35.8%). with these jobs. In this analysis it is only possible to By age groups, women in the 18-29 year age group say that in some economic or psychological way, the in urban areas are the most active in the labor market “opportunity cost� of working is higher for these low- with participation being still low at around 30%.7 skilled women than the returns they would receive in After that the participation of women in urban areas the labor market. This being said, it is also possible declines further (See Figure 2). It is also observed that to say that, given that 73.7% of women in urban areas the difference between the labor force participation of (above the age of 15) are low-skilled and mostly females in urban and rural areas becomes wider after inactive, integrating these women into the labor the age of 29; and narrower after age of 60. In the market would significantly increase the current levels same analysis, male labor force participation does not of female labor force participation. substantially differ across urban and rural for young men up to the age of 45, but falls sharply for urban 20. The participation issue related to high-skilled men after that age. women in urban Turkey is one of early-exit from the labor market. While the labor force participation rate of university educated women in urban areas Figure 2: Female Participation in the labor force is low particularly in urban areas is high around 80% between the ages of 25-44, this (Labor force participation rates by gender, age group and level is reduced in half (down to around 40%) for the urban rural areas) 45-54 year old group.8 We observe a certain decline in the participation levels of women who have only completed primary school or secondary school after age 45, but the decline in their participation levels is nowhere as steep as the one for women with tertiary degrees. For illiterate women with no schooling, overall levels of participation is low as mentioned previously, but these women actually stay in the labor market until a later age. This is likely to be a function of low social security coverage for this group, and their need to work under conditions of poverty rather than a desire to work in old age. 19. Labor force participation, especially in 21. In rural areas, education does not factor so urban areas, is strongly associated with levels much into labor force participation decisions. of educational attainment of women and low There is less variation in rural areas in terms of levels labor force participation is more common of educational attainment among women, with 38% among low-skilled urban women in Turkey. of women in rural areas having no diploma and 43% The overall labor activity of women (between the of women having only completed primary school. 7 The cross-sectional analysis presented here does not take into consideration the cohort effects that may be present. Cohort effects help assess changes in participation by age groups and allow tracking the successive cohorts. The labor participation trend of age groups shown in Figure-2 does not show the successive cohorts. 8 Given that this analysis only makes use of cross-sectional data, it is not possible to comment here on cohort effects and whether younger generations of women are also going to be exhibiting early exit from the labor market. Changes to social security and pension law is expected to postpone the age of exit from the labor market of these high-skilled women in the future. In the current regime, still a women having served for 20 years would be entitled for pension. Recent Trends in Female Labor Force Participation in Turkey 6 These women, nevertheless, participate in the labor up 16% of the employed population in the working market in rural areas: in fact, 90% of the employment age group of women, up from 13% in 2003, while in the agricultural sector is by such women who have this group constitutes only around 7% of the overall completed primary school or less. Thus, we can say working age-population. that women with low levels of education are deterred from entering the labor market only in urban areas. Table 4: Distribution of the Female Employed by Level of Education Figure 3: Female Labor Force Participation in Urban Areas change by Level of Education and Age, 2006 Source: LFS 2006, Authors’ calculations 22. For the male population, not having any formal education or having low levels of education is not a deterrent in entering the labor market both in urban and rural areas in Turkey. In urban areas, in Source: LFS 2003, 2004, 2005 and 2006 the 25-49 year old group, 74% of illiterate men with no schooling are active in the labor market, compared 24. There is a large gap in hourly earnings for low to 91% of primary school graduates and 94% and skilled men and women in Turkey, though this gap 95% of secondary school and university graduates is not observable for highly skilled workers. The respectively. The difference between the participation hourly earnings for low-skilled men in urban areas is rates of men across different levels of educational 1.4-1.5 times that of hourly mean earnings for women, attainment is certainly not as striking in urban areas while for high-skilled men and women in urban areas as it is for women. Similar to women, however, men the difference in hourly wages is negligible (See Figure start exiting the labor market after age 45 and this fall 4). In rural areas, the picture in terms of earnings for is common across all educational groups. low-skilled women is not that different, where again there is a large wage differential between men and 23. The levels of education for women closely follow women in low-skilled jobs. As of 2006, a man in a the sectors of employment, with women in the low-skilled job in rural areas made 1.64 times the agricultural sector having lower levels of education. hourly wage of a woman in a similar job.9 The average years of schooling for women working in the agricultural sector is only around five years and 25. One reason for low female labor force 1-in-3 women who work in the agricultural sector is participation of women in urban areas, may be either illiterate or has not completed primary school. the low earnings potential of available jobs for In contrast, women working in the non-agricultural women with low skills. Given that most women sector have higher levels of education. In fact, close working in rural areas are already unpaid family to 70% of women in the non-agricultural sector hold workers, earnings circumstances in rural areas secondary education (38%) or university degrees likely impact the decision to supply labor less (30%). Women who hold university degrees make than in urban areas. Another factor that needs to be 9 It is important to note here that these comparisons are only crosstabs with cross-sectional data, and in order to measure proper gender disparities in earnings, one would need to use more detailed earnings equations, controlling for more factors. Recent Trends in Female Labor Force Participation in Turkey 7 considered is the opportunity cost of working in urban same age group who are currently not working, 32% and rural areas. If in urban areas, the opportunity cost “do not have a job and are looking for a job�, 28% are of working for women is high (with low availability of “retired� and 12% are “handicapped/sick or too old to day-care options for children, and the inability to share work�. responsibility with extended family on household chores), then it is likely that women whose earnings 27. Running the same analysis for women in are low would choose to stay home rather than take different categories, by urban and rural and by low-paid jobs. In other words, the earnings potential levels of educational attainment we get similar for low-skilled women in urban areas might not be results. Even among highly-skilled urban women “high enough� in Turkey to justify them to leave home (where highly-skilled is defined as holding a secondary for work. These hypotheses would need to be analyzed school or university degree), we see that 59% of further with qualitative data. those who are currently not working report “being a housewife� or “taking care of children� as the reason 4. “Life Events� and Participation in for not working. the Labor Market 28. This being said, the labor force participation 26. In the DHS ever-married women sample, women of women in high-skilled and low-skilled groups who are currently not working (and who are between responds differently to specific life events. Figure the ages of 20-65) overwhelmingly state “being a 5 provides a rough chronology of events that take housewife� or taking care of children as being the place in a woman’s life starting from being single main reason for not working. Of the women in the (never married), to being married with no children or working age group, who have ever been married, 58% pregnancies, to the first pregnancy and then the birth state being a housewife as a reason for not working, of respective children. The women in the sample are while 9% state “taking care of children� as the reason separated into urban high-skilled, urban low-skilled for not working. Only 6% of those who are currently and rural groups and their probability of working is not working are looking for a job, hence indicating analyzed separately. Due to the cross-section nature of the low rate of “undesired� unemployment among data, the analysis does not correct for cohort effects women (See Table 5). For men in the same age but provides a snap-shot picture of the current working group, the story is quite different: of the men in the status of women having experienced these life events. Figure 4: Mean Hourly Real Wages (by gender skill-level and urban/rural) 4.0 Urban Rural 4.0 3.5 3.5 3.0 3.0 2.5 2.5 male high-skilled 2.0 2.0 female high-skilled 1.5 1.5 male low-skilled 1.0 1.0 female low-skilled 0.5 0.5 0.0 0.0 2003 2004 2005 2006 2003 2004 2005 2006 Source: Household Budget Survey, (2003-2006). In this analysis, high skilled is defined as having a secondary school diploma or higher. 29. The probability of working for high-skilled words, marriage and the first pregnancy does not women in urban areas increases until the birth seem to be have a negative association with labor of the first child, and then declines afterwards. force participation of such women at the onset of their Whereas a highly-skilled woman in an urban area career and married life. What is interesting is that right who has never been married before, works 43% after the birth of their first child, the likelihood of of the time, a married woman in the same category these highly-skilled women to be working drops by 15 works 54% of the time before her first pregnancy and percentage points down to 41% and does not recover 56% of the time during her first pregnancy. In other again in consequent years (see Figure 5). Recent Trends in Female Labor Force Participation in Turkey 8 Table 5: Main reasons for not working women in Turkey as a result of migration, and another third report their husband’s family not approving of their work participation as the main reason for quitting. In rural areas, the number of women who quit work are much less significant than in urban areas, yet in rural areas these two reasons for quitting work after marriage also prevail. Figure 5: Chronology of life events and the probability of working for women (for women ages 20-65)10 Source: TDHS 2003 30. On the other hand, for low-skilled women in urban areas the probability of participation is around 32% (for married women with no children) and declines significantly down to 15% during their first pregnancy. Their participation rate never quite recovers from that level and only about 1 in 5 low- Source data: Turkey DHS 2003 skilled women in urban areas with children continue Figure 6: Labor Force Participation for women by migration to work. The situation is different in rural areas: while status and educational attainment (for women ages 20-45 during their pregnancy, the women in rural areas also only) reduce their supply of labor (likely as a result of the nature of physical work required in agriculture), but then recovers after the birth of the first child (See again Figure 5). The existence of children in rural areas does not hinder women from continuing to work around the family farm or within the village. This result, which is also supported by the multivariate analysis in the next section, may be a function of the availability of care by other women and relatives in the extended households in rural areas. 31. The subcategory of women who worked before marriage, but quit working afterwards is an interesting category for analysis given that there is a large change Source data: TDHS 2003 in labor force participation following marriage. The DHS survey has a question targeting particularly these 32. While migration11 seems to be an important women, and asking for their reasons for quitting work reason that hinders women’s labor force after they got married. In urban areas, the women participation, the negative association between who quit working after marriage list “having moved migration from rural areas and labor force or migrated� as one of the top reasons for having participation disappears when controlling for stopped working. Another important reason quoted for educational attainment of women. The DHS data quitting work after marriage in urban areas, is that the allows us to look at the birth place of a woman and husband’s family does not allow the woman to work. her current place of residence. Figure 6, provides About a third of women report quitting after marriage information on labor force participation of 3 different 10 There are no observations in the data set for urban low skilled never-married women, hence the analysis of urban low skilled women does not include this category. 11 For more on the effects of migration please see Dayioglu and Kirdar (2009), Ozden mimo. (2008) and Angel-Urdinola (2009). Recent Trends in Female Labor Force Participation in Turkey 9 categories of women according to their migration last month� or “usually working� or “currently looking status from rural to urban areas: (i) those who were for a job�. The results of the two probit regressions are born in rural areas and are currently still living in rural very similar and the explanation below is provided for areas, (ii) those who were born in rural areas but are Panel A. currently living in urban areas, (ii) those born in urban areas and are currently living in urban areas.12 The 34. All explanatory variables in the regression are women who were born in rural areas and stayed there expressed as dummy variables and the coefficients (denoted by the green line) have relatively higher labor reported in the regression represent the change in the force participation when compared to the other groups probability of working (dF/dx) for a discrete change of women in all education categories except for higher of the explanatory variables from 0 to 1. The sample education. Women in urban areas, whether they were in this model comes from the ever-married women born in rural areas or urban areas before have very questionnaire in TDHS 2003 data. This survey has a similar levels of labor force participation – at around sample of 8,075 ever-married women at age 15-49. The 20% for women with primary school degree or less and multivariate analysis is carried out for 3 different sub- around 28% for women with secondary school degrees. samples of the survey and the whole sample separately. Women who were born in rural areas but moved to The results are presented in Table 6 Panel A and B in urban areas later, and who hold a university degree, the following 4 columns: Column (1) reports results interestingly have higher labor force participation for highly skilled women in urban areas, column (2) than women with same educational classifications but for low skilled women in urban areas, Column (3) for were born in urban areas.13 Therefore, one can say women in rural areas and Column (4) for all women that migration status to urban areas is not associated in the sample. The explanatory variables in the probit with lower labor force participation for women, when analysis can be categorized as (i) background variables education levels are controlled for. This statement is (such as place of birth, mother tongue spoken at first also confirmed in the next section when we control for home and current place of residence), (ii) education more characteristics of these women in the multivariate variables for the woman and her husband, (iii) wealth analysis. status of household derived from the household assets index and (iv) household composition, pregnancy 5. Multivariate Analysis on the status and number of children in household (v) cultural Probability of Working for Women and social proxies for traditional family values. The results are presented as follows: 33. The multivariate analysis provided in this section looks at the correlates of female labor force 35. Urban/Rural Place of Residence: The urban/ participation in Turkey. The analysis is run twice rural divide in terms of female labor force participation for two different dependent variables: the analysis in is quite strongly pronounced again in the multivariate Table 6 panel A takes the probability of “working� analysis controlling for other characteristics. In the for a woman as the dependent variable and runs a overall sample, the probability of a woman working probit model for the probability of this variable going is lower by 31% in urban areas when compared with from 0 to 1. The definition of working is given by the rural areas. combination of the variables in DHS that ask “whether the woman has worked in the past month� or “if she 36. Birth region: The provinces in Turkey are divided usually works�. In Table 6 Panel B the dependent into 3 major regions for this analysis East, Central and variable is the probability of participating in the labor West (the Mediterranean and the Black Sea regions force, defined in the same way as the dependent variable are included in the Central part of the country). The for working but also adding those who are currently category that is dropped from the regression is Eastern looking for a job as participating in the labor force. Turkey and the other two regions are compared to Thus, the dependent variable in the probit regressions this region. In the overall sample, the women born in Table 6 Panel B is defined as: “having worked in the in Eastern provinces have the lowest likelihood of 12 In this analysis, we did not look at women born in urban areas and are currently living in rural areas as this was a very small subgroup in the sample. 13 Note that this may be due to selection: for women who come out of rural areas and choose to go to university may also be more interested to pursue a career. Recent Trends in Female Labor Force Participation in Turkey 10 working. Those who were born in central provinces are is a very small percentage of the total sample, the 5% more likely, and those who were born in western coefficient is still statistically significant. From this provinces are 10% more likely to have worked in the analysis, it is possible to conclude that while a higher past month when compared to women born in eastern education degree is associated with a strong jump in provinces (controlling for all other factors such as the probability of working, lower levels of education education level). This being said, in rural areas, and and even a secondary school degree, does not increase among women in urban areas with high skills, the birth the likelihood of working for a woman in Turkey when region does not make a difference in the probability compared to the group with no formal education. of working controlling for all else. 40. Husband’s education: The husband’s level of 37. Urban/Rural Place of Birth: In the overall education in Turkey, is associated with a decline in sample, controlling for current place of residence, the probability of working for women in the overall urban or rural place of birth does not make a difference sample, this association is particularly strong in the in the probability of working for women. Surprisingly, sample of women in urban areas who are low-skilled. for urban highly skilled women, coming from a rural For high-skilled women in urban areas, their husband’s background is even associated with an increase in level of education is not a significant factor. For these the probability of working by about 10%. This is an women, only their own level of education matters in interesting finding that even more strongly confirms the probability of participating in the labor force. For the statement made in Figure 6 where controlling rural women, once again, the husband’s education for education levels, migration to urban areas is not does not take on a statistically significant coefficient. associated with a decline in women’s labor force However, for urban low-skilled women, the probability participation. of working is lower, the higher the level of education of the husband. This result implies that in urban areas 38. Mother Tongue: The mother tongue variable is when the education level of the husband increases setup as a dummy variable that takes on the value of (and perhaps he is able to maintain a certain standard 1 if Turkish was the primary language spoken in the woman’s first household. This variable takes on no of living for the family) the woman’s probability of significant value in these regressions in any of the sub- working decreases if she has a low level of education. categories or in the overall sample. This finding is also consistent with the coefficients on the wealth index which we discuss next. 39. Own education: The education variables are defined in 4 categories in this analysis. The first 41. Wealth quintile: The wealth quintiles in the category is “being illiterate or having no diploma from analysis are constructed using the Filmer-Pritchett primary school�. This category is dropped out of the asset index in the DHS survey. The asset index is regression and all other categories are compared to this already constructed in raw DHS dataset using the lowest level of education. In the overall sample, having durable goods in the household and certain household a primary school degree (5 years of education) is not characteristics. The poorest quintile in this set-up associated with higher probability of working, while is Wealth Quintile 1 and this is the category that is having a secondary school degree is associated with a dropped from the regression. In the overall sample, 11%, and having a university degree is associated with increased wealth quintiles is associated with lower a 48% increase in the probability of working when levels of female labor force participation. A woman compared to women with no diploma. In urban areas, in the highest wealth quintile in terms of the assets among high skilled women (which only includes the index, is 13.1% less likely to be working as a woman secondary school and university graduates), having a in the lowest quintile. This is a counter-intuitive university degree is associated with a 32% increase in finding from an economic point of view, because the probability of working. In rural areas, a primary normally one would expect that in households where school degree is associated with a 6.4% increase in the women work, the income level and therefore the probability of working when compared to a woman wealth quintile might also be higher. In spite of such in rural areas with no diploma. A university degree in a potential positive relationship between the two rural areas is also associated with a very high increase variables, wealth in Turkey seems to consistently be in probability of working (around 36%). Although the associated with lower levels of female labor force group of women in rural areas with university degrees participation, rather than higher levels. In a sense, Recent Trends in Female Labor Force Participation in Turkey 11 women who live in households where the husband’s urban areas while for highly skilled women in urban education level is higher, and where the wealth index areas (as well as among rural women in top quintiles), is higher, can afford not to work. This phenomenon is wealth level is not associated with higher (or lower) observed more strongly among low-skilled women in probability of working. Table 6a: Multivariate Analysis on the probability of working for women Dependent variable: Probability of Working in the last month or usually working Dependent variabl e: Working or Usually Working (1) (2) (3) (4) VARIABLES Urban Hi gh Skil led Urban Low Skilled Rural TO TAL Age 0.0858*** 0.0362*** 0.0326*** 0.04 49*** (0.0189) (0.0063 4) (0.0110) (0 .0 0581) Age Squared -0 .0 0129*** -0.000525*** -0.0003 63** -0.0006 22*** (0.000276) (0.000 1) (0.000164) (0.0001) Urban -0 .3 13*** (0.0149) Bi rth Region: Central 0.091 1 0.040 8* 0 .0 0674 0.0491** (0.0601) (0.023 7) (0.0846) (0.0241) Bi rth Region: West 0.081 5 0.0939*** 0.0313 0.09 98*** (0.0585) (0.028 4) (0.0845) (0.0263) Pl ace of chil dhood residence i s a village 0.0978** -0.0110 0.120*** 0.0152 (0.0493) (0.013 0) (0.0359) (0.0134) Cu rrent Region: Central -0.056 6 0.0633** -0.0291 0.0248 (0.0609) (0.025 8) (0.0828) (0.0245) Cu rrent Region: West -0.081 9 0.00374 -0.0747 -0.0311 (0.0567) (0.023 4) (0.0807) (0.0232) Mother Tongue of woman is Turki sh 0.014 0 0.0120 0.0546 0.0226 (0.0785) (0.019 8) (0.0403) (0.0190) Own Education (compl ete primary) 0.00745 0.06 36** 0.0154 (0.017 3) (0.0310) (0.0167) Own Education (compl ete secondary) -0.319*** 0 .0 0813 0 .1 07*** (0.0329) (0.0749) (0.0288) Own Education (compl ete higher educati on) 0.356*** 0 .4 81*** (0.0437) (0.0273) Husband's Education (complete primary) -0.16 1 -0.0596** 0.0402 -0.0307 (0.275) (0.024 1) (0.0382) (0.0220) Husband's Education (complete secondary) -0.19 9 -0.0701*** -0.0695 -0.08 41*** (0.282) (0.024 0) (0.0532) (0.0245) Husband's Education (complete higher education) -0.12 6 -0.112*** -0.0870 -0.0622** (0.302) (0.024 2) (0.0804) (0.0288) Cu rrently Pregnant -0.053 4 -0.0676*** -0.110*** -0.07 84*** (0.0614) (0.025 3) (0.0420) (0.0219) Number of Children Under 5 = 1 -0.0643* -0.0825*** -0.0139 -0.06 20*** (0.0359) (0.013 9) (0.0289) (0.0135) Number of Children Under 5 = 2 -0.120** -0.0848*** -0.0170 -0.07 50*** (0.0606) (0.017 7) (0.0365) (0.0181) Number of Children Under 5 = 3 or more -0.0724*** -0.0813* -0.09 01*** (0.026 6) (0.0458) (0.0248) Number of additi onal women (other than the one i nt ervi ewed in HH) above age 20 -0.017 7 0.0343*** 0.0462*** 0.03 75*** (0.0261) (0.0084 7) (0.0126) (0 .0 0730) Wealth Qui nt ile 2 -0.066 3 -0.0719*** -0.0433 -0.06 90*** (0.187) (0.019 5) (0.0310) (0.0181) Wealth Qui nt ile 3 -0.099 1 -0.0815*** -0.0179 -0.07 80*** (0.173) (0.019 8) (0.0354) (0.0188) Wealth Qui nt ile 4 -0.10 9 -0.0897*** -0.08 13** -0 .1 05*** (0.173) (0.020 2) (0.0384) (0.0189) Wealth Qui nt ile 5 -0.049 9 -0.131*** -0.156*** -0 .1 31*** (0.183) (0.019 0) (0.0520) (0.0207) Marriage was arranged by the family (s2 68_1 ==2) -0.0661* -0.0334** 0.0865*** -0.00708 (0.0374) (0.013 2) (0.0236) (0.0121) Brides money was pai d by groom's family in fi rst marriage 0.14 0 0.0143 0.0173 0.0228 (0.130) (0.017 6) (0.0272) (0.0160) Woman has a male dominant view of the world * -0.052 6 0.0160 0.0711*** 0.0209* (0.0383) (0.012 9) (0.0273) (0.0125) Observations 1177 465 8 2084 7924 St andard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Recent Trends in Female Labor Force Participation in Turkey 12 Table 6b: Multivariate Analysis on the probability of labor force participation for women Dependent variable: Probability of Working in the last month or usually working or currently looking for a job Dependent variable: Labor Force Participation (1) (2) (3) (4) VARIABLES Urban High Skilled Urban Low Skilled Rural TOTAL Age 0.0995*** 0.0381*** 0.0350*** 0.04 80*** (0.0189) (0.0066 0) (0.0110) (0 .0 0590) Age Squared -0 .0 0153*** -0.000567*** -0.0004 09** -0.0006 83*** (0.000278) (0.000 1) (0.000163) (0.0001) Urban -0 .2 96*** (0.0149) Birth Region: Central 0.041 3 0.044 3* -0.00 0166 0.0433* (0.0605) (0.024 7) (0.0839) (0.0243) Birth Region: West 0.038 4 0.0998*** 0.0251 0.09 33*** (0.0592) (0.029 2) (0.0840) (0.0263) Place of childhood residence is a village 0.0823* -0.0271** 0.111*** -0.00191 (0.0490) (0.013 6) (0.0359) (0.0137) Cu rrent Region: Central -0.032 9 0.0864*** -0.0170 0.0443* (0.0625) (0.027 0) (0.0821) (0.0249) Cu rrent Region: West -0.082 0 0.0150 -0.0745 -0.0228 (0.0579) (0.024 6) (0.0803) (0.0236) Mother Tongue of woman is Turkish -0.0084 4 0.0165 0.0495 0.0240 (0.0781) (0.020 8) (0.0401) (0.0193) Own Education (complete primary) -0.00246 0.06 31** 0.00759 (0.018 4) (0.0309) (0.0171) Own Education (complete secondary) 0.0309 0 .1 41*** (0.0725) (0.0286) Own Education (complete higher education) 0.306*** 0.360*** 0 .4 86*** (0.0329) (0.0365) (0.0247) Husband's Education (complete primary) 0.077 3 -0.0685*** 0.0365 -0.0353 (0.282) (0.025 3) (0.0381) (0.0225) Husband's Education (complete secondary) 0.041 0 -0.0829*** -0.0732 -0.09 40*** (0.284) (0.025 2) (0.0531) (0.0252) Husband's Education (complete higher education) 0.12 7 -0.137*** -0.0977 -0.07 64*** (0.281) (0.024 8) (0.0803) (0.0294) Cu rrently Pregnant -0.058 5 -0.0876*** -0.114*** -0.09 22*** (0.0632) (0.025 9) (0.0419) (0.0224) Number of Children Under 5 = 1 -0.119*** -0.104*** -0.0256 -0.08 75*** (0.0364) (0.014 5) (0.0288) (0.0137) Number of Children Under 5 = 2 -0.141** -0.114*** -0.0279 -0 .1 04*** (0.0626) (0.017 8) (0.0364) (0.0182) Number of Children Under 5 = 3 or more -0.112*** -0.09 48** -0 .1 28*** (0.025 5) (0.0458) (0.0245) Number of additional women (other than the one interviewed in HH) above age 20 -0.0068 4 0.0382*** 0.0428*** 0.03 95*** (0.0262) (0.0089 3) (0.0125) (0 .0 0749) Wealth Quintile 2 -0.063 2 -0.0866*** -0.0587* -0.08 59*** (0.192) (0.020 5) (0.0310) (0.0186) Wealth Quintile 3 -0.084 7 -0.0969*** -0.0320 -0.09 09*** (0.181) (0.020 8) (0.0354) (0.0194) Wealth Quintile 4 -0.15 2 -0.119*** -0.09 00** -0 .1 34*** (0.174) (0.020 8) (0.0385) (0.0192) Wealth Quintile 5 -0.10 1 -0.165*** -0.169*** -0 .1 68*** (0.180) (0.019 3) (0.0520) (0.0209) Marriage was arranged by the family (s2 68_1 ==2) -0.102*** -0.0406*** 0.0841*** -0.0161 (0.0377) (0.013 9) (0.0235) (0.0123) Brides money was paid by groom's family in first marriage 0.16 4 0.00869 0.0128 0.0172 (0.120) (0.018 3) (0.0271) (0.0163) Woman has a male dominant view of the world * -0.056 5 0.0105 0.0739*** 0.0166 (0.0387) (0.013 6) (0.0272) (0.0127) Observations 1179 465 8 2084 7926 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Recent Trends in Female Labor Force Participation in Turkey 13 42. Pregnancy and child birth: In the overall the groom’s family to the bride’s family) and (iii) sample, pregnancy and child birth are associated with the woman has a male-dominant view of the world.14 lower probabilities of working for women in Turkey: These traditional-value system proxies do not take on a woman who is currently pregnant is 8% less likely any significant coefficient in the overall sample. In to be working controlling for all else, and a woman the urban and rural sub-samples these variables take with 1 child below the age of 5 is 6% less likely to on different signs: If the marriage of the woman was be working compared to a married woman with no arranged by her family, then this is associated with children. For highly skilled women in urban areas, a 7% decline in her probability of working in urban pregnancy does not take on a statistically significant areas, while it is associated with an 8% increase in coefficient in terms of the probability of working probability of working in rural areas. The payment although the birth of the first child is associated with of bride’s money during the wedding does not take a lower probability of working by 6%. For low skilled on a statistically significant coefficient in any of the women in urban areas, however, both pregnancy and sub-samples or in the overall sample. In general, it is having children below the age of 5 are associated with possible to say that cultural variables that signal more lower levels of participation. For low skilled women traditional values for the household are associated in urban areas, having 1 child is associated with a with higher participation levels for women in rural reduction in probability of working by 8% compared areas and lower participation levels for urban areas, to having no children. The additional children after that controlling for all other characteristics. one child, do not make a difference in the probability of working for low skilled urban women. This can be 6. Conclusion contrasted with the situation of rural women: while the 44. This paper has been motivated by the low and labor force participation is lower during pregnancy for declining levels of female labor force participation in rural women (likely to be as a result of the physical Turkey. Women’s labor force participation levels have work they are involved in), after they give birth come down from 48% in 1980 down to its current levels their probability of working does not change, when at around 26% in 2006. The levels of participation is compared to women with no children. Only if rural Turkey are now lower than in all OECD countries, and women have 3 or more children under the age of lower even than many countries in the Middle East five, then their probability of working is lower than a (such as Iran, Pakistan, Syria, Libya and Kuwait) that woman with no children in rural areas. We have also historically have had low female participation rates. tested the correlation between having an additional woman in the household (above the age of 20 and who 45. The decline in labor force participation has could act as a care-taker of children) and labor force continued in the period analyzed in this paper 2003- participation and found that having such a person in 2006, with declining levels of employment of women the household is associated with a 4% increase in the as unpaid family workers in the agricultural sector. The probability of working in the overall sample. reduction in the number of women in the agricultural sector has not been absorbed by other sectors in the 43. Cultural and social variables: The DHS dataset economy. The low-skilled women who leave the allows for the analysis of certain cultural/social agricultural sector, it seems, are unable (or unwilling) proxies for traditional values at the household level. to find jobs in urban areas thus driving down the level These variables were added to the analysis to inform of female labor force participation in urban areas. the debate around the cultural versus economic reasons When controlling for education levels, migration from for female labor force participation in Turkey. There rural to urban areas is not associated with a decline are three variables used in this analysis to signal for in labor force participation of women. However, traditional values in the household: (i) the marriage urban migration from rural areas is associated with a was arranged by the families, (ii) “brides money� significant decline in the labor force participation for (başlık parası) was paid during the wedding (from low-skilled women. Given that low skilled women 14 Male dominant view of the world is a variable that combines information from the following three questions. If the woman has answered “yes� to any of the following then she is classified as having a male-dominant view: (i) important decisions should be taken by men (ii) men are wiser than women (iii) women should not argue with men (iv) male child should get more education. These questions are found in section s767 of the DHS 2003 survey for Turkey. Recent Trends in Female Labor Force Participation in Turkey 14 make up 74% of the working age population of urban the household and the education level of the husband women (and 80% of the working population of all increases, low-skilled women in urban areas are more women) in Turkey, increasing the activity level of these likely to not be working, indicating that if they can women in the labor market is important for raising the afford it these women may actually prefer to stay at overall levels of participation for women. Although home than to work. (iv) The cultural/social proxies for early-exit is more widely observed among high skilled traditional family values are associated with a decline women, especially for university graduates, their in the labor force participation of urban women, more overall participation rates are high and low female so than rural women in the sample. labor force participation is an issue among low skilled women in urban areas more so than in other groups. 47. The combination of these supply and demand side factors are currently negatively correlated with 46. Four findings in this paper analysis are key for the labor force participation decisions of urban low- understanding the incentives that face low-skilled skilled women in Turkey. There is a certain degree women in urban areas and that determine the supply of preferences and cultural values that seem to play and demand for their labor: (i) There is a large gap into these decisions, but this is only a small part of in earnings for low skilled men and women in the picture as the multivariate analysis also suggests. Turkey both in urban and rural areas, which may be The high opportunity cost of ‘home production’ (for reducing the incentives for urban low-skilled women instance in the form of high child-care fees) and to participate in the labor market (ii) In the absence the low wage level compared to men in the labor of affordable childcare, urban low-skilled women market for these urban women may explain the more face a high opportunity cost for working not justified dominant economic reasons for their low participation by their low wage levels outside the home. For high level. Further qualitative analysis would be useful in skilled women in urban areas, and for rural women the disentangling the impact that each of these supply and number of children do not play as significant a role in demand factors variables have on the decision-making the probability of working. (iii) As the wealth status of process of low-skilled women in urban areas. Recent Trends in Female Labor Force Participation in Turkey 15 Annex - Tables Table A-1: Hierarchical Decomposition of the Total Labor Force (Hierarchical rates) Note: Changes shown between years 2003 and 2006 Source: LFS 2003, 2004, 2005 and 2006 Table A-2: Hierarchical Decomposition of the Female Labor Force (Hierarchical rates) Table A-3: Hierarchical Decomposition of the Male Labor Force (Hierarchical rates) Note: Changes shown between years 2003 and 2006 Source: LFS 2003, 2004, 2005 and 2006 Recent Trends in Female Labor Force Participation in Turkey 16 Table A-4: Employment Categories, Shares in Total Employment 2003 2004 2005 2006 Change Source: LFS 2003, 2004, 2005 and 2006 Table A-5: Employment Categories, Shares in Male Employment 2003 2004 2005 2006 Change Source: LFS 2003, 2004, 2005 and 2006 Table A-6: Distribution of the Male Employed by Economic Sector Sector of Activity (1-9) 2003 2004 2005 2006 Change Source: LFS 2003, 2004, 2005 and 2006 Recent Trends in Female Labor Force Participation in Turkey 17 Table A-7: Distribution of Male Employed by Level of Education Note: Changes shown between years 2003 and 2006 Source: LFS 2003, 2004, 2005 and 2006 Recent Trends in Female Labor Force Participation in Turkey 18 Annex-1 Definition of Input Variables (iii) Level of education: Two different sets of categories were defined under education levels. (i) Age: Given that this variable was categorical In most cases, 4 levels of education are used: “Illiterate or Incomplete Primary�, “Complete instead required as continuous, a continuous Primary�, “Complete Secondary�, “Tertiary�. age variable was randomly created. Then, was The other set of 6 categories are: “Illiterate�, fitted into the program successfully. “No Schooling�, “Primary School�, “Basic or Junior Secondary School�, “Senior Secondary (ii) Gender: It was defined as a dummy variable, Schooling (including vocational)�, “Higher 1=Male and 0=Female Education�. Education Levels (iv) Employment variables: Definition for c. Persons employed: Comprises all the employment variables was based on noninstitutional working age population TURKSTAT’s definitions but limited for who are included in the “persons at work� population at working-age (15-64) instead of and “not at work� described below. age 15 and over. TURKSTAT’s definitions15 d. Persons at work: Persons economically related to labor force statistics are noted active during the reference period for below: at least one hour as a regular employee, casual employee, employer, self employed a. Labour force: Comprises all employed or unpaid family worker. persons and all unemployed. e. Employment rate: Employment rate is b. Labour force participation rate: Indicates the ratio of employed persons to the the ratio of the labour force to non- non-institutional working age (15-64) institutional working age population. population. 15 TURKSTAT (2007) Household Labor Force Statistics 2006, pp.XXIV Recent Trends in Female Labor Force Participation in Turkey 19 f. Persons unemployed: The unemployed codes were used. (1) Agriculture, forestry comprises all persons at working age who and fishing (2) Mining (3) Manufacturing were not employed (neither worked for (4) Electricity, gas and water supply (5) profit, payment in kind or family gain at Construction (6) Wholesale retail trade, any job even for one hour, who have no job restaurants and hotels (7) Transportation, attachment) during the reference period communication and storage (8) Financial who have used at least one channels for intermediation, real estate, renting and business seeking a job during the last three months activities (9) Public and Government services, and were available to start work within education, health and social work, community two weeks. Services. Persons who have already found a job (viii) Region: SRE-1 Level identification was used. and will start to work within 3 months, Regional identifiers were only available for the or established his/her own job but were years 2004, 2005 and 2006. waiting to complete necessary documents to start work were also considered to be unemployed if they were available to start work within two weeks. SRE-1 Classification g. Unemployment rate: Is the ratio of 1 Istanbul unemployed persons to the labor force. 2 West Marmara 3 Aegean h. Employment status: All persons who are currently employed and persons employed 4 East Marmara in the past are classified according to 5 Western Anatolia International Classification on Status in 6 Mediterranean Employment (ICSE,1993): 7 Central Anatolia i. Regular employee 8 Western Black Sea 9 Eastern Black Sea ii. Casual employee 10 Northeastern Anatolia iii. Employer 11 Middle eastern Anatolia 12 Southeastern Anatolia iv. Self employed v. Unpaid family worker (v) Earnings: It was defined as “monthly net (ix) Hours: Number of hours worked in a week income in cash�. was set as 45. (vi) Work Category: According to TURKSTAT’s (x) Informality: In this paper, informality refers to categorization; except unpaid family workers, those who are not registered within the social regular employees (Wage/salary workers), security system. casual employees, employer and self-employed categories were decomposed as “registered� and (xi) Discouraged: The definition from TURKSTAT “unregistered� in order to identify informality is used, which refers persons who are available in profile analyses. to start a job but are not seeking because of not knowing where to search a job because of not (vii) Sector of economic activity: For main activity knowing where to search or who believe no job coding, TURKSTAT’s classification of 9 sector is available for him/her in the region. Recent Trends in Female Labor Force Participation in Turkey 20 Annex-2: International Labor Organization (ILO) Definitions16 The Economically Active Population comprises national circumstances, according to one or more of the all persons of either sex who furnish the supply of following criteria: (i) The continued receipt of wage or labor for the production of goods and services during salary; (ii) An assurance of return to work following a specified time-reference period. According to the the end of the contingency, or an agreement as to the 1993 version of the System of National Accounts, date of return; (iii) The elapsed duration of absence production includes all individual or collective goods from the job which, wherever relevant, may be that or services that are supplied to units other than their duration for which workers can receive compensation producers, or intended to be so supplied, including the benefits withoutobligations to accept other jobs? production of goods or services used up in the process (b) “Self-employment�: of producing such goods or services; the production of all goods that are retained by their producers for (b1) “At work�: persons who during the reference their own final use; the production of housing services period performed some work for profit or family gain, by owner-occupiers and of domestic and personal in cash or in kind; services produced by employing paid domestic staff. (b2) “With an enterprise but not at work�: persons with Two useful measures of the economically active an enterprise, which may be a business enterprise, a population are the usually active population measured farm or a service undertaking, who were temporarily in relation to a long reference period such as a year, not at work during the reference period for any specific and the currently active population, or, equivalently, reason. the labor force measured in relation to a short reference period such as one day or one week. (2) For operational purposes, the notion “some work� may be interpreted as work for at least one hour. Employment is defined as follows in the Resolution concerning statistics of the economically active (3) Persons temporarily not at work because of illness population, employment, unemployment and or injury, holiday or vacation, strike or lockout, underemployment, adopted by the Thirteenth educational or training leave, maternity or parental International Conference of Labor Statisticians leave, reduction in economic activity, temporary (Geneva, 1982): disorganization or suspension of work due to such reasons as bad weather, mechanical or electrical (1) The “employed� comprise all persons above breakdown, or shortage of raw materials or fuels, or a specific age who during a specified brief period, other temporary absence with or without leave should either one week or one day, were in the following be considered as in paid employment provided they categories: had a formal job attachment. (a) “Paid employment�: (4) Employers, own-account workers and members of producers’ cooperatives should be considered as in (a1) “At work�: persons who during the reference self-employment and classified as “at work� or “not at period performed some work for wage or salary, in work�, as the case may be. cash or in kind; (5) Unpaid family workers at work should be considered (a2) “With a job but not at work�: persons who, as in self-employment irrespective of the number of having already worked in their present job, were hours worked during the reference period. Countries temporarily not at work during the reference period that prefer for special reasons to set a minimum time and had a formal attachment to their job. This formal criterion for the inclusion of unpaid family workers job attachment should be determined in the light of among the employed should identify and separately 16 World Bank Poverty Reduction Group, Automated labor market diagnostics for low and middle income countries: ADePT Labor User Guide http:// siteresources.worldbank.org/INTPOVRES/Resources/ADePT Labor Guide.pdf, pp.50 Recent Trends in Female Labor Force Participation in Turkey 21 classify those who worked less than the prescribed placing or answering newspaper advertisements; time. seeking assistance of friends or relatives; looking for land, building, machinery or equipment to establish (6) Persons engaged in the production of economic own enterprise; arranging for financial resources; goods and services for own and household consumption applying for permits and licenses, etc. should be considered as in self-employment if such production comprises an important contribution to the (2) In situations where the conventional means of total consumption of the household. seeking work are of limited relevance, where the labor market is largely unorganized or of limited scope, (7) Apprentices who received pay in cash or in where labor absorption is, at the time, inadequate, kind should be considered in paid employment and or where the labor force is largely self-employed, classified as “at work� or “not at work� on the same the standard definition of unemployment given in basis as other persons in paid employment. subparagraph (1) above may be applied by relaxing the criterion of seeking work. (8) Students, homemakers and others mainly engaged in non-economic activities during the reference period, (3) In the application of the criterion of current who at the same time were in paid employment or availability for work, especially in situations covered self-employment as defined in subparagraph (1) above by subparagraph (2) above, appropriate tests should be should be considered as employed on the same basis as developed to suit national circumstances. Such tests other categories of employed persons and be identified may be based on notions such as present desire for separately, where possible. work and previous work experience, willingness to take up work for wage or salary on locally prevailing (9) Members of the armed forces should be included terms, or readiness to undertake self-employment among persons in paid employment. The armed activity given the necessary resources and facilities. forces should include both the regular and temporary members as specified in the most recent revision of the (4) Notwithstanding the criterion of seeking work International Standard Classification of Occupations embodied in the standard definition of unemployment, (ISCO). persons without work and currently available for work that had made arrangements to take up paid Unemployment is defined as follows in the employment or undertake self-employment activity at Resolution concerning statistics of the economically a date subsequent to the reference period should be active population, employment, unemployment considered as unemployed. and underemployment, adopted by the Thirteenth International Conference of Labor Statisticians (5) Persons temporarily absent from their jobs with no (Geneva, 1982): formal job attachment that were currently available for work and seeking work should also be regarded (1) The “unemployed� comprise all persons above a as unemployed in accordance with the standard specified age who during the reference period were: definition of unemployment. Countries may, however, (a) “Without work�, i.e. were not in paid employment depending on national circumstances and policies, or self-employment prefer to relax the seeking work criterion in the case of persons temporarily laid off. In such cases, persons (b) “Currently available for work�, i.e. were available temporarily laid off who were not seeking work but for paid employment or self-employment during the classified as unemployed should be identified as a reference period; and separate subcategory. (c) “Seeking work�, i.e. had taken specific steps in a (6) Students, homemakers and others mainly engaged specified reference period to seek paid employment in non-economic activities during the reference period or self-employment. The specific steps may include that satisfy the criteria laid down in subparagraphs registration at a public or private employment exchange; (1) and (2) above should be regarded as unemployed application to employers; checking at worksites, on the same basis as other categories of unemployed farms, factory gates, market or other assembly places; identified separately, where possible. Recent Trends in Female Labor Force Participation in Turkey 22 References Alkan, D. (1995) Women’s Employment and Income T. Bulutay (ed.) The New Developments in Distribution by Gender in Turkey, Unpublished National Accounts, SIS: Ankara Master’s Thesis: Middle East Technical University Kocak, S. (1999) Gender Discrimination in the Turkish Labor Market, Unpublished Ph.D. Thesis, De Baslevent, C. and O. Onaran (2003) Are Married Montfort University, England Women in Turkey are More Likely to Become Added or Discouraged Workers? Labour 27 (3) Palaz, S. (2006?) Women’s Labor Force Participation pp.439-458 in Turkey, in Social Politics Conference Series (Sosyal Siyaset Konferanslari) Dayioglu, Meltem, (2000), “Labour Market Participation of Women in Turkey�, in Acar F. Pancaroğlu, N.S. (2006) Problems of Women and Gunes-Ayata (eds.) Gender and Identity Participation in Labor Force and Employment Construction: Women of Central Asia, Caucasus in Urban Areas: The Case of Izmit (Kentlerde and Turkey, The Netherlands: E. S. Brill Kadınların İşgücüne ve İstihdama Katılım Sorunları: İzmit Örneği), Unpublished Master’s Erman, T. (1998) The impact of migration on rural Thesis. Kocaeli University: Kocaeli women in Turkey: Four emergent patterns, Gender & Society 12 (2) pp. 146-167 Ozar, S. and G. Günlük-Şenesen, (1998), “Determinants of Female (non) Participation in the Urban labour Erman, T. (2001) Rural Migrants and Patriarchy in Force in Turkey�, METU Studies in Development, Turkish Cities, International Journal of Urban 25(2), pp.311-328 and Regional Research 25 (1), 118–133 State Planning Organization (2007) 9th Development Eyüboğlu, A., Özar, Ş. & Tanrıöver, H. T. (2000). The plan 2007-2013: The Labor Market, Ad-Hoc Socioeconomic and Cultural Aspects of Urban Committee Report, Prime Ministry of Republic of Women’s Participation Problems (Kentlerde Turkey, Ankara Kadınların İş Yaşamına Katılım Sorunlarının Sosyo-ekonomik ve Kültürel Boyutları)-2000- Turkish Enterprise and Business Confederations KSSGM (TURKONFED) (2007) Women in Business World (İş Dünyasında Kadın) Gunduz-Hosgor, A. and J. Smits (2006) Variation in Labor Market Participation of Married TURKSTAT (2007) Household Labor Force Statistics Women in Turkey: Radboud University 2006, Prime Ministry Republic of Turkey, Turkish Statistical Institute: Ankara Ince and Demir (2006) The Determinants of Female Labor Force: Empirical Evidence from Turkey, World Bank (2000) Turkey Economic Reforms, Living Eskisehir Osmangazi University, Journal of Standards and Social Welfare Study Faculty of Administrative Sciences and Economics, 1 (1) pp 71-90. World Bank (2004) Bridging the Gender Gap in Turkey: A Milestone towards Faster Socio- Kasnakoglu, Z. and M. Dayioglu (1997) Female Labor economic Development and Poverty Reduction Force Participation and Earnings Differentials between Genders in Turkey, in J. Rives and M. World Bank, (2006), Turkey Labor Market Study, A Yousefi (eds.) Economic Dimensions of Gender World Bank Country Study, Washington, D.C. Inequality, Praeger: London World Bank, (2008), World Development Indicators, Kasnakoglu, Z. and M. Dayioglu (2002), Measuring Development Data Group, The World Bank: the Value of Home Production in Turkey, in Washington, D.C. Notes: Notes: Notes: Notes: World Bank Copyright @ 2010 The International Bank for Reconstruction and Development The World Bank 1818 H Street, NW Washington, DC 20433, USA All rights reserved