43935 2005 er 1. mb Nove,s Serie School to work transitions in Georgia: a preliminary analysis based Papergn on household budget survey data Worki Project L. Guarcello S. Lyon Work F. C. Rosati C. Valdivia Children's November 2005 Understanding School to work transitions in Georgia: a preliminary analysis based on household budget survey data L. Guarcello* S. Lyon* F. C. Rosati* C. Valdivia* Working Paper November 2005 Understanding Children's Work (UCW) Project University of Rome "Tor Vergata" Faculty of Economics V. Columbia 2 00133 Rome Tor Vergata Tel: +39 06.7259.5618 Fax: +39 06.2020.687 Email: info@ucw-project.org As part of broader efforts toward durable solutions to child labor, the International Labour Organization (ILO), the United Nations Children's Fund (UNICEF), and the World Bank initiated the interagency Understanding Children's Work (UCW) project in December 2000. The project is guided by the Oslo Agenda for Action, which laid out the priorities for the international community in the fight against child labor. Through a variety of data collection, research, and assessment activities, the UCW project is broadly directed toward improving understanding of child labor, its causes and effects, how it can be measured, and effective policies for addressing it. For further information, see the project website at www.ucw- project.org. This paper is part of the research carried out within UCW (Understanding Children's Work), a joint ILO, World Bank and UNICEF project. The views expressed here are those of the authors' and should not be attributed to the ILO, the World Bank, UNICEF or any of these agencies' member countries. *UCW-Project and University of Rome "Tor Vergata" School to work transitions in Georgia: a preliminary analysis based on household budget survey data Working Paper November 2005 ABSTRACT In Georgia, the lack of employment opportunities and with it, the loss of positive motivation and hope in a better future, is among the critical challenges facing the current generation of young people. Many of the employment problems of Georgian young people are rooted in the critical period of transition from education to working life. Yet the routes that young people take from education to employment are poorly understood, and data relating to this transition period are scarce. There is therefore limited empirical basis for formulating policies and programmes promoting youth employment and successful school to work transitions. This paper constitutes a starting point for more detailed analysis on youth labour market status in the Georgian context and it study is aimed at contributing to fill the lack of information about the transition from education to working life. It therefore analyses a set of youth education and employment indicators based on 2002 Georgia Household Budget Survey. Particular emphasis is placed on measuring the initial transition from school to work for different groups of young people, and on identifying the factors affecting this transition. School to work transitions in Georgia: a preliminary analysis based on household budget survey data Working Paper November 2005 CONTENTS 1. Background....................................................................................................................................1 2. Country context: macroeconomic and labour market trends................................................2 3. Overview of the time use patterns of young people...............................................................5 4. Status of young people in the labour market............................................................................7 4.1 Youth unemployment...........................................................................................................7 4.2 Youth inactivity....................................................................................................................10 4.3 Youth employment conditions..........................................................................................11 4.4 Youth labour market disadvantage...................................................................................13 5. Measuring the duration of the transition from school to work...........................................16 5.1 A Synthetic Indicator..........................................................................................................17 5.2 Empirical implementation..................................................................................................19 6. Assessment of the transition to working life..........................................................................20 6.1 Assessment of the duration and timing of the transition based on estimated probabilities..................................................................................................................................20 6.2 Assessment of the duration and composition of the transition applying cohort indicators (OECD) .....................................................................................................................22 6.3 Factors influencing schooling and employment decision.............................................24 7. Summary of main findings and possible next steps ..............................................................25 Appendix 1.........................................................................................................................................27 Table A1: Results of bivariate probit estimates............................................................................27 Table A2.1:Marginal effects on the probability of beeing employed........................................28 Table A2.2: Marginal effects on the probability of beeing in school........................................28 1 UCW WORKING PAPER SERIES, NOVEMBER 2005 1. BACKGROUND 1. Youth unemployment and underemployment represent growing concerns worldwide. According to ILO estimates, youth in 2002 made up 41 percent of the world's unemployed, 88 million persons in absolute terms. Young workers everywhere invariably have higher rates of joblessness and unemployment and much lower earnings than older workers. Young people are also tend to be concentrated in low-skill informal work, or in hazardous forms of work that are ill-suited to their age and experience. 2. In Georgia, the lack of employment opportunities and with it, the loss of positive motivation and hope in a better future, is among the critical challenges facing the current generation of young people. This is true for youth living in towns and cities with traditional labour markets, and in rural areas where jobs are few. In all, one of every four young persons in the labour force is unable to find a job. It takes an average of six to eight years for Georgian young people to settle into work after leaving school. 3. Many of the employment problems of Georgian young people are rooted in the critical period of transition from education to working life. Yet the routes that young people take from education to employment are poorly understood, and data relating to this transition period are scarce. There is therefore limited empirical basis for formulating policies and programmes promoting youth employment and successful school to work transitions. 4. This study is aimed at beginning to fill this gap by analysing a set of youth education and employment indicators based on 2002 Georgia Household Budget Survey. Particular emphasis will be placed on measuring the initial transition from school to work for different groups of young people, and on identifying the factors affecting this transition. The analysis will include the composition, as well as the timing and duration, of the transition period. 5. The study is structured as follows. Section 2 provides a general overview of macro-economic and labour market trends, as background for the discussion on youth employment in Georgia in the following sections. Section 3 presents a descriptive overview of the time use patterns of young people and how these patterns differ by individual and household characteristics. Section 4 examines the status of young people in the labour market, and the extent to which they are disadvantaged vis-à-vis adult workers. Section 5 discusses the construction of a synthetic indicator measuring the duration and timing of the transition from school to work. Section 6 then applies this indicator to assess the transition to working life in the Georgian context. Section 7 concludes and looks at areas of future research. SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 2 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA 2. COUNTRY CONTEXT: MACROECONOMIC AND LABOUR MARKET TRENDS1 6. Following independence, Georgia went through an economic collapse, and by the end of 1994 output had fallen by two thirds. Economic stabilization and structural reform measures launched in 1994 succeeded in restoring economic growth; growth averaged 10 percent over the two years 1996 and 1997. However, subsequent economic performance has been weaker: real GDP growth has slowed to 3 percent per year since 1998, reflecting uneven progress in reforms, two major droughts (in 1998 and 2000), and the lingering effects of the 1998 Russian crisis. Today, real GDP is still only 40 percent of its level at independence. With an annual per capita GDP (PPP) of US$2,664 in 2000, Georgia is one of the poorest countries in ECA.2 Table 1. - Georgia: Selected macro-economic indicators, 1995 ­ 2001 1995 1996 1997 1998 1999 2000 2001 Annual Real GDP Growth (%) 2.6 10.5 10.6 2.9 3.0 1.9 4.5 GDP Level (1990=100) 29.6 32.7 36.1 37.2 38.3 39.0 40.8 Average Annual Inflation, CPI (%) 162.7 39.3 7.0 3.6 19.1 4.0 4.7 FDI (million USD) 6.3 54.4 236.3 221.0 61.7 152.6 96.1 Exchange Rate, GEL/US$ (Average) 1.280 1.250 1.297 1.39 2.02 1.98 2.07 Source: World Bank, IMF, ILO, Georgia: The World Bank (2002) Georgia Poverty Update (2002), Rep. No. 22350-GE and UNICEF (2002), Social Monitor 2002, UNICEF Innocenti Research Centre: Florence data. 7. Economic growth has had only a modest impact on household welfare, and in recent years growth in incomes and private consumption has lagged behind GDP growth. Likewise, the employment content of GDP growth has been insufficient to generate enough new jobs to expand opportunities for the poor. This reflects the relatively narrow sectoral base of the economic recovery, with gains concentrated in industries with only a moderate impact on employment, mainly communications, financial intermediation and transport: while some 75 percent of the real value added in the economy occurred in these industries, they have only 5 percent aggregate share in employment. Moreover, about half of the population, which depends on agriculture for their livelihood, was adversely affected by declining agricultural production. Consequently, the gains of growth were not shared equally, and inequality increased: in 2000, the Gini coefficient (consumption) was 0.39. 8. Increasing inequality and falling consumption increased vulnerability and pushed poverty levels up. Poverty incidence gradually increased from some 14 percent in 1997 to 23 percent in 2000. At the same time, there was a steady increase in the depth and severity of poverty. More remarkably, while only some 20 percent of Georgians currently may be chronically poor, many more are economically vulnerable: over 40 percent of people experience poverty at least once during the year, reflecting a high degree of volatility in household consumption. It is estimated that over 50 percent of the Georgian population is vulnerable to poverty for any upcoming year. 1This section is drawn primarily from World Bank, Child Welfare Note ­ Georgia, unpublished draft, 2004. 2 In 2000, Georgia's per capita GDP in purchasing parity terms is higher than in Moldova (US$2,109), similar to Armenia (US$2,559) and Kyrgyz Republic (US$ 2,711) and lower than in Azerbaijan (US$ 2,936) and the other European ECA countries. In comparison, the average per capita GDP for ECA amounted to PPP$ 6,794 ( see The World Bank, World Development Indicators 2002). 3 UCW WORKING PAPER SERIES, NOVEMBER 2005 Table 2. - Dynamics of GDP, Employment, Productivity and Wages (1995=100) 1996 1997 1998 1999 2000 GDP growth 110.4 122.0 125.7 129.4 131.8 Employment growth 105.2 115.2 104.0 106.2 108.6 Productivity growth 105.2 106.8 121.7 123.2 123.2 Real wage 149.1 201.4 253.4 258.7 317.0 Source: UNICEF (2002), Social Monitor 2002, UNICEF Innocenti Research Centre: Florence and calculations. 9. The capacity of the public sector to stimulate economic growth and provide quality services to citizens has been fragile. The bulk of budget expenditures (over 90 percent in 2000) was used to cover recurrent costs, in particular transfers (24 percent) - pensions, poverty benefits, assistance to internally displaced people (IDPs), and only some nine percent was allocated for capital expenditures. Altogether, expenditures on social insurance and welfare, health and education account for close to 45 percent of public spending. 10. While employment has expanded since the mid-1990s, and the employment rate is at a respectable 65 percent, employment opportunities differ significantly between urban and rural areas ­ the employment rate among the urban population is a low 46 percent, and in rural areas it is 73 percent. This reflects the low employment content of industrial growth, and it may reflect underemployment resulting from an overhang of labour in the rural areas. Registered unemployment is at 17 percent, but this may well underestimate the actual rate of unemployment, which is estimated by official sources to be closer to 20-25 percent.3 Again, unemployment is significantly higher in urban than in rural areas ­ 26 percent and 6 percent respectively. To a large extent, high unemployment reflects labour shedding from state enterprises, which the private sector has not been able to absorb. Migration abroad, especially to Russia, has served as a risk management strategy in many poor households and has to some extent eased the pressure on the labour market. Table 3. - Labour force, 1995-2000 1995 1996 1997 1998 1999 2000 Labour force participation rate (%) 70 65 Employment rate (%) 59.4 62.5 68.4 61.8 63.1 64.5 Annual registered unemployment rate (average percent 2.6 2.4 5.0 5.0 5.5 5.9 of the labour force) Unemployment rate, ILO methodology ... 11.6 5.2 11.1 12.7 10.1 Source: UNICEF (2002), Social Monitor 2002, UNICEF Innocenti Research Centre: Florence; The World Bank (1997), Georgia Poverty Assessment. 11. Labour market status is the main determinant of household poverty. While the unemployed and non-participants in the labour market are most likely to be poor, the majority of the poor in Georgia are the working poor, whose earnings are insufficient to pull their families out of poverty. These are often self-employed, underemployed in unrestructured enterprises or employed in the informal sector with insecure, temporary and low productivity jobs. There is also a significant disadvantage to rural location. Earnings inequality is high ­ the typical "well-paid" worker receives ten 3Parliament of Georgia, see: http://www.parliament.ge/ECONOMICS/ SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 4 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA times more than a "poorly paid" worker. There are two groups in the labour market who are at a particular disadvantage ­ women and internally displaced persons (IDPs). There is a large and persistent gender gap in earnings between men and women with similar characteristics (by about ten percent on average, controlling for other factors). The IDPs face extensive barriers to entry into the labour market, lack information about employment opportunities or the connections needed to get a job. The jobs they do get are routinely low paying and insecure.4 12. Increased vulnerability has meant an increasing incidence of working children, and the age at which children go to work is declining - in 2000, children age 12 to 14 constituted the largest age groups of working children. A high number of primary and secondary school students work, either in the household or outside the family. This is one of the adverse consequences of the transition: the incidence of child and adolescent labour has risen with household poverty. A study by the State Department for Statistics of Georgia (SDS) indicates that some 16 percent of children age 7 to 17 (823,200 children) fall into the category of working children.5 Of them, 95 percent are enrolled school, while 5 percent (42,000) do not attend school. 13. Child labour is of two main types: (i) economic activity for cash compensation, mostly outside the household; and (ii) household work. It mainly occurs in poor families. According to the SDS survey, 58 per cent of children who are in school are involved in both economic activity and household work, while 15 per cent are involved in economic activity only. Rural children are more frequently engaged in economic activity than children from towns and cities, and boys are much more frequently engaged in economic activity than girls. Some 79 per cent of all children who go to school and work are from rural Georgia. Boys make up over 80 per cent of all the children who go to school and work at the same time. In the town of Guria, almost every third child is working, in Samtskhe-Javakheti, every fourth child. 14. Temporary jobs are the prevalent form of work for the children who are in school; some 97 percent of them have temporary jobs - 87 percent work for their families, 5 per cent work for private businesses, and 3 percent work on their own. Some 95 per cent of working children are engaged in agriculture, 3.2 percent in trade and services. 4The World Bank (2002), Georgia Poverty Update, January 10, 2002 (Report No. 22350-GE) 5The survey on child labour was carried out by the SDS with the support of ILO in August and November 1999 and in February and May 2000, and is included in: Analytical Report: Trends of Child and Family Well-Being in Georgia (2001). 5 UCW WORKING PAPER SERIES, NOVEMBER 2005 3. OVERVIEW OF THE TIME USE PATTERNS OF YOUNG PEOPLE 15. This section analyses data relating to the time use patterns of Georgian young people aged 16-24 years.6 Table 4 breaks the youth population down into four unique activity categories7 ­ only in education; combining education and employment; only in employment;8 unemployed;9 and inactive.10 It indicates that education accounts for the largest proportion of young people (43 percent), though secondary and post- secondary enrolment in Georgia is low relative to other Central Asian countries. 16. Among the remaining non-student 16-24 year-olds, those in employment are matched by those that are jobless, suggesting that many young people encounter difficulties transitioning to working life upon leaving school. About two-thirds of jobless youth, in turn, are inactive while the remaining one-third is in the labour force but unable to find a job. The issues of unemployment and joblessness are discussed in more detail in Section 4. 17. Individual and household characteristics appear to have an important influence on young people's time use patterns, as also shown in Table 4: · Age: Most obviously, time use differs with age, as the 16-24 years age range is a period of transition from adolescence to adulthood, and from education to working life. Compared to young adults (20-24 year-olds), teenagers (16-19 year-olds) are more involved in education and less involved in the labour force (employed and unemployed). Teenagers are also less likely to be inactive. Education involvement begins to fall at age 17, roughly coinciding with the end of secondary education, and employment involvement rises from age 19 years onwards. All but 15 percent of young people leave school by age 24, but 60 percent have not settled into employment. The school to work transition is discussed in detail in Sections 5 and 6. · Gender: Female youth involvement in post-secondary and tertiary education is slightly higher than that of male youth, but female young people are much less likely than male youth to be in the labour force upon leaving education. Female labour force involvement is about half that of males, while female inactivity rates are more than double male rates. As discussed below, the "inactive" category captures not only discouraged workers but also persons performing domestic duties and child-rearing, activities typically assigned to females. While women in the labour force experience roughly the same risk of unemployment as their male 6The "youth" or "young person" population typically refers to the 15-24 years age cohort. The narrower 16- 24 years age cohort is used in this report because data were not available for young people aged 15 years. 7 The data do not allow to unambiguously identify youth both working and attending school. 8An employed person is a one who fulfils any of the following:-a) paid employment; b) at work; c) with a job but not at work at present. This includes persons waiting to rejoin employment. This category includes employers or persons in self-employment. This category of persons should include unpaid family labour who holds a job in a market-oriented establishment irrespective of the number of hours worked during a reference period. However, some countries prefer for special reasons to set a minimum time criterion of the inclusion of unpaid family labour among the employed. Usually, if person works for more than 7+ hours a day, they are considered employed 9An unemployed person is a person who fulfils either or all of the following criterion: - a) Without work; b) Currently available for work or; c) Seeking work by taking necessary steps to seek paid employment such steps include applying for jobs, registered in an agency. 10An "inactive" person is a person who is neither in the labour force (employed or unemployed) nor in education. SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 6 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA counterparts, there are strong indications that they are disadvantaged in terms of remuneration and access to certain segments of the labour market.; Table 4. - Time use patterns by various background characteristics, 16-24 years age group Distribution of youth by activity status Jobless Background characteristic (1) (2) (3) (4) Total (3)+(4) In education Employed Unemployed Inactive(a) Total 43.3 28.4 8.8 19.5 100 28.3 Age 16 66.1 21.4 3.6 8.9 100 12.5 17 68.7 17.8 3.1 10.4 100 13.6 18 56.1 22.1 3.7 18.2 100 21.9 19 51.7 21.6 7.3 19.4 100 26.7 20 47.5 27.9 7.9 16.8 100 24.7 21 41.8 30.8 7.3 20.0 100 27.3 22 40.0 31.7 12.8 15.6 100 28.4 23 28.0 33.7 12.6 25.8 100 38.4 24 15.3 40.7 15.5 28.5 100 44.0 Sex Female 45.8 20.9 6.9 26.4 100 33.3 Male 40.5 36.7 10.9 11.8 100 22.7 Nationality Georgian 48.3 25.9 8.3 17.5 100 25.8 Azeri 18.1 40.4 5.1 36.4 100 41.5 Abkhazian 0.0 25.0 0.0 75.0 100 75 Greek 25.0 37.5 12.5 25.0 100 37.5 Ossetian 28.3 43.5 10.9 17.4 100 28.3 Russian 44.8 8.6 27.6 19.0 100 46.6 Armenian 24.1 47.0 12.9 16.0 100 28.9 Ukrainian 20.0 0.0 0.0 80.0 100 80 Other 14.6 16.4 25.5 43.6 100 69.1 HH head education Elementary or less(b) 36.1 31.6 11.0 21.3 100 32.3 Not completed secondary(c) 26.8 37.3 10.0 25.9 100 35.9 Secondary(d) 39.3 30.6 9.1 20.9 100 30 Higher education 63.9 17.5 7.0 11.6 100 18.6 Employment status of Employed 39.0 34.0 7.8 19.2 100 27 HH head Not employed 52.5 15.9 11.3 20.3 100 31.6 HH income quintile 1 31.8 31.0 10.1 27.2 100 37.2 2 43.2 24.4 11.1 21.3 100 32.4 3 41.3 28.5 8.4 21.8 100 30.2 4 45.2 30.7 8.8 15.3 100 24.0 5 54.2 27.7 5.6 12.5 100 18.1 Notes: (a) "Inactive" refers to group not in labour force and not in education; (b) Completed 4-5 grades or less; (c) Completed 8-9 grades; (d) General education, lyceum, gymnasium, vocational-technical Source: UCW calculations based on Georgia Household Budget Survey, 2002 · Nationality: Nationality appears to have a strong influence on the opportunities available to young people. Overall, Georgian youth are more likely to be in school and less likely to be jobless than young people of other minority nationalities. Russian and Azeri youth face the highest levels of joblessness, at 47 and 42 percent, respectively11; · Parental education: Parents' education appears to positively influence children's educational attainment and job prospects. Young people with educated parents are more likely to be in school and less likely to be jobless than young people with less educated parents. The differences in time use by parents' educational status, however, are not large with the exception of parents with higher education and; 11 Figures should be treated with caution due to small sample size 7 UCW WORKING PAPER SERIES, NOVEMBER 2005 · Household income: Household poverty appears to diminish opportunities available to young people. While school enrolment at the compulsory levels vary little by poverty status, youth from poor households are less likely to stay in school beyond compulsory education. Access to fee-based upper secondary and higher education remains strictly circumscribed by affordability for the poor. Other sources suggest that youth from poor households also benefit less from private tutoring to compensate for deficient in-school teaching; private lessons are twice as frequent among the non-poor as among the poor.12 Poor youth, on the other hand, are much more likely to form part of the ranks of the jobless: jobless rate of poor youth is almost twice that of youth from wealthy households. 18. The data unfortunately do not permit a breakdown of time use patterns by residence. Other information sources, however, point to substantial rural-urban disparities in terms of educational involvement (favouring urban youth) and employment involvement (favouring rural dwellers). While enrolment rates differ little by residence at the compulsory level, there is a dramatic drop in rural relative to urban enrolment at the post-compulsory levels. Overall employment rates stood at 46 percent in urban areas in 2000, against 73 percent in rural areas. The unemployment rate for the same year was 26 percent in urban areas against just six percent in rural areas.13 Decisions concerning education involvement are of course affected by perceptions of job prospects, and urban children may stay in school longer as a response to poor immediate job prospects. 4. STATUS OF YOUNG PEOPLE IN THE LABOUR MARKET 4.1 Youth unemployment 19. Youth unemployment is the most important and common measure of youth labour market status. The effects of prolonged unemployment early in a person's working life are well-documented: it may permanently impair his or her productive potential and therefore influence lifetime patterns of employment, pay and unemployment. In Georgia, research also points to links between youth unemployment and high risk behaviours, substance abuse, youth crime levels and youth delinquency rates.14Youth unemployment is included as an indicator for monitoring the UN Millennium Development Goal to "develop and implement strategies for decent and productive work for youth."15 20. Levels of unemployment are very high among Georgian young people, highlighting the difficulties they encounter in making the transition from education to working life. Almost one in four 16-24 year-olds (24 percent) in the labour force, and one in ten of all 16-24 year-olds (nine percent), is affected by unemployment. This level of youth unemployment, however, is not unusual in the context of the Eastern Europe and Central Asia regions (Figure 1). While Georgia level of youth unemployment is not among the highest in the region, it is still above that of a large number of countries. 12 World Bank, Child Welfare Note ­ Georgia, unpublished draft, 2004. 13 World Bank, Child Welfare Note for Georgia, unpublished draft, 2004. 14 According to figure from the State Department of Georgia, for example, just under half of all adolescents have used drugs. Some youth are also forced to participate in commercial sex work (CSW) as a means to escape poverty and find employment. Almost one half (42 percent) of all CSWs in Georgia are female youth between the ages of 16-25 years. 15See http://millenniumindicators.un.org/unsd/mi/mi_goals.asp. SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 8 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA Figure 1. Youth unemployment rates, Georgia versus selected Central Asian and South-Eastern Europe countries, around 2001(a) Notes: (a) Survey methodologies and reference years differ across the countries; comparisons are therefore indicative only. Source: UCW calculations based on Georgia Household Budget Survey 2002, World Bank Labour Force Survey data and UNICEF TransMONEE database 2004 21. Youth unemployment estimates need to be interpreted with caution, however, particularly when looked at in isolation from unemployment dynamics. Low outflows from unemployment and long spell durations are likely to indicate employment problems, but high outflows and short spell durations may merely reflect active search on the part of youth for their "preferred" work. The negative effects of unemployment are therefore largely associated to prolonged (and/or repeated) spells of unemployment, rather than the incidence of unemployment per se. Unfortunately, data on unemployment duration were not available in the Georgian Household Budget Survey 2002. 9 UCW WORKING PAPER SERIES, NOVEMBER 2005 Table 5. - Indicators of unemployment and joblessness for youth, by various background characteristics Jobless to non- Background characteristic Unemployment ratio(a) Unemployment rate(b) Jobless ratio(c) student population ratio(d) Age 16-19 4.8 18.8 20.9 50.3 20-24 11.1 25.2 32.5 49.7 16-24 8.8 23.6 28.3 49.9 25-55 9.1 11.45 28.4 28.7 Sex Female 6.9 24.8 33.3 61.4 Male 10.9 22.9 22.7 38.2 Nationality Georgian 8.3 24.3 25.8 49.9 Azeri 5.1 11.2 41.5 50.7 Abkhazian 0.0 0.0 75 75.0 Greek 12.5 25.0 37.5 50.0 Ossetian 10.9 20.0 28.3 39.4 Russian 27.6 76.2 46.6 84.4 Armenian 12.9 21.5 28.9 38.1 Ukrainian 0.0 - 80 100.0 Other 25.5 60.9 69.1 80.8 HH head education Elementary or less(e) 11.0 25.8 32.3 50.5 Not completed secondary(f) 10.0 21.1 35.9 49.0 Secondary(g) 9.1 22.9 30 49.5 Higher education 7.0 28.6 18.6 51.5 Employment status of Employed 7.8 34.3 27 62.0 HH head Not employed 11.3 29.0 31.6 53.6 HH income quintile 1 10.1 17.5 37.2 44.5 2 11.1 19.5 32.4 45.1 3 8.4 19.1 30.2 42.9 4 8.8 18.7 24.0 44.3 5 5.6 16.8 18.1 66.5 Notes: (a) Unemployment ratio refers to total unemployed expressed as a proportion of total population in same age range; (b) Unemployment rate refers to total unemployed as a proportion of total workforce in the same age range; (c) Jobless ratio refers to total jobless expressed as a proportion of total population in same age range; (d) Refers to total jobless expressed as a proportion of total non-student population in same age group (e) Completed grades 4-5 or less; (f) Completed grades 8-9; (g) General education, lyceum, gymnasium, vocational-technical. Source: UCW calculations based on Georgia Household Budget Survey, 2002 22. Not all Georgian young people face the same risk of unemployment. As shown in Table 5, aggregate figures for the 16-24 year-old population as a whole mask large variations in unemployment by individual and household characteristics. Young adults are more likely to experience difficulty in finding jobs than teenagers. Youth unemployment is negatively correlated to household income level and the educational 23. status of the household head. Young people from households headed by an unemployed person are much more likely to be themselves unemployed. Female youth face a lower risk of unemployment than male youth, but difference is not large. 24. A higher level of educational attainment does not appear to reduce the risk of unemployment faced by young people. Indeed, the opposite appears to hold true. As shown in Figure 2, 20-24 year-olds in the workforce with at least a special secondary education are more than twice as likely to be unemployed as their similarly-aged counterparts with secondary education or less. This is partially the product of the fact that less-educated young people by definition begin their transition to work at an earlier age, and therefore have had more time to secure employment. But even among 30-34 year-olds, all whom have had ample job search time, more educated persons face a greater risk of unemployment. This finding raises questions about the ability of SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 10 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA Figure 2. Young adult employment status, by level of education attainment and age cohort Source: UCW calculations based on Georgia Household Budget Survey 2002 the Georgian schooling system to equip young people with the requisite education and entry-level job skills demanded by the labour market. 4.2 Youth inactivity 25. A very large proportion of the Georgian youth population is also "inactive", i.e., neither in education nor the labour force. This group is also likely to be at risk of encountering difficulties in finding and sustaining stable employment. One-fifth of total Georgian young people, and over one-third of total non-students, is inactive, again with large variation by individual and household characteristics (Table 5).16 Levels of inactivity levels are much higher among young adults (20-24 year-olds) than adolescents (as more of the latter group are still in school), but actually peak during the period from 25-29 years for both males and females (Figure 3). Inactivity appears to have a particularly important gender dimension: females are much more likely than males to be inactive at every age, with the greatest variation by sex occurring during women's child-bearing years. Figure 3. Inactivity ratio, by age range and sex Source: UCW calculations based on Georgia Household Budget Survey 2002 16 Combining the inactive and the unemployed youth yields total jobless youth, another important indicator of youth employment disadvantage. Twenty-eight percent of total young people, and half of total non-students, are jobless. 11 UCW WORKING PAPER SERIES, NOVEMBER 2005 26. To what extent do inactive youth represent discouraged workers as opposed to persons who have opted for involvement in activities outside the labour force? Unfortunately, the data do not permit the drawing of a clear line between the two possibilities, meaning that estimates of inactivity (and joblessness) must be interpreted with caution. While some inactive youth may have left or never entered the labour force because of poor job prospects, others may be involved in domestic duties and/or child rearing and still others may be involved in non-formal education or similar activities contributing to their future employability. It is plausible that inactivity is more a reflection of employment difficulties for male youth than female youth, as males are unlikely to stay out of the labour force in order to perform domestic duties or rear children. 27. The issue of inactivity among young people is very important for its economic and social consequences and requires an in depth analysis that is beyond the scope of the present paper. 4.3 Youth employment conditions 28. Obtaining employment per se is an insufficient condition for a successful entry into the labour market. Indicators reflecting the conditions of the employed are also critical to assessing the labour market success of young people. This section examines key characteristics of youth employment. Data for a range of descriptive indicators relating to youth employment are analysed, in order to develop a statistical profile of young people's work. 29. Table 6, which breaks down the employed youth population by broad occupational category, indicates that non-waged labour performed within the household is by far the most important form of youth work. Almost three of every four employed young people work without monetary wages for their families. Most of this group works on family farms, a reflection of the continued importance of the agriculture sector in the Georgian economy. Of the remaining working youth, 16 percent are in waged employment and seven percent work on non-family farms. 30. Occupational category also varies considerably by individual and household characteristics: · Age: There is a shift away from family-based non-waged work and towards waged work outside the family as young people grow older. Non-wage family work still, however, accounts for two-thirds of total employment for the 20-24 age group; · Sex: Female youth are more likely than male youth to be in waged work; differences by sex in other occupational categories are generally small. But other forms of gender bias in the labour market are reportedly significant, and likely also affect young female workers;17 · Educational status of household head: The education of the household head appears to improve the chances of young people of securing paid work outside the household. Almost 40 percent of working youth of educated parents are in waged work, compared to only 13 percent of working youth of uneducated parents; 17 There is a large and persistent gap in earnings between men and women with similar characteristics (of about 10 percent on average controlling for other factors). The distribution in occupations is also unequal, with women overrepresented in semi-skilled positions and underrepresented in senior positions (World Bank Poverty Survey...FULL CITATION) SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 12 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA Table 6. - Youth employment characteristics by key background indicators, 16-24 years age group Occupational category Person Employee, Farmer working in Non-wage Ave. weekly Background characteristic wage labour working on non agric. labour in a Non-wage working or self Employer private or sector or in HH labour for a Other hours employed rented land professional enterprise friend activities Total 16.44 0.47 7.2 3.99 70.79 0.94 0.16 41.3 16-19 2.9 0.0 8.2 3.2 85.1 0.6 0.0 48.2 Age group 20-24 21.4 0.6 6.8 4.3 65.6 1.1 0.2 40.8 Male 1.6 0.0 12.0 4.7 81.2 0.5 0.0 53.5 16-19 Female 4.6 0.0 3.3 1.3 90.1 0.7 0.0 41.5 Total 2.9 0.0 8.2 3.2 85.1 0.6 0.0 48.2 20-24 Male 18.4 0.8 7.6 5.6 66.7 0.8 0.2 43.2 Female 26.7 0.3 5.6 2.1 63.6 1.5 0.3 37.5 Sex and age Total 21.4 0.6 6.8 4.3 65.6 1.1 0.2 40.8 group 25-29 Male 37.7 0.8 11.3 8.6 40.5 0.5 0.6 45.5 Female 40.7 0.5 6.9 3.4 48.3 0.2 0.0 31.2 Total 38.9 0.7 9.5 6.5 43.6 0.4 0.4 39.9 30-35 Male 32.3 2.3 15.8 14.0 34.6 0.5 0.5 47.3 Female 44.3 0.0 8.1 6.3 40.7 0.6 0.0 35.5 Total 37.6 1.3 12.4 10.6 37.3 0.5 0.3 41.8 Georgian 19.7 0.4 7.2 3.7 67.8 1.0 0.2 41.0 Azeri 2.0 1.3 9.8 6.5 79.7 0.7 0.0 50.0 Abkhazian 0.0 0.0 0.0 0.0 100.0 0.0 0.0 Greek 0.0 0.0 66.7 0.0 33.3 0.0 0.0 Nationality Ossetian 5.0 0.0 0.0 0.0 90.0 5.0 0.0 9.0 Russian 80.0 0.0 0.0 20.0 0.0 0.0 0.0 34.0 Armenian 8.7 0.0 5.3 1.3 84.0 0.7 0.0 32.2 Other 55.6 0.0 0.0 33.3 11.1 0.0 0.0 61.9 Employment Employed 12.8 0.5 6.5 3.7 75.7 0.8 0.1 41.0 status, HH Not employed 34.4 0.5 10.4 5.7 46.7 1.9 0.5 41.5 head Elementary or less(b) 13.3 0.0 10.8 6.0 69.9 0.0 0.0 29.5 Education Not completed 4.6 0.0 7.8 5.9 79.7 1.3 0.7 40.6 attainment of 2ndary(c) HH head Secondary(d) 14.8 0.5 6.8 3.5 73.4 0.9 0.1 43.1 Higher education 38.6 1.3 6.3 3.8 48.7 1.3 0.0 40.1 1 10.8 0.4 9.6 4.4 73.2 1.2 0.4 10.8 2 16.9 0.0 8.0 2.2 71.6 1.3 0.0 16.9 HH income quintile 3 11.8 0.4 4.4 2.2 79.8 1.5 0.0 11.8 4 15.2 1.0 8.3 3.8 71.4 0.3 0.0 15.2 5 28.8 0.4 5.8 7.5 56.7 0.4 0.4 28.8 Notes: (b) Completed 4-5 grades or less; (c) Completed 8-9 grades; (d) General education, lyceum, gymnasium, vocational-technical Source: UCW calculations based on Georgia Household Budget Survey 2002 · Household income: Poverty also appears to affect chances of obtaining waged employment. Over one-quarter of working youth from rich households are in paid work against only nine percent of working youth from poor households. Working youth from rich households also put in considerably longer weekly working hours than their poorer counterparts (44 hours versus 32 hours); and · Employment status of household head: Working youth of unemployed parents are much more likely to be in paid work than working youth of employed parents, suggesting that these young people are more often relied upon as family breadwinners. 13 UCW WORKING PAPER SERIES, NOVEMBER 2005 31. What do these breakdowns by occupation say about employment quality? The generally low level of waged employment and high level of informal work is significant given that waged employment is typically the most sought-after form of work among young people, and is most likely to offer a measure of job stability and some form of benefits coverage. Informal farm work, on the other hand, is typically low paid and seasonal, and studies indicate that this work does not constitute a reliable route out of poverty.18 In urban settings, informal work frequently means insecure, non-family work in settings where labour and safety regulations do not apply, leaving workers susceptible to workplace exploitation. In both urban and rural settings, work in the informal economy is generally a poor alternative to formal sector employment. Table 7. - Youth employment characteristics by age group and sex Age Contract type(a) Job stability(b) group Sex Written Verbal Regular Temp. Seasonal Casual Male 66.7 33.3 58.3 33.3 8.3 - 16-19 Female 28.6 71.4 66.7 22.2 11.1 - Total 40.0 60.0 61.9 28.6 9.5 - Male 86.1 13.9 76.4 8.1 12.2 3.4 20-24 Female 64.8 35.2 84.0 9.0 3.0 4.0 Total 76.4 23.6 79.4 8.5 8.5 3.6 Male 85.6 14.4 75.0 10.0 11.9 3.1 16-24 Female 62.2 37.8 82.6 10.1 3.7 3.7 Total 74.6 25.4 78.1 10.0 8.6 3.4 Notes: (a) Refers on to persons that are employees; (b) Refers only to persons that are employee, employer, or in non-agricultural sector or in professional activities Source: UCW calculations based on Georgia Household Budget Survey 2002 32. For the minority of children that are in formal sector work, around three-fourths enjoy written contracts and describe their employment as "regular" rather than "seasonal", "temporary" or "casual" (Table 7). 4.4 Youth labour market disadvantage 33. Comparing youth and adult unemployment rates provides some indication of the extent to which young workers are disadvantaged in relation to their adult counterparts in securing jobs. As shown in Table 8, young people and adults are roughly equally likely to find themselves unemployed, inactive or jobless. Young people in the workforce, however, are more than twice as likely as their adult counterparts to be without a job, suggesting that there are specific barriers to youth employment that need to be addressed by policymakers. young people in Eastern Europe and other Central Asia countries also find themselves in a disadvantaged labour market position relative to their adult counterparts (Figure 4). 34. The unemployment rate peaks among 20-24 year-olds, but remains very high among the following (25-29 years) population cohort, before falling sharply thereafter (Figure 6). This again illustrates that in many cases the period required to settle into work extends well into adulthood. The labour market status of 25-29 year-olds also constitutes an important policy concern. 18See, for example, World Bank Poverty Study GET FULL CITATION SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 14 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA Table 8. - Differences in youth and adult unemployment and jobless indicators Age group Unemployment ratio Unemployment rate Inactivity ratio Jobless ratio 16-19 4.8 18.8 16.1 20.9 Youth 20-24 11.1 25.2 21.4 32.5 16-24 8.8 23.6 19.5 28.3 Adult 25-55 9.1 11.45 19.3 28.4 16-19 0.53 1.64 0.83 0.74 Youth to adult 20-24 1.22 2.20 1.11 1.14 Ratios 16-24 0.97 2.06 1.01 1.00 Source: UCW calculations based on Georgia Household Budget Survey 2002 Figure 4. - Ratio of youth to adult unemployment rates, Georgia versus selected Central Asian and South-Eastern Europe countries, around 2001(a) Notes: (a) Survey methodologies and reference years differ across the countries; comparisons are therefore indicative only . Source: UCW calculations based on Household Budget Survey 2002, World Bank Labour Force Survey data and UNICEF TransMONEE database 2004 Figure 5. - Unemployment ratio, by age range and sex Source: UCW calculations based on Georgia Household Budget Survey 2002 Figure 6. - Unemployment rate, by age range and sex 15 UCW WORKING PAPER SERIES, NOVEMBER 2005 Source: UCW calculations based on Georgia Household Budget Survey 2002 35. Differences between youth and adults in terms of work characteristics also provide an indication of youth labour market disadvantage. As shown in Table 9, the occupational profile of young workers differs dramatically from their adult counterparts. While youth work is concentrated overwhelming in non-waged family employment, adult work is distributed more evenly across waged work, farm work and family work. Young people are much less likely than adults to be involved in waged work, and much more likely to be performing informal work. This suggests that adult workers in general enjoy a greater degree of job security and social protection, and are less exposed to the instability and various risks associated with informal sector work. Young people and adults differ little in terms of the intensity of work, each averaging around 41 working hours per week. Table 9. - Differences in youth and adult employment characteristics Work modality Ave. weekly Employee, Person working hours Employee, wage Farmer working in Non-wage Background characteristic Non-wage wage labour or Employer working on non agric. labour in alabour for a Other labour or self private or sector or in HH friend self employed rented land professional enterprise activities employed Youth (16-24 years) 16.4 0.5 7.2 4.0 70.8 0.9 0.2 41.3 Adults (25-54 years) 36.7 1.6 21.6 11.2 28.4 0.2 0.2 0.2 41.6 Source: UCW calculations based on Georgia Household Budget Survey 2002 Table 10. - Youth employment characteristics by age group and sex Contract type(a) Job stability(b) Age group Written Verbal Regular Temp. Seasonal Casual Youth (16-24 years) 74.6 25.4 78.1 10.0 8.6 3.4 Adults (25-54 years) 81.2 18.8 83.9 6.1 6.5 3.5 Notes: (a) Refers on to persons that are employees; (b) Refers only to persons that are employee, employer, or in non-agricultural sector or in professional activities Source: UCW calculations based on Georgia Household Budget Survey 2002 36. Among those in formal sector employment, adults are more likely than young people to benefit from a written contract and to enjoy "regular" rather than "temporary", "seasonal" or "casual" employment (Table 10). SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 16 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA 5. MEASURING THE DURATION OF THE TRANSITION FROM SCHOOL TO WORK19 37. The majority of youth, in both developed and developing countries, transits through school before entering beginning to work. Often some period of a time elapses between the end of the school cycle and the start of the productive cycle. The transition process from school to work serves different purposes and its length and nature are arguably the result of a variety of forces. 38. In the simplest human capital model, individuals acquire education up to the point where the marginal return to one additional year of education is higher than its marginal cost, the latter largely being the opportunity cost of being out of work. In this stylized model, there is no transition from school to work, as individuals start working just after they leave school, and there is no room for either voluntary or involuntary unemployment as the model implicitly assumes zero utility of leisure and excess labour demand. 39. In reality, though, such transition is unlikely to be immediate as young individuals will spend some time looking for the best job match. Wait unemployment can hence arise if there are returns to search. In addition, young workers might well experience consecutive spells of employment in different jobs as they search (on the job) for better opportunities than the one currently at hand or they might alternate periods of employment to periods of unemployment if on the job search is ineffective. 40. Even in a world when there is no return to search, and hence where there are no efficiency gains associated to the search process, (voluntary or involuntary) youth unemployment will arise is the demand labour is low relative to the supply (and wages do not adjust), or market wages is below workers' reservation wages. Young individuals who are looking for their first job are particularly at risk of falling into involuntary unemployment if they are poor substitutes for adult workers or there are rigidities in the labour market (such as hiring and firing costs20) that make the substitution between adult and young workers costly for the firm. Eventually young individuals might end up being absorbed into the labour market as the older cohorts retire, but this process might turn out to be lengthy and hampered by the arrival on the market of new cohorts of school leavers. Again, in a world with unemployment or inactivity, workers might alternate spells of employment and unemployment or change jobs as labour demand or reservation wages change over a worker's life cycle. 41. The process is made even more complex by the fact that school leaving time is endogenous and most likely influenced by the expectation about the transition to work and the kind of job that will be obtained at the end of the transition. A better understanding to this transition period would require integrating the analysis of optimal school leaving age with that of employment search and labour force participation.21 Here we limit our attention to the issue of measuring such a transition in a way that is suitable for cross country comparison and as a basis for further analysis. 42. Based on the above discussion, it should be clear that the transition from school to work is by no means a linear well defined process, with individuals leaving school once for all, possibly searching over a certain period of time and then landing in their first job, the latter being a definite port of entry into employment for life. Perhaps the 19For a more detailed discussion of the school to work transition issues and indicators see "Transition from education to the labour market in Sub-Saharan Africa: An analysis for 13 countries" ,UCW, 2005 20See for example Bentollilla and Bertola (1990) and Canziani and Petrongolo ( ) 21In a companion paper we are trying to approach these issues using a real option approach. 17 UCW WORKING PAPER SERIES, NOVEMBER 2005 start point of this transition is well defined if individuals never re-enter into school and if school attendance is universal. The greatest difficulty arises if one tries to define the end point of this transition. Individuals might alternate periods of employment to periods of unemployment, change jobs or possibly even stay out of work for the rest of their life. Young individuals might take up temporary jobs, work in the household farm or enterprise or devote to household chores for lack of better work opportunities or for the potential return these initial work experience have in terms of future employment and income prospects. These problems are particularly relevant in developed countries and in the urban areas of the developing countries where women's labour force participation (at least in the market) is low, individuals often associate work to schooling, and , most important, underemployment, self employment, home production, and causal employment are widespread. 43. Although in principle very important, the issues highlighted above make relatively little sense when one is confronted with the data, especially the ones from developing countries. In most cases the data provide only information on whether an individual in school and/or in employment (perhaps distinguishing between market and non-market work). In the next section, hence, we develop a simple indicator that in view of data limitations does not make justice of the issues raised above. 5.1 A Synthetic Indicator 44. We develop a simple indicator of transition from school to work that should be comparable across countries. In order to describe the transition process from school to work we derive the distribution of school leaving age and the distribution of age of entry into the first job. As a synthetic indicator of this transition we compute the difference between the average school leaving age and the average age of first entry into work. 45. We are not the first ones to attempt to describe the school to work transition process. For example OECD (1998a, 1999, 2000) uses the age at which 50 per cent of individuals are in employment to determine the end point of the transition. Measures of transition based on such definition implicitly assume that the overall portion of individuals getting into employment is above 50% (otherwise no transition would be ever completed) and that the overall proportion of individuals who enter in employment in any given country is roughly comparable (otherwise this indicator is biased by the overall differences in participation across countries). None of these assumptions is likely to be true, especially in developing countries. Similar problems occur when estimating the starting point of the transition. For example, OECD indicators implicitly assume that all children do transit through the school system and that the vast majority of them stays in school at least until the end of compulsory school. An assumption that can be hardly maintained in most developing countries. 46. While the assumptions at the base of the OECD indicator arguably represent no much of a problem in developed countries, they might be a serious source of bias, as just mentioned, in comparing data from developing countries with very different levels of overall labour market participation in adulthood, especially among women, and of school attendance. 47. Below we try to circumvent these problems by standardizing our measures of school to work transition to the population at risk, i.e. those who indeed eventually transit through school and participate to the labour force. 48. Ideally to model the transition process from school to work, one would need longitudinal data with detailed job history information that follow individuals from childhood into adulthood or alternatively cross sectional data with retrospective SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 18 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA information that allow to reconstruct work histories. In the absence of these data, which is generally the case in developed countries, one can use cross sectional data to measure the length of the transition. Under appropriate assumptions, the available cross sectional data allow consistently identify the parameters of interest. 49. Indicators and their interpretation depends on the underlying assumptions, we find then necessary to spend some time describing such assumptions also in order to favour comparability with other indicators. 50. Suppose there exists an age amin, such that for a>amin individuals never transit into school and such that for a<=amin individuals never transit out of school. 51. In this case at agemin at which those who ever transit through school all happen to be in school. In this case it is easy to show that if by S we denote the event of being in school, the probability of leaving school at age a, denoted by SLa is nothing but: (1) SLa=-[P(Sa+1)-P(Sa)] a>amin i.e. the change in enrolment across two consecutive ages. Equation (1) simply states that, if, say 90% of children arein school at age 10 and 80% are in school at age 11, then 10% of children must have dropped out between age 10 and age 11. 52. Assume in addition that for any age a=amax individuals never transit into work. Again this implies that at amax all who ever work are simultaneously in work. This assumption - that is admittedly more unrealistic than the previous one - rules exit from employment. before amax and exit from inactivity above amax. In this case, if by W we denote work and by EWa the probability of entry into work at age a this is (2) EWa =P(Wa+1)-P(Wa) aamin a [SLa/P(Samin)] and the distribution of age of entry into work is (4) E(EW)=a chi2 = 0.0000 variable Coef. Std. z P>|z| [95% Conf. nterval] Employ E age 0.1977 0.0270 7.32 0.000 0.1448 0.2507 age2 -0.0021 0.0005 -4.08 0.000 -0.0031 -0.0011 heduc_less then primary 0.3793 0.0602 6.30 0.000 0.2614 0.4973 heduc_not completedsecondary 0.4449 0.0558 7.97 0.000 0.3355 0.5544 Heduc completed secondary 0.2180 0.0359 6.07 0.000 0.1476 0.2884 lnexp 0.0654 0.0210 3.12 0.002 0.0243 0.1065 head_employ 0.4375 0.0306 14.30 0.000 0.3775 0.4974 Nationality dummies: Other -0.2439 0.0788 -3.10 0.002 -0.3983 -0.0895 Azeri 0.2417 0.0534 4.52 0.000 0.1369 0.3464 Armenian 0.3396 0.0559 6.07 0.000 0.2299 0.4492 _cons -4.5727 0.3514 -13.01 0.000 -5.2613 -3.8841 Study only age -0.1658 0.0486 -3.41 0.001 -0.2611 -0.0706 age2 -0.0011 0.0011 -1.06 0.288 -0.0032 0.0009 heduc_less then primary * -0.4867 0.0805 -6.05 0.000 -0.6445 -0.3290 heduc_not completedsecondary* -0.7062 0.0757 -9.32 0.000 -0.8547 -0.5578 Heduc completed secondary* -0.4127 0.0408 -10.11 0.000 -0.4927 -0.3327 ln hh. expenditure 0.1782 0.0272 6.56 0.000 0.1249 0.2315 Employment status of H. head* -0.3303 0.0370 -8.92 0.000 -0.4029 -0.2578 Nationality dummies: Other* -0.4432 0.1000 -4.43 0.000 -0.6392 -0.2472 Azeri* -0.8321 0.0822 -10.12 0.000 -0.9932 -0.6710 Armenian* -0.3895 0.0750 -5.20 0.000 -0.5364 -0.2426 _cons 3.6080 0.5632 6.41 0.000 2.5040 4.7119 /athrho -2.4199 0.3746 -6.46 0.000 -3.1540 -1.6858 rho -0.9843 0.0117 -0.9964 -0.9336 Likelihood-ratio test of rho=0: chi2(1) = 1706.77 Prob > chi2 = 0.0000 SCHOOL TO WORK TRANSITIONS IN GEORGIA: A PRELIMINARY 28 ANALYSIS BASED ON HOUSEHOLDS BUDGET SURVEY DATA TABLE A2.1:MARGINAL EFFECTS ON THE PROBABILITY OF BEEING EMPLOYED. Marginal effects after biprobit y = Pr(employ=1,studyonly=0) (predict, p10) = .43780473 variable dy/dx Std. Err. z P>|z| [ 95% C.I. ] X age 0.0779 0.0106 7.33 0.000 0.0571 0.0988 25.522 age2 -0.0008 0.0002 -4.08 0.000 -0.0012 -0.0004 680.329 heduc_less then primary * 0.1504 0.0236 6.38 0.000 0.1042 0.1966 0.075 heduc_not completedsecondary* 0.1760 0.0216 8.13 0.000 0.1336 0.2184 0.094 Heduc completed secondary* 0.0853 0.0139 6.13 0.000 0.0580 0.1126 0.634 ln hh. expenditure 0.0258 0.0083 3.12 0.002 0.0096 0.0420 4.074 Employment status of H. head* 0.1682 0.0113 14.83 0.000 0.1460 0.1905 0.695 Nationality dummies: Other* -0.0936 0.0292 -3.21 0.001 -0.1507 -0.0364 0.033 Azeri* 0.0960 0.0213 4.52 0.000 0.0544 0.1377 0.071 Armenian* 0.1348 0.0220 6.12 0.000 0.0916 0.1780 0.063 (*) dy/dx is for discrete change of dummy variable from 0 to 1 TABLE A2.2: MARGINAL EFFECTS ON THE PROBABILITY OF BEEING IN SCHOOL. Marginal effects after biprobit y = Pr(employ=0,studyonly=1) (predict, p01) = .08833069 variable dy/dx Std. Err. z P>|z| [95% C.I. ] X age -0.027 0.009 -3.10 0.002 -0.043 -0.010 25.522 age2 0.000 0.000 -1.10 0.273 0.000 0.000 680.329 heduc_less then primary * -0.058 0.007 -7.97 0.000 -0.073 -0.044 0.075 heduc_not completedsecondary* -0.076 0.006 -12.23 0.000 -0.088 -0.064 0.094 Heduc completed secondary* -0.071 0.008 -8.86 0.000 -0.087 -0.056 0.634 ln hh. expenditure 0.029 0.004 6.35 0.000 0.020 0.037 4.074 Employment status of H. head* -0.058 0.007 -7.83 0.000 -0.072 -0.043 0.695 Nationality dummies: Other* -0.053 0.009 -6.02 0.000 -0.070 -0.036 0.033 Azeri* -0.081 0.006 -13.74 0.000 -0.093 -0.070 0.071 Armenian* -0.049 0.008 -6.51 0.000 -0.064 -0.034 0.063 (*) dy/dx is for discrete change of dummy variable from 0 to 1