Determinants of unemployment duration in Ukraine

Abstract

This paper presents first evidence on the determinants of unemployment duration in Ukraine between 1997 and 2003, using individual-level data from the first wave of the Ukrainian Longitudinal Monitoring Survey (ULMS -2003). It investigates the conditional probability of an individual leaving unemployment to employment or economic inactivity in any particular month of his spell out of work by estimating it in a discrete time independent competing risks framework with flexible baseline hazard rates and gamma-distributed unobserved heterogeneity. The results in all specifications indicate no significant effect of receiving unemployment benefits but significant negative effect of having income from casual activities, subsidiary farming, household income or pension on the hazard of reemployment. Multivariate analysis also suggests that policies to reduce long-term unemployment should focus on older workers, less educated individuals, residents of small towns and rural area in the regions with relatively high unemployment rates. Olga Kupets NON-TECHNICAL SUMMARYThe persistent and stagnant character of unemployment over the last decade in Ukraine has become an overwhelming concern for policymakers and for society in general. The problems of unemployment are aggravated even more because the incidence of long-term unemployment and the average duration of unemployment appear to have decreased slowly in response to increases in labor demand in previous years. This implies that there are potentially serious barriers existing between long-term unemployed and new job opportunities. Consequently, one possible way to tackle the problem of long-term unemployment in Ukraine is to combat the inflow into long-term unemployment by offering more assistance to job losers before they reach the stage of long-term unemployment (i.e. preventive measures). A second important way is to apply measures focused on the needs of the more disadvantaged groups which aim at reducing the existing stock of chronic unemployed. In this context, it is of vital importance to understand the forces which tend to shape the structure of unemployment duration and its dynamics in order to properly design the social and economic policy model. The main purpose of this study is to determine factors which affect the probability of reemployment or withdrawing from the labor force after a period of unemployment in Ukraine over the last years. In particular we look at the impact of unemployment benefits and alternative sources of income during an unemployment spell, various individual and local labor market characteristics.The theoretical framework of our empirical study is job search approach. This paper builds on previous works in developed countries by estimating the conditional probability of leaving unemployment in a discrete time independent competing risks framework with flexible baseline hazard rates and gamma-distributed unobserved heterogeneity. The data base is a sample of unemployment spells experienced by individuals over the period

Costs and Benefits of Labour Mobility between the EU and the Eastern Partnership Partner Countries - Country Report: Ukraine

“…Indeed, as shown by Lehmann et al (2010), workers with high school and college education are less likely to be displaced or quit jobs than less educated workers. Kupets (2006) finds that higher education significantly increases the employment hazard rate.…”

“…Bank Ukraine "Labour Demand Study" (2009) 27 reports an oversupply of white-collar workers and a deficit of blue-collar, especially skilled, ones. Fedorenko (2008) reports that the number of students in colleges and universities was more than five times higher than the number of students in technical and vocational schools, while in the Ukrainian job market only 20% of vacancies require university degrees and 80% of vacancies require other levels of skill.…”

“…Despite this, the share of people with higher education among migrants is lower than in the Ukrainian population. Note also, while people with higher education are more likely to find a job in Ukraine (Kupets, 2006), the returns to education are lower in Ukraine than in most other European and CIS countries (Coupe and Vakhitova, 2011).…”

Application of correspondence analysis to the identification of the influence of features of unemployed persons on the unemployment duration

“…The problem of the intensity of seeking work is more rarely analysed [Taşçı 2008]. Most results of the analyses shows that a higher level of education shortens the duration of unemployment [Kupets 2006, data: Ukrainian Longitudinal Monitoring Survey, 1998Bieszk-Stolorz and Markowicz 2011, data: Local Labour Office Szczecin 2011, survival analysis for censored data, Kaplan-Meier estimator, Cox regression; Grogan and van den Berg 2001, data: Russian Longitudinal Monitoring Survey, 1994-1996Mavridis 2015, data: British Household Panel Survey, 1991, survival functions, Kaplan-Meier estimator, Cox proportional hazard model]. The same conclusion could be found in Kerckhofes, de Neubourg, and Palm [1994]; Ahn, de la Rica, and Ugidos [1999]; Daras and Jerzak [2005]; Carroll [2006]; Grzenda [2012]; Sasaki, Kohara, and Machikita [2013]; Kołodziejczak and Wysocki [2013]; Rotaru [2014].…”

“…There is a difference between women and men. Married men have higher chances of getting work and their unemployment duration is shorter [Kupets 2006;Long 2009;Grzenda 2012]. However married women have lower chances for getting work and their unemployment duration is longer [Stetsenko 2003].…”