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MODELLING TIME OF UNEMPLOYMENT VIA COX PROPORTIONAL MODEL

MODELLING TIME OF UNEMPLOYMENT VIA COX PROPORTIONAL MODEL. Jan Popelka Department of Statistics and Probability University of Economics , Prague. Previous model. LABOR OFFICE IN PRIBRAM Subjects registered in January 2002 Follow-up period: from January 2002 to June 2003 (18 months)

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MODELLING TIME OF UNEMPLOYMENT VIA COX PROPORTIONAL MODEL

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  1. MODELLING TIME OF UNEMPLOYMENT VIA COX PROPORTIONAL MODEL Jan Popelka Department of Statistics and Probability University of Economics, Prague

  2. Previous model LABOR OFFICE IN PRIBRAM • Subjects registered in January 2002 • Follow-up period: from January 2002 to June 2003 (18 months) • 597 unemployed (175 right censored) FACTORS • age, sex, education Applied Statistics 2005

  3. Previous model • AGE and AGE^2 variables (continuous) DISPUTABLE CONCLUSIONS: • No relationship between sex and the probability of exiting to a job • No difference between subjects with tertiary and basic education Applied Statistics 2005

  4. New model LABOR OFFICE IN PRIBRAM • Subjects registered in 2002 • Follow-up period: January 2002 – July 2004 (30 months) • 4275 unemployed Applied Statistics 2005

  5. New model FACTORS • Age • Sex • Education • Season of registration by Labor office • Place of living • State of health • Martial status Applied Statistics 2005

  6. AGE Minimum 15 years Maximum 61 years Mean 33 years Median 30 years SEX Females 51% (52%) Males 49% (48%) PLACE OF LIVING Towns 58% Villages 42% New model - Factors Applied Statistics 2005

  7. New model - Factors EDUCATION • Basic 16% (18%) • Secondary without GCE 48% (50%) • Secondary with GCE 32% (29%) • Tertiary 4% (3%) (180 subjects) Applied Statistics 2005

  8. SEASON OF REGISTRATION Spring 20% Summer 28% Autumn 35% Winter 17% MARTIAL STATUS Single, divorced or widowed 56% Married or common-law marriage 44% STATE OF HEALTH Perfect 89% Disabled 4% Full or partial disability pension 7% New model - Factors Applied Statistics 2005

  9. Arguments for survival analysis • 1309 observations is right censored - no exit to job or lost to follow up • Duration of unemployment is positively skewed Applied Statistics 2005

  10. Cox proportional model • Distribution of duration of unemployment and error components is not known • Cox proportional hazard model • Estimated hazard ratios are easy to explain Applied Statistics 2005

  11. Comparison of alternative models Likelihood ratio test Applied Statistics 2005

  12. Cox proportional model estimation (* P<0.1, ** P<0.05, *** P<0.01) Applied Statistics 2005

  13. Survival function estimation Continuous age model.Female, basic education, registered in winter, perfect health condition, village, single. Distinction by age. Interval classified age model.Estimated survival function for female, basic education, registered in winter, perfect health condition, village, single. Distinction by age. Applied Statistics 2005

  14. Survival function estimation Interval classified age model. Female, 33 years old, registered in winter, perfect health condition, village, single. Distinction by level of education. Applied Statistics 2005

  15. Survival function estimation Interval classified age model. Male, 33 years old, secondary education with GCE, registered in winter, village, single. Distinction by state of health. Applied Statistics 2005

  16. Next research • Orientation on the Czech Republic as a complex • Influence of regional diversification should be examined • Influence of other factors • Relationship between the length of unemployment and the age of subjects Applied Statistics 2005

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