Influence of vocational training on wages and mobility of workers - evidence from Poland Jacek Liwiński Faculty of Economic Sciences, University of Warsaw.

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Presentation transcript:

Influence of vocational training on wages and mobility of workers - evidence from Poland Jacek Liwiński Faculty of Economic Sciences, University of Warsaw

Human capital theories  Becker’s theory (1962)  New theories: eg. Acemoglu, Pischke (1999) Different assumptions: – Perfect vs. imperfect competition in the labour market University of Ljubljana, September 2009

 Assumptions: – Perfect competition in the labour market – Investments in general vs. specific human capital – Human capital may be specific for firms, economic sectors or occupations Becker (1962)

 Implications: 1.Investment in general human capital: – is financed by employee only – increases employee’s wage – has no influence on employee’s mobility 2.Investment in specific human capital: – is financed by both employee and employer – increases employee’s wage – decreases employee’s mobility

Acemoglu, Pischke (1999)  Assumption: Imperfect competition in the labour market – different reasons: – Cost of changing jobs – Asymmetry of information – Efficiency wages – Human capital is not perfectly transferable

Acemoglu, Pischke (1999)  Implication: Investment in general human capital may be financed by an employee: – If expected mobility of the employee is low, – And if the resulting increase in productivity exceeds the increase in wage

Goals 1.To analyse the influence of vocational training on employees’ mobility between: – firms, – economic sectors, – occupations. 2.To analyse the influence of vocational training on wages in the present job (firm).

Analysis of mobility: (1) Data  Polish Labour Force Survey, : – Employees at the age of 15-59/64, – Quarterly and yearly panels

Analysis of mobility: (2) Dependent variables  Mobility between firms: 1 – employee flows to another firm between period t 0 and t 1 in a panel, 0 – no flow between firms (base category)  Mobility between economic sectors: 1 – employee flows to another economic sector between period t 0 and t 1 in a panel, 0 – no flow between sectors (base category)

Analysis of mobility: (2) Dependent variables  Mobility between occupations: 1 – employee flows to another 5-digit occupation between period t 0 and t 1 in a panel, 2 – employee flows to another 3-digit occupation between period t 0 and t 1 in a panel, 3 – no flow between occupations (base category)

Analysis of mobility: (3) Independent variables 1.Participation in a vocational training 2.General employee’s characteristics (gender, age, level of education, place of residence) 3.Employee’s characteristics associated with present job (job tenure, wages, working time, type of contract, occupation) 4.Characteristics of employer (economic sector, firm size, ownership sector)

Analysis of mobility: (4) Econometric model  In case of mobility between firms and mobility between economic sectors: logit model  In case of mobility between occupations: multinomial logit model

Analysis of mobility: (5) Problem of endogeneity  Employers may be training first of all the least mobile workers  Some trainings may be associated with the willingness to change a job (firm and/or occupation)

Analysis of mobility: (6) Results 1.Mobility between firms: – Neither general nor specific trainings have a significant influence on mobility between firms 2.Mobility between economic sectors: – General trainings do not have a significant influence on mobility between sectors – Specific trainings have a negative influence on mobility between sectors – On average the probability of flowing between 3- digit occupations within a year is 3,2%, while in case of participants of specific training – 1,9%.

Analysis of mobility: (6) Results 3.Mobility between occupations: – General trainings do not have a significant influence on mobility between occupations – Specific trainings do not have a significant influence on mobility between 5-digit occupations, but they have a negative influence on mobility between 3- digit occupations. – On average the probability of flowing between 3- digit occupations within a year is 1,2%, while in case of participants of specific training – 0,6%.

Analysis of wages: (1) Data  Polish Labour Force Survey, : – Employees at the age of 15-59/64, – Quarterly and yearly panels

Analysis of wages: (2) Dependent variable  Growth rate of hourly net wage in the period of a quarter or a year after participation in a vocational training.

Analysis of wages: (3) Independent variables 1.Participation in a vocational training 2.General employee’s characteristics (gender, age, level of education, place of residence) 3.Employee’s characteristics associated with present job (job tenure, wages, working time, type of contract, occupation) 4.Characteristics of employer (economic sector, firm size, ownership sector)

Analysis of wages: (4) Econometric model  OLS linear regression

Analysis of wages: (6) Results 1.Participation in general training has a positive impact on wages. 2.Participation in specific vocational training does not have any influence on wages.

Conclusions The results of the analysis only partially support the predictions of the Becker ’ s theory. 1.In agreement with the theory: – investments in general training do not have any influence on worker ’ s inter-firm mobility and have a positive impact on wages, – investments in specific human capital significantly decrease the probability of changing an occupation or an economic sector.

Conclusions 2.It is not consistent with the theory that: – investments in specific human capital do not have any influence on inter-firm mobility, – specific vocational training does not have any influence on wages.

Thank you for your attention.