| Abstract [eng] |
SUMMARY 77 pages, 21 tables, 16 pictures, 95 references This paper aims to assess the effects of active labour market policy (ALMP) on employment in Lithuania. It examines employment and unemployment trends, as well as the allocation of funds for implementing these policy measures. The study analyses and synthesises scientific literature, strategic and legal documents, databases, and other sources of information. Data from the Lithuanian Employment Service, Eurostat, and the Lithuanian Statistics Department were used to conduct the research. In order to evaluate the impact of active labour market policy measures on employment, the study utilises descriptive statistics methods, such as data grouping and graphical modelling, to identify changes in the relevant indicators. Additionally, correlation analysis, Granger causality tests, and regression analysis are conducted. Summarising the analysis process, Pearson correlation coefficient revealed that the ALMP measures of support for training, supported employment, and mobility support exhibited the strongest relationship with the employment rates of different demographic groups in Lithuania from 2008 to 2021. These measures demonstrated a significant correlation with the employment rates of women, men, older individuals (55-64 years), and youth (16-29 years). On the other hand, the ALMP support for job creation displayed the weakest connection with all the target population groups examined. After conducting a correlational analysis between ALMP measures and the employment level in Lithuania in 2008-2021, it can be stated that the dependence between the number of persons sent to ALMP measures and the employment level was average - 0.7. The strongest correlation, i.e. - 0.9, determined between the level of employment and the ALMP measure - supported employment, since as employment increases, the number of people participating in this measure decreases. Also, there was an average negative dependence between the number of individuals sent to ALMP measures and registered job vacancies, since as registered job vacancies increase, the number of people sent to active labor market measures decreases. In addition, a Granger causality test was conducted to investigate the relationship between the number of individuals sent to ALMP measures and the employment level in Lithuania from 2008 to 2021. According to the results of the Granger causality test, when the dependent variable is the level of employment and the independent variable is the number of persons sent to ADRP measures, it is likely that ADRP measures could be the cause of employment. Moreover, it was also observed that not only the ALMP measures had an impact on the growth of the employment level in Lithuania, but also the employment level had an impact on the number of people sent to the ALMP measures. Furthermore, a linear multiple regression model was developed to assess the influence of various economic indicators on changes in the employment level. The model considered indicators such as foreign direct investment at the end of the period, gross domestic product per inhabitant at the prices of that time, a minimum monthly wage, inflation, tax wedge, and expenses for social benefits. Among these factors, the gross domestic product at the prices of that time and social welfare expenses were identified as likely impacting changes in employment in Lithuania between 2008 and 2021. Finally, lagging regression calculations indicated that the number of persons sent to ALMP measures would affect changes in the employment level with an average delay of 1-2 years. |
