Internal labour market mobility in 2005–2014 in Latvia: the micro data approach

Abstract

Based on labour force survey micro data for 2005-2014 this research evaluates labour market internal mobility in Latvia comparing periods before, during and after the crisis. We also provide the comparison of Latvia's situation with other euro area countries, which is of particular interest since labour flow statistics for Latvia are not present in major reports on the European labour market. Labour flow estimates and the survival analysis indicate that labour market in Latvia is internally mobile; it accelerated economic recovery after the crisis and is enhancing Latvia's ability to adjust quickly to internal and external shocks. The flexibility of contract options and working hours, serve as a labour market mobility boosting mechanism. The survival analysis indicates that the flows from/to employment to/from unemployment in Latvia are determined by the characteristics of particular worker groups and the performance of particular sectors of the economy. ARTICLE HISTORY

Análisis de las transiciones ocupacionales en México. Una aproximación a través de un modelo paramétrico flexible

“…Respecto a la escolaridad, varios autores coinciden en que los mayores niveles de instrucción disminuyen el riesgo de transitar de la ocupación a otros estados (Fadejeva y Opmane, 2016;Fabrizi y Mussida, 2009;Ortiz, 2005). Por ejemplo, Kaiser (2006) afirma que las personas con educación superior en ocupaciones tecnológicamente orientadas tienen una probabilidad relativamente menor de perder el trabajo en comparación con quienes sólo cuentan con educación secundaria.…”

Assessing the Job-Finding Probability of Older and Prime-Age Unemployed Workers

“…For the sake of simplicity, we prefer to adopt a model involving only those older and prime-age unemployed workers who have remained active on the labour market after job loss. See, e.g., Fadejeva and Opmane (2016) for an analogous estimation strategy.…”

“…The explanatory variables include years of education, and the coefficients are insignificant in all the models applied. Fadejeva and Opmane (2016) estimate the impact of three different types of tertiary education (social sciences, technical sciences, and other) on the job-finding probability of unemployed individuals in Latvia during 2005-2014. They find a significantly positive impact over the whole period investigated (relative to secondary education) only for unemployed workers with a degree in social sciences.…”