Journal for Labour Market Research最新文献

This paper presents an average treatment effect analysis of Spain's furlough program during the onset of the COVID-19 pandemic. Using 2020 labour force quarterly microdata, we construct a counterfactual made of comparable nonfurloughed individuals who lost their jobs and apply propensity score matching based on their pretreatment characteristics. Our findings show that the probability of being re-employed in the next quarter significantly increased for the treated (furlough granted group). These results appear robust across models, after testing a wide range of matching specifications that reveal a reemployment probability premium of near 30 percentage points in the group of workers who had been furloughed for a single quarter. Nevertheless, a different time arrangement affected the magnitude of the effect, suggesting that it may decrease with the furlough duration. Thus, an analogous analysis for a longer (two quarter) scheme estimated a still positive but smaller effect, approximately 12 percentage points. Although this finding might alert against long lasting schemes under persistent recessions, this policy still stands as a useful strategy to face essentially transitory adverse shocks.

In response to COVID-19 most governments used some form of lockdown policy to manage the pandemic. This required making iterative policy decisions in a rapidly changing epidemiological environment resulting in varying levels of lockdown stringency over time. While studies estimating the labour market effects of lockdown policies exist in both developed and developing countries, there is limited evidence on the impact of variation in lockdown stringency, particularly in developing countries. Such variation may have large heterogenous effects both on aggregate and between worker groups. In this paper, we estimate the causal effect of lockdown stringency on employment probabilities, adopting a quasi-experimental design on unique labour force panel data from South Africa. South Africa is a useful case study given its upper-middle-income status and relatively small informal sector, thus serving as an example to a variety of developing and developed country economies. We find that the negative employment effects of the country's lockdown policy were driven by effects on the informal sector. Furthermore, we observe important effect heterogeneity by employment formality as the stringency of the country's lockdown regulations changed over time. We find that more stringent lockdown levels negatively affected informal, but not formal sector employment, while less stringent levels negatively affected formal, but not informal sector employment. From a policy perspective, evidence of such heterogeneity can inform decisions around the optimal targeting of support as the pandemic progresses and lockdown policies are reconsidered.

Latin America was one of the regions hardest hit by the COVID-19 pandemic. This paper analyses, from a dynamic and comparative perspective, labour transitions triggered by the pandemic in six Latin American countries: Argentina, Brazil, Costa Rica, Mexico, Paraguay, and Peru. Special attention is paid to transits around labour informality during this period. Unlike previous crises, the fall in informal occupations deepened the overall contraction in employment. This was explained by a significant increase in exit rates from these jobs and, to a lesser extent, by reductions in entry rates. Most of the informal workers who lost their jobs left the labour force. Contrary to this labour movement, transits from informal to formal jobs significantly dropped during the most critical phase in this crisis. Partial recovery in employment since mid-2020 has been led by an increase in informal jobs. The labour dynamic has been different between men and women. This study reveals the relevance of dynamic analysis to clearly identify labour transitions that occurred during a labour crisis of unprecedented intensity and characteristics in Latin America.

Supplementary information: The online version contains supplementary material available at 10.1186/s12651-023-00342-x.

Background: The influence of both individual factors and, in particular, the regional labour market on the return to work after medical rehabilitation is to be analyzed based on comprehensive administrative data from the German Pension Insurance and Employment Agencies.

Method: For rehabilitation in 2016, pre- and post-rehabilitation employment was determined from German Pension Insurance data for 305,980 patients in 589 orthopaedic rehabilitation departments and 117,386 patients in 202 psychosomatic rehabilitation departments. Labour market data was linked to the district of residence and categorized into 257 labour market regions. RTW was operationalized as the number of employment days in the calendar year after medical rehabilitation. Predictors are individual data (socio-demographics, rehabilitation biography, employment biography) and contextual data (regional unemployment rate, rehabilitation department level: percentage of patients employed before). The estimation method used was fractional logit regression in a cross-classified multilevel model.

Results: The effect of the regional unemployment rate on RTW is significant yet small. It is even smaller (orthopaedics) or not significant (psychosomatics) when individual employment biographies (i.e., pre-rehabilitation employment status) are inserted into the model as the most important predictors. The interaction with pre-rehabilitation employment status is not substantial.

Conclusions: Database and methods are of high quality, however due to the nonexperimental design, omitted variables could lead to bias and limit causal interpretation. The influence of the labour market on RTW is small and proxied to a large extent by individual employment biographies. However, if no (valid) employment biographies are available, the labour market should be included in RTW analyses.

Supplementary information: The online version contains supplementary material available at 10.1186/s12651-023-00330-1.