The first chapter studies the effect of employer concentration on the provision of on-the-job training and their combined impact on wages. I develop an oligopsony model of the labor market, where employers strategically decide wages and on-the-job training investment according to the employment concentration they face in a local labor market. High levels of employer concentration reduce both the separation and recruitment wage elasticities. As a result, employers in highly concentrated markets find hiring new workers more challenging, yet losing employees poached by competitors is at the same time more unlikely. On top of increasing workers' productivity, on-the-job training has an ambiguous effect on labor supply elasticities. Testable predictions for training and wages are derived and confronted with comparable microdata on training from Italy. Specifically, I estimate with an instrumental variable approach that high employer concentration in a local labor market (i) positively affects employer-provided training, (ii) reduces wages, and (iii) decreases the productivity returns of training investment. Finally, these findings suggest that using employer concentration as a direct measure of labor market competition underestimates the negative effect of concentration on wages. The second chapter provides a new set of stylized facts on firm provision of on-the-job training and local labor market competition by exploiting the language used in job vacancies. We take a supervised machine learning approach to identify training offers in more than 12 million US job vacancies. We show our measure correlates well with established on-the-job training measures at the occupation, industry, and regional level. We find that around 20% of job posts offer on-the-job training, with an upward trend over the last decade. Training offers are positively correlated with local labor market concentration, a finding that is robust to an instrumental variables strategy based on the local differential exposure to national firm-level trends. Moving from the first to the third quartile of labor concentration increases training by almost 5%. We interpret our results through the lens of a directed search model where training acts to reduce the queue to fill a vacancy and training has a greater expected benefit to the employer in less competitive labor markets given the lower separation rates. The third chapter analyses the relationship between labor market concentration and employers' skill demand. Using a novel data set on Italian online job vacancies during 2013-2018 we show that employers in a highly concentrated labor market demand competencies associated with the ability of workers to learn faster (e.g. Social skills) rather than actual knowledge. They also require less experience but higher education. These results are consistent with the hypothesis that employers in more concentrated labor markets are more prone to train their employees. Instead of looking for workers who already have job-specific skills, they look for workers who can acquire them faster and efficiently.
Essays on Labor Market Competition and On-the-Job Training
MARCATO, ALBERTO
2023
Abstract
The first chapter studies the effect of employer concentration on the provision of on-the-job training and their combined impact on wages. I develop an oligopsony model of the labor market, where employers strategically decide wages and on-the-job training investment according to the employment concentration they face in a local labor market. High levels of employer concentration reduce both the separation and recruitment wage elasticities. As a result, employers in highly concentrated markets find hiring new workers more challenging, yet losing employees poached by competitors is at the same time more unlikely. On top of increasing workers' productivity, on-the-job training has an ambiguous effect on labor supply elasticities. Testable predictions for training and wages are derived and confronted with comparable microdata on training from Italy. Specifically, I estimate with an instrumental variable approach that high employer concentration in a local labor market (i) positively affects employer-provided training, (ii) reduces wages, and (iii) decreases the productivity returns of training investment. Finally, these findings suggest that using employer concentration as a direct measure of labor market competition underestimates the negative effect of concentration on wages. The second chapter provides a new set of stylized facts on firm provision of on-the-job training and local labor market competition by exploiting the language used in job vacancies. We take a supervised machine learning approach to identify training offers in more than 12 million US job vacancies. We show our measure correlates well with established on-the-job training measures at the occupation, industry, and regional level. We find that around 20% of job posts offer on-the-job training, with an upward trend over the last decade. Training offers are positively correlated with local labor market concentration, a finding that is robust to an instrumental variables strategy based on the local differential exposure to national firm-level trends. Moving from the first to the third quartile of labor concentration increases training by almost 5%. We interpret our results through the lens of a directed search model where training acts to reduce the queue to fill a vacancy and training has a greater expected benefit to the employer in less competitive labor markets given the lower separation rates. The third chapter analyses the relationship between labor market concentration and employers' skill demand. Using a novel data set on Italian online job vacancies during 2013-2018 we show that employers in a highly concentrated labor market demand competencies associated with the ability of workers to learn faster (e.g. Social skills) rather than actual knowledge. They also require less experience but higher education. These results are consistent with the hypothesis that employers in more concentrated labor markets are more prone to train their employees. Instead of looking for workers who already have job-specific skills, they look for workers who can acquire them faster and efficiently.File | Dimensione | Formato | |
---|---|---|---|
Marcato Alberto, PhD Thesis.pdf
accesso aperto
Descrizione: Marcato Alberto, PhD Thesis
Tipologia:
Tesi di dottorato
Dimensione
6.98 MB
Formato
Adobe PDF
|
6.98 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.