Work in progress
In this paper we investigate the role of firms when they face a mass layoff. We investigate a simple question: `when things go bad, who gets fired first?'. Using administrative and survey data for France, we first show that the companies that had a mass layoff used this event to restructure their workforce. We observe a small but significant increase in the composition of social skills and a decrease in manual skills and cognitive skills within the firm, as compared to the control group. The restructuring of the workforce demonstrates that firms use layoff strategically to recompose, and then selective displacement plays an important role. We also investigate the factors that determining who is fired. The results indicate that firms strategically chose which workers to displace, and that demographic characteristics, perceived cost and skills mismatch are determining factors.
This paper gives a new answer to an old question in labor economics, ``Who matches with whom?'', by introducing a setting where firms and workers are different in many dimensions and we allow workers to be over and under qualified for the jobs they end up occupying. I present a random search model with two sided multidimensional heterogeneity in which firms choose and post a wage with commitment i.e. maintaining the posted wage, independent of the productivity of the new worker. Posted wages determine the set of acceptable jobs for each worker and a unique applicants pool for each firm. The composition of these sets varies in size and composition across workers and firms. The optimal posted wage level takes into consideration the requirements of each firm and the characteristics of the applicants pool. In equilibrium, sorting is assortative but mismatches can occur across all skills dimensions. Using French data on workers observed skills and matches, I estimate the structural parameters associated with the model for France. I find that the disutility of non cognitive skills is higher when mismatched, while employers value more highly good matches on cognitive skills. I also find that the number of dimensions plays an important role, since it is another source for frictions.
- Matching heterogeneous skills demand and supply under limited rationality (with D. Margolis)
This paper models the labor market matching process when skills are multidimensional and workers are naive about the strategic behavior of their competitors. Using supply and demand side data on multidimensional skills from Colombia, the paper numerically solves for the equilibrium allocation of workers to jobs that solves the naive worker problem and finds that the allocation is inefficient, in that workers over-weight job availability at the expense of matching to jobs for which they are over-qualified, leaving less qualified workers to match to jobs with higher skill demands. Three counterfactual simulations suggest training of long-term unemployed can be the most effective at improving the efficiency of the allocation of workers to jobs by both making them better matches for medium skilled jobs and by reducing the likelihood that high skilled individuals will be hired for jobs for which they are overqualified, providing them an incentive to apply increasingly for high-skilled jobs.
- Which Workers are Most Exposed to covid-19 and Social Distancing Effects in a Dual Labour Market? (link)(with D. Bosworth aand J. Cárdenas) Revista de Economía del Rosario, Vol. 24 Núm. 2 (2021): 24-2
Efectos de corto plazo del COVID-19 sobre la desigualdad del ingreso laboral en Colombia. Book chapter. (forthcomming)
Metodología para el análisis de demanda laboral mediante datos de internet: el caso colombiano. (with J. Cárdenas and J. Guataqui) Revista de Economía del Rosario, 18(01), 93-126. (2015)
La problemática del análisis laboral de demanda en Colombia. (with J. Cárdenas and J. Guataqui) Perfil de Coyuntura Económica, (24), 71-107. (2014)
- Colombian Atlas of Economic complexity. (Bancoldex and CID Harvard). Vacancies collection, consolidation and processing.