Nathan Vieira*, Zheng Wang**

Séminaires internes
phd seminar

Nathan Vieira*, Zheng Wang**

AMSE
What is the best discrete short-time work policy during recessions?*
The linking effect: causal identification and estimation of the effect of peer relationship**
Lieu

IBD Salle 24

Îlot Bernard du Bois - Salle 24

AMU - AMSE
5-9 boulevard Maurice Bourdet
13001 Marseille

Date(s)
Mardi 10 mai 2022| 11:00 - 12:30
Contact(s)

Kenza Elass : kenza.elass[at]univ-amu.fr
Camille Hainnaux : camille.hainnaux[at]univ-amu.fr
Daniela Horta Saenz : daniela.horta-saenz[at]univ-amu.fr
Jade Ponsard : jade.ponsard[at]univ-amu.fr

Résumé

*I propose an optimal short-time work policy and a new mechanism explaining the "German miracle" during the great recession. I show that firms facing financial constraints can adopt a suboptimal employment decision when experiencing an unanticipated productivity shock. In this perspective, the policy-maker can remove rigidities in the labor market and finance a short-time work policy to allow firms to adopt an employment decision closer to the optimal one. Therefore, the short-time work policy positively affects employment, aggregate production, and workers' utility during and after recessions. I model a two-period labor market with a representative worker, a representative firm and a policy-maker. During the first period, a negative productivity shock that has a lasting effect hit the economy. Depending on the capacity of the labor market to adapt to the new economic condition through the hourly wage, the short-time compensation level, and the number of hours worked, the shock can lead to excessive layoffs. Then, I study whether the intervention of a budget constraint policy is desirable and what is the optimal short-time work policy.

**In this paper I propose a new causal framework to study the effect of peer relationships. Moreover, an identification strategy based on unconfoundedness is provided for peer networks that are endogenously formed. Thanks to the nature of network data, confounders can be inferred from the adjacency matrix, and therefore the identification does not require the assumption that all confounders have been observed. The identification strategy suggests the use of propensity score based estimators, which means estimation can be easily and flexibly done with existing statistical packages. Finally, an empirical application on the effect of friendship is analysed.