A Kink that Makes You Sick: the Effect of Sick Pay on Absence in a Social Insurance System

Petri Böckerman (), Ohto Kanninen and Ilpo Suoniemi

No 297, Working Papers from Työn ja talouden tutkimus LABORE, The Labour Institute for Economic Research LABORE

Abstract: We examine the effect of the replacement rate of a social insurance system on sickness absence by exploiting a regression kink design. The elasticity of absence with respect to the benefit level, in addition to risk preferences, is a critical parameter in defining the optimal sickness insurance scheme. Using a large administrative dataset, we find a robust behavioral response. The statistically significant point estimate of the elasticity of the duration of sickness absence with respect to the replacement rate in a social insurance system is on the order of 1. Given our estimate, we characterize the optimal benefit level.

Keywords: Sick pay; labor supply; sickness absence; regression kink design; social insurance (search for similar items in EconPapers)
JEL-codes: H55 I13 J22 (search for similar items in EconPapers)
Pages: 55 pages
Date: 2015-11-18
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://labore.fi/wp-content/uploads/2015/11/Tyopapereita-297.pdf First version, 2015 (application/pdf)

Related works:
Working Paper: A Kink that Makes You Sick: the Effect of Sick Pay on Absence in a Social Insurance System (2014)
Working Paper: A Kink that Makes you Sick: the Effect of Sick Pay on Absence in a Social Insurance System (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pst:wpaper:297

Access Statistics for this paper

More papers in Working Papers from Työn ja talouden tutkimus LABORE, The Labour Institute for Economic Research LABORE Contact information at EDIRC.
Bibliographic data for series maintained by Jaana Toivainen ().