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Social Security Programs and Retirement around the WorldMicro-Estimation$
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Jonathan Gruber and David A. Wise

Print publication date: 2004

Print ISBN-13: 9780226310183

Published to Chicago Scholarship Online: February 2013

DOI: 10.7208/chicago/9780226309989.001.0001

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PRINTED FROM CHICAGO SCHOLARSHIP ONLINE (www.chicago.universitypressscholarship.com). (c) Copyright University of Chicago Press, 2020. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in CHSO for personal use.date: 05 June 2020

Estimating Models of Retirement Behavior on French Data

Estimating Models of Retirement Behavior on French Data

Chapter:
(p.235) 4 Estimating Models of Retirement Behavior on French Data
Source:
Social Security Programs and Retirement around the World
Author(s):

Ronan Mahieu

Didier Blanchet

Publisher:
University of Chicago Press
DOI:10.7208/chicago/9780226309989.003.0005

This chapter, which examines the factors that determine retirement behavior in France, begins by reviewing the features of the French pension system. The analysis concentrates on two subpopulations: wage earners belonging to the private sector and civil servants. The chapter gives a detailed account of rules governing pensions for these two categories, including possibilities of early exit from the labor force, through either early retirement or specific features of unemployment insurance. It then describes data sets used and explains why the analysis focuses on three specific cohorts: cohort 1930 for workers in the private sector, and cohorts 1930 and 1932 for civil servants. Next, the chapter moves to a descriptive analysis of incentives to withdraw from the labor force that apply to these cohorts, given their specific histories. These incentives are then introduced in probit models of withdrawal from the labor force. The final section presents simulations derived from these models.

Keywords:   France, pension system, private-sector employees, civil servants, early retirement, probit models, labor force

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