The aggregate implications of changes in the labour force composition
The aggregate implications of changes in the labour force composition
Labour composition by gender, age, and education has undergone dramatic changes over the last half century in the United States. Furthermore, the volatility of total market hours differs systematically between genders, age, and education groups. Reduced form exercises and a large-scale business cycle model suggest that these demographic patterns account for between 15% and 30% of the observed changes in aggregate volatility over this period of time. Furthermore, these demographic changes are responsible for a considerable fraction of the average growth rate of GDP. To solve the model over this large transition, a new algorithm is developed which extends perturbation methods to the stochastic transition path and can be applied to a broad class of DSGE models.
University of Southampton
Mennuni, Alessandro
18a3b238-2d5b-4219-8d50-7c87765007a4
8 February 2018
Mennuni, Alessandro
18a3b238-2d5b-4219-8d50-7c87765007a4
Mennuni, Alessandro
(2018)
The aggregate implications of changes in the labour force composition
Southampton.
University of Southampton
52pp.
Record type:
Monograph
(Working Paper)
Abstract
Labour composition by gender, age, and education has undergone dramatic changes over the last half century in the United States. Furthermore, the volatility of total market hours differs systematically between genders, age, and education groups. Reduced form exercises and a large-scale business cycle model suggest that these demographic patterns account for between 15% and 30% of the observed changes in aggregate volatility over this period of time. Furthermore, these demographic changes are responsible for a considerable fraction of the average growth rate of GDP. To solve the model over this large transition, a new algorithm is developed which extends perturbation methods to the stochastic transition path and can be applied to a broad class of DSGE models.
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lab comp 08 02 2018 submission EER
- Author's Original
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Published date: 8 February 2018
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Local EPrints ID: 420281
URI: http://eprints.soton.ac.uk/id/eprint/420281
PURE UUID: 242746ee-41e3-4a27-986b-08879075ef72
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Date deposited: 03 May 2018 16:30
Last modified: 15 Mar 2024 19:39
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Author:
Alessandro Mennuni
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