A dynamic life cycle model for Germany with unemployment uncertainty

This work analyzes the saving and consumption behavior of agents faced with the possibility of unemployment in a dynamic and stochastic life cycle model. The intertemporal optimization is based on Dynamic Programming with a backward recursion algorithm. The implemented uncertainty is not based on income shocks as it is done in traditional life cycle models but uses Markov probabilities where the probability for the next employment status of the agent depends on the current status. The utility function used is a CRRA function (constant relative risk aversion), combined with a CES function (constant elasticity of substitution) and has several consumption goods, a subsistence level, money and a bequest function.

Level thesis:degree_level

thesis.doctoral

Grantor dc:publisher

Universität Potsdam

Year

2009

Author dc:creator

• Biewald, Anne

Contributors dc:contributor

• Jaeger, Carlo

• Lebenszyklusmodell
• Deutschland
• Arbeitslosigkeit
• Markov Wahrscheinlichkeiten
• Sparraten
• life cycle model
• Germany
• unemployment
• markov chains
• saving rates

Statement dc:rights

• Keine öffentliche Lizenz: Unter Urheberrechtsschutz

Repository record source_url

https://publishup.uni-potsdam.de/frontdoor/index/index/docId/3195

OAI identifier oai:identifier

oai:kobv.de-opus4-uni-potsdam:3195