Rationing & Bayesian expectations with application to the labour market
The first goal of the present work focuses on the need for different rationing methods of the The Global Change and Financial Transition (GFT) work- ing group at the Potsdam Institute for Climate Impact Research (PIK): I provide a toolbox which contains a variety of rationing methods to be ap- p...
Main Author: | |
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Format: | Doctoral Thesis |
Language: | English |
Published: |
Universität Potsdam
2006
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Subjects: | |
Online Access: | http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-15217 http://opus.kobv.de/ubp/volltexte/2007/1521/ |
Summary: | The first goal of the present work focuses on the need for different rationing
methods of the The Global Change and Financial Transition (GFT) work-
ing group at the Potsdam Institute for Climate Impact Research (PIK): I
provide a toolbox which contains a variety of rationing methods to be ap-
plied to micro-economic disequilibrium models of the lagom model family.
This toolbox consists of well known rationing methods, and of rationing
methods provided specifically for lagom. To ensure an easy application the
toolbox is constructed in modular fashion.
The second goal of the present work is to present a micro-economic
labour market where heterogenous labour suppliers experience consecu-
tive job opportunities and need to decide whether to apply for employ-
ment. The labour suppliers are heterogenous with respect to their qualifi-
cations and their beliefs about the application behaviour of their competi-
tors. They learn simultaneously – in Bayesian fashion – about their individ-
ual perceived probability to obtain employment conditional on application
(PPE) by observing each others’ application behaviour over a cycle of job
opportunities. === In vorliegender Arbeit beschäftige ich mich mit zwei Dingen. Zum einen
entwickle ich eine Modellierungstoolbox, die verschiedene Rationierungs-
methoden enthält. Diese Rationierungsmethoden sind entweder aus der
Literatur bekannt, oder wurden speziell für die lagom Modellfamilie ent-
wickelt.
Zum anderen zeige ich, dass man mit Hilfe von Rationierungsmetho-
den aus der Modellierungstoolbox einen fiktiven Arbeitsmarkt modellie-
ren kann. Auf diesem agieren arbeitssuchende Agenten, die heterogen im
Bezug auf ihre Qualifikation und ihre Vorstellungen über das Bewerbungs-
verhalten ihrer Konkurrenten sind. Sie erfahren aufeinanderfolgende Job-
angebote und beobachten das Bewerbungsverhalten ihrer Konkurrenten,
um in Bayesianischer Weise über ihre individuelle Wahrscheinlichkeit eine
Stelle zu erhalten zu lernen. |
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