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Bliss and growth: Optimal policies under uncertainty

Authors: Voyvoda, Ebru;

Bliss and growth: Optimal policies under uncertainty

Abstract

This thesis conducts a study on growth theory by analyzing how the results of the current optimal growth theory change when households are assumed to have bliss points in their consumption sets. For this purpose a discrete-time, one-sector, stochastic model of endogenous growth, adopting constant returns to scale technology and quadratic utility function, is constructed. The solution of the model through “value function iteration” shows the existence of qualitatively different equilibria, depending on the initial state of the economy. This result demonstrates that it is possible to combine “poverty traps” and “sustained growth” into a common analytical framework.

Cataloged from PDF version of article.

Includes bibliographical refences.

Voyvoda, Ebru

Country
Turkey
Related Organizations
Keywords

Economic development--Mathematical models, 330, poverty traps, Economics, sustained growth, Mathematical optimization, value function iteration, Sustainable development., Values, Mathematical optimization., Economic development--Mathematical models., bliss, Sustainable development, Optimal growth, HD75.5 .V69 1998, Values., Ekonomi, Continuous development

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green