Arbeitspapier

Robust Decision-Making under Risk and Ambiguity

Economists often estimate economic models on data and use the point estimates as a stand-in for the truth when studying the model's implications for optimal decision-making. This practice ignores model ambiguity, exposes the decision problem to misspecification, and ultimately leads to post-decision disappointment. Using statistical decision theory, we develop a framework to explore, evaluate, and optimize robust decision rules that explicitly account for estimation uncertainty. We show how to operationalize our analysis by studying robust decisions in a stochastic dynamic investment model in which a decision-maker directly accounts for uncertainty in the model's transition dynamics.

Sprache
Englisch

Erschienen in
Series: Discussion Paper ; No. 463

Klassifikation
Wirtschaft
Criteria for Decision-Making under Risk and Uncertainty
Operations Research; Statistical Decision Theory
Intertemporal Firm Choice: Investment, Capacity, and Financing
Thema
decision-making under uncertainty
robust Markov decision process

Ereignis
Geistige Schöpfung
(wer)
Blesch, Maximilian
Eisenhauer, Philipp
Ereignis
Veröffentlichung
(wer)
Ludwig-Maximilians-Universität München und Humboldt-Universität zu Berlin, Collaborative Research Center Transregio 190 - Rationality and Competition
(wo)
München und Berlin
(wann)
2023

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Blesch, Maximilian
  • Eisenhauer, Philipp
  • Ludwig-Maximilians-Universität München und Humboldt-Universität zu Berlin, Collaborative Research Center Transregio 190 - Rationality and Competition

Entstanden

  • 2023

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