Arbeitspapier

Robust decision-making under risk and ambiguity

Economists often estimate a subset of their model parameters outside the model and let the decision-makers inside the model treat these point estimates as-if they are correct. This practice ignores model ambiguity, opens the door for misspecification of the decision problem, and leads to post-decision disappointment. We develop a framework to explore, evaluate, and optimize decision rules that explicitly account for the uncertainty in the first step estimation using statistical decision theory. We show how to operationalize our analysis by studying a stochastic dynamic investment model where the decision-makers take ambiguity about the model's transition dynamics directly into account.

Language
Englisch

Bibliographic citation
Series: ECONtribute Discussion Paper ; No. 104

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

Event
Geistige Schöpfung
(who)
Blesch, Maximilian
Eisenhauer, Philipp
Event
Veröffentlichung
(who)
University of Bonn and University of Cologne, Reinhard Selten Institute (RSI)
(where)
Bonn and Cologne
(when)
2021

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Blesch, Maximilian
  • Eisenhauer, Philipp
  • University of Bonn and University of Cologne, Reinhard Selten Institute (RSI)

Time of origin

  • 2021

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