# Robust decision-making under risk and ambiguity

@inproceedings{Blesch2021RobustDU, title={Robust decision-making under risk and ambiguity}, author={Maximilian Blesch and Philipp Eisenhauer}, year={2021} }

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…

## One Citation

### Structural Models for Policy-Making: Coping with Parametric Uncertainty

- EconomicsSSRN Electronic Journal
- 2021

The ex-ante evaluation of policies using structural econometric models is based on estimated parameters as a stand-in for the true parameters. This practice ignores uncertainty in the counterfactual…

## References

SHOWING 1-10 OF 105 REFERENCES

### Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher

- Economics
- 1987

This paper formulates a simple, regenerative, optimal-stopping model of bus-eng ine replacement to describe the behavior of Harold Zurcher, superinte ndent of maintenance at the Madison (Wisconsin)…

### Robust Dynamic Programming

- Mathematics, EconomicsMath. Oper. Res.
- 2005

It is proved that when this set of measures has a certain "rectangularity" property, all of the main results for finite and infinite horizon DP extend to natural robust counterparts.

### Robust Solutions of Optimization Problems Affected by Uncertain Probabilities

- Computer Science, MathematicsManag. Sci.
- 2013

The robust counterpart of a linear optimization problem with φ-divergence uncertainty is tractable for most of the choices of φ typically considered in the literature and extended to problems that are nonlinear in the optimization variables.

### Econometrics for Decision Making: Building Foundations Sketched by Haavelmo and Wald

- Economics
- 2019

This paper proposes statistical decision theory as a framework for evaluation of the performance of models in decision making, and considers the common practice of as-if optimization: specification of a model, point estimation of its parameters, and use of the point estimate to make a decision that would be optimal if the estimate were accurate.

### Maximum likelihood estimation of discrete control processes

- Mathematics
- 1988

Consider the following “inverse stochastic control” problem. A statistician observes a realization of a controlled stochastic process $\{ d_t ,x_t \} $ consisting of the sequence of states $x_t$, and…

### Statistical Decision Theory and Bayesian Analysis

- Computer Science
- 1988

An overview of statistical decision theory, which emphasizes the use and application of the philosophical ideas and mathematical structure of decision theory. The text assumes a knowledge of basic…

### Theory Of Decision Under Uncertainty

- Economics
- 2009

This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories. It focuses on the meaning of probability, discussing some…

### Data-driven robust optimization

- Computer ScienceMath. Program.
- 2018

This work proposes a novel schema for utilizing data to design uncertainty sets for robust optimization using statistical hypothesis tests, and shows that data-driven sets significantly outperform traditional robust optimization techniques whenever data is available.