EconBase
← All papers

Improving Robust Decisions with Data

Xiaoyu Cheng

arXiv 25 Oct 2023 · Theoretical Economics

arXiv:2310.16281 · PDF · Extracted main text

Abstract

A decision-maker faces uncertainty governed by a data-generating process (DGP), which is only known to belong to a set of sequences of independent but possibly non-identical distributions. A robust decision maximizes the expected payoff against the worst possible DGP in this set. This paper characterizes when and how such robust decisions can be improved with data, measured by the expected payoff under the true DGP, no matter which possible DGP is the truth. It further develops novel and simple inference methods to achieve it, as common methods (e.g., maximum likelihood) may fail to deliver such an improvement.

Citation extraction

51
references
66
in-text mentions
51
distinct cited
1
self-citations
12,827
main-text words

appendix boundary found by appendix_command · 66% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Epstein and Schneider (2007) Learning under Ambiguity0.81142100%
2Reshidi, Thereze and Zhang (2025) Asymptotic Learning with Ambiguous Information0.81142100%
3Cheng (2022) Relative Maximum Likelihood updating of ambiguous beliefs self0.73732100%
4Athey and Levin (2018) The value of information in monotone decision problems0.64422100%
5Epstein, Kaido and Seo (2016) Robust Confidence Regions for Incomplete Models0.64422100%
6Wang (1993) On the number of success in independent trials0.51121100%
7Blum and Rosenblatt (1967) On Partial a Priori Information in Statistical Inference0.40511100%
8Brown, Cai and DasGupta (2001) Interval Estimation for a Binomial Proportion0.40511100%
9Cao (2014) Non-IIDness Learning in Behavioral and Social Data0.40511100%
10Carroll (2015) Robustness and Linear Contracts0.40511100%

Showing the top 10 of 51 scored citations.