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Informativeness under Model Uncertainty: Shadow Prices and Ridge Penalties

Jieun Lee, Esfandiar Maasoumi

arXiv 16 Apr 2026 · Econometrics

arXiv:2604.15571 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We develop inference under model uncertainty due to weak, noisy, multiple candidate restrictions and theories, and nuisance control covariates. A unified framework is given with degrees of misspecification and corresponding shadow prices, based on a Lagrangian constrained optimization approach, and a data$-$driven tolerance parameter selected via a Stein$-$type (shrinkage) risk criterion. A debiasing step is based on Karush$-$Kuhn$-$Tucker conditions. We introduce individual shadow prices (ISP) for different restrictions to measure empirical relevance and propose a plateau rule to separate signal from noise. We establish consistency and asymptotic normality of the estimators and characterize the ISP. Simulations and an application to a Solow growth model illustrate the method$^{\prime}$s practical usefulness.

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28
references
33
in-text mentions
28
distinct cited
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self-citations
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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
1Chernozhukov, V. and Chetverikov, D. and Demirer, M. and Duflo, E. a… (2018) Double/debiased machine learning for treatment and structural parameters0.64422100%
2Solow, R (1956) A Contribution to the Theory of Economic Growth0.64422100%
3Swan, T (1956) Economic growth and capital accumulation0.64422100%
4Christensen, T. and Connault, B (2023) Counterfactual sensitivity and robustness0.51121100%
5Gospodinov, N. and Kan, R. and Robotti, C (2014) Misspecification-robust inference in linear asset-pricing models with irrelevant risk factors0.51121100%
6Blundell, R (2005) How revealing is revealed preference?0.40511100%
7Bonhomme, S. and Weidner, M (2022) Minimizing sensitivity to model misspecification0.40511100%
8Campbell, J. Y. and Shiller, R. J (1987) Cointegration and tests of present value models0.40511100%
9Drukker, D. M. and Liu, D (2022) Finite-sample results for lasso and stepwise Neyman-orthogonal Poisson estimators0.40511100%
10Durlauf, S. N. and Johnson, P. A (1995) Multiple regimes and cross‐country growth behaviour0.40511100%

Showing the top 10 of 28 scored citations.