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Inference for an algorithmic fairness-accuracy frontier

Liu, Yiqi; Molinari, Francesca - 2025 - This draft: June 13, 2025

literature, such as (i) whether excluding group identity from use in training the algorithm is optimal and (ii) whether there are … less discriminatory alternatives to a given algorithm. In addition, we construct an estimator for the distance between a … given algorithm and the fairest point on the frontier, and characterize its asymptotic distribution. Using Monte Carlo …

Persistent link: https://www.econbiz.de/10015419993

Inference for high-dimensional sparse econometric models

Belloni, Alexandre; Chernozhukov, Victor; Hansen, … - 2011

econometrics. High dimensional sparse models arise in situations where many regressors (or series terms) are available and the …-dimensional econometrics ; instrumental regression ; partially linear regression ; returns-to-schooling ; growth regression …

Persistent link: https://www.econbiz.de/10009419335

Inference on breakdown frontiers

Masteny, Matthew A.; Poirierz, Alexandre - 2017

A breakdown frontier is the boundary between the set of assumptions which lead to a specific conclusion and those which do not. In a potential outcomes model with a binary treatment, we consider two conclusions: First, that ATE is at least a specific value (e.g., nonnegative) and second that the...

Persistent link: https://www.econbiz.de/10011645504

Impossible inference in econometrics : theory and applications

Bertanha, Marinho; Moreira, Marcelo J. - 2019 - This version: November 14, 2018

This paper studies models in which hypothesis tests have trivial power, that is, power smaller than size. This testing impossibility, or impossibility type A, arises when any alternative is not distinguishable from the null. We also study settings where it is impossible to have almost surely...

Persistent link: https://www.econbiz.de/10011958082

An econometric perspective on algorithmic subsampling

Lee, Sokbae; Ng, Serena - 2020

Datasets that are terabytes in size are increasingly common, but computer bottlenecks often frustrate a complete analysis of the data. While more data are better than less, diminishing returns suggest that we may not need terabytes of data to estimate a parameter or test a hypothesis. But which...

Persistent link: https://www.econbiz.de/10012216998

Ill-conditioned problems, Fisher information, and weak instruments

Forchini, Giovanni (contributor); … - 2005

Persistent link: https://www.econbiz.de/10002741502

Inference for rank-rank regressions

Četverikov, Denis N.; Wilhelm, Daniel - 2023

Slope coefficients in rank-rank regressions are popular measures of intergenerational mobility, for instance in regressions of a child's income rank on their parent's income rank. In this paper, we first point out that commonly used variance estimators such as the homoskedastic or robust...

Persistent link: https://www.econbiz.de/10014416045

Robust estimation and inference in panels with interactive fixed effects

Armstrong, Timothy B.; Weidner, Martin; Zeleneev, Andrei - 2024

We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with a factor structure). We demonstrate that existing estimators and confidence intervals (CIs) can be heavily biased and size-distorted when some of the factors are weak. We...

Persistent link: https://www.econbiz.de/10015168548

Inference on sets in finance

Chernozhukov, Victor; Kocatulum, Emre; Menzel, Konrad - 2012

In this paper we introduce various set inference problems as they appear in finance and propose practical and powerful inferential tools. Our tools will be applicable to any problem where the set of interest solves a system of smooth estimable inequalities, though we will particularly focus on...

Persistent link: https://www.econbiz.de/10009492357

Set identified linear models

Bontemps, Christian; Magnac, Thierry; Maurin, Eric - 2011

We analyze the identification and estimation of parameters β satisfying the incomplete linear moment restrictions E(z T(x β-y)) = E(zTu(z)) where z is a set of instruments and u(z) an unknown bounded scalar function. We first provide empirically relevant examples of such a set-up. Second, we...

Persistent link: https://www.econbiz.de/10008990533