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Algorithms are increasingly used to aid with high-stakes decision making. Yet, their predictive ability frequently exhibits systematic variation across population subgroups. To assess the trade-off between fairness and accuracy using finite data, we propose a debiased machine learning estimator...
Persistent link: https://www.econbiz.de/10015419993
This paper presents a computationally efficient method for binary classification using Manski's (1975,1985) maximum score model when covariates are discretely distributed and parameters are partially but not point identified. We establish conditions under which it is minimax optimal to allow for...
Persistent link: https://www.econbiz.de/10015439509
The paper introduces a new type of shrinkage estimation that is not based on asymptotic optimality but uses artificial intelligence (AI) techniques to shrink the sample eigenvalues. The proposed AI Shrinkage estimator applies to both linear and nonlinear shrinkage, demonstrating improved...
Persistent link: https://www.econbiz.de/10015407991
This paper deals with a nonlinear filtering problem in which a multi-dimensional signal process is additively affected by a process v whose components have paths of bounded variation. The presence of the process v prevents from directly applying classical results and novel estimates need to be...
Persistent link: https://www.econbiz.de/10012550287
Several econometric models for the analysis of relationships with limited dependent variables have been proposed, including the probit, Tobit, two-limit probit, ordered discrete, and friction models. Widespread application of these methods has been hampered by the lack of suitable computer...
Persistent link: https://www.econbiz.de/10012479065
We benchmark seven global optimization algorithms by comparing their performance on challenging multidimensional test functions as well as a method of simulated moments estimation of a panel data model of earnings dynamics. Five of the algorithms are taken from the popular NLopt open-source...
Persistent link: https://www.econbiz.de/10012480284
We show that exact computation of a family of 'max weighted score' estimators, including Manski's max score estimator, can be achieved efficiently by reformulating them as mixed integer programs (MIP) with disjunctive constraints. The advantage of our MIP formulation is that estimates are exact...
Persistent link: https://www.econbiz.de/10012726371
Ricardo Chacoacute;n generalized Johan Gielis's superformula by introducing elliptic functions in place of trigonometric functions. In this paper an attempt has been made to fit the Chacoacute;n-Gielis curves (modified by various functions) to simulated data. Estimation has been done by the...
Persistent link: https://www.econbiz.de/10012731627
This paper presents the construction of a particle filter, which incorporates elements inspired by genetic algorithms, in order to achieve accelerated adaptation of the estimated posterior distribution to changes in model parameters. Specifically, the filter is designed for the situation where...
Persistent link: https://www.econbiz.de/10012794245
We describe an efficient estimation method for large-scale tree logit models, using a novel change-of-variables transformation that allows us to express the negative log-likelihood as a difference of strictly convex functions. Exploiting this representation, we design a fast iterative method...
Persistent link: https://www.econbiz.de/10012848687