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Machine learning econometrics : Bayesian algorithms and methods

Korobilis, Dimitris; Pettenuzzo, Davide - 2020

Persistent link: https://www.econbiz.de/10012243263

Machine learning econometrics : Bayesian algorithms and methods

Korobilis, Dimitris; Pettenuzzo, Davide - 2020

Persistent link: https://www.econbiz.de/10012660846

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

A novel machine learning-based attacker detection system to secure location aided routing in MANETs

Suma, R.; Premasudha, B. G.; Ram, V. Ravi - In: International journal of networking and virtual … 22 (2020) 1, pp. 17-41

Persistent link: https://www.econbiz.de/10012178061

Chapter 9. Solution and Estimation Methods for DSGE Models

Fernández-Villaverde, J.; Rubio-Ramírez, J.F.; … - In: Handbook of macroeconomics : volume 2, v. 2A-2B SET, (pp. 527-724). 2016

This chapter provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field.

Persistent link: https://www.econbiz.de/10014024288