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Empirical model discovery and theory evaluation : automatic selection methods in econometrics
Authors: ---
ISBN: 0262324415 9780262324410 1306957869 9781306957861 0262324423 9780262028356 0262028352 Year: 2014 Publisher: Cambridge, Massachusetts ; London, England : The MIT Press,

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Abstract

A synthesis of the authors' groundbreaking econometric research on automatic model selection, which uses powerful computational algorithms and theory evaluation.


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Interactive Monte Carlo experimentation in econometrics using PcNaive 5
Authors: ---
ISBN: 9780955212789 0955212782 9780955212796 9780955212772 9780955212765 0955212774 0955212790 0955212766 Year: 2009 Publisher: London : Timberlake Consultants Ltd,


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The practice of econometric theory : an examination of the characteristics of econometric computation
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ISBN: 3540755705 9786612287978 1282287974 3540755713 Year: 2009 Publisher: Berlin ; London ; New York : Springer,

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Abstract

Econometric theory, as presented in textbooks and the econometric literature generally, is a somewhat disparate collection of findings. Its essential nature is to be a set of demonstrated results that increase over time, each logically based on a specific set of axioms or assumptions, yet at every moment, rather than a finished work, these inevitably form an incomplete body of knowledge. The practice of econometric theory consists of selecting from, applying, and evaluating this literature, so as to test its applicability and range. The creation, development, and use of computer software has led applied economic research into a new age. This book describes the history of econometric computation from 1950 to the present day, based upon an interactive survey involving the collaboration of the many econometricians who have designed and developed this software. It identifies each of the econometric software packages that are made available to and used by economists and econometricians worldwide.


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Handbook of computational econometrics.
Authors: ---
ISBN: 9780470743850 0470743859 Year: 2009 Publisher: Chichester Wiley

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"Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation. Each topic is fully introduced before proceeding to a more in-depth examination of the relevant methodologies and valuable illustrations. This book: Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies. Brings together contributions from leading researchers. Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation. This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels"--Provided by publisher. "This project's main focus is to provide a handbook on all areas of computing that have a major impact, either directly or indirectly, on econometric techniques and modelling. The book sets out to introduce each topic along with a more in-depth look at methodologies used in computational econometrics, to include use of econometric software and evaluation, bootstrap testing, algorithms for control and optimization and looks at recent computational advances"--Provided by publisher.


Book
Microeconometrics using Stata
Authors: ---
ISBN: 9781597180733 1597180734 Year: 2010 Publisher: College Station, Tex. : Stata Press,

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This text presents an introduction to microeconometrics and how to do microeconometric research using Stata. The authors address each topic with an in-depth Stata example and demonstrate how to use Stata's programming features to implement methods for which Stata does not have a specific command.

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