Data for: Unveiling covariate inclusion structures in economic growth regressions using latent class analysis

Main Author: Crespo Cuaresma, Jesus
Other Authors: Moser, Mathias , Hofmarcher, Paul, Grün, Bettina, Humer, Stefan
Format: Dataset
Terbitan: Mendeley , 2016
Subjects:
Online Access: https:/data.mendeley.com/datasets/nxwnd9pnns
ctrlnum 0.17632-nxwnd9pnns.1
fullrecord <?xml version="1.0"?> <dc><creator>Crespo Cuaresma, Jesus</creator><title>Data for: Unveiling covariate inclusion structures in economic growth regressions using latent class analysis</title><publisher>Mendeley</publisher><description>Abstract of associated article: We propose the use of Latent Class Analysis methods to analyze the covariate inclusion patterns across specifications resulting from Bayesian model averaging exercises. Using Dirichlet Process clustering, we are able to identify and describe dependency structures among variables in terms of inclusion in the specifications that compose the model space. We apply the method to two datasets of potential determinants of economic growth. Clustering the posterior covariate inclusion structure of the model space formed by linear regression models reveals interesting patterns of complementarity and substitutability across economic growth determinants.</description><subject>Economics</subject><subject>Macroeconomics</subject><contributor>Moser, Mathias </contributor><contributor>Hofmarcher, Paul</contributor><contributor>Gr&#xFC;n, Bettina</contributor><contributor>Humer, Stefan</contributor><type>Other:Dataset</type><identifier>10.17632/nxwnd9pnns.1</identifier><rights>Creative Commons Attribution 4.0 International</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><relation>https:/data.mendeley.com/datasets/nxwnd9pnns</relation><date>2016-10-24T08:13:44Z</date><recordID>0.17632-nxwnd9pnns.1</recordID></dc>
format Other:Dataset
Other
author Crespo Cuaresma, Jesus
author2 Moser, Mathias
Hofmarcher, Paul
Grün, Bettina
Humer, Stefan
title Data for: Unveiling covariate inclusion structures in economic growth regressions using latent class analysis
publisher Mendeley
publishDate 2016
topic Economics
Macroeconomics
url https:/data.mendeley.com/datasets/nxwnd9pnns
contents Abstract of associated article: We propose the use of Latent Class Analysis methods to analyze the covariate inclusion patterns across specifications resulting from Bayesian model averaging exercises. Using Dirichlet Process clustering, we are able to identify and describe dependency structures among variables in terms of inclusion in the specifications that compose the model space. We apply the method to two datasets of potential determinants of economic growth. Clustering the posterior covariate inclusion structure of the model space formed by linear regression models reveals interesting patterns of complementarity and substitutability across economic growth determinants.
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institution Universitas Islam Indragiri
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collection Artikel mulono
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repoId IOS7969
first_indexed 2020-04-08T08:32:41Z
last_indexed 2020-04-08T08:32:41Z
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