Crespo Cuaresma, Jesus ORCID: https://orcid.org/0000-0003-3244-6560 and Grün, Bettina and Hofmarcher, Paul and Humer, Stefan and Moser, Mathias
(2016)
Unveiling Covariate Inclusion Structures In Economic Growth Regressions Using Latent Class Analysis.
European Economic Review, 81.
pp. 189-202.
ISSN 0014-2921
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Abstract
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.
Item Type: | Article |
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Additional Information: | To see the final version of this paper please visit the publisher's website. Access to the published version may require a subscription. The original publication is available at www.elsevier.com. |
Keywords: | Economic growth determinants; Bayesian model averaging; Latent class analysis; Dirichlet processes |
Classification Codes: | JEL C11; C21; O47 |
Divisions: | Departments > Volkswirtschaft > Makroökonomie Forschungsinstitute > Human Capital and Development Forschungsinstitute > Verteilungsfragen Kompetenzzentren > Sustainability Transf. & Responsibility |
Version of the Document: | Accepted for Publication |
Depositing User: | Gertraud Novotny |
Date Deposited: | 07 Aug 2017 09:33 |
Last Modified: | 02 Dec 2019 09:21 |
Related URLs: | |
FIDES Link: | https://bach.wu.ac.at/d/research/results/71188/ |
URI: | https://epub.wu.ac.at/id/eprint/5674 |
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