Concept-Based Bayesian Model Averaging and Growth Empirics

CentER Discussion Paper Series No. 2012-017

39 Pages Posted: 17 Feb 2012

See all articles by J.R. Magnus

J.R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics

Wendun Wang

Erasmus University Rotterdam (EUR) - Department of Econometrics

Multiple version iconThere are 2 versions of this paper

Date Written: February 16, 2012

Abstract

In specifying a regression equation, we need to determine which regressors to include, but also how these regressors are measured. This gives rise to two levels of uncertainty: concepts (level 1) and measurements within each concept (level 2). In this paper we propose a hierarchical weighted least squares (HWALS) method to address these uncertainties. We examine the effects of different growth theories taking into account the measurement problem in the growth regression. We find that estimates produced by HWALS provide intuitive and robust explanations. We also consider approximation techniques when the number of variables is large or when computing time is limited, and we propose possible strategies for sensitivity analysis.

Keywords: Hierarchical model averaging, Growth determinants, Measurement

JEL Classification: C51, C52, C13, C11

Suggested Citation

Magnus, Jan R. and Wang, Wendun, Concept-Based Bayesian Model Averaging and Growth Empirics (February 16, 2012). CentER Discussion Paper Series No. 2012-017. Available at SSRN: https://ssrn.com/abstract=2006429 or http://dx.doi.org/10.2139/ssrn.2006429

Jan R. Magnus (Contact Author)

Vrije Universiteit Amsterdam, School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081HV
Netherlands

Wendun Wang

Erasmus University Rotterdam (EUR) - Department of Econometrics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Register to save articles to
your library

Register

Paper statistics

Downloads
44
Abstract Views
348
PlumX Metrics