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A Comparison of Two Averaging Techniques with an Application to Growth Empirics

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Author Info
Magnus, J.R.
Powell, O.R.
Prufer, P. (Tilburg University, Center for Economic Research)

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Abstract

Empirical growth research faces a high degree of model uncertainty. Apart from the neoclassical growth model, many new (endogenous) growth models have been proposed. This causes a lack of robustness of the parameter estimates and makes the determination of the key determinants of growth hazardous. The current paper deals with the fundamental issue of parameter estimation under model uncertainty, and compares the performance of various model averaging techniques. In particular, it contrasts Bayesian model averaging (BMA) ? currently one of the standard methods used in growth empirics ? with weighted-average least squares (WALS), a method that has not previously been applied in this context.

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Publisher Info
Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2008-39.

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Date of creation: 2008
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Handle: RePEc:dgr:kubcen:200839

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Find related papers by JEL classification:
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis

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