Jointness in Bayesian Variable Selection with Applications to Growth Regression

By E. Ley, Mark F. J. Steel. 2006

120 citations recorded by the source corpus.

The authors present a measure of jointness to explore dependence among regressors in the context of Bayesian model selection. The jointness measure they propose equals the posterior odds ratio between those models that include a set of variables and the models that only include proper subsets. They show its application in cross-country growth regressions using two data-sets from the model-averaging growth literature.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/96fb6e044e7fcdf09aed0133502eb21054278583

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In Economics and Econometrics

Citations in the corpus

On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression (2007, unknown): “In this paper we use the Fortran code from FLS updated to account for data sets with more than 52 regressors, as explained in Ley and Steel (2007).”
Weighted‐Average Least Squares (WALS): A Survey (2016, unknown): “For example, WALS cannot handle jointness (Ley and Steel, 2007; Doppelhofer and Weeks, 2009).”
A comparison of two model averaging techniques with an application to growth empirics (2010, background): “Recent examples of such prior robustness checks for BMA include Ley and Steel (2007b) and Eicher, Papageorgiou, and Raftery (2007).”
Bayesian Model Averaging and Weighted-Average Least Squares: Equivariance, Stability, and Numerical Issues (2011, unknown): “To shed some light on these two topics, we use the same dataset analyzed by Salai-Martin, Doppelhofer, and Miller (2004), Ley and Steel (2007), and Magnus, Powell, and Prüfer (2010), which includes 67 determinants of the average GDP growth rate per capita of 88 countries from 1960–1996.”
Model Averaging in Economics: An Overview (2015, unknown): “Ley and Steel (2007) and Doppelhofer and Weeks (2009) define ex-post measures of dependence among explanatory variables that appear in linear regression models.”
Model Averaging and Its Use in Economics (2017, methodology): “Man (2017) compares different jointness measures using data from a variety of disciplines and finds that results differ substantially between the measures of Doppelhofer and Weeks (2009) on the one hand and Ley and Steel (2007) on the other hand.”