On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression
We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior assumptions on the inference concerning model size, posterior inclusion probabilities of regressors and on predictive performance. We illustrate these issues in the context of cross-country growth regressions using three datasets with 41-67 potential drivers of growth and 72-93 observations. Finally, we recommend priors for use in this and related contexts.
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| Format: | Journal Article biblioteca |
| Language: | EN |
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2009
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| Subjects: | Single Equation Models, Single Variables: General C200, Model Construction and Estimation C510, Forecasting Methods, Simulation Methods C530, Measurement of Economic Growth, Aggregate Productivity, Cross-Country Output Convergence O470, |
| Online Access: | http://hdl.handle.net/10986/4690 |
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dig-okr-1098646902021-04-23T14:02:19Z On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression Ley, Eduardo Steel, Mark F. J. Single Equation Models Single Variables: General C200 Model Construction and Estimation C510 Forecasting Methods Simulation Methods C530 Measurement of Economic Growth Aggregate Productivity Cross-Country Output Convergence O470 We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior assumptions on the inference concerning model size, posterior inclusion probabilities of regressors and on predictive performance. We illustrate these issues in the context of cross-country growth regressions using three datasets with 41-67 potential drivers of growth and 72-93 observations. Finally, we recommend priors for use in this and related contexts. 2012-03-30T07:29:15Z 2012-03-30T07:29:15Z 2009 Journal Article Journal of Applied Econometrics 08837252 http://hdl.handle.net/10986/4690 EN http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank Journal Article |
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Banco Mundial |
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Estados Unidos |
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biblioteca |
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America del Norte |
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Biblioteca del Banco Mundial |
| language |
EN |
| topic |
Single Equation Models Single Variables: General C200 Model Construction and Estimation C510 Forecasting Methods Simulation Methods C530 Measurement of Economic Growth Aggregate Productivity Cross-Country Output Convergence O470 Single Equation Models Single Variables: General C200 Model Construction and Estimation C510 Forecasting Methods Simulation Methods C530 Measurement of Economic Growth Aggregate Productivity Cross-Country Output Convergence O470 |
| spellingShingle |
Single Equation Models Single Variables: General C200 Model Construction and Estimation C510 Forecasting Methods Simulation Methods C530 Measurement of Economic Growth Aggregate Productivity Cross-Country Output Convergence O470 Single Equation Models Single Variables: General C200 Model Construction and Estimation C510 Forecasting Methods Simulation Methods C530 Measurement of Economic Growth Aggregate Productivity Cross-Country Output Convergence O470 Ley, Eduardo Steel, Mark F. J. On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression |
| description |
We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior assumptions on the inference concerning model size, posterior inclusion probabilities of regressors and on predictive performance. We illustrate these issues in the context of cross-country growth regressions using three datasets with 41-67 potential drivers of growth and 72-93 observations. Finally, we recommend priors for use in this and related contexts. |
| format |
Journal Article |
| topic_facet |
Single Equation Models Single Variables: General C200 Model Construction and Estimation C510 Forecasting Methods Simulation Methods C530 Measurement of Economic Growth Aggregate Productivity Cross-Country Output Convergence O470 |
| author |
Ley, Eduardo Steel, Mark F. J. |
| author_facet |
Ley, Eduardo Steel, Mark F. J. |
| author_sort |
Ley, Eduardo |
| title |
On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression |
| title_short |
On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression |
| title_full |
On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression |
| title_fullStr |
On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression |
| title_full_unstemmed |
On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression |
| title_sort |
on the effect of prior assumptions in bayesian model averaging with applications to growth regression |
| publishDate |
2009 |
| url |
http://hdl.handle.net/10986/4690 |
| work_keys_str_mv |
AT leyeduardo ontheeffectofpriorassumptionsinbayesianmodelaveragingwithapplicationstogrowthregression AT steelmarkfj ontheeffectofpriorassumptionsinbayesianmodelaveragingwithapplicationstogrowthregression |
| _version_ |
1756571537070096384 |