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How Useful Is Bagging in Forecasting Economic Time Series? A Case Study of U.S. Consumer Price Inflation

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References

1969The Combination of Forecasts3,194 cited
2002Forecasting Using Principal Components From a Large Number of Predictors2,990 cited
2002Macroeconomic Forecasting Using Diffusion Indexes2,550 cited
1993Introduction to Multiple Time Series Analysis1,912 cited
1986Forecasting With Bayesian Vector Autoregressions—Five Years of Experience1,231 cited
2003Forecasting Output and Inflation: The Role of Asset Prices1,076 cited
2003Monetary policy in a data-rich environment702 cited
2002Stock return predictability and model uncertainty636 cited
2004Bootstrapping autoregressions with conditional heteroskedasticity of unknown form631 cited
2003Macroeconomic forecasting in the Euro area: Country specific versus area-wide information415 cited
2003Do financial variables help forecasting inflation and real activity in the euro area?336 cited
1993Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates307 cited
2008Bayesian Model Averaging and exchange rate forecasts247 cited
2001Stock Return Predictability: A Bayesian Model Selection Perspective240 cited

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