کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5096990 | 1376562 | 2008 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components? Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?](/preview/png/5096990.png)
چکیده انگلیسی
This paper considers Bayesian regression with normal and double-exponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices. Moreover, we study conditions for consistency of the forecast based on Bayesian regression as the cross-section and the sample size become large. This analysis serves as a guide to establish a criterion for setting the amount of shrinkage in a large cross-section.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 146, Issue 2, October 2008, Pages 318-328
Journal: Journal of Econometrics - Volume 146, Issue 2, October 2008, Pages 318-328
نویسندگان
Christine De Mol, Domenico Giannone, Lucrezia Reichlin,