کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
998335 1481457 2011 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Forecast combination through dimension reduction techniques
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری کسب و کار و مدیریت بین المللی
پیش نمایش صفحه اول مقاله
Forecast combination through dimension reduction techniques
چکیده انگلیسی

This paper considers several methods of producing a single forecast from several individual ones. We compare “standard” but hard to beat combination schemes (such as the average of forecasts at each period, or consensus forecast and OLS-based combination schemes) with more sophisticated alternatives that involve dimension reduction techniques. Specifically, we consider principal components, dynamic factor models, partial least squares and sliced inverse regression.Our source of forecasts is the Survey of Professional Forecasters, which provides forecasts for the main US macroeconomic aggregates. The forecasting results show that partial least squares, principal component regression and factor analysis have similar performances (better than the usual benchmark models), but sliced inverse regression shows an extreme behavior (performs either very well or very poorly).

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Forecasting - Volume 27, Issue 2, April–June 2011, Pages 224–237
نویسندگان
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