کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5066543 1476787 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dynamic model averaging in large model spaces using dynamic Occam׳s window
موضوعات مرتبط
علوم انسانی و اجتماعی اقتصاد، اقتصادسنجی و امور مالی اقتصاد و اقتصادسنجی
پیش نمایش صفحه اول مقاله
Dynamic model averaging in large model spaces using dynamic Occam׳s window
چکیده انگلیسی

Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam׳s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Economic Review - Volume 81, January 2016, Pages 2-14
نویسندگان
, ,