Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31304 
Year of Publication: 
2005
Series/Report no.: 
Working Paper No. 2006-21
Publisher: 
Rutgers University, Department of Economics, New Brunswick, NJ
Abstract: 
This chapter discusses estimation, specification testing, and model selection of predictive density models. In particular, predictive density estimation is briefly discussed, and a variety of different specification and model evaluation tests due to various authors including Christoffersen and Diebold (2000), Diebold, Gunther and Tay (1998), Diebold, Hahn and Tay (1999), White (2000), Bai (2003), Corradi and Swanson (2005a,b,c,d), Hong and Li (2003), and others are reviewed. Extensions of some existing techniques to the case of out-of-sample evaluation are also provided, and asymptotic results associated with these extensions are outlined.
Subjects: 
block bootstrap
density and conditional distribution
forecast accuracy testing
mean square error
parameter estimation error
JEL: 
C22
C51
Document Type: 
Working Paper

Files in This Item:
File
Size
520.59 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.