EconPapers    
Economics at your fingertips  
 

Multivariate density forecast evaluation: A modified approach

Stanley Iat-Meng Ko and Sung Y. Park

International Journal of Forecasting, 2013, vol. 29, issue 3, 431-441

Abstract: We consider methods of evaluating multivariate density forecasts. Most previous studies use a stacked vector which is formed by the sequence of transformed marginal and conditional variables to evaluate density forecasts. However, these methods lack power when there is contemporaneous correlation among the variables. We propose a new method which is a location-adjusted version of that used by Clements and Smith (2002) Some Monte Carlo simulations show that our test has a higher power than the previous methods in the literature. Two empirical applications also show the usefulness of our proposed test.

Keywords: Multivariate density forecasts; Contemporaneous correlation (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207013000071
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:29:y:2013:i:3:p:431-441

DOI: 10.1016/j.ijforecast.2012.11.006

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:intfor:v:29:y:2013:i:3:p:431-441