EconPapers    
Economics at your fingertips  
 

UNCERTAINTY AND DENSITY FORECASTS OF ARMA MODELS: COMPARISON OF ASYMPTOTIC, BAYESIAN, AND BOOTSTRAP PROCEDURES

João Henrique Gonçalves Mazzeu, Esther Ruiz and Helena Veiga ()

Journal of Economic Surveys, 2018, vol. 32, issue 2, 388-419

Abstract: The objective of this paper is to analyze the effects of uncertainty on density forecasts of stationary linear univariate ARMA models. We consider three specific sources of uncertainty: parameter estimation, error distribution, and lag order. Depending on the estimation sample size and the forecast horizon, each of these sources may have different effects. We consider asymptotic, Bayesian, and bootstrap procedures proposed to deal with uncertainty and compare their finite sample properties. The results are illustrated constructing fan charts for UK inflation.

Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://doi.org/10.1111/joes.12197

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:bla:jecsur:v:32:y:2018:i:2:p:388-419

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0950-0804

Access Statistics for this article

More articles in Journal of Economic Surveys from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2019-10-21
Handle: RePEc:bla:jecsur:v:32:y:2018:i:2:p:388-419