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

C-Tier
Journal: Journal of Economic Surveys
Year: 2018
Volume: 32
Issue: 2
Pages: 388-419

Score contribution per author:

0.335 = (α=2.01 / 3 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:bla:jecsur:v:32:y:2018:i:2:p:388-419
Journal Field
General
Author Count
3
Added to Database
2026-01-29