UNCERTAINTY AND DENSITY FORECASTS OF ARMA MODELS: COMPARISON OF ASYMPTOTIC, BAYESIAN, AND BOOTSTRAP PROCEDURES
JoÃ£o Henrique GonÃ§alves Mazzeu,
Esther Ruiz and
Helena Veiga ()
Journal of Economic Surveys, 2018, vol. 32, issue 2, 388-419
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.
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jecsur:v:32:y:2018:i:2:p:388-419
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