On bootstrapping tests of equal forecast accuracy for nested models

Firmin Doko Tchatoka and Qazi Haque

No 2020-03, School of Economics and Public Policy Working Papers from University of Adelaide, School of Economics and Public Policy

Abstract: The asymptotic distributions of the recursive out-of-sample forecast accuracy test statistics depend on stochastic integrals of Brownian motion when the models under comparison are nested. This often complicates their implementation in practice because the computation of their asymptotic critical values is costly. Hansen and Timmermann (2015, Econometrica) propose a Wald approximation of the commonly used recursive F-statistic and provide a simple characterization of the exact density of its asymptotic distribution. However, this characterization holds only when the larger model has one extra predictor or the forecast errors are homoscedastic. No such closed-form characterization is readily available when the nesting involves more than one predictor and heteroskedasticity is present. We first show both the recursive F-test and its Wald approximation have poor finite-sample properties, especially when the forecast horizon is greater than one. We then propose an hybrid bootstrap method consisting of a block moving bootstrap (which is nonparametric) and a residual based bootstrap for both statistics, and establish its validity. Simulations show that our hybrid bootstrap has good finite-sample performance, even in multi-step ahead forecasts with heteroscedastic or autocorrelated errors, and more than one predictor. The bootstrap method is illustrated on forecasting core inflation and GDP growth.

Keywords: Out-of-sample forecasts; HAC estimator; Moving block bootstrap; Bootstrap consistency (search for similar items in EconPapers)
JEL-codes: C12 C15 C32 (search for similar items in EconPapers)
Date: 2020-02
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://media.adelaide.edu.au/economics/papers/doc/wp2020-03.pdf (application/pdf)

Related works:
Journal Article: On bootstrapping tests of equal forecast accuracy for nested models (2023)
Working Paper: On bootstrapping tests of equal forecast accuracy for nested models (2020)
Working Paper: On bootstrapping tests of equal forecast accuracy for nested models (2020)
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:adl:wpaper:2020-03

Access Statistics for this paper

More papers in School of Economics and Public Policy Working Papers from University of Adelaide, School of Economics and Public Policy Contact information at EDIRC.
Bibliographic data for series maintained by Qazi Haque ().