Bias-corrected estimation in potentially mildly explosive autoregressive models

Hendrik Kaufmannz () and Robinson Kruse
Additional contact information
Hendrik Kaufmannz: Leibniz University Hannover, Postal: School of Economics and Management, Institute of Statistics, Königsworther Platz 1, D-30167 Hannover, Germany

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: This paper provides a comprehensive Monte Carlo comparison of different finite-sample bias-correction methods for autoregressive processes. We consider classic situations where the process is either stationary or exhibits a unit root. Importantly, the case of mildly explosive behaviour is studied as well. We compare the empirical performance of an indirect inference estimator (Phillips, Wu, and Yu, 2011), a jackknife approach (Chambers, 2013), the approximately median-unbiased estimator by Roy and Fuller (2001) and the bootstrap- aided estimator by Kim (2003). Our findings suggest that the indirect inference approach o ers a valuable alternative to other existing techniques. Its performance (measured by its bias and root mean squared error) is balanced and highly competitive across many different settings. A clear advantage is its applicability for mildly explosive processes. In an empirical application to a long annual US Debt/GDP series we consider rolling window estimation of autoregressive models. We find substantial evidence for time-varying persistence and periods of explosiveness during the Civil War and World War II. During the recent years, the series is nearly explosive again. Further applications to commodity and interest rate series are considered as well.

Keywords: Bias-correction; Explosive behavior; Rolling window estimation (search for similar items in EconPapers)
JEL-codes: C13 C22 H62 (search for similar items in EconPapers)
Pages: 30
Date: 2013
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://repec.econ.au.dk/repec/creates/rp/13/rp13_10.pdf (application/pdf)

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:aah:create:2013-10

Access Statistics for this paper

More papers in CREATES Research Papers from Department of Economics and Business Economics, Aarhus University
Bibliographic data for series maintained by ().