Testing for Parameter Instability in Competing Modeling Frameworks

Tinbergen Institute 14-010/IV/71

40 Pages Posted: 18 Jan 2014 Last revised: 6 Feb 2014

See all articles by Francesco Calvori

Francesco Calvori

University of Florence - Dipartimento di Statistica, Informatica, Applicazioni (DiSIA)

Drew Creal

University of Chicago - Booth School of Business - Econometrics and Statistics

Siem Jan Koopman

Vrije Universiteit Amsterdam - School of Business and Economics; Tinbergen Institute; Aarhus University - CREATES

Andre Lucas

VU Amsterdam - School of Business and Economics; Tinbergen Institute

Date Written: January 28, 2014

Abstract

We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under the alternative. We compare the test's performance with that of alternative tests developed for competing time-varying parameter frameworks, such as structural breaks and observation driven parameter dynamics. The new test has higher and more stable power against alternatives with frequent regime switches or with non-local parameter driven time-variation. For parameter driven time variation close to the null or for infrequent structural changes, the test of Muller and Petalas (2010) performs best overall. We apply all tests empirically to a panel of losses given default over the period 1982-2010 and find significant evidence of parameter variation in the underlying beta distribution.

Keywords: time-varying parameters; observation driven models; parameter driven models; structural breaks; generalized autoregressive score model; regime switching; credit risk

JEL Classification: C12, C52, C22

Suggested Citation

Calvori, Francesco and Creal, Drew and Koopman, Siem Jan and Lucas, Andre, Testing for Parameter Instability in Competing Modeling Frameworks (January 28, 2014). Tinbergen Institute 14-010/IV/71. Available at SSRN: https://ssrn.com/abstract=2379997 or http://dx.doi.org/10.2139/ssrn.2379997

Francesco Calvori (Contact Author)

University of Florence - Dipartimento di Statistica, Informatica, Applicazioni (DiSIA) ( email )

Viale Morgagni, 59
Florence, 50134
Italy

Drew Creal

University of Chicago - Booth School of Business - Econometrics and Statistics ( email )

Chicago, IL 60637
United States

Siem Jan Koopman

Vrije Universiteit Amsterdam - School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081 HV
Netherlands
+31205986019 (Phone)

HOME PAGE: http://sjkoopman.net

Tinbergen Institute ( email )

Gustav Mahlerplein 117
1082 MS Amsterdam
Netherlands

HOME PAGE: http://personal.vu.nl/s.j.koopman

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Andre Lucas

VU Amsterdam - School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081 HV
Netherlands
+31 20 598 6039 (Phone)
+31 20 598 6020 (Fax)

HOME PAGE: http://personal.vu.nl/a.lucas

Tinbergen Institute

Roetersstraat 31
Amsterdam, 1018 WB
Netherlands

HOME PAGE: http://www.tinbergen.nl

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