Asymptotic Theory for Regressions with Smoothly Changing Parameters

Asymptotic Theory for Regressions with Smoothly Changing Parameters Abstract : We derive asymptotic properties of the quasi-maximum likelihood estimator of smooth transition regressions when time is the transition variable. The consistency of the estimator and its asymptotic distribution are examined. It is shown that the estimator converges at the usual -rate and has an asymptotically normal distribution. Finite sample properties of the estimator are explored in simulations. We illustrate with an application to US inflation and output data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Time Series Econometrics de Gruyter

Asymptotic Theory for Regressions with Smoothly Changing Parameters

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Publisher
de Gruyter
Copyright
Copyright © 2013 by the
ISSN
2194-6507
eISSN
1941-1928
DOI
10.1515/jtse-2012-0024
Publisher site
See Article on Publisher Site

Abstract

Abstract : We derive asymptotic properties of the quasi-maximum likelihood estimator of smooth transition regressions when time is the transition variable. The consistency of the estimator and its asymptotic distribution are examined. It is shown that the estimator converges at the usual -rate and has an asymptotically normal distribution. Finite sample properties of the estimator are explored in simulations. We illustrate with an application to US inflation and output data.

Journal

Journal of Time Series Econometricsde Gruyter

Published: Apr 30, 2013

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