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Asymptotic Theory for Regressions with Smoothly Changing Parameters

Eric Hillebrand (), Marcelo Medeiros () and Xu Junyue ()
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Xu Junyue: MFE Program, Haas School of Business, University of California Berkeley, Berkeley, CA, USA

Journal of Time Series Econometrics, 2013, vol. 5, issue 2, 133-162

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.

Date: 2013
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Working Paper: Asymptotic Theory for Regressions with Smoothly Changing Parameters (2012) Downloads
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