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Journal of Time Series Econometrics

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Asymptotic Theory for Regressions with Smoothly Changing Parameters

Eric Hillebrand
  • Corresponding author
  • CREATES, Aarhus University, Aarhus, Denmark
  • Email:
/ Marcelo C. Medeiros
  • Department of Economics, Pontifical Catholic University of Rio De Janeiro, Rio de Janeiro, RJ, Brazil
  • Email:
/ Junyue Xu
  • MFE Program, Haas School of Business, University of California Berkeley, Berkeley, CA, USA
  • Email:
Published Online: 2013-04-30 | DOI: https://doi.org/10.1515/jtse-2012-0024

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.

Keywords: regime switching; smooth transition regression; asymptotic theory

JEL Codes: C22


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About the article

Published Online: 2013-04-30

Note that, contrary to the work on multiple structural breaks, for each break there are two nuisance parameter ( and c) instead of one.

Citation Information: Journal of Time Series Econometrics, ISSN (Online) 1941-1928, ISSN (Print) 2194-6507, DOI: https://doi.org/10.1515/jtse-2012-0024. Export Citation

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