Asymptotic Theory for Regressions with Smoothly Changing Parameters
Eric Hillebrand (),
Marcelo Medeiros () and
Xu Junyue ()
Additional contact information
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: 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.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed
Downloads: (external link)
https://www.degruyter.com/view/j/jtse.2013.5.issue ... -0024.xml?format=INT (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Working Paper: Asymptotic Theory for Regressions with Smoothly Changing Parameters (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bpj:jtsmet:v:5:y:2013:i:2:p:133-162:n:3
Ordering information: This journal article can be ordered from
Access Statistics for this article
Journal of Time Series Econometrics is currently edited by Javier Hidalgo
More articles in Journal of Time Series Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().