Likelihood-Ratio-Based Confidence Intervals for Multiple Threshold Parameters

Donayre Luiggi ()
Additional contact information
Donayre Luiggi: Department of Economics, University of Minnesota – Duluth, 1318 Kirby Dr., Duluth, MN 55812, USA

Studies in Nonlinear Dynamics & Econometrics, 2025, vol. 29, issue 5, 561-573

Abstract: This paper proposes the inversion of likelihood ratio tests for the construction of confidence intervals for multiple threshold parameters. Using Monte Carlo simulations, conservative likelihood-ratio-based confidence intervals are shown to exhibit empirical coverage rates at least as high as nominal levels for all threshold parameters, while still being informative in the sense of only including relatively few observations in each confidence interval. These findings are robust to the magnitude of the threshold effect, the sample size and the presence of serial correlation. Applications to existing models with multiple thresholds for U.S. real GDP growth and for the wage Phillips curve demonstrate how the proposed approach is empirically relevant to make inferences about the uncertainty of threshold estimates.

Keywords: confidence intervals; multiple-regime threshold regression; likelihood ratio; Monte Carlo simulations (search for similar items in EconPapers)
JEL-codes: C15 C22 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/snde-2023-0029 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:29:y:2025:i:5:p:561-573:n:1001

Ordering information: This journal article can be ordered from
https://www.degruyte ... ournal/key/snde/html

DOI: 10.1515/snde-2023-0029

Access Statistics for this article

Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach

More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().