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Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples

Author

Listed:
  • Donayre Luiggi

    (Department of Economics, University of Minnesota – Duluth, 1318 Kirby Dr., Duluth, MN 55812, USA)

  • Eo Yunjong

    (School of Economics, University of Sydney, Sydney 2006, Australia)

  • Morley James

    (School of Economics, University of New South Wales, Sydney 2052, Australia)

Abstract

Within the context of threshold regressions, we show that asymptotically-valid likelihood-ratio-based confidence intervals for threshold parameters perform poorly in finite samples when the threshold effect is large. A large threshold effect leads to a poor approximation of the profile likelihood in finite samples such that the conventional approach to constructing confidence intervals excludes the true threshold parameter value too often, resulting in low coverage rates. We propose a conservative modification to the standard likelihood-ratio-based confidence interval that has coverage rates at least as high as the nominal level, while still being informative in the sense of including relatively few observations of the threshold variable. An application to thresholds for US industrial production growth at a disaggregated level shows the empirical relevance of applying the proposed approach.

Suggested Citation

  • Donayre Luiggi & Eo Yunjong & Morley James, 2018. "Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(1), pages 1-11, February.
    • Handle: RePEc:bpj:sndecm:v:22:y:2018:i:1:p:11:n:4
    DOI: 10.1515/snde-2016-0084
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    Cited by:

    1. Donayre, Luiggi, 2022. "On the behavior of Okun's law across business cycles," Economic Modelling, Elsevier, vol. 112(C).
    2. Takatoshi Sasaki & Hiroki Yamamoto & Jouchi Nakajima, 2023. "Nonlinear Input Cost Pass-through to Consumer Prices: A Threshold Approach," Bank of Japan Working Paper Series 23-E-9, Bank of Japan.
    3. Donayre, Luiggi & Loomer, Lacey, 2025. "Regime-dependent health care employment dynamics in recessions," Research in Economics, Elsevier, vol. 79(2).
    4. Nebot, César & Beyaert, Arielle & García-Solanes, José, 2019. "New insights into the nonlinearity of Okun's law," Economic Modelling, Elsevier, vol. 82(C), pages 202-210.

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    Keywords

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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