IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v22y2018i2p16n1.html
   My bibliography  Save this article

Estimation and inference of threshold regression models with measurement errors

Author

Listed:
  • Chong Terence Tai-Leung

    (Lau Chor Tak Institute of Global Economics and Finance and Department of Economics, The Chinese University of Hong Kong, Hong Kong, China)

  • Chen Haiqiang

    (Wang Yanan Institute for Studies in Economics, Xiamen University , Xiamen, Fujian, China)

  • Wong Tsz-Nga

    (Federal Reserve Bank of Richmond, Research Department, Richmond, VA, USA)

  • Yan Isabel Kit-Ming

    (Department of Economics and Finance, City University of Hong Kong, Hong Kong, China)

Abstract

An important assumption underlying standard threshold regression models and their variants in the extant literature is that the threshold variable is perfectly measured. Such an assumption is crucial for consistent estimation of model parameters. This paper provides the first theoretical framework for the estimation and inference of threshold regression models with measurement errors. A new estimation method that reduces the bias of the coefficient estimates and a Hausman-type test to detect the presence of measurement errors are proposed. Monte Carlo evidence is provided and an empirical application is given.

Suggested Citation

  • Chong Terence Tai-Leung & Chen Haiqiang & Wong Tsz-Nga & Yan Isabel Kit-Ming, 2018. "Estimation and inference of threshold regression models with measurement errors," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1-16, April.
    • Handle: RePEc:bpj:sndecm:v:22:y:2018:i:2:p:16:n:1
    DOI: 10.1515/snde-2014-0032
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/snde-2014-0032
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/snde-2014-0032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chong, Terence Tai-Leung, 2001. "Structural Change In Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 17(1), pages 87-155, February.
    2. Astatkie, T. & Watts, D. G. & Watt, W. E., 1997. "Nested threshold autoregressive (NeTAR) models," International Journal of Forecasting, Elsevier, vol. 13(1), pages 105-116, March.
    3. Terence Tai-Leung Chong, 2003. "Generic consistency of the break-point estimator under specification errors," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 167-192, June.
    4. Jushan Bai & Haiqiang Chen & Terence Tai-Leung Chong & Seraph Xin Wang, 2008. "Generic consistency of the break-point estimators under specification errors in a multiple-break model," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 287-307, July.
    5. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
    6. K. S. Chan & H. Tong, 1986. "On Estimating Thresholds In Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(3), pages 179-190, May.
    7. Amemiya, Yasuo, 1985. "Instrumental variable estimator for the nonlinear errors-in-variables model," Journal of Econometrics, Elsevier, vol. 28(3), pages 273-289, June.
    8. Susanne M. Schennach, 2004. "Estimation of Nonlinear Models with Measurement Error," Econometrica, Econometric Society, vol. 72(1), pages 33-75, January.
    9. Haiqiang Chen & Terence Chong & Jushan Bai, 2012. "Theory and Applications of TAR Model with Two Threshold Variables," Econometric Reviews, Taylor & Francis Journals, vol. 31(2), pages 142-170.
    10. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    11. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    12. Amemiya, Yasuo, 1990. "Two-stage instrumental variables estimators for the nonlinear errors-in-variables model," Journal of Econometrics, Elsevier, vol. 44(3), pages 311-332, June.
    13. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    14. Jeong, Jinook & Maddala, G S, 1991. "Measurement Errors and Tests for Rationality," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(4), pages 431-439, October.
    15. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2002. "Estimation and model selection based inference in single and multiple threshold models," Journal of Econometrics, Elsevier, vol. 110(2), pages 319-352, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lixiong Yang, 2023. "Variable selection in threshold model with a covariate-dependent threshold," Empirical Economics, Springer, vol. 65(1), pages 189-202, July.
    2. Ebrahimi Salari, Taghi & Naji Meidani, Ali Akbar & Shabani Koshalshahi, Zeinab & Ajori Ayask, Amir Abbas, 2022. "The threshold effect of HDI on the relationship between financial development and oil revenues," Resources Policy, Elsevier, vol. 76(C).
    3. Lixiong Yang & Chingnun Lee & I‐Po Chen, 2021. "Threshold model with a time‐varying threshold based on Fourier approximation," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 406-430, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haiqiang Chen & Terence Chong & Jushan Bai, 2012. "Theory and Applications of TAR Model with Two Threshold Variables," Econometric Reviews, Taylor & Francis Journals, vol. 31(2), pages 142-170.
    2. Chong, Terence Tai Leung & Yan, Isabel K., 2014. "Estimating and Testing Threshold Regression Models with Multiple Threshold Variables," MPRA Paper 54732, University Library of Munich, Germany.
    3. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    4. Chong, Terence T.L. & Yan, Isabel K., 2018. "Forecasting currency crises with threshold models," International Economics, Elsevier, vol. 156(C), pages 156-174.
    5. Jean-Marc Le Caillec, 2021. "Threshold autoregressive model blind identification based on array clustering," Post-Print hal-03210735, HAL.
    6. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    7. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    8. Chong Terence T. L. & He Qing & Hinich Melvin J, 2008. "The Nonlinear Dynamics of Foreign Reserves and Currency Crises," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(4), pages 1-18, December.
    9. repec:wyi:journl:002152 is not listed on IDEAS
    10. Koo, Bonsoo & Seo, Myung Hwan, 2015. "Structural-break models under mis-specification: Implications for forecasting," Journal of Econometrics, Elsevier, vol. 188(1), pages 166-181.
    11. Martinez Oscar & Olmo Jose, 2012. "A Nonlinear Threshold Model for the Dependence of Extremes of Stationary Sequences," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-39, September.
    12. Li, Tong, 2002. "Robust and consistent estimation of nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 110(1), pages 1-26, September.
    13. Li, Dong & Tong, Howell, 2016. "Nested sub-sample search algorithm for estimation of threshold models," LSE Research Online Documents on Economics 68880, London School of Economics and Political Science, LSE Library.
    14. Terence Tai-Leung Chong, 2007. "Estimating the Fractionally Integrated Model with a Break in the Differencing Parameter," Economics Bulletin, AccessEcon, vol. 3(67), pages 1-10.
    15. Seo, Myung Hwan & Shin, Yongcheol, 2016. "Dynamic panels with threshold effect and endogeneity," Journal of Econometrics, Elsevier, vol. 195(2), pages 169-186.
    16. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2020. "Desperate Times Call For Desperate Measures: Government Spending Multipliers In Hard Times," Economic Inquiry, Western Economic Association International, vol. 58(4), pages 1949-1957, October.
    17. Rulon D. Pope & Jeffrey T. LaFrance & Richard E. Just, 2007. "Imperfect Price Deflation in Production Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(3), pages 738-754.
    18. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
    19. Hahn, Jinyong & Hausman, Jerry & Kim, Jeonghwan, 2021. "A small sigma approach to certain problems in errors-in-variables models," Economics Letters, Elsevier, vol. 208(C).
    20. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.
    21. repec:ebl:ecbull:v:3:y:2007:i:67:p:1-10 is not listed on IDEAS
    22. Pang, Tianxiao & Tai-Leung Chong, Terence & Zhang, Danna & Liang, Yanling, 2018. "Structural Change In Nonstationary Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 34(5), pages 985-1017, October.

    More about this item

    Keywords

    Hausman-type test; measurement error; threshold model;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sndecm:v:22:y:2018:i:2:p:16:n:1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.