IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/103488.html
   My bibliography  Save this paper

Jump or kink: note on super-efficiency in segmented linear regression break-point estimation

Author

Listed:
  • Chen, Yining

Abstract

We consider the problem of segmented linear regression with a single breakpoint, with the focus on estimating the location of the breakpoint. If $n$ is the sample size, we show that the global minimax convergence rate for this problem in terms of the mean absolute error is $O(n^{-1/3})$. On the other hand, we demonstrate the construction of a super-efficient estimator that achieves the pointwise convergence rate of either $O(n^{-1})$ or $O(n^{-1/2})$ for every fixed parameter value, depending on whether the structural change is a jump or a kink. The implications of this example and a potential remedy are discussed.

Suggested Citation

  • Chen, Yining, 2020. "Jump or kink: note on super-efficiency in segmented linear regression break-point estimation," LSE Research Online Documents on Economics 103488, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:103488
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/103488/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Hidalgo, Javier & Lee, Jungyoon & Seo, Myung Hwan, 2019. "Robust inference for threshold regression models," Journal of Econometrics, Elsevier, vol. 210(2), pages 291-309.
    3. Rafal Baranowski & Yining Chen & Piotr Fryzlewicz, 2019. "Narrowest‐over‐threshold detection of multiple change points and change‐point‐like features," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(3), pages 649-672, July.
    4. Ritabrata Das & Moulinath Banerjee & Bin Nan & Huiyong Zheng, 2016. "Fast Estimation of Regression Parameters in a Broken-Stick Model for Longitudinal Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1132-1143, July.
    5. Wishart, Justin Rory, 2011. "Minimax lower bound for kink location estimators in a nonparametric regression model with long-range dependence," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1871-1875.
    6. Bruce E. Hansen, 2017. "Regression Kink With an Unknown Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 228-240, April.
    Full references (including those not matched with items on IDEAS)

    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. Chih‐Hao Chang & Kam‐Fai Wong & Wei‐Yee Lim, 2023. "Threshold estimation for continuous three‐phase polynomial regression models with constant mean in the middle regime," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(1), pages 4-47, February.
    2. Lixiong Yang, 2023. "Variable selection in threshold model with a covariate-dependent threshold," Empirical Economics, Springer, vol. 65(1), pages 189-202, July.
    3. Andreas Anastasiou & Piotr Fryzlewicz, 2022. "Detecting multiple generalized change-points by isolating single ones," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(2), pages 141-174, February.
    4. Cui, Junfeng & Wang, Guanghui & Zou, Changliang & Wang, Zhaojun, 2023. "Change-point testing for parallel data sets with FDR control," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    5. Lee, Yoonseok & Wang, Yulong, 2023. "Threshold regression with nonparametric sample splitting," Journal of Econometrics, Elsevier, vol. 235(2), pages 816-842.
    6. Andrews, Isaiah & Kitagawa, Toru & McCloskey, Adam, 2021. "Inference after estimation of breaks," Journal of Econometrics, Elsevier, vol. 224(1), pages 39-59.
    7. Alfonso Mendoza-Velázquez & Heidi J. Smith & Diego Mendoza-Martínez, 2023. "Regional Growth, Debt Thresholds and Subnational Sustainability," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 18(2), pages 1-23, Abril - J.
    8. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    9. Chuang Wan & Wei Zhong & Wenyang Zhang & Changliang Zou, 2023. "Multikink quantile regression for longitudinal data with application to progesterone data analysis," Biometrics, The International Biometric Society, vol. 79(2), pages 747-760, June.
    10. Somlanare Romuald Kinda & Relwendé Sawadogo, 2023. "Does financial development really spur industrialization in sub‐Saharan African countries?," African Development Review, African Development Bank, vol. 35(4), pages 390-402, December.
    11. Konstantina Manou & Panagiotis Palaios & Evangelia Papapetrou, 2019. "Housing wealth, household debt and financial assets: are there implications for consumption?," Working Papers 263, Bank of Greece.
    12. Segun Thompson Bolarinwa & Richard Olaolu Olayeni & Xuan Vinh Vo, 2021. "Is there a nonlinear relationship between nonperforming loans and bank profitability? Evidence from dynamic panel threshold," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(3), pages 649-661, April.
    13. Yoonseok Lee & Yulong Wang, 2020. "Inference in Threshold Models," Center for Policy Research Working Papers 223, Center for Policy Research, Maxwell School, Syracuse University.
    14. Hidalgo, Javier & Lee, Jungyoon & Seo, Myung Hwan, 2019. "Robust inference for threshold regression models," Journal of Econometrics, Elsevier, vol. 210(2), pages 291-309.
    15. Alfonso Mendoza-Velazquez & Heidi J. Smith & Diego Mendoza-Martinez, 2022. "Subnational Regional Growth, Debt Thresholds and Sustainability," Working Paper Series Sobre México 2022001, Sobre México. Temas en economía.
    16. Matthew Backus & Sida Peng, 2019. "On Testing Continuity and the Detection of Failures," NBER Working Papers 26016, National Bureau of Economic Research, Inc.
    17. Holger Dette & Theresa Eckle & Mathias Vetter, 2020. "Multiscale change point detection for dependent data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1243-1274, December.
    18. V., Ernesto Guerra & H., Eugenio Bobenrieth & H., Juan Bobenrieth & Wright, Brian D., 2023. "Endogenous thresholds in energy prices: Modeling and empirical estimation," Energy Economics, Elsevier, vol. 121(C).
    19. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    20. Kelly Burns & Imad Moosa, 2017. "Demystifying the Meese–Rogoff puzzle: structural breaks or measures of forecasting accuracy?," Applied Economics, Taylor & Francis Journals, vol. 49(48), pages 4897-4910, October.

    More about this item

    Keywords

    change-point; minimax rate; Pointwise rate; Structural break;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ehl:lserod:103488. 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: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    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.