IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v68y2025i5d10.1007_s00181-024-02700-1.html
   My bibliography  Save this article

Random change point model with an application to the potato’s contribution to population

Author

Listed:
  • Qing Jiang

    (Beijing Normal University)

  • Meng Li

    (Beijing Normal University)

  • Xingwei Tong

    (Beijing Normal University)

  • Qiang Wu

    (Beijing Normal University)

  • Xun Zhang

    (Beijing Normal University)

Abstract

In this paper, we investigate a linear regression model with a change point that depends on an unknown random threshold of a covariate. We account for the heterogeneity of change points, propose an EM estimation method for both the regression and change point parameters, and employ the supremum test of score statistics to detect the random change point. We establish the consistency and asymptotic normality of our estimation method in theory, and verify these properties through simulation studies. Furthermore, we apply our methodology to the case of Nunn and Qian (2011) on the introduction of potatoes to the Old World. Our analysis reveals that the introduction of potatoes played a significant role in the population growth observed during the eighteenth and nineteenth centuries. Importantly, we demonstrate that there exists a threshold effect of the amount of suitable land, with heterogeneity across countries, on stimulating population growth, as estimated by our random change point model.

Suggested Citation

  • Qing Jiang & Meng Li & Xingwei Tong & Qiang Wu & Xun Zhang, 2025. "Random change point model with an application to the potato’s contribution to population," Empirical Economics, Springer, vol. 68(5), pages 2455-2474, May.
    • Handle: RePEc:spr:empeco:v:68:y:2025:i:5:d:10.1007_s00181-024-02700-1
    DOI: 10.1007/s00181-024-02700-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-024-02700-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00181-024-02700-1?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Caner, Mehmet & Hansen, Bruce E., 2004. "Instrumental Variable Estimation Of A Threshold Model," Econometric Theory, Cambridge University Press, vol. 20(5), pages 813-843, October.
    2. Nathan Nunn & Nancy Qian, 2011. "The Potato's Contribution to Population and Urbanization: Evidence From A Historical Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(2), pages 593-650.
    3. Stéphane Bonhomme & Elena Manresa, 2015. "Grouped Patterns of Heterogeneity in Panel Data," Econometrica, Econometric Society, vol. 83(3), pages 1147-1184, May.
    4. Lee, Yoonseok & Wang, Yulong, 2024. "Testing For Homogeneous Thresholds In Threshold Regression Models," Econometric Theory, Cambridge University Press, vol. 40(3), pages 608-651, June.
    5. Liangjun Su & Zhentao Shi & Peter C. B. Phillips, 2016. "Identifying Latent Structures in Panel Data," Econometrica, Econometric Society, vol. 84, pages 2215-2264, November.
    6. Casini, Alessandro & Perron, Pierre, 2022. "Generalized Laplace Inference In Multiple Change-Points Models," Econometric Theory, Cambridge University Press, vol. 38(1), pages 35-65, February.
    7. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    8. Casini, Alessandro & Perron, Pierre, 2021. "Continuous record Laplace-based inference about the break date in structural change models," Journal of Econometrics, Elsevier, vol. 224(1), pages 3-21.
    9. Shimizu, Kenichi, 2023. "Asymptotic properties of Bayesian inference in linear regression with a structural break," Journal of Econometrics, Elsevier, vol. 235(1), pages 202-219.
    10. Jushan Bai, 1997. "Estimation Of A Change Point In Multiple Regression Models," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 551-563, November.
    11. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    12. David Card & Alexandre Mas & Jesse Rothstein, 2008. "Tipping and the Dynamics of Segregation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(1), pages 177-218.
    13. Lin Chang-Ching & Ng Serena, 2012. "Estimation of Panel Data Models with Parameter Heterogeneity when Group Membership is Unknown," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 42-55, August.
    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. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    2. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    3. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Correction to: Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3093-3093, December.
    4. Lee, Yoonseok & Wang, Yulong, 2023. "Threshold regression with nonparametric sample splitting," Journal of Econometrics, Elsevier, vol. 235(2), pages 816-842.
    5. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    6. Wang, Yiren & Phillips, Peter C.B. & Su, Liangjun, 2024. "Panel data models with time-varying latent group structures," Journal of Econometrics, Elsevier, vol. 240(1).
    7. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    8. Shimizu, Kenichi, 2023. "Asymptotic properties of Bayesian inference in linear regression with a structural break," Journal of Econometrics, Elsevier, vol. 235(1), pages 202-219.
    9. Carlos Castro & Cristhian Rodriguez, 2016. "Racial and spatial interaction for neighborhood dynamics in Chicago," Documentos de Trabajo 14589, Universidad del Rosario.
    10. Nibbering, D. & Paap, R., 2019. "Panel Forecasting with Asymmetric Grouping," Econometric Institute Research Papers EI-2019-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Octavio Fernández-Amador & Joseph F. Francois & Doris A. Oberdabernig & Patrick Tomberger, 2020. "Economic growth, sectoral structures, and environmental methane footprints," Applied Economics, Taylor & Francis Journals, vol. 52(13), pages 1460-1475, March.
    12. Gupta, Mahima & Dubey, Amlendu, 2025. "Structural characteristics and non-linear fiscal multipliers," Economic Systems, Elsevier, vol. 49(1).
    13. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2012. "Is Globalization Driving Efficiency? A Threshold Stochastic Frontier Panel Data Modeling Approach," Review of International Economics, Wiley Blackwell, vol. 20(3), pages 563-579, August.
    14. Custodio João, Igor & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2023. "Dynamic clustering of multivariate panel data," Journal of Econometrics, Elsevier, vol. 237(2).
    15. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    16. Casini, Alessandro & Perron, Pierre, 2021. "Continuous record Laplace-based inference about the break date in structural change models," Journal of Econometrics, Elsevier, vol. 224(1), pages 3-21.
    17. Afi Etonam Adetou & Komlan Fiodendji, 2019. "Finance, Institutions, Remittances and Economic growth: New Evidence from a Dynamic Panel Threshold Analysis," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(2), pages 1-4.
    18. Chen, Chaoyi & Pinar, Mehmet & Stengos, Thanasis, 2021. "Determinants of renewable energy consumption: Importance of democratic institutions," Renewable Energy, Elsevier, vol. 179(C), pages 75-83.
    19. Zhonghui Zhang & Chihwa Kao & Jungbin Hwang, 2025. "High-Dimensional Weighted K-Means with Serial Dependence," Working papers 2025-09, University of Connecticut, Department of Economics.
    20. James Temitope Dada & Taiwo Akinlo, 2021. "Foreign direct investment and poverty reduction in sub-Saharan Africa: does environmental degradation matter?," Future Business Journal, Springer, vol. 7(1), pages 1-10, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:empeco:v:68:y:2025:i:5:d:10.1007_s00181-024-02700-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.