IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v249y2025ipbs0304407625000594.html

Estimating coefficient-by-coefficient breaks in panel data models

Author

Listed:
  • Kaddoura, Yousef

Abstract

When estimating structural breaks, existing econometric methods adopt an approach in which either all parameters change simultaneously, or they remain the same. In this paper, we consider the estimation of panel data models when an unknown subset of coefficients is subject to breaks. The challenge lies in estimating the breaks for each coefficient. To tackle this, we propose a new estimator for panel data, the “Coefficient-by-Coefficient Lasso” break estimator. This estimator is derived by penalizing the coefficients with a fused penalty and using component-wise adaptive weights. We present this estimator for two scenarios: those with homogeneous breaks and those with heterogeneous breaks. We show that the method identifies the number and dates of breaks for all coefficients with high probability and that the post-selection estimator is asymptotically normal. We examine the small-sample properties of the method through a Monte Carlo study and further apply it to analyze the influence of socioeconomic factors on crime.

Suggested Citation

  • Kaddoura, Yousef, 2025. "Estimating coefficient-by-coefficient breaks in panel data models," Journal of Econometrics, Elsevier, vol. 249(PB).
  • Handle: RePEc:eee:econom:v:249:y:2025:i:pb:s0304407625000594
    DOI: 10.1016/j.jeconom.2025.106005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304407625000594
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jeconom.2025.106005?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. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    2. Stéphane Bonhomme & Elena Manresa, 2015. "Grouped Patterns of Heterogeneity in Panel Data," Econometrica, Econometric Society, vol. 83(3), pages 1147-1184, May.
    3. Badi H. Baltagi, 2006. "Estimating an economic model of crime using panel data from North Carolina," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 543-547, May.
    4. Lu, Xun & Su, Liangjun, 2016. "Shrinkage estimation of dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 190(1), pages 148-175.
    5. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2020. "Change point estimation in panel data with time‐varying individual effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 712-727, September.
    6. Mojtaba Ghasemi, 2017. "Crime and punishment: evidence from dynamic panel data model for North Carolina (2003–2012)," Empirical Economics, Springer, vol. 52(2), pages 723-730, March.
    7. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    8. Baltagi, Badi H. & Liu, Long, 2009. "A note on the application of EC2SLS and EC3SLS estimators in panel data models," Statistics & Probability Letters, Elsevier, vol. 79(20), pages 2189-2192, October.
    9. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
    10. Liangjun Su & Xia Wang & Sainan Jin, 2019. "Sieve Estimation of Time-Varying Panel Data Models With Latent Structures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 334-349, April.
    11. Yousef Kaddoura & Joakim Westerlund, 2023. "Estimation of Panel Data Models with Random Interactive Effects and Multiple Structural Breaks when T is Fixed," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 778-790, July.
    12. Angela K. Dills & Jeffrey A. Miron & Garrett Summers, 2010. "What Do Economists Know about Crime?," NBER Chapters, in: The Economics of Crime: Lessons For and From Latin America, pages 269-302, National Bureau of Economic Research, Inc.
    13. Gombay, Edit & Horváth, Lajos, 1994. "An application of the maximum likelihood test to the change-point problem," Stochastic Processes and their Applications, Elsevier, vol. 50(1), pages 161-171, March.
    14. Wuyi Wang & Peter C. B. Phillips & Liangjun Su, 2018. "Homogeneity pursuit in panel data models: Theory and application," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 797-815, September.
    15. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.
    16. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    17. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    18. Cherry, Todd L. & List, John A., 2002. "Aggregation bias in the economic model of crime," Economics Letters, Elsevier, vol. 75(1), pages 81-86, March.
    19. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    20. Cornwell, Christopher & Trumbull, William N, 1994. "Estimating the Economic Model of Crime with Panel Data," The Review of Economics and Statistics, MIT Press, vol. 76(2), pages 360-366, May.
    21. Maurice J. G. Bun & Richard Kelaher & Vasilis Sarafidis & Don Weatherburn, 2020. "Crime, deterrence and punishment revisited," Empirical Economics, Springer, vol. 59(5), pages 2303-2333, November.
    22. Horváth, Lajos & Hušková, Marie & Rice, Gregory & Wang, Jia, 2017. "Asymptotic Properties Of The Cusum Estimator For The Time Of Change In Linear Panel Data Models," Econometric Theory, Cambridge University Press, vol. 33(2), pages 366-412, April.
    23. 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.
    24. Jaromír Antoch & Jan Hanousek & Lajos Horváth & Marie Hušková & Shixuan Wang, 2019. "Structural breaks in panel data: Large number of panels and short length time series," Econometric Reviews, Taylor & Francis Journals, vol. 38(7), pages 828-855, August.
    25. Gombay, Edit & Horváth, Lajos, 1996. "On the Rate of Approximations for Maximum Likelihood Tests in Change-Point Models," Journal of Multivariate Analysis, Elsevier, vol. 56(1), pages 120-152, January.
    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. Otilia Boldea & Alastair R. Hall, 2025. "Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments," Papers 2507.22204, arXiv.org.

    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. 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).
    2. Ali Mehrabani & Shahnaz Parsaeian, 2025. "Shrinkage Estimation and Identification of Latent Group Structures in Panel Data with Interactive Fixed Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202516, University of Kansas, Department of Economics.
    3. Otilia Boldea & Alastair R. Hall, 2025. "Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments," Papers 2507.22204, arXiv.org.
    4. Jiang, Peiyun & Kurozumi, Eiji, 2026. "A new test for common breaks in heterogeneous panel data models," Econometrics and Statistics, Elsevier, vol. 37(C), pages 87-125.
    5. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2021. "Nonstationary panel models with latent group structures and cross-section dependence," Journal of Econometrics, Elsevier, vol. 221(1), pages 198-222.
    6. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    7. Rogneda Vasilyeva & Anton Skrobotov & Aleksei Tsarev, 2025. "Structural breaks in panel data: COVID-19 pandemic in Russian regions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 80, pages 117-142.
    8. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    9. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    10. 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.
    11. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    12. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2022. "Multiple Structural Breaks in Interactive Effects Panel Data and the Impact of Quantitative Easing on Bank Lending," Papers 2211.06707, arXiv.org, revised Jan 2023.
    13. Guliyev, Hasraddin, 2025. "Heterogeneous panel data model with sharp and smooth changes: Testing green growth hypothesis in G7 countries," Innovation and Green Development, Elsevier, vol. 4(3).
    14. Oguzhan Akgun & Ryo Okui, 2025. "Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation," Papers 2511.18550, arXiv.org.
    15. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    16. Wang, Xia & Jin, Sainan & Li, Yingxing & Qian, Junhui & Su, Liangjun, 2025. "On time-varying panel data models with time-varying interactive fixed effects," Journal of Econometrics, Elsevier, vol. 249(PB).
    17. Dai, Siqi & Hong, Yongmiao & Li, Haiqi & Zheng, Chaowen, 2025. "Shrinkage estimation of spatial panel data models with multiple structural breaks and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 251(C).
    18. Langevin, R.;, 2024. "Consistent Estimation of Finite Mixtures: An Application to Latent Group Panel Structures," Health, Econometrics and Data Group (HEDG) Working Papers 24/16, HEDG, c/o Department of Economics, University of York.
    19. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    20. Chen, Sanpan & Cui, Guowei & Zhang, Jianhua, 2017. "On testing for structural break of coefficients in factor-augmented regression models," Economics Letters, Elsevier, vol. 161(C), pages 141-145.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

    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:eee:econom:v:249:y:2025:i:pb:s0304407625000594. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.