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Change Point Estimation in Panel Data with Time-Varying Individual Effects

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  • Otilia Boldea
  • Bettina Drepper
  • Zhuojiong Gan

Abstract

This paper proposes a method for estimating multiple change points in panel data models with unobserved individual effects via ordinary least-squares (OLS). Typically, in this setting, the OLS slope estimators are inconsistent due to the unobserved individual effects bias. As a consequence, existing methods remove the individual effects before change point estimation through data transformations such as first-differencing. We prove that under reasonable assumptions, the unobserved individual effects bias has no impact on the consistent estimation of change points. Our simulations show that since our method does not remove any variation in the dataset before change point estimation, it performs better in small samples compared to first-differencing methods. We focus on short panels because they are commonly used in practice, and allow for the unobserved individual effects to vary over time. Our method is illustrated via two applications: the environmental Kuznets curve and the U.S. house price expectations after the financial crisis.

Suggested Citation

  • Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2018. "Change Point Estimation in Panel Data with Time-Varying Individual Effects," Papers 1808.03109, arXiv.org.
  • Handle: RePEc:arx:papers:1808.03109
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    Cited by:

    1. 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.
    2. 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.
    3. Yiannis Karavias & Paresh Kumar Narayan & Joakim Westerlund, 2023. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 653-666, July.
    4. Westerlund, Joakim & Nordström, Marcus, 2021. "Breaks in persistence in fixed-T panel data," Economics Letters, Elsevier, vol. 205(C).

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