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PanelTM: an R package for two- and three-way dynamic panel threshold regression model

Author

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  • F. Marta L. Di Lascio

    (Free University of Bozen-Bolzano, Italy)

  • Selene Perazzini

    (Free University of Bozen-Bolzano, Italy)

Abstract

This paper presents the R package PanelTM, which provides tools for estimating twoand three-way dynamic panel threshold regression models. Estimation is performed using a generalized method of moments approach based on first-difference transformations and instrumental variables as developed by Seo and Shin (2016) and applied in a threeway fashion by Di Lascio and Perazzini (2024, 2022). In addition to model estimation, PanelTM offers functionalities for change point detection, simulation and performance evaluation within panel structures with regime switches. The package is particularly suited to applications requiring the identification of structural breaks in complex panel data, with support for both exogenous and endogenous variables and for threshold heterogeneity across multiple dimensions.

Suggested Citation

  • F. Marta L. Di Lascio & Selene Perazzini, 2025. "PanelTM: an R package for two- and three-way dynamic panel threshold regression model," BEMPS - Bozen Economics & Management Paper Series BEMPS113, Faculty of Economics and Management at the Free University of Bozen.
    • Handle: RePEc:bzn:wpaper:bemps113
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    References listed on IDEAS

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    1. 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.
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    8. Woosik Gong & Myung Hwan Seo, 2022. "Bootstraps for Dynamic Panel Threshold Models," Papers 2211.04027, arXiv.org, revised Jul 2025.
    9. Seo, Myung Hwan & Shin, Yongcheol, 2016. "Dynamic panels with threshold effect and endogeneity," Journal of Econometrics, Elsevier, vol. 195(2), pages 169-186.
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    More about this item

    Keywords

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    JEL classification:

    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • 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
    • L66 - Industrial Organization - - Industry Studies: Manufacturing - - - Food; Beverages; Cosmetics; Tobacco

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