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Estimation of heterogeneous spatial panel data models with multiple structural breaks and a multifactor error structure

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  • Dai, Siqi
  • Wang, Wenting
  • Zheng, Chaowen

Abstract

This study considers heterogeneous spatial panel data models with multifactor errors and multiple unknown structural breaks in unit-specific coefficients. To address the dual challenges of endogeneity and heterogeneity across both time and cross-sectional units, we first eliminate factor dependence using a robust common correlated effects approach that relies exclusively on cross-sectional averages of the regressors, an approach we term CCEX. Multiple structural breakpoints are then estimated by the simultaneous estimation procedure of Bai and Perron (1998). We also propose a sequential test to determine the number of breaks. Within each identified regime, heterogeneous parameters are estimated by integrating CCEX with instrumental variables techniques. The proposed method yields consistent estimation for number of breaks, break dates and structural parameters, with Monte Carlo simulations demonstrating its superior finite-sample performance.

Suggested Citation

  • Dai, Siqi & Wang, Wenting & Zheng, Chaowen, 2026. "Estimation of heterogeneous spatial panel data models with multiple structural breaks and a multifactor error structure," Economics Letters, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:ecolet:v:266:y:2026:i:c:s0165176526002442
    DOI: 10.1016/j.econlet.2026.113050
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    Keywords

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    JEL classification:

    • 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
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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