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A panel quantile model via correlated random effects approach for testing pecking order theory

Author

Listed:
  • Zongwu Cai
  • Meng Shi
  • Wuqing Wu
  • Yue Zhao

Abstract

This article investigates the relative importance of internal and external sources of funds in financing activities across different levels of investment activities by proposing a panel data quantile regression model with correlated random effects, accounting for heteroscedasticity in both firm-specific individuals and distribution of investment. A new estimation method, which takes the influence of disturbance into account, is proposed by using the integrated quasi-likelihood function for the conditional quantile model and Laplace approximation. The large sample theory for the proposed estimator and the corresponding asymptotic χ2 test are investigated. A Monte Carlo simulation is conducted to examine the finite sample performance of the proposed estimator. Finally, empirical results find strong evidence that the financing hierarchy of U.S. firms is in accordance with the first rung of the pecking order theory across all levels of investments from 10% to 90%, but for the second rung of the pecking order theory, only at 30% to 70% levels of investments.

Suggested Citation

  • Zongwu Cai & Meng Shi & Wuqing Wu & Yue Zhao, 2026. "A panel quantile model via correlated random effects approach for testing pecking order theory," Econometric Reviews, Taylor & Francis Journals, vol. 45(2), pages 206-232, February.
    • Handle: RePEc:taf:emetrv:v:45:y:2026:i:2:p:206-232
    DOI: 10.1080/07474938.2025.2561261
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