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Testing Financial Hierarchy Based on A PDQ-CRE Model

Author

Listed:
  • Zongwu Cai

    (Department of Economics, The University of Kansas, Lawrence, KS 66045, USA)

  • Meng Shi

    (Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, Beijing 100190, and School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, Beijing 100049, China)

  • Yue Zhao

    (School of Business, Renmin University of China, Beijing, Beijing 100872, China)

  • Wuqing Wu

    (School of Business, Renmin University of China, Beijing, Beijing 100872, China)

Abstract

This paper 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 (PDQ-CRE), which accounts for heteroscedasticity in both firm-specific individuals and distribution of investment. A new estimation method is proposed by using the quasi-likelihood function for conditional quantile model and Laplace approximation. We show that the proposed estimator is consistent and normally distributed. A Monte Carlo simulation is conducted to examine the performance of the estimator in finite samples. Finally, empirical results find a 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%.

Suggested Citation

  • Zongwu Cai & Meng Shi & Yue Zhao & Wuqing Wu, 2020. "Testing Financial Hierarchy Based on A PDQ-CRE Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202011, University of Kansas, Department of Economics, revised Jul 2020.
    • Handle: RePEc:kan:wpaper:202011
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    File URL: http://www2.ku.edu/~kuwpaper/2020Papers/202011.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Correlated Random Effects; Panel Data; Pecking Order Theory; Quantile Regression Model; Quasi-Maximum Likelihood Estimator;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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