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Testing Financial Hierarchy Based on A PDQ-CRE Model

Zongwu Cai, Meng Shi, Yue Zhao and Wuqing Wu
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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

No 202011, WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS from University of Kansas, Department of Economics

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%.

Keywords: Correlated Random Effects; Panel Data; Pecking Order Theory; Quantile Regression Model; Quasi-Maximum Likelihood Estimator (search for similar items in EconPapers)
JEL-codes: C31 C33 (search for similar items in EconPapers)
Date: 2020-07, Revised 2020-07
New Economics Papers: this item is included in nep-ecm, nep-ore and nep-sbm
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