Quantile Regression Analysis of Corporate Liquidity: Evidence from the U.S. Property–Liability Insurance Industry

Vincent Y Chang and Jeffrey Tsai ()
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Vincent Y Chang: Department of Insurance, Chaoyang University of Technology, 168, Jifong E. Road, Wufong District, Taichung, Taiwan 41349, R.O.C. Email: vcchang@cyut.edu.tw

The Geneva Papers on Risk and Insurance - Issues and Practice, 2014, vol. 39, issue 1, 77-89

Abstract: This study analyses the determinants of corporate liquidity for the U.S. property–liability insurance industry from 2006 to 2010. Unlike previous studies using the ordinary least squares (OLS) approach, this study applies the quantile regression (QR) method. The QR method provides further insights on how insurers’ liquidity level is determined, especially for the firms at the lower and the higher quantiles. We found that leverage and organisational structure have opposite effects on insurers’ liquidity in the lower and the higher quantile groups. The empirical results also show that most firm-specific characteristics and macroeconomic conditions influence the insurers’ liquidity, which are consistent with the findings of the OLS approach in previous studies.

Date: 2014
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