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.

This study investigates whether U.S. property-liability insurers change their demand for reinsurance after demutualization. Our empirical results show that the overall demand for reinsurance of converting insurers is not statistically different after the conversion. Furthermore, we find that converting insurers decrease the demand for reinsurance from non-affiliated reinsurers, but increase the demand for reinsurance from affiliated reinsurers after the conversion. One possible explanation is that converting insurers may treat reinsurance to affiliated reinsurers as risk retention rather than risk transfer so that they can reduce reinsurance cost. Another interesting finding is that converting insurers increase demand for reinsurance from non-affiliated reinsurers before conversion.

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By using a two-stage quantile regression approach (2SQR), this study demonstrates how the insurer's leverage is determined across various quantiles. The evidence shows that the influence of the business concentration and marketing channel at the lower leverage quantiles is opposite to that at the higher leverage quantiles, which proposes that the mean effects of the two-stage ordinary least squares method are insufficient to capture the effects of business strategies on the insurer's capital structure determination. Moreover, the 2SQR evidence also shows that the magnitude of the impacts for some determinations varies among the different leverage quantiles. In sum, the evidence suggests that these two competing approaches should be viewed as complementary functions when discussing the insurer's capital structure.JEL Classifications: G22, G32, G33