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Reinsurance and Liquidity: Evidence from the United Kingdom General Insurance Industry

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Abstract

This paper aims to simultaneously examine the effect of liquidity on reinsurance use and the reverse causality of reinsurance on liquidity. Using a sample of U.K. general insurers from 1994 to 2011, we find that insurers with higher liquidity tend to purchase more reinsurance, and those with higher reinsurance dependence tend to maintain higher liquidity. Our data indicates that the cash-constraint argument dominates the substitution argument. We further find an inverted U-shaped relation between reinsurance and liquidity. Particular attention should be paid to the less liquid insurers that purchase less reinsurance because they have both less underwriting and liquidity risk management, and thus are exposed to a higher level of insolvency risk.

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Notes

  1. For example, Cole and McCullough (2006); Adams et al. (2008); Shiu (2011).

  2. Chang and Jeng (2015).

  3. For example, Lee and Lee (2012); Chang (2014).

  4. For example, Chang and Tsai (2014).

  5. Wang (2003); James, (2007).

  6. Cole and McCullough (2006).

  7. Niehaus and Mann (1992).

  8. Lee and Lee (2012).

  9. Chang (2014).

  10. Hau (2006).

  11. Chang and Yang (2014).

  12. Adiel (1996); Froot (2001); Shiu (2009).

  13. Zou et al. (2003).

  14. Rochet and Villeneuve (2011).

  15. Regan and Hur (2007).

  16. As indicated in Hau (2006), insurance can provide firms with additional liquidity. Reinsurance can therefore be considered as an alternative liquidity source of insurers. If this is the case, reinsurance and liquidity could be endogenous variables. Following Wooldridge (2006), we therefore conduct an endogeneity test to examine whether the reinsurance and liquidity variables are endogenous variables before estimating the simultaneous equations model. The endogeneity test results show that endogeneity is an issue in our data; we therefore decide to use 2SLS to estimate the model. See the Appendix for the details.

  17. This measure of reinsurance extent is commonly seen in insurance literature, such as Colquitt and Hoyt (1997); Cummins et al. (1997) and Shiu (2011).

  18. We are grateful to an anonymous referee for pointing out that not all invested assets can be liquidated at a liquidity crunch. Thus, the ratio of cash and marketable securities to book value of assets might be a better proxy for liquidity. Owing to unavailability of bond durations in our data set, however, we cannot use this short-term liquidity measurement.

  19. For example, Cole and McCullough (2006); Adams et al. (2008); Shiu (2011); Chang and Tsai (2014).

  20. Cole and McCullough (2006); Kader et al. (2010); Shiu (2011).

  21. Mayers and Smith (1990).

  22. We winsorise the sample by setting the data below the 0.5th percentile to the 0.5th percentile, and data above the 99.5th percentile to the 99.5th percentile.

  23. Warner (1977).

  24. Chen et al. (2001); Garven and Lamm-Tennant (2003); Powell and Sommer (2007); Adams et al. (2008).

  25. Garven and Lamm-Tennant (2003); Shortridge and Avila (2004); Adams et al. (2008); Shiu (2011).

  26. For example, Shortridge and Avila (2004); Cole and McCullough (2006); Shiu (2011).

  27. Colquitt and Hoyt (1997); Cummins et al. (2001).

  28. Adams et al. (2008).

  29. Shiu (2011).

  30. Adams et al. (2008); Shiu (2011).

  31. Chen et al. (2001).

  32. Kim et al. (1998); Opler et al. (1999); Shiu (2006); Chang and Tsai (2014).

  33. Shiu (2006).

  34. Gujarati (2004).

  35. White’s (1980).

  36. Han and Qiu (2007).

  37. The Hausman test statistic is 72.68 for Eq. (1) and 88.09 for Eq. (2). We also conduct the LM test for both equations to determine whether OLS or panel data models are more appropriate. The LM test statistic is 811.47 for Eq. (1) and 1,470.83 for Eq. (2). Taken together, the fixed-effects model is more appropriate for our data.

  38. The results are available from authors on request.

  39. Studenmund (2001).

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Authors and Affiliations

  1. Department of Business Administration, National Cheng Kung University, 1, University Road, Tainan, 701, Taiwan

    Hui-Hsuan Liu & Tsung-Chi Liu

  2. Department of Risk Management and Insurance, Risk and Insurance Research Center, College of Commerce, National Chengchi University, 64, Sec. 2, Zhinan Road, Wenshan District, Taipei, 11605, Taiwan

    Yung-Ming Shiu

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  1. Hui-Hsuan Liu
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Appendix

Appendix

As shown in Table A1, both F-values are significant at the 0.01 level, indicating that both reinsurance and liquidity are endogenous variables. Since endogeneity is an issue in our data, we therefore decide to use 2SLS to estimate the model. However, it is important to note that 2SLS cannot be applied to an equation unless that equation is identified. The identification problem should be addressed. Since the number of predetermined (exogenous plus lagged endogenous) variables in the system is equal to the number of slope coefficients in the equation, the order condition is thus satisfied. The rank condition is also met because the equation can be estimated using 2SLS.Footnote 41

Table A1 The results for the endogenous tests
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Liu, HH., Shiu, YM. & Liu, TC. Reinsurance and Liquidity: Evidence from the United Kingdom General Insurance Industry. Geneva Pap Risk Insur Issues Pract 41, 307–324 (2016). https://doi.org/10.1057/gpp.2015.23

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