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Competition and Scale Economy Effects of the Dutch 2006 Health-Care Insurance Reform

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Abstract

This paper investigates competitive behaviour and scale economies of the health-care insurance market in the Netherlands over the period 1995–2012. We focus on the impact on the market structure of the 2006 health-care reform, which replaced the dual system of public and private insurance with a single compulsory health insurance scheme in which insurance providers compete for customers in a free market. We start with estimating unused scale economies and find that, after the health-care reform in 2006, unused scale economies at around 20 per cent are much higher than before the reform (4 per cent), pointing to a relative increase of fixed costs. Our interpretation of this change is that fixed costs increased after the reform, as insurers now have to monitor care providers and negotiate with them about lower prices or higher quality. To measure competition directly, we apply a novel approach that estimates the impact of marginal costs as an indicator of inefficiency on either market shares or net profits. Over time, competition in health insurance has increased significantly, but reform-induced market turbulences in 2006 caused a fall in the average level of competitive pressure. After the reform, competition continued to improve.

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Notes

  1. Daley and Gubb (2011).

  2. Schäfer et al. (2010).

  3. The Parliament remains responsible for the composition of the basic health insurance package, while the Minister of health prescribes the "cost" price of the basic health-care package.

  4. Daley and Gubb (2011, p. 9).

  5. Raith (2003); Hay and Liu (1997).

  6. Kox and Van Leeuwen (2011).

  7. We follow the literature and use cost functions rather than production functions. See Coelli et al. (1998, pp. 43–49); Bikker and Bos (2008, p. 14).

  8. Hay and Liu (1997); Boone (2001, 2008).

  9. Bikker and Van Leuvensteijn (2015).

  10. Bikker and Van Leuvensteijn (2008); Bikker (2016a).

  11. Bikker and Bos (2008).

  12. Gaynor and Town (2011, p. 83).

  13. Cummins and Weiss (2014).

  14. Bikker and Gorter (2011).

  15. Greß et al. (2007).

  16. Van den Ven and Schut (2009, p. 253).

  17. Swiss Re (2011); Leu et al. (2009).

  18. Leu et al. (2009).

  19. HHI is defined as the sum of the squared market share, expressed in percentages, so that theoretically, the HHI ranges between 0 and 10,000. Numbers are based on health insurance premium income and measured at aggregate level during 1995–2012.

  20. Yang (2006).

  21. Dafny (2010).

  22. Choi and Weiss (2005); Robinson (2004).

  23. Dranove and Satterthwaite (2000); Gaynor and Vogt (2000); Herrick (2007); Gaynor and Town (2011).

  24. Cummins et al. (2010).

  25. Fenn et al. (2008).

  26. Cummins and Rubio-Misas (2006).

  27. Fecher et al. (1991).

  28. Kasman and Turgutlu (2009).

  29. Cummins and Xie (2013).

  30. Hirao and Inoue (2004).

  31. Cummins and Rubio (2006); Cummins and Xie (2013); Bikker and Gorter (2011).

  32. Toivanen (1997).

  33. Cummins and Weiss (2014, pp. 26–33).

  34. Bikker (2016b).

  35. This is the first simplification, which is due to the functional form in Equation (1) of the non-linear output terms, that is, in deviation from the respective (geometric) mean. The second is that the cross-output terms in Equation (1) disappear entirely in Equation (2), after taking first derivatives.

  36. Bos (2004).

  37. Among others, Choi and Weiss (2005) provide evidence for the non-life insurance industry that supports the efficient structure hypothesis.

  38. Hay and Liu’s (1997).

  39. Theil (1969).

  40. Hay and Liu (1997); Bikker and Van Leuvensteijn (2008).

  41. Mayers and Smith (1988).

  42. Davidson and MacKinnon (1993).

  43. Results not presented in Table 3 are available from the author upon request.

  44. Concavity exists when at least one of the squared output terms has a significant positive coefficient.

  45. This is in line with what was found earlier for other financial institutions: non-life insurers (Bikker and Gorter 3), life insurers (Bikker 2016a), pension funds (Bikker 2016b) and banks (Hughes and Mester 2013).

  46. A Wald test on homogeneity in input prices is not rejected. All test results are available from the authors upon request.

  47. Note that the coefficients of the variables that represent a trend and are invariate across insurers (wage index, HHI and time) should be considered with greater caution, due to possible multicollinearity.

  48. Bikker and Gorter (2011); Eling and Luhnen (2010); Cummins et al. (2004).

  49. Coelli et al. (1998).

  50. Due to the functional form of the model, companies reporting negative profits (losses) are excluded from the analysis. However, this is not expected to create a bias in the results (see Boone 2008).

  51. We prefer the detailed model-based estimates of marginal costs (MC) over alternative inefficiency measures such as data envelopment analysis (DEA) and the stochastic cost frontier approach (SCFA). DEA ignores the existence of model errors and is very sensitive for measurement errors. SCFA inefficiency estimates includes all types of heterogeneity and of possible not explained noise, as long as its sign is positive.

  52. Results not presented in Table 4 are available from the author upon request.

  53. A random-effect model was rejected by the Wu–Hausman test, in favour of the fixed-effects model.

  54. Available from the author upon request.

  55. Average costs are less precise as they do not distinguish between fixed and variable costs. However, it is quite common to approximate average variable costs by average costs. Average costs results are available from the author upon request.

  56. Van Leuvensteijn et al. (2011).

  57. Van Leuvensteijn et al. (2011) estimate a model without the lagged "market share" so that β is their long-term PCS indicator.

  58. Bikker (2016a).

  59. Creusen et al. (2006).

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Authors and Affiliations

  1. Utrecht University, Utrecht, Netherlands

    Jacob A. Bikker

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Appendix: Data and estimates

Appendix: Data and estimates

Table A1 Estimates of the health insurance cost model based on claims (1995–2012)
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Table A2 Alternative estimates of the health insurance cost model based on premiums (2006–2012, excl. NHSI, unweighted)
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Table A3 FE estimates for the non-dynamic health-care PCS model (1995–2012)
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Table A4 FE estimates for the dynamic health-care PCS model using average costs (1995–2012)
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Table A5 PCS health insurance model estimates over time, based on marginal cost (since 2006 including former NHSI)
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Bikker, J.A. Competition and Scale Economy Effects of the Dutch 2006 Health-Care Insurance Reform. Geneva Pap Risk Insur Issues Pract 42, 53–78 (2017). https://doi.org/10.1057/s41288-016-0038-8

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