Etude des marchés d'assurance non-vie à l'aide d'équilibres de ...

tel-00703797, version 2 - 7 Jun 2012
typeclassFC 0.0259947 0.0012908 20.139 < 2e-16 ***
diffdriverPH2all drivers > 24 0.1603390 0.0110572 14.501 < 2e-16 ***
diffdriverPH2commercial 0.5143316 0.0338102 15.212 < 2e-16 ***
diffdriverPH2learner 17 0.2501158 0.0642750 3.891 9.97e-05 ***
diffdriverPH2same -0.1661160 0.0111876 -14.848 < 2e-16 ***
diffdriverPH2young drivers 0.2524112 0.0158128 15.962 < 2e-16 ***
gender -0.0593577 0.0088454 -6.711 1.94e-11 ***
Log(theta) 0.2848294 0.0330418 8.620 < 2e-16 ***
Zero-inflation model coefficients (binomial with logit link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) -7.299505 0.367536 -19.861 < 2e-16 ***
lastprem_group2(500,5e+03] -0.484487 0.081025 -5.979 2.24e-09 ***
diff2tech -7.214606 0.562964 -12.815 < 2e-16 ***
isinsuredinaccident -0.256634 0.098848 -2.596 0.00942 **
polage -0.011704 0.004260 -2.747 0.00601 **
polholderage 0.094674 0.004658 20.326 < 2e-16 ***
---
Signif. codes: 0 ’***’ 0.001 ’**’ 0.01 ’*’ 0.05 ’.’ 0.1 ’ ’ 1
Theta = 1.3295
Number of iterations in BFGS optimization: 77
Log-likelihood: -2.81e+04 on 24 Df
GLM outputs for Subsection 1.5.3
1.8. Appendix
It follows the regression summary for ordered logistic regression for FC agent subset.
Call: polr(formula = deductibleFC3 ~ nbclaim08FC + ClaimNBhat + bonuspercentnew +
lastprem_group2 + diff2tech + isinsuredinaccident + polage +
vehiclage + polholderage + typeclassFC, data = subdata, Hess = TRUE,
method = "logistic")
Coefficients:
Value Std. Error t value pvalue
nbclaim08FC -2.900e-02 8.425e-03 -3.442e+00 0.180
ClaimNBhat 1.656e+00 9.401e-02 1.762e+01 0.036
bonuspercentnew 1.391e-02 3.357e-04 4.143e+01 0.015
lastprem_group2(500,5e+03] -3.026e-01 1.129e-02 -2.679e+01 0.024
diff2tech -1.720e+00 6.900e-02 -2.493e+01 0.026
isinsuredinaccident -2.964e-01 9.988e-03 -2.968e+01 0.021
polage -2.789e-02 3.594e-04 -7.759e+01 0.008
vehiclage 4.625e-02 1.056e-03 4.381e+01 0.015
polholderage -9.538e-03 2.921e-04 -3.266e+01 0.019
typeclassFC 1.169e-01 1.154e-03 1.013e+02 0.006
Intercepts:
Value Std. Error t value
0|150 -2.3565 0.0354 -66.5322
150|300 -0.4060 0.0334 -12.1655
300|500 4.1764 0.0341 122.4217
Residual Deviance: 664289.21
AIC: 664315.21
The GLM regression summary for lapse on the FC agent subset including deductible choice
probabilities is available on request to the author.
GAM outputs for Subsection 1.6.2
Below we give the regression summary for the TPL agent dataset. Other summaries are
available on request to the author.
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