Table 6:

Binary logistic regressions for three model specifications. Subsample A.

VariableModel 1Model 2Model 3
Estimatep-valueEstimatep-valueEstimatep-value
X1General risk propensity–0.0800.420
X2Financial risk propensity0.0300.758
X3Relative risk propensity 0.2640.090
X4Male0.2120.5420.1160.7390.1220.719
X5Age–0.1480.479–0.1500.471–0.1240.560
X6Marriage1.1500.0071.1140.0091.1330.008
X7Bequest motive (number of kids)–0.3160.037–0.3280.028–0.2930.053
X8Education0.8730.0660.8530.0700.9950.040
X9Economics status–0.1400.218–0.1640.144–0.1380.221
X10Real estate0.1970.6440.1980.6430.1290.764
X11Financial investments0.8120.0620.7700.0780.7070.106
X12Expected lifetime0.2740.4290.2660.4420.2740.432
X13Time preference0.4250.2220.3960.2510.5210.143
X14Trust in annuity provider0.339<0.0010.3230.0010.3230.001
X15Demand for commitment0.7370.0380.7150.0440.6760.059
 Constant–0.7190.678–0.7820.652–1.0410.554
 Hosmer-Lemeshow8.0760.4267.8000.4538.8960.351
 R-Nagelkerke0.2320.2290.245
 Confusion matrix in %69.6 (70.2; 66.9)64.9 (68.3;61.4)69.0 (72.2;65.9)
Source: own elaboration.
Note: For the confusion matrix, the first value denotes the proportion of all correctly classified observations. This includes the share of correctly classified annuity certain choices (the first value in bracket) and the share of correctly classified lifetime annuity choices (the second value in bracket).

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