Table A3:

Binary logistic regressions for three specifications. Subsample B.

VariableModel 1Model 2Model 3
Estimatep-valueEstimatep-valueEstimatep-value
X1General risk propensity–0.1810.016
X2Financial risk propensity0.0130.850
X3Relative risk propensity0.3260.001
X4Male0.0420.859–0.0400.865–0.0640.785
X5Age0.1170.1830.1290.1380.1190.177
X6Marriage0.6760.0220.5620.0530.5830.046
X7Bequest motive (number of kids)–0.2320.048–0.2300.045–0.2260.054
X8Education0.1940.4850.2010.4640.2290.415
X9Economics status0.1370.0900.0930.2360.1210.126
X10Real estate–0.1370.658–0.0960.755–0.1050.733
X11Financial investments0.3530.2320.3230.2690.3330.264
X12Expected lifetime0.4890.0360.4550.0490.4160.076
X13Time preference0.5140.0310.4580.0520.6110.012
X14Trust in annuity provider0.235< 0.0010.2010.0030.2000.003
X15Demand for commitment0.5760.0180.5150.0320.5200.032
 Constant–2.4880.002–2.803< 0.001–2.797< 0.001
 Hosmer-Lemeshow3.7400.88010.3430.2422.7150.951
 R-Nagelkerke0.1450.1260.163
 Confusion matrix in %64.8 (72.0; 56.7)60.9 (67.7;53.4)64.8 (69.8; 59.2)
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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