Appendix Table 1.
Maximum-Likelihood Estimates of Log Risk Tolerance
| Latent Variable: Log of Noisy Risk Tolerance: ξit
| ||||
|---|---|---|---|---|
| Mean Effect
|
Std. Dev. Effect | |||
| Variable | Direct | Type | Composite | |
| Constant |
−3.30 (0.74) |
1.46 (0.49) |
||
| Male |
0.14 (0.04) |
0.12 (0.02) |
||
| Black |
−0.28 (0.06) |
0.18 (0.03) |
||
| Hispanic | −0.03 −(0.03) |
0.10 (0.05) |
||
| 1937–1941 Cohorts |
0.16 (0.06) |
0.003 (0.04) |
||
| 1942–1947 Cohorts | 0.16 (0.10) |
0.03 (0.07) |
||
| High School Drop Out | 0.02 (0.06) |
0.09 (0.03) |
||
| Some College |
0.17 (0.05) |
0.03 (0.03) |
||
| College Graduate |
0.22 (0.06) |
−0.01 (0.04) |
||
| Post Graduate |
0.32 (0.06) |
0.03 (0.04) |
||
| Index Consumer Sentiment / 10 |
0.09 (0.02) |
−0.04 (0.02) |
||
| Current Age / 10 |
−0.17 (0.08) |
0.02 (0.05) |
||
| Currently Married | 0.11 (0.09) |
−0.07 (0.06) |
||
| Fraction Exact Probability |
0.82 (0.10) |
−0.42 (0.07) |
||
| Previous Job Displacement | −0.06 (0.07) |
0.01 (0.05) |
||
| Previous Health Condition | −0.09 (0.06) |
−0.05 (0.05) |
||
| Log (Current Income) / 10 | 0.29 (0.34) |
0.14 (0.25) |
||
| Log (Current + Wealth) / 10 | 0.10 (0.17) |
−0.22 (0.11) |
||
| Log (| Current − Wealth |) / 10 | 0.35 (0.21) |
−0.10 (0.13) |
||
| Proportion of Years Married |
−0.27 (0.10) |
−0.05 (0.07) |
||
| Panel Average FEP |
0.27 (0.14) |
−0.57 (0.09) |
||
| Ever Job Displacement |
0.19 (0.06) |
0.02 (0.05) |
||
| Ever Health Condition | 0.02 (0.06) |
0.02 (0.04) |
||
| Log (Average Income) / 10 | 0.60 (0.45) |
0.68 (0.30) |
||
| Log (Average + Wealth) / 10 | −0.07 (0.22) |
0.31 (0.14) |
||
| Log (| Average − Wealth |) / 10 | 0.15 (0.30) |
0.51 (0.18) |
||
| “New Job” Version | −0.08 (0.09) |
−0.07 (0.06) |
||
NOTE: Standard errors are in parentheses. Estimates in bold are statistically significant at the 5% level. The log-likelihood is −23573.5. The sample includes 12,003 individuals. The estimated standard deviation of the unpredictable persistent component of risk tolerance is 0.72. The standard deviation of the transitory component is where σe is the parameter vector of the standard deviation effects. The gambles in the 1992 and 1994 HRS ask about a new job, whereas the wording in the later waves removes the status quo bias. See the notes on Table 4–7 and text for details on the variables.