Finally, as the last within-country analysis for the U.S., we investigate age effects in
Figure 7.
Figure 7: Welfare Losses, ∆W0 / W0, for U.S. (SCF) Data; Gender = 0 (male),
γ = 2, δ = 0.97, Age = 30, 50, or 65, Education = Middle, Labor Income = Median
(age-specific)
--- put Figure 7 here ---
The magnitude of differences in welfare losses according to age shown in Figure 7
are difficult to interpret. At different ages, the discounted value of the expected labor
income stream changes following the curves depicted in Figure 2. Furthermore, the
income quantiles are different. Finally, the time horizon—and thus the number of
future welfare losses discounted—is different between different age groups. Thus,
only some results can be clearly identified. For example, for individuals age 65, the
welfare losses are the lowest, because the gap between optimal and empirical asset
allocation is the smallest. Furthermore, there are fewer future periods with welfare
losses. This also explains to some extent why younger age is associated with higher
welfare losses.
6.2 Results for German Individuals
In this section, we repeat the analysis given in section 6.1 for the German EVS data.
Figure 8 shows the effect of a variation in labor income, net worth, and gender for
German individuals.
Figure 8: Welfare Losses, ∆W0 / W0, for German (EVS) Data; Gender = 0 (male)
or 1 (female), γ = 2, δ = 0.97, Age = 50, Education = Middle
--- put Figure 8 here ---
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