_3.1 Impact of cohort effects_ To disentangle the age-specific correlation with well-being from that of the cohort effect, we add indicators for birth decades to the above regressions. The results for the IVS data and regressions with individual controls are given in Table 2, which reveals that not all functional forms of age remain significant when we control for cohort effects. For instance, although the U-shape remains robust for the ECA countries in column (1), the squared specification for Western Europe (column 2) fails to reach significance for the linear term even though it remains jointly significant. This latter could imply that well-being increases throughout the lifespan. The cohort effects themselves take varying signs but mostly fail to reach significance. Moreover, a within-comparison of the cohort dummies reveals only small differences, with only those born in 1990 and after showing significantly higher well-being in ECA countries.

The second pair of columns, regressions (3) and (4), illustrate the S-shape of well-being for ECA and Western European countries. Comparing these specifications (see Tables 1 and 2) reveals that the inclusion of cohort effects has only a small impact on the age coefficients: as minima and maxima move toward younger age, well-being levels become lower in older age, a pattern observable for both ECA countries and Western Europe. The non-functional form of age mostly mimics the cubic term (Figure 2, bottom panels): the age coefficients for ECA lose their significance after the late 50s, but those for Western Europe show only a small decrease from 18–22 until the early 40s. In line with the functional form, the point estimate for wellbeing appears to decline for Western Europeans in the oldest age group, even though it is not significantly different from that for the young reference group. Interestingly, the cohort dummies for the ECA region (column 5) are also not significant, except for the 1930 birth cohort, which experienced the deprivation related to World War II at a very young age. Most cohort dummies for Western Europe, in contrast, are significant and negative, pointing to the relatively higher well-being of those in the oldest cohort (born before 1919).<sup>13</sup> The marginal effects in Figure 2 show quite constant well-being over time, with slight downturns in middle and old age.

To confirm the importance of cohort effects and their interplay with the age specification, we apply the same method used for the IVS data to the LiTS data set (age range of 18–99), although we cannot make direct comparisons between the ECA and Western Europe because the LiTS only covers ECA countries in more than one wave. The age pattern revealed by the LiTS results (Figure 3) is similar to that from the IVS with some noteworthy exceptions: First, the LiTS results for the cubic age specification provide little support for a second turning point in well-being, as maxima are estimated to be beyond normal life expectancy, and thus suggest

> 13 It should be noted, however, that the reference cohort (born before 1919) is a very select sample, not only because of their survival but also because their early years coincide with turbulent times (e.g., the 1917 October Revolution and WWI).

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