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NOBUS We used the NOBUS4 survey exclusively for the instrumental variable procedure, and we again used the self-reported health status as a health proxy: the dummy healthGOOD comprises both “excellent” and “good” self-rated health status (as in the RLMS analysis). We used a two-stage least squares (2SLS) regression of the logarithm ➤➤ 4 While the RLMS has certain advantages – in particular that it is repeated annually, allowing comparisons over time – the NOBUS survey, so far only held once (in 2003), covers a far larger share of the population – about 44 500 households – and is representative both nationally and for 46 of the larger subjects of the Russian Federation.

The magnitude of its effect is large compared to other variables in the model. In either approach, the effect of chronic illness is found to vary with income: the lower the income the more chronic illness affects the retirement decision. 8 This is the “panel” component of the RLMS, which in principle offers important opportunities for testing hypotheses that involve a causal perspective. One shortcoming of this panel dimension is that it does not feature a true panel design, as households that moved from their dwelling and individuals who moved from their household are not followed.

6 1818 Notes: *** 1% significance level; ** 5% significance level; * 10% significance level; Number of obs. 8969. Alcohol consumption was found to increase by about 10 g per day as a consequence of a death in the household. If the deceased was employed, then the survivor’s alcohol consumption increased 25 g per day. Using the same two years, we employed a tobit model including essentially the same control variables as in the depression model. Surprisingly, if the deceased was the household head, there was no independent impact, at least not in the short term that we examined.

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