Differential Results by Other Variables

Type of Pension The impact of the type of pension on the analyzed relationship is interesting for two reasons: First, pensioners who died receiving an old–age pen-sion benefit from a longer duration, which is certainly due to their better health status. The alternative—receiving a pension due to a reduction of the earnings ca-pacity or disability pension—is an (almost) ultimate means of helping those who are unable to work, beyond any temporary rehabilitation. In addition, at the legal retirement age, all disability pensions are transformed into old–age pensions, such that there is legal restriction of the age at death for those who receive a disability pension and die during this time. (See Figure 3.7, the results are confirmed by the signs of the parametric identification).

17See Lusardi and Mitchell (2007) on the impact of financial literacy on retirement–related behavior.

The authors can show that education determines financial literacy, especially the necessary knowl-edge for retirement planning.

CHAPTER3 Rich and Healthy—Better than Poor and Sick?

Solid: mts.= 0, dashed: mts.<6, dotted: mts.≥6. Left panel (a1): not instrumented, right panel: instrumented (a2). Men only, explanatory variable: total benefit claims.

(c) Multi–variate, Left panel: men, right panel: women. Explanatory variable: total benefit claims.

Figure 3.5: Results by Health–Status I

Second, the impact of benefit claims differs by the kind of pension. While I find for those with old–age pensions the already familiar positive impact on duration, there is virtually no influence of benefit claims on people with disability pensions.

This corresponds to a recent finding by Kiuila and Mieszkowski (2007), who find that life expectancy is—under some circumstances— not related to income at all, but ultimately determined by independent health factors. A similar argument I find in Adams et al. (2003), who claim that the impact of income on health depend on the type of illness. These arguments carry over to the analysis of the duration of the benefit spell: Conditional on being in very bad health, benefit claims lose their impact on duration, as opposed to my findings with respect to transitory spells of ill–health.

Unemployment I apply a similar stratification to the months spent in unemploy-ment (hence, the individual had not been unemployed at all, less than six months, or six months and more, see Figure 3.8), and the general shape of the benefit claims–

duration relationship is not affected, no matter if total benefit claims (instrumented

CHAPTER3 Rich and Healthy—Better than Poor and Sick?

(a) Solid: mts.= 0, dashed: mts.<6, dotted: mts.≥6. Men only, explanatory variable: average benefit claims.

(c) Multi–variate, left panel: men, right panel: women. Explanatory variable: average benefit claims.

Figure 3.6: Results by Health–Status II

or not) or average benefit claims serve as explanatory variable. Differences in be-tween different unemployment groups are virtually not present.

Still, the coefficients of the unemployment variable (see Tables 3.3, 3.4, and 3.5) are significantly negative in most specifications, hence, pensioners who had to suf-fer from unemployment spells have shorter pension benefit spells. This result is not universal, as one partially linear specification produces an insignificant coefficient, and least squares regressions yield once an insignificant and once even a signifi-cantly positive sign. In all cases, the absolute value is small, especially compared to the ill–health variable, the largest coefficient indicates that each month in un-employment reduces duration of the benefit spell approximately 14 days. Shorter duration of individuals in unemployment is compatible with the negative effect of unemployment on life expectancy I find in Chapter 4.

Residence There is little to no difference in the impact of benefit claims on dura-tion if the sample is divided in West and East Germany. If I use total benefit claims, it is apparent that at the right end of the benefit claims distribution, the gradient

CHAPTER3 Rich and Healthy—Better than Poor and Sick?

Solid: old–age pension, dashed: disability pension. Left panel: not instrumented, right panel: instrumented (partially linear). Men only, explanatory variable: total benefit claims.

Solid: old–age pension, dashed: disability pension. Men only, explanatory variable: average claims per year.

Figure 3.7: Results by Type of Pension

for East Germany is very steep. Notice, however, that there are still more than 6% of all observations in the area with more than 60 points of total benefit claims, such that the steep increase in this area is reliable, and not an artifact of outliers, see Figure 3.9. The sign of the coefficients of the East–dummy (see Tables 3.4 and 3.5) are ambiguous; depending on the exact specification, the sign ranges from sig-nificantly negative over insignificant to sigsig-nificantly positive. The most reliably specifications—namely, regressions on the restricted data set, weighted and either IV or average claims as explanatory variable—yield a positive or insignificant sign.

This is certainly due to (1) institutional factors, because large unemployment in East Germany corresponds to the utilization of early retirement schemes wherever possible, and (2) due to the fact that conditional on reaching retirement age, life expectancy in East Germany is not so different from West Germany anymore, and in some instances even higher (see Chapter 4 on life expectancies as a function of benefit claims).

CHAPTER3 Rich and Healthy—Better than Poor and Sick?

Solid: mts.= 0, dashed: mts.<6, dotted: mts.≥6. Left panel: not instrumented (a1), right panel: instrumented (a2). Men only, explanatory variable: total benefit claims.

(a) Solid: mts.= 0, dashed: mts.<6, dotted: mts.≥6. Men only, explanatory variable: average claims per year.

Figure 3.8: Results by Unemployment

Birth Cohorts The weighting scheme I introduce in Equation (3.1) is not neces-sary, if the whole analysis is stratified along birth cohorts. A specific life expectancy at birth is related to each birth cohort, such that there is no need to account for over or under–sampling of different cohorts.

I distinguish cohorts of individuals born between 1920 and 1929 and 1930 to 1939, respectively. The level effect between the both cohorts is a result of the con-struction and the absence of the weighting schemewithineach cohort, as the later cohort had to die relatively early in order to be part of the sample, which has a negative effect on duration as well.

In each cohort, I find an increasing relationship between benefit claims and du-ration, though the impact of benefit claims is less pronounced for the later birth cohort. (See Figure 3.10).

Years of Contribution Finally, the analysis takes years of contribution into ac-count. If years of contributions are considered parametrically (b, d), see Tables 3.3, 3.4, and 3.5, they enter almost always negatively (except of the full, instrumented

CHAPTER3 Rich and Healthy—Better than Poor and Sick?

Solid: West, dashed: East. Left panel: not instrumented (1), right panel: instrumented (a2). Men only, explanatory variable: total benefit claims.

(a) Solid: West, dashed: East. Men only, explanatory variable: average claims per year.

Figure 3.9: Results by Residence

and unweighted specification). This is confirmed by the locally linear specifications (see Figure 3.11), where I find a monotone ordering of the three groups (less than 30 years at the top, between 30 and 40 years in the middle, and more then 40 years at the bottom). The link is easily identified, because if pensioners contributed longer to the pension system, this can at least partially be attributed to delayed retirement, which in turn reduces the duration of the benefit spell.