Frans van Poppel: a sort of farewell. Liber Amicorum. - NIDI

adjustments and reactions are the so-called ‘period effects’. These two effects, together withthe physiological effect of aging, the social influence of family members and peers, and lifecycle circumstances, largely determine the overall outcome. But the study of period effectsdoes by no means imply that only period measures should be used. When examining cohortprofiles, a given period related ‘shock’ of any importance will show up for all cohorts, butat different ages, and in the instance of cohort-period interaction, the magnitude of the effectof the ‘shock’ will vary according to the life cycle stage of each cohort. The breakthrough ofhormonal contraception during the late 1960 s and 1970 s only affected the stopping behaviorof older women, whereas it affected the entire fertile life span of the younger ones, therebyopening up the possibility for a massive postponement of first births. In other words, periodshocks are best studied by assessing their differentiated effect at the various ages and lifecycle stages of each of the successive cohorts. One does not at all need period measures ofdemographic events to do that finer work.This throws us back to period measures and their use. Period measures are synthetic measuresthat are summations of slices of the life cycle unfolding of different cohorts. Fertility, nuptialityor mortality experiences over a short period of time are just summed up to arrive at a finalproduct which is not representative for any of the contributing cohorts. These measures haveno meaning in real life. 2 The only exception is of course that of perfect stationarity. In fact,to give these period measures any meaning, the stationarity condition –i.e. the hypothesisof a frozen society in which cohorts are mere copies of each other– is absolutely essential.Incidentally, this not only pertains to the Total Fertility Rate and to the Singulate MeanAge at Marriage (SMAM) 3 , but also to all the indirectly standardized ‘Princeton measures’(i.e. Coale’s Ig, Im, Ih or If). All these are frequently used measures, because they providesummaries. But only quick and dirty ones. In fact, period measures are merely accountancytricks for impatient users. Indeed, to get an idea of a final intensity 4 , one has to be patient andwait till a certain age is reached by which most of the events have occurred. 5 But nothing willprevent us from measuring the events up to an earlier point (defined by either age or duration)to see where successive cohorts had arrived by that point. One way of doing this is to take a2It could be argued that Kuczynski’s gross and net reproduction rates (GRR and NRR) were major historical stepsforward. But these period measures and especially the NRR led very illustrious demographers down the garden pathand into the belief that Europe was going to die out. Despite the fact that the Lexis diagram was long known by the1930 s , the impact of a tempo shift was totally ignored, together with cohort analyses.3The inventor of SMAM, John Hajnal, was vividly aware of this condition, much more so than many subsequent userswho prefer the blurring effect of SMAM over the clean analysis of proportions married up to a given age (e.g. 20, 25 or30) at various points in time.4The final intensity of mortality is of course always unity, and much of what is going to be said here pertains to otherdemographic events.5The classic objection to cohort analysis is that profiles are incomplete. Here this “impatience factor” shows up veryclearly. It goes without saying that all one can do is try to complete the schedules for cohorts that are far enough, andpurely speculate or write scenarios for those that are just starting with the unfolding of the life course. Just face the factthat the future is unknown for younger cohorts, but that we can monitor their progress, year after year, with a minimumof data requirements.40