Distinguishing aging,period and cohort effects in longitudinal studies of elderly populations

In the analysis of longitudinal data sets describing the characteristics of elderly populations it is useful to distinguish aging, period, and cohort effects. An aging effect is a change in variable values which occurs among all cohorts independently of time period, as each cohort grows older. A cohort effect is a change which characterizes populations born at a particular point in time, but which is independent of the process of aging. A period effect is a change which occurs at a particular time, affecting all age groups and cohorts uniformly. In this paper a dummy variable regression technique and a parallel graphical technique are introduced as means of identifying aging, cohort, and period effects in a longitudinal data set. These techniques are applied to data describing Los Angeles County which appeared in the censuses of 1940, 1950, 1960 and 1970. Trends in residential density, home ownership, housing value, apartment living, rental rates, one-person households and racial composition are investigated, and aging, cohort and period effects are noted and interpreted.