Identifying age, period and cohort effects: Are the new methods really better?ISER Internal Seminars

How and why do people and societies change? We often wrestle with the question of whether shifts in attitudes and behaviour are associated with age or the life course, historical period, or birth cohort / generation. The problem of disentangling age, period and cohort effects has become a staple issue in longitudinal analysis.

New statistical approaches to age-period-cohort analysis (e.g. cross-classified multilevel models, intrinsic estimator, maximum entropy) have appeared in the past decade. Despite (or perhaps because of) their technical impenetrability, many scholars use them relatively uncritically. They have come to be seen as state-of-the-art tools that should be used in preference to less sophisticated methods. Using religious change in Great Britain and the United States as empirical illustrations, I argue that these new techniques are no more likely to produce correct solutions than approaches that explicitly call on substantive assumptions. I propose an alternative strategy based on visualisation and an iterative inductive-deductive approach.

Presented by:

David Voas (ISER)

Date & time:

9 Oct 2013 12:00 pm


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