Alignment, Clocking, and Macro Patterns of Episodes in the Life Course}

Timothy Riffe , Universidad del País Vasco & Ikerbasque (Basque Foundation for Science)
Angelo Lorenti , Max Planck Institute for Demographic Research (MPIDR)
Andrés Castro, Max Planck Institute for Demographic Research

Individuals are often observed passing through a sequence of discrete states in trajectory data. These are usually either simplified into transition probabilities to derive asymptotic values of aggregate statistics using Markov assumptions, or else retained for pattern and group detection using sequence analysis. Markov-derived aggregate statistics are of limited scope, and sequence analysis appears aimed at inferring typologies rather than generating demographic aggregates. We propose a structured framework to generate novel aggregate demographic patterns and summary indices from trajectory data, including trajectories generated from Markov models by proposing a simple and extensible grammar of operations for trajectory data. We introduce the concepts of clocking and alignment as a new framework for generating novel statistics from trajectories. We use published transition probabilities to simulate discrete trajectories of employment states to demonstrate concepts. We use retrospective fertility and union trajectories from Colombian Demographic and Health Surveys data and disability trajectories simulated from European Statistics on Income and Living Conditions for Italy (EU-SILC) for example applications. We demonstrate several new demographic aggregate patterns in the areas of disability inequalities and birth intervals. We demonstrate the flexibility of this framework and the ease of generating macro patterns. An R package is provided to facilitate experimentation with these operations.

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 Presented in Session 48. Data and Methods