Measuring the Nature of Individual Sequences

This study reviews and compares indicators that can serve to characterize numerically the nature of state sequences. It also introduces several new indicators. Alongside basic measures such as the length, the number of visited distinct states, and the number of state changes, we shall consider composite measures such as turbulence and the complexity index, and measures that take account of the nature (e.g., positive vs. negative or ranking) of the states. The discussion points out the strange behavior of some of the measures-Elzinga's turbulence and the precarity index of Ritschard, Bussi, and O'Reilly in particular-and propositions are made to avoid these flaws. The usage of the indicators is illustrated with two applications using data from the Swiss Household Panel. The first application tests the U-shape hypothesis about the evolution of life satisfaction along the life course, and the second one examines the scarring effect of earlier employment sequences.

Automated summary

This study reviews and compares indicators that can numerically describe the nature of state sequences, and introduces several new indicators. The discussion points out the strange behavior of some of the indicators and proposes hypotheses to avoid these flaws. The usage of the indicators is illustrated through two applications using data from the Swiss Household Panel.