Measuring Sequence Quality

Abstract

We propose a new measure to quantify the quality of binary sequences that can be meaningfully interpreted as series of successes and failures. We operationalize the concept of positive and negative sequences by formulating general properties that a quality measure must adhere to, construct a measure that fulfills these requirements, and show that such measure can be modeled in a theoretically meaningful way. We apply such measure of sequence quality to data from the Household, Income, and Labour Dynamics in Australia (HILDA) Survey over the period 2001 to 2013, and model the evolution of employment career quality after the occurrence of an initial spell of unemployment, providing a direct test of unemployment “scarring” theories. We define states of unemployment and inactivity as failures and those of employment as successes to predict whether prior unemployment leads to descending spirals into inactivity and joblessness or whether patterns of full career recovery exist. Our findings lend support to scarring theories by demonstrating that, despite recovery trends, career disparities among previously unemployed workers persist long after their first unemployment experience. We conclude discussing implications of the findings and proposing directions for future extensions of the measure.