Earnings Mobility and Inequality: An Integrated Framework
46 Pages Posted: 20 Dec 2012
Date Written: November 2012
In this paper we propose an integrated framework for the analysis of earnings inequality and mobility, which enables the analysis of the distributional dimension of inequality reduction from mobility, an assessment of the economic drivers of mobility and a sense of which drivers are equalising and dis-equalising. In particular we are able to capture the extent to which life-cycle characteristics, key life events, job related characteristics, and changes in working time affect overall mobility and inequality. The framework also offers a bounded approach to isolating the underlying inequality reduction resulting from mobility from measurement error which can otherwise lead to a substantial upward bias. Using data from the Australian HILDA survey we find evidence of a sizable degree of earnings mobility in Australia over the years 2001/2 to 2008/9. The raw inequality reduction resulting from economic mobility was 0.148 Gini points from an initial estimate of 0.368, however, the bounded range based on two alternative versions of two stage estimation lies between 0.072 and 0.102 or between ¼ and 1/3 of original inequality. We show how the inequality reduction from mobility is primarily driven in the bottom part of the initial distribution, with the upper tail being particularly prone to measurement issues. A sizeable part of the identified mobility is simply driven by age-earnings growth that sees more rapid wage increases for younger workers and wage progression among women in notably stronger in reducing inequality because they start lower in distribution. Yet this rather smooth picture of earnings rising with age is shown to be substantially driven by a series of less frequent step changes associated with job-tojob moves, promotions and taking on more responsibility. There are also shocks which run against this equalising process, most notably job loss, which has substantial negative effects on earnings and disproportionately falls on lower waged workers.
Keywords: earnings, mobility, distributional analysis, measurement error
JEL Classification: D31, J01, J60
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