Improving the Measurement of Earnings Dynamics

Moira Daly, Dmytro Hryshko () and Iourii Manovskii

No 22938, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: The stochastic process for earnings is the key element of incomplete markets models in modern quantitative macroeconomics. We show that a simple modification of the canonical process used in the literature leads to a dramatic improvement in the measurement of earnings dynamics in administrative and survey data alike. Empirically, earnings at the start or end of earnings spells are lower and more volatile than the observations in the interior of earnings histories, reflecting the effects of working less than the full year as well as deviations of wages due to e.g. tenure effects. Ignoring these properties of earnings, as is standard in the literature, leads to a substantial mismeasurement of the variances of permanent and transitory shocks and induces the large and widely documented divergence in the estimates of these variances based on fitting the earnings moments in levels or growth rates. Accounting for these effects enables more accurate analysis using quantitative models with permanent and transitory earnings risk, and improves empirical estimates of consumption insurance against permanent earnings shocks.

JEL-codes: D31 D91 E21 (search for similar items in EconPapers)
Date: 2016-12
New Economics Papers: this item is included in nep-mac
Note: EFG LS
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Citations: View citations in EconPapers (9)

Published as Moira Daly & Dmytro Hryshko & Iourii Manovskii, 2022. "IMPROVING THE MEASUREMENT OF EARNINGS DYNAMICS," International Economic Review, vol 63(1), pages 95-124.

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Journal Article: IMPROVING THE MEASUREMENT OF EARNINGS DYNAMICS (2022)
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