Please use this identifier to cite or link to this item:
|Title:||Do firm effects drift? Evidence from Washington Administrative Data|
Woodbury, Stephen A.
|Abstract:||We investigate the time-series properties of firm effects in the AKM models popularized by Abowd et al. (1999). We consider two approaches. The first approach — labelled as the rolling approach — estimates AKM models separately in each T = 2 adjacent time interval. The second approach is based on an extension of the original AKM — labelled as the Time Varying AKM Model (TV-AKM) — in which we allow for unrestricted interactions of year and firm dummies. We correct for biases in the resulting variance decompositions using the leave out correction of Kline et al. (2019). These approaches allow us to examine how firm effects evolve stochastically, their relation to the business cycle, and their contribution to changes in the wage structure at a higher frequency than previously possible. Using data from Washington State, we find that firm effects in earnings and hourly wages are highly persistent. The autocorrelation coefficient between firm effects for wage rates in 2002 and 2014 is 0.74, and between firm effects for earnings in 2002 and 2014 is 0.82. The rolling approach uncovers a significant degree of cyclicality in firm effects. Variability in firm premiums tended to increase during the great recession while the degree of worker and firm assortativity decreased. Time-varying firm effects explains 13% of the variance of log wages and 21% of the variance of log earnings in the Washington state over 2002–2014. Between 2002-2003 and 2013-2014 the variance of firm wage premia decreased by 10%, but this decline was offset by increases in the variance in individual premia and increases in assortative matching that resulted in an overall increase in the variance of wages. Auxiliary evidence suggests that misspecification in AKM models due to the drifting of firm effects is a second-order concern.|
|Appears in Collections:||IRS Working Papers|
Files in This Item:
|629.pdf||1.64 MB||Adobe PDF||View/Download|
Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.