Semiparametric estimation of the canonical permanent-transitory model of earnings dynamics

Artikel

This paper presents identification and estimation results for a flexible state space model. Our modification of the canonical model allows the permanent component to follow a unit root process and the transitory component to follow a semiparametric model of a higher-order autoregressive-moving-average (ARMA) process. Using panel data of observed earnings, we establish identification of the nonparametric joint distributions for each of the permanent and transitory components over time. We apply the identification and estimation method to the earnings dynamics of U.S. men using the Panel Survey of Income Dynamics (PSID). The results show that the marginal distributions of permanent and transitory earnings components are more dispersed, more skewed, and have fatter tails than the normal and that earnings mobility is much lower than for the normal. We also find strong evidence for the existence of higher-order ARMA processes in the transitory component, which lead to much different estimates of the distributions of and earnings mobility in the permanent component, implying that misspecification of the process for transitory earnings can affect estimated distributions of the permanent component and estimated earnings dynamics of that component. Thus our flexible model implies earnings dynamics for U.S. men different from much of the prior literature.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 10 ; Year: 2019 ; Issue: 4 ; Pages: 1495-1536 ; New Haven, CT: The Econometric Society

Classification and Topics

• Classification: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Wages, Compensation, and Labor Costs: General
• Subject: Earnings dynamics ; semiparametric estimation ; state space model

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hu, Yingyao ; Moffitt, Robert A. ; Sasaki, Yuya
• Event: Veröffentlichung
• (who): The Econometric Society
• (where): New Haven, CT
• (when): 2019

Further information

• DOI: doi:10.3982/QE1117
• Handle: http://hdl.handle.net/10419/217173
• Last update: 10.03.2025, 11:43 AM CET