Economics at your fingertips  

Nonparametric heteroskedasticity in persistent panel processes: An application to earnings dynamics

Irene Botosaru and Yuya Sasaki

Journal of Econometrics, 2018, vol. 203, issue 2, 283-296

Abstract: This paper considers a dynamic panel model where a latent state variable follows a unit root process with nonparametric heteroskedasticity. We develop constructive nonparametric identification and estimation of the skedastic function. Applying this method to the Panel Survey of Income Dynamics (PSID) in the framework of earnings dynamics, we found that workers with lower pre-recession permanent earnings had higher earnings risk during the three most recent recessions.

Keywords: Conditional heteroskedasticity; Nonparametric identification; Earnings risk (search for similar items in EconPapers)
JEL-codes: C14 C23 E24 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2019-09-10
Handle: RePEc:eee:econom:v:203:y:2018:i:2:p:283-296