# Using semi-parametric methods in an analysis of earnings mobility

*Shawn W. Ulrick*

*Econometrics Journal*, 2008, vol. 11, issue 3, pages 478-498

**Abstract:**
This paper describes a dynamic random effects econometric model from which inferences on earnings mobility may be made. It answers questions such as, given some initial level of observed earnings, what is the probability that an agent with certain characteristics will remain below a specified level of earnings (for example the poverty level) for a specified number of time periods? Existing research assumes that the distributions of the unobserved permanent and transitory shocks in the model are known up to finitely many parameters. However, predictions of earnings mobility are highly sensitive to assumptions about these distributions. The present paper estimates the distributions of the random effects non-parametrically. The results are used to predict the probabilities of remaining in a low state of earnings. The results from the non-parametric distributions are contrasted to those obtained under a normality assumption. Using the non-parametrically estimated distributions gives estimated probabilities that are smaller than those obtained under the normality assumption. Through a Monte Carlo experiment and by examining unconditional predicted earnings distributions, it is demonstrated that the non-parametric method is likely to be considerably more accurate, and that assuming normality may give quite misleading results. Copyright Journal compilation Royal Economic Society 2008. No claim to original US government works

**Date:** 2008

**References:** Add references at CitEc

**Citations** View citations in EconPapers (1) Track citations by RSS feed

**Downloads:** (external link)

http://www.blackwell-synergy.com/doi/abs/10.1111/j.1368-423X.2008.00248.x link to full text (text/html)

Access to full text is restricted to subscribers.

**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:** http://EconPapers.repec.org/RePEc:ect:emjrnl:v:11:y:2008:i:3:p:478-498

**Ordering information:** This journal article can be ordered from

http://www.ectj.org

Access Statistics for this article

Econometrics Journal is currently edited by *Richard J. Smith*, *Oliver Linton*, *Pierre Perron*, *Jaap Abbring* and *Marius Ooms*

More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.

Series data maintained by Wiley-Blackwell Digital Licensing ().