Semiparametric Models

Joel L. Horowitz ()
Additional contact information
Joel L. Horowitz: University of Iowa

Working Papers from University of Iowa, Department of Economics

Abstract: Much empirical research in the social sciences is concerned with estimating conditional mean functions. The most frequently used estimation methods assume that the conditional mean function is known up to a set of constant parameters that can be estimated from data. Such methods are called parametric. Their use greatly simplifies estimation and inference but is rarely justified by theoretical or other a priori considerations. Estimation and inference based on convenient but incorrect assumptions about the form of the conditional mean function can be highly misleading. Semiparametric methods reduce the strength of the assumptions required for estimation and inference, thereby reducing the opportunities for obtaining misleading results. In addition, semiparametric methods mitigate certain disadvantages of fully nonparametric methods that make no assumptions about the shape of the conditional mean function. This article describes three important semiparametric models for conditional mean functions. These are single index, partially additive, and additive models. These models are compared with parametric and fully nonparametric models. An example based on real data illustrates the pitfalls of parametric models and the advantages of semiparametric ones.

Keywords: Kernel estimator; single-index model; additive model; partially linear model (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2000-01
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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: https://EconPapers.repec.org/RePEc:uia:iowaec:00-01

Access Statistics for this paper

More papers in Working Papers from University of Iowa, Department of Economics University of Iowa, Department of Economics, Henry B. Tippie College of Business, Iowa City, Iowa 52242. Contact information at EDIRC.
Bibliographic data for series maintained by None ( this e-mail address is bad, please contact ).