This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Non- and semi-parametric estimation of age and time heterogeneity in repeated cross-sections: an application to self-reported morbidity and general practitioner utilization1

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
David Parkin (Department of Epidemiology and Public Health, University of Newcastle upon Tyne, Newcastle upon Tyne, UK)
Nigel Rice
Matthew Sutton (National Primary Care R&D Centre, Centre for Health Economics, University of York, York, UK)

Additional information is available for the following registered author(s):

Abstract

Patterns of self-reported morbidity and general practitioner (GP) utilization exhibit complex age, sex and time heterogeneity. Underlying patterns are often obscured by data which are overly 'rough' because of noise associated with adjacent year fluctuations. In this paper we describe methods to obtain smoothed estimates of age, time and birth-cohort effects using data from the General Household Survey (GHS), covering the period 1984-1995|6 inclusive. The methods outlined offer powerful analytic tools to research complex profiles or trends, particularly over age or time.

The relationships of the morbidity and GP utilization measures with age, sex and survey year characteristics are estimated non-parametrically using roughness penalized least squares (RPLS). A semi-parametric extension of this model is used to estimate the effect of the morbidity variables on GP utilization. Tests are employed for various forms of age and time heterogeneity including birth-cohort effects. Linear age specifications are rejected for all variables and evidence is found of time heterogeneity in one of the morbidity measures-limiting long-standing illness (LS)-and GP utilization. The advantages of employing non- and semi-parametric estimations in the presence of complex relationships such as those observed for age and time profiles are discussed. Adoption of these techniques by applied econometricians working in health economics is encouraged. Copyright © 1999 John Wiley & Sons, Ltd.

Download Info
To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 8 (1999)
Issue (Month): 5 ()
Pages: 429-440
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:wly:hlthec:v:8:y:1999:i:5:p:429-440

Contact details of provider:
Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords:

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Kosei Fukuda, 2007. "An empirical analysis of US and Japanese health insurance using age-period-cohort decomposition," Health Economics, John Wiley & Sons, Ltd., vol. 16(5), pages 475-489. [Downloadable!]
Statistics
Access and download statistics

Did you know? All the bibliographic data shown here has been contributed by volunteers, thereby helping to keep this service free.

This page was last updated on 2009-12-13.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.