Testing for an Economic Gradient in Health Status Using Subjective Data
Can self-assessments of health reveal the true health differentials between 'rich' and 'poor'? The potential sources of bias include psychological adaptation to ill-health, socioeconomic covariates of health reporting errors and income measurement errors. We propose an estimation...
Main Authors: | , |
---|---|
Format: | Journal Article |
Language: | EN |
Published: |
2012
|
Subjects: | |
Online Access: | http://hdl.handle.net/10986/4726 |
id |
okr-10986-4726 |
---|---|
recordtype |
oai_dc |
spelling |
okr-10986-47262021-04-23T14:02:19Z Testing for an Economic Gradient in Health Status Using Subjective Data Lokshin, Michael Ravallion, Martin Health Production I120 Socialist Institutions and Their Transitions: Consumer Economics Health Education and Training: Welfare, Income, Wealth, and Poverty P360 Can self-assessments of health reveal the true health differentials between 'rich' and 'poor'? The potential sources of bias include psychological adaptation to ill-health, socioeconomic covariates of health reporting errors and income measurement errors. We propose an estimation method to reduce the bias by isolating the component of self-assessed health that is explicable in terms of objective health indicators and allowing for broader dimensions of economic welfare than captured by current incomes. On applying our method to survey data for Russia we find a pronounced (nonlinear) economic gradient in health status that is not evident in the raw data. This is largely attributable to the health effects of age, education and location. 2012-03-30T07:29:26Z 2012-03-30T07:29:26Z 2008 Journal Article Health Economics 10579230 http://hdl.handle.net/10986/4726 EN http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank Journal Article Russian Federation |
repository_type |
Digital Repository |
institution_category |
Foreign Institution |
institution |
Digital Repositories |
building |
World Bank Open Knowledge Repository |
collection |
World Bank |
language |
EN |
topic |
Health Production I120 Socialist Institutions and Their Transitions: Consumer Economics Health Education and Training: Welfare, Income, Wealth, and Poverty P360 |
spellingShingle |
Health Production I120 Socialist Institutions and Their Transitions: Consumer Economics Health Education and Training: Welfare, Income, Wealth, and Poverty P360 Lokshin, Michael Ravallion, Martin Testing for an Economic Gradient in Health Status Using Subjective Data |
geographic_facet |
Russian Federation |
relation |
http://creativecommons.org/licenses/by-nc-nd/3.0/igo |
description |
Can self-assessments of health reveal the true health differentials between 'rich' and 'poor'? The potential sources of bias include psychological adaptation to ill-health, socioeconomic covariates of health reporting errors and income measurement errors. We propose an estimation method to reduce the bias by isolating the component of self-assessed health that is explicable in terms of objective health indicators and allowing for broader dimensions of economic welfare than captured by current incomes. On applying our method to survey data for Russia we find a pronounced (nonlinear) economic gradient in health status that is not evident in the raw data. This is largely attributable to the health effects of age, education and location. |
format |
Journal Article |
author |
Lokshin, Michael Ravallion, Martin |
author_facet |
Lokshin, Michael Ravallion, Martin |
author_sort |
Lokshin, Michael |
title |
Testing for an Economic Gradient in Health Status Using Subjective Data |
title_short |
Testing for an Economic Gradient in Health Status Using Subjective Data |
title_full |
Testing for an Economic Gradient in Health Status Using Subjective Data |
title_fullStr |
Testing for an Economic Gradient in Health Status Using Subjective Data |
title_full_unstemmed |
Testing for an Economic Gradient in Health Status Using Subjective Data |
title_sort |
testing for an economic gradient in health status using subjective data |
publishDate |
2012 |
url |
http://hdl.handle.net/10986/4726 |
_version_ |
1764392522291871744 |