How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam

Research on economic growth and inequality inevitably raises issues concerning economic mobility because the relationship between long-run inequality and short-run inequality is mediated by income mobility; for a given level of short-run inequality, greater mobility implies lower long-run inequality...

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Main Author:	Glewwe, Paul
Format:	Journal Article
Language:	en_US
Published:	Oxford University Press on behalf of the World Bank 2013
Subjects:	autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors
Online Access:	http://hdl.handle.net/10986/16351

id	okr-10986-16351
recordtype	oai_dc
spelling	okr-10986-163512021-04-23T14:03:28Z How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam Glewwe, Paul autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors Research on economic growth and inequality inevitably raises issues concerning economic mobility because the relationship between long-run inequality and short-run inequality is mediated by income mobility; for a given level of short-run inequality, greater mobility implies lower long-run inequality. But empirical measures of both inequality and mobility tend to be biased upward due to measurement error in income and expenditure data collected from household surveys. This paper examines how to reduce or remove this bias using instrumental variable methods, and provides conditions that instrumental variables must satisfy to provide consistent estimates. This approach is applied to panel data from Vietnam. The results imply that at least 15 percent, and perhaps as much as 42 percent, of measured mobility is upward bias due to measurement error. The results also suggest that measurement error accounts for at least 12 percent of measured inequality. 2013-12-04T17:40:37Z 2013-12-04T17:40:37Z 2012-06-01 Journal Article World Bank Economic Review 1564-698X http://hdl.handle.net/10986/16351 en_US CC BY-NC-ND 3.0 IGO http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank Oxford University Press on behalf of the World Bank Journal Article Vietnam
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	en_US
topic	autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors
spellingShingle	autocorrelation covariance Econometrics economic growth equations functional forms household surveys Hypotheses income independent variables inequality instrumental variables long-run inequality matrices Matrix Measurement Error measurement errors Sample size standard deviations standard errors Glewwe, Paul How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam
geographic_facet	Vietnam
description	Research on economic growth and inequality inevitably raises issues concerning economic mobility because the relationship between long-run inequality and short-run inequality is mediated by income mobility; for a given level of short-run inequality, greater mobility implies lower long-run inequality. But empirical measures of both inequality and mobility tend to be biased upward due to measurement error in income and expenditure data collected from household surveys. This paper examines how to reduce or remove this bias using instrumental variable methods, and provides conditions that instrumental variables must satisfy to provide consistent estimates. This approach is applied to panel data from Vietnam. The results imply that at least 15 percent, and perhaps as much as 42 percent, of measured mobility is upward bias due to measurement error. The results also suggest that measurement error accounts for at least 12 percent of measured inequality.
format	Journal Article
author	Glewwe, Paul
author_facet	Glewwe, Paul
author_sort	Glewwe, Paul
title	How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam
title_short	How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam
title_full	How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam
title_fullStr	How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam
title_full_unstemmed	How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam
title_sort	how much of observed economic mobility is measurement error? iv methods to reduce measurement error bias, with an application to vietnam
publisher	Oxford University Press on behalf of the World Bank
publishDate	2013
url	http://hdl.handle.net/10986/16351
_version_	1764432937948807168

How Much of Observed Economic Mobility is Measurement Error? IV Methods to Reduce Measurement Error Bias, with an Application to Vietnam

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