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. 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. Copyright 2012, Oxford University Press.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 26 (2012)
Issue (Month): 2 ()
|Contact details of provider:|| Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK|
Phone: (202) 477-1234
Fax: 01865 267 985
Web page: http://wber.oxfordjournals.org/
More information through EDIRC
|Order Information:||Web: http://www.oup.co.uk/journals|
When requesting a correction, please mention this item's handle: RePEc:oup:wbecrv:v:26:y:2012:i:2:p:236-264. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.