Testing for a common latent variable in a linear regression: Or how to "fix" a bad variable by adding multiple proxies for it

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dc.contributor.author Wittenberg, Martin
dc.date.accessioned 2013-10-11T12:30:45Z
dc.date.available 2013-10-11T12:30:45Z
dc.date.issued 2005-10
dc.identifier.isbn 1-77011-067-4
dc.identifier.uri http://hdl.handle.net/11090/661
dc.description.abstract We analyse models in which additional “controls” or proxies are included in a regression. This might occur intentionally if there is significant measurement error in a key regressor or if a key variable is not measured at all. We develop a test of the hypothesis that a subset of the regressors are all proxying for the same latent variable and we show how an estimate of the structural coefficient might be obtained more efficiently than is available in the current literature. We apply the procedure to the determinants of sleep among young South Africans. We show that the income variable in the time use survey is badly measured. Nevertheless the measured impact of income on sleep is significant and amounts to 35 minutes per day between children with the median income and those in the topmost income bracket. Including a variety of asset proxies increases the estimated size of the coefficient enormously. The specification tests indicate that some of the asset proxies, however, have independent effects. Access to electricity, in particular, is not simply proxying for income. Instead it seems to be capturing access to various forms of entertainment, such as television. Even when this independent effect is properly accounted for, the size of the income coefficient is still 40% to 100% larger than in the specifications without the proxies. en_US
dc.language.iso en en_US
dc.publisher CSSR and SALDRU en_US
dc.relation.ispartofseries CSSR/SALDRU Working Papers;132
dc.subject Latent variable en_US
dc.subject Econometrics en_US
dc.subject Regression en_US
dc.subject Linear regression en_US
dc.subject Control variables en_US
dc.subject Proxy variables en_US
dc.subject Income en_US
dc.subject Sleep en_US
dc.subject Specification test en_US
dc.subject Income coefficient en_US
dc.subject Measurement error en_US
dc.title Testing for a common latent variable in a linear regression: Or how to "fix" a bad variable by adding multiple proxies for it en_US
dc.type Working Paper en_US


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