Reducing bias due to missing values of the response variable by joint modeling with an auxiliary variable
AbstractIn this paper, we consider the problem of missing values of a continuous response variable that cannot be assumed to be missing at random. The example considered here is an analysis of pupil's subjective engagement at school using longitudinal survey data, where the engagement score from wave 3 of the survey is missing due to a combination of attrition and item non-response. If less engaged students are more likely to drop out and less likely to respond to questions regarding their engagement, then missingness is not ignorable and can lead to inconsistent estimates. We suggest alleviating this problem by modelling the response variable jointly with an auxiliary variable that is correlated with the response variable and not subject to non-response. Such auxiliary variables can be found in administrative data, in our example, the National Pupil Database containing test scores from national achievement tests. We estimate a joint model for engagement and achievement to reduce the bias due to missing values of engagement. A Monte Carlo study is performed to compare our proposed multivariate response approach with alternative approaches such as the Heckman selection model and inverse probability of selection weighting.
Download InfoIf 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.
Bibliographic InfoPaper provided by Department of Quantitative Social Science - Institute of Education, University of London in its series DoQSS Working Papers with number 12-05.
Date of creation: 29 Jun 2012
Date of revision:
Contact details of provider:
Postal: Department of Quantitative Social Science. 20 Bedford Way London WC1H 0AL
Phone: (44) (0)20 7612 6654. Eliminate (44) and add (0) if calling from inside the UK. Add (44) and eliminate (0) if calling from abroad.
Fax: (44) (0)20 7612 6686
Web page: http://www.ioe.ac.uk/study/departments/369.html
More information through EDIRC
Auxiliary variable; joint model; multivariate regression; not missing at random; sample selection bias; seemingly-unrelated regressions; selection model; SUR;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
This paper has been announced in the following NEP Reports:
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.:
- Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
- Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-90, March.
- Lee Lillard & James P. Smith & Finis Welch, 2004.
"What Do We Really Know About Wages: The Importance of Nonreporting and Census Imputation,"
Labor and Demography
- Lillard, Lee & Smith, James P & Welch, Finis, 1986. "What Do We Really Know about Wages? The Importance of Nonreporting and Census Imputation," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 489-506, June.
- Lorraine Dearden & Alfonso Miranda & Sophia Rabe-Hesketh, 2011.
"Measuring school value added with administrative data: the problem of missing variables,"
DoQSS Working Papers
11-05, Department of Quantitative Social Science - Institute of Education, University of London.
- Lorraine Dearden & Alfonso Miranda & Sophia Rabe‐Hesketh, 2011. "Measuring School Value Added with Administrative Data: The Problem of Missing Variables," Fiscal Studies, Institute for Fiscal Studies, vol. 32(2), pages 263-278, 06.
- Whitney Newey, 1999.
"Two Step Series Estimation of Sample Selection Models,"
99-04, Massachusetts Institute of Technology (MIT), Department of Economics.
- Whitney K. Newey, 2009. "Two-step series estimation of sample selection models," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages S217-S229, 01.
- Little, Roderick J A, 1985. "A Note about Models for Selectivity Bias," Econometrica, Econometric Society, vol. 53(6), pages 1469-74, November.
- Puhani, Patrick A, 2000. " The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lindsey Macmillan).
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.