This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Imposing Moment Restrictions From Auxiliary Data By Weighting

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Judith K. Hellerstein
Guido W. Imbens

Additional information is available for the following registered author(s):

Abstract

In this paper we analyze the estimation of coefficients in regression models under moment restrictions in which the moment restrictions are derived from auxiliary data. The moment restrictions yield weights for each observation that can subsequently be used in weighted regression analysis. We discuss the interpretation of these weights under two assumptions: that the target population (from which the moments are constructed) and the sampled population (from which the sample is drawn) are the same, and that these populations differ. We present an application based on omitted ability bias in estimation of wage regressions. The National Longitudinal Survey Young Men's Cohort (NLS) - in addition to containing information for each observation on wages, education, and experience - records data on two test scores that may be considered proxies for ability. The NLS is a small dataset, however, with a high attrition rate. We investigate how to mitigate these problems in the NLS by forming moments from the joint distribution of education, experience, and log wages in the 1% sample of the 1980 U.S. Census and using these moments to construct weights for weighted regression analysis of the NLS. We analyze the impacts of our weighted regression techniques on the estimated coefficients and standard errors of returns to education and experience in the NLS controlling for ability, with and without the assumption that the NLS and the Census samples are random samples from the same population. © 1999 by the President and Fellows of Harvard College and the Massachusetts Institute of Technolog

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. 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.

File URL: http://www.catchword.com/cgi-bin/cgi?ini=bc&body=linker&reqidx=0034-6535(19990201)81:1L.1;1-
File Format: text/html
File Function:
Download Restriction: Access to full text is restricted to subscribers.

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.

Publisher Info
Article provided by MIT Press in its journal The Review of Economics and Statistics.

Volume (Year): 81 (1999)
Issue (Month): 1 (February)
Pages: 1-14
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:tpr:restat:v:81:y:1999:i:1:p:1-14

Contact details of provider:
Web page: http://mitpress.mit.edu/journals/

Order Information:
Web: http://mitpress.mit.edu/journal-home.tcl?issn=00346535

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords:

Other versions of this item:

References listed on IDEAS
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.:
  1. Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," Harvard Institute of Economic Research Working Papers 1736, Harvard - Institute of Economic Research.
    Other versions:
  2. Hausman, Jerry A & Wise, David A, 1979. "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment," Econometrica, Econometric Society, vol. 47(2), pages 455-73, March. [Downloadable!] (restricted)
  3. Imbens, G.W., 1991. "An Efficient Method Of Moments Estimator For Discrete Choice Models With Choice-Based Sampling," Harvard Institute of Economic Research Working Papers 1546, Harvard - Institute of Economic Research.
    Other versions:
  4. Keane, Michael & Moffitt, Robert & Runkle, David, 1988. "Real Wages over the Business Cycle: Estimating the Impact of Heterogeneity with Micro Data," Journal of Political Economy, University of Chicago Press, vol. 96(6), pages 1232-66, December. [Downloadable!] (restricted)
  5. Ridder, Geert, 1992. "An empirical evaluation of some models for non-random attrition in panel data," Structural Change and Economic Dynamics, Elsevier, vol. 3(2), pages 337-355, December. [Downloadable!] (restricted)
  6. Imbens, G.W. & Lancaster, T., 1991. "Combining Micro and Macro Data in Microeconometric Models," Harvard Institute of Economic Research Working Papers 1578, Harvard - Institute of Economic Research.
    Other versions:
  7. Imbens, G., 1993. "A New Approach to Generalized Method on Moments Estimation," Harvard Institute of Economic Research Working Papers 1633, Harvard - Institute of Economic Research.
  8. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May. [Downloadable!] (restricted)
  9. McKinley Blackburn & David Neumark, 1991. "Unobserved Ability, Efficiency Wages, and Interindustry Wage Differentials," NBER Working Papers 3857, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  10. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, 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.)

  1. Daniel Egel & Bryan S. Graham & Cristine Campos de Xavier Pinto, 2008. "Inverse Probability Tilting and Missing Data Problems," NBER Working Papers 13981, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  2. Changchun Wu & Runchu Zhang, 2006. "An Information-theoretic Approach to the Effective Usage of Auxiliary Information from Survey Data," Annals of the Institute of Statistical Mathematics, Springer, vol. 58(3), pages 499-509, September. [Downloadable!] (restricted)
  3. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," NBER Technical Working Papers 0220, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  4. Michael Rendall & Ryan Admiraal & Alessandra DeRose & Paola DiGiulio & Mark Handcock & Filomena Racioppi, 2008. "Population constraints on pooled surveys in demographic hazard modeling," Statistical Methods and Applications, Springer, vol. 17(4), pages 519-539, October. [Downloadable!] (restricted)
  5. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 1998. "Combining Panel Data Sets with Attrition and Refreshment Samples," Tinbergen Institute Discussion Papers 98-033/4, Tinbergen Institute. [Downloadable!]
    Other versions:
  6. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  7. Elbers, Chris & Lanjouw, Jean O. & Lanjouw, Peter, 2002. "Micro-level estimation of welfare," Policy Research Working Paper Series 2911, The World Bank. [Downloadable!]
  8. William J Carrington & John L Eltinge & Kristin McCue, 2000. "An Economist's Primer on Survey Samples," Working Papers 00-15, Center for Economic Studies, U.S. Census Bureau. [Downloadable!]
  9. Paul J. Devereux & Gautam Tripathi, 2008. "Optimally combining Censored and Uncensored Datasets," Working Papers 200820, School Of Economics, University College Dublin. [Downloadable!]
    Other versions:
  10. F Bravo, 2008. "Effcient M-estimators with auxiliary information," Discussion Papers 08/26, Department of Economics, University of York. [Downloadable!]
  11. repec:bep:sndecm:11:2007:4:1531-1531 is not listed on IDEAS
  12. Artem Prokhorov & Peter Schmidt, 2008. "GMM Redundancy Results for General Missing Data Problems," Working Papers 08003, Concordia University, Department of Economics. [Downloadable!]
    Other versions:
  13. Aviv Nevo, 2001. "Using Weights to Adjust for Sample Selection When Auxiliary Information is Available," NBER Technical Working Papers 0275, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  14. Michael S. Rendall & Ryan Admiraal & Alessandra De Rose & Paola Di Giulio & Mark S. Handcock & Filomena Racioppi, 2006. "Population constraints on pooled surveys in demographic hazard modeling," MPIDR Working Papers WP-2006-039, Max Planck Institute for Demographic Research, Rostock, Germany. [Downloadable!]
Statistics
Access and download statistics

Did you know? IDEAS also covers the most complete directory of Economics departments and institutes, EDIRC.

This page was last updated on 2009-11-16.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.