IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/18859.html
   My bibliography  Save this paper

What Are We Weighting For?

Author

Listed:
  • Gary Solon
  • Steven J. Haider
  • Jeffrey Wooldridge

Abstract

The purpose of this paper is to help empirical economists think through when and how to weight the data used in estimation. We start by distinguishing two purposes of estimation: to estimate population descriptive statistics and to estimate causal effects. In the former type of research, weighting is called for when it is needed to make the analysis sample representative of the target population. In the latter type, the weighting issue is more nuanced. We discuss three distinct potential motives for weighting when estimating causal effects: (1) to achieve precise estimates by correcting for heteroskedasticity, (2) to achieve consistent estimates by correcting for endogenous sampling, and (3) to identify average partial effects in the presence of unmodeled heterogeneity of effects. In each case, we find that the motive sometimes does not apply in situations where practitioners often assume it does. We recommend diagnostics for assessing the advisability of weighting, and we suggest methods for appropriate inference.

Suggested Citation

  • Gary Solon & Steven J. Haider & Jeffrey Wooldridge, 2013. "What Are We Weighting For?," NBER Working Papers 18859, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18859
    Note: CH DEV ED HC HE LS PE TWP
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w18859.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. O'Connell, Philip J. & Russell, Helen & FitzGerald, John, 2006. "Human Resources," Book Chapters, in: Morgenroth, Edgar (ed.),Ex-Ante Evaluation of the Investment Priorities for the National Development Plan 2007-2013, Economic and Social Research Institute (ESRI).
    2. Steven D. Levitt, 1998. "Juvenile Crime and Punishment," Journal of Political Economy, University of Chicago Press, vol. 106(6), pages 1156-1185, December.
    3. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
    4. Card, David & Krueger, Alan B, 1992. "Does School Quality Matter? Returns to Education and the Characteristics of Public Schools in the United States," Journal of Political Economy, University of Chicago Press, vol. 100(1), pages 1-40, February.
    5. Elder Todd E & Goddeeris John H & Haider Steven J, 2011. "A Deadly Disparity: A Unified Assessment of the Black-White Infant Mortality Gap," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 11(1), pages 1-44, June.
    6. Stephen G. Donald & Kevin Lang, 2007. "Inference with Difference-in-Differences and Other Panel Data," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 221-233, May.
    7. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    8. Justin Wolfers, 2006. "Did Unilateral Divorce Laws Raise Divorce Rates? A Reconciliation and New Results," American Economic Review, American Economic Association, vol. 96(5), pages 1802-1820, December.
    9. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
    10. Dickins, William T, 1990. "Error Components in Grouped Data: Is It Ever Worth Weighting?," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 328-333, May.
    11. Jeffrey M. Wooldridge, 1999. "Asymptotic Properties of Weighted M-Estimators for Variable Probability Samples," Econometrica, Econometric Society, vol. 67(6), pages 1385-1406, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    2. David Gunawan & William Griffths & Anatasios Panagiotelis and Duangkamon Chotikapanich, 2017. "Bayesian Weighted Inference from Surveys "Abstract: Data from large surveys are often supplemented with sampling weights that are designed to reflect unequal probabilities of response and selecti," Department of Economics - Working Papers Series 2030, The University of Melbourne.
    3. Gary Solon & Steven J. Haider & Jeffrey M. Wooldridge, 2015. "What Are We Weighting For?," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 301-316.
    4. Rucker C. Johnson, 2011. "Long-run Impacts of School Desegregation & School Quality on Adult Attainments," NBER Working Papers 16664, National Bureau of Economic Research, Inc.
    5. Maria Iacovou, 2002. "Class Size in the Early Years: Is Smaller Really Better?," Education Economics, Taylor & Francis Journals, vol. 10(3), pages 261-290.
    6. Fitzsimons, Emla & Malde, Bansi & Mesnard, Alice & Vera-Hernández, Marcos, 2016. "Nutrition, information and household behavior: Experimental evidence from Malawi," Journal of Development Economics, Elsevier, vol. 122(C), pages 113-126.
    7. Saul D. Hoffman & E. Michael Foster, 2000. "AFDC Benefits and Nonmarital Births to Young Women," Journal of Human Resources, University of Wisconsin Press, vol. 35(2), pages 376-391.
    8. Stella Min & Miles G. Taylor, 2018. "Racial and Ethnic Variation in the Relationship Between Student Loan Debt and the Transition to First Birth," Demography, Springer;Population Association of America (PAA), vol. 55(1), pages 165-188, February.
    9. Dhaval Dave & Bo Feng & Michael F. Pesko, 2019. "The effects of e‐cigarette minimum legal sale age laws on youth substance use," Health Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 419-436, March.
    10. Terence C. Cheng & Pravin K. Trivedi, 2015. "Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the Mabel Survey," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1101-1117, September.
    11. Ammermueller, Andreas & Kuckulenz, Anja & Zwick, Thomas, 2009. "Aggregate unemployment decreases individual returns to education," Economics of Education Review, Elsevier, vol. 28(2), pages 217-226, April.
    12. Hans J. Baumgartner, 2003. "Are There Any Class Size Effects On Early Career Earnings In West Germany?," HEW 0305004, University Library of Munich, Germany, revised 05 Nov 2003.
    13. Cantarella, Michele & Strozzi, Chiara, 2019. "Workers in the Crowd: The Labour Market Impact of the Online Platform Economy," IZA Discussion Papers 12327, Institute of Labor Economics (IZA).
    14. Peter Gottschalk & Michael Hansen, 2003. "Is the Proportion of College Workers in Noncollege Jobs Increasing?," Journal of Labor Economics, University of Chicago Press, vol. 21(2), pages 409-448, April.
    15. Bertrand, Marianne & Hanna, Rema & Mullainathan, Sendhil, 2010. "Affirmative action in education: Evidence from engineering college admissions in India," Journal of Public Economics, Elsevier, vol. 94(1-2), pages 16-29, February.
    16. Verdugo, Gregory, 2016. "Real wage cyclicality in the Eurozone before and during the Great Recession: Evidence from micro data," European Economic Review, Elsevier, vol. 82(C), pages 46-69.
    17. Jens Ludwig & Jeffrey R. Kling, 2007. "Is Crime Contagious?," Journal of Law and Economics, University of Chicago Press, vol. 50, pages 491-518.
    18. Lihui Zhang, 2016. "Are youth offenders responsive to changing sanctions? Evidence from the Canadian Youth Criminal Justice Act of 2003," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(2), pages 515-554, May.
    19. A. Colin Cameron & Douglas L. Miller, 2010. "Robust Inference with Clustered Data," Working Papers 106, University of California, Davis, Department of Economics.
    20. Fitzsimons, Emla & Malde, Bansi & Mesnard, Alice & Vera-Hernández, Marcos, 2012. "Household Responses to Information on Child Nutrition: Experimental Evidence from Malawi," CEPR Discussion Papers 8915, C.E.P.R. Discussion Papers.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:18859. 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: (). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.