IDEAS home Printed from https://ideas.repec.org/a/sae/evarev/v12y1988i1p3-58.html
   My bibliography  Save this article

Assessing the Quality of Longitudinal Surveys

Author

Listed:
  • Robert F. Boruch

    (Northwestern University)

  • Robert W. Pearson

    (Social Science Research Council and Columbia University)

Abstract

A growing concern has emerged in recent years about the use of relatively large national longitudinal surveys. This concern arises in part from a heightened sensitivity to the diminished support for new data-collection programs across the U.S. federal statistical system and the increasing competition throughout the research and policy communities for what have undoubtedly always been scarce resources for research. Despite this concern, there have yet to be developed tools for evaluating the relative or comparative value of longitudinal surveys and criteria by which more intelligent decisions can be made with respect to whether an ongoing survey should be continued or terminated This article argues that criteria are unlikely to be developed for evaluating whether one longitudinal survey is "better" than another, but that one can assess the quality and usefulness of a particular survey, and it suggests specific guidelines for such assessments.

Suggested Citation

  • Robert F. Boruch & Robert W. Pearson, 1988. "Assessing the Quality of Longitudinal Surveys," Evaluation Review, , vol. 12(1), pages 3-58, February.
  • Handle: RePEc:sae:evarev:v:12:y:1988:i:1:p:3-58
    DOI: 10.1177/0193841X8801200101
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0193841X8801200101
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0193841X8801200101?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. repec:pri:indrel:dsp014m90dv50s is not listed on IDEAS
    2. Orley Ashenfelter & Gary Solon, 1982. "Longitudinal Labor Market Data: Sources, Uses, and Limitations," Working Papers 535, Princeton University, Department of Economics, Industrial Relations Section..
    3. Thomas Fraker & Rebecca Maynard, 1987. "The Adequacy of Comparison Group Designs for Evaluations of Employment-Related Programs," Journal of Human Resources, University of Wisconsin Press, vol. 22(2), pages 194-227.
    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. James J. Heckman, 1991. "Randomization and Social Policy Evaluation Revisited," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.
    2. Clampit, Jack & Gaffney, Nolan & Fabian, Frances & Stafford, Thomas, 2023. "Institutional misalignment and escape-based FDI: A prospect theory lens," International Business Review, Elsevier, vol. 32(3).
    3. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    4. Metcalf, Charles E., 1997. "The Advantages of Experimental Designs for Evaluating Sex Education Programs," Children and Youth Services Review, Elsevier, vol. 19(7), pages 507-523, November.
    5. Ari Hyytinen & Jaakko Meriläinen & Tuukka Saarimaa & Otto Toivanen & Janne Tukiainen, 2018. "When does regression discontinuity design work? Evidence from random election outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 1019-1051, July.
    6. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    7. Gonzalo Nunez-Chaim & Henry G. Overman & Capucine Riom, 2024. "Does subsidising business advice improve firm performance? Evidence from a large RCT," CEP Discussion Papers dp1977, Centre for Economic Performance, LSE.
    8. Larry L. Orr, 2018. "The Role of Evaluation in Building Evidence-Based Policy," The ANNALS of the American Academy of Political and Social Science, , vol. 678(1), pages 51-59, July.
    9. Kenneth Fortson & Natalya Verbitsky-Savitz & Emma Kopa & Philip Gleason, 2012. "Using an Experimental Evaluation of Charter Schools to Test Whether Nonexperimental Comparison Group Methods Can Replicate Experimental Impact Estimates," Mathematica Policy Research Reports 27f871b5b7b94f3a80278a593, Mathematica Policy Research.
    10. 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.
    11. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    12. David H. Dean & Robert C. Dolan & Robert M. Schmidt, 1999. "Evaluating the Vocational Rehabilitation Program Using Longitudinal Data," Evaluation Review, , vol. 23(2), pages 162-189, April.
    13. Ferraro, Paul J. & Miranda, Juan José, 2014. "The performance of non-experimental designs in the evaluation of environmental programs: A design-replication study using a large-scale randomized experiment as a benchmark," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 344-365.
    14. Ham, John C. & LaLonde, Robert J., 2005. "Special issue on Experimental and non-experimental evaluation of economic policy and models," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 1-13.
    15. Nianbo Dong & Mark W. Lipsey, 2018. "Can Propensity Score Analysis Approximate Randomized Experiments Using Pretest and Demographic Information in Pre-K Intervention Research?," Evaluation Review, , vol. 42(1), pages 34-70, February.
    16. Astrid Grasdal, 2001. "The performance of sample selection estimators to control for attrition bias," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 385-398, July.
    17. Lechner, Michael & Wunsch, Conny, 2013. "Sensitivity of matching-based program evaluations to the availability of control variables," Labour Economics, Elsevier, vol. 21(C), pages 111-121.
    18. Kenneth Fortson & Philip Gleason & Emma Kopa & Natalya Verbitsky-Savitz, "undated". "Horseshoes, Hand Grenades, and Treatment Effects? Reassessing Bias in Nonexperimental Estimators," Mathematica Policy Research Reports 1c24988cd5454dd3be51fbc2c, Mathematica Policy Research.
    19. Kenneth A. Couch & Dana W. Placzek, 2010. "Earnings Losses of Displaced Workers Revisited," American Economic Review, American Economic Association, vol. 100(1), pages 572-589, March.
    20. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.

    More about this item

    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:sae:evarev:v:12:y:1988:i:1:p:3-58. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.