IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v237y2023i2s0304407623002336.html
   My bibliography  Save this article

What is a standard error? (And how should we compute it?)

Author

Listed:
  • Wooldridge, Jeffrey M.

Abstract

I review the definition of a standard error from a frequentist perspective, including both exact analysis and asymptotic analysis. Using the linear model for illustration, I discuss the model-based, design-based, and sampling-based approaches to uncertainty in obtaining standard errors. The model-based approach is widely applicable and produces reasonable measures of estimator precision in many settings. In some situations, particularly in the context of clustering, the model-based approach can suffer from ambiguity, and can lead to standard errors that are systematically biased. A combination of the design-based and sampling-based approaches requires the researcher to think about the variation in key explanatory variables when computing standard errors, and it can even apply to cases where the entire population is observed.

Suggested Citation

  • Wooldridge, Jeffrey M., 2023. "What is a standard error? (And how should we compute it?)," Journal of Econometrics, Elsevier, vol. 237(2).
  • Handle: RePEc:eee:econom:v:237:y:2023:i:2:s0304407623002336
    DOI: 10.1016/j.jeconom.2023.105517
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304407623002336
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jeconom.2023.105517?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Standard error; Model-based approach; Design-based approach; Sampling-based approach; Clustering;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

    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:eee:econom:v:237:y:2023:i:2:s0304407623002336. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.