IDEAS home Printed from https://ideas.repec.org/a/ags/agreko/345236.html
   My bibliography  Save this article

The standard error of regressions: a note on new evidence of significance misuse

Author

Listed:
  • Mbatha, C.N.
  • Gustafsson, M.A.

Abstract

There is a body of literature dealing with the improper use of statistical significance within economic analysis. Amongthe problematic usages that have been identified are fundamental misunderstandings about the influence of sample design and size on statistical significance, an excessive focus on statistical significance to the exclusion of economic and policy significance, and a harmful conflation of these two very different types of significance. An analysis of 51 agricultural economics papers reviewed and presented at an African conference in 2010 finds improper usage of statistical significance that is comparable or worse in nature and extent to that found in a previous meta analysis focusing on published articles in the American Economic Review in the 1980s and 1990s: well over half of the papers employed what is termed “sign” and “asterisks” econometrics. Overall, the findings underline the need for clearly stated and consistent analytical methods in producing papers as well as for careful review and selection of papers that employ regression analysis.

Suggested Citation

  • Mbatha, C.N. & Gustafsson, M.A., 2013. "The standard error of regressions: a note on new evidence of significance misuse," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 52(01), March.
    • Handle: RePEc:ags:agreko:345236
    DOI: 10.22004/ag.econ.345236
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/345236/files/The%20standard%20error%20of%20regressions%20%20a%20note%20on%20new%20evidence%20of%20significance%20misuse.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.345236?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. Deirdre N. McCloskey & Stephen T. Ziliak, 1996. "The Standard Error of Regressions," Journal of Economic Literature, American Economic Association, vol. 34(1), pages 97-114, March.
    2. Stephen T. Ziliak & Deirdre N. McCloskey, 2004. "Size Matters: The Standard Error of Regressions in the American Economic Review," Econ Journal Watch, Econ Journal Watch, vol. 1(2), pages 331-358, August.
    3. McCloskey, Donald N, 1985. "The Loss Function Has Been Mislaid: The Rhetoric of Significance Tests," American Economic Review, American Economic Association, vol. 75(2), pages 201-205, May.
    4. Romer, Christina D, 1986. "Is the Stabilization of the Postwar Economy a Figment of the Data?," American Economic Review, American Economic Association, vol. 76(3), pages 314-334, June.
    5. Parcell, Joseph L. & Kastens, Terry L. & Dhuyvetter, Kevin C. & Schroeder, Ted C., 2000. "Agricultural Economists' Effectiveness In Reporting And Conveying Research Procedures And Results," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 29(2), pages 1-10, October.
    6. T. Dudley Wallace, 1977. "Pretest Estimation in Regression: A Survey," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 59(3), pages 431-443.
    7. Stan du Plessis, 2006. "The miracle of the Septuagint and the promise of data mining in economics," Working Papers 15/2006, Stellenbosch University, Department of Economics.
    8. Aye, Goodness C. & Mungatana, Eric D., 2010. "Technological Innovation and Efficiency in the Nigerian Maize Sector: Parametric Stochastic and Non-parametic Distance Function Approaches," 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa 95965, African Association of Agricultural Economists (AAAE).
    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. repec:ags:ijag24:345236 is not listed on IDEAS
    2. Parcell, Joe L. & Kastens, Terry L. & Dhuyvetter, Kevin C. & Schroeder, Ted C., 2000. "Agricultural Economists' Effectiveness in Reporting and Conveying Research Procedures and Results," Agricultural and Resource Economics Review, Cambridge University Press, vol. 29(2), pages 173-182, October.
    3. Stephen T. Ziliak & Deirdre N. McCloskey, 2013. "We Agree That Statistical Significance Proves Essentially Nothing: A Rejoinder to Thomas Mayer," Econ Journal Watch, Econ Journal Watch, vol. 10(1), pages 97-107, January.
    4. Black, Bernard & Hollingsworth, Alex & Nunes, Letícia & Simon, Kosali, 2022. "Simulated power analyses for observational studies: An application to the Affordable Care Act Medicaid expansion," Journal of Public Economics, Elsevier, vol. 213(C).
    5. Kevin Hoover & Mark Siegler, 2008. "Sound and fury: McCloskey and significance testing in economics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 15(1), pages 1-37.
    6. Altman, Morris, 2004. "Statistical significance, path dependency, and the culture of journal publication," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(5), pages 651-663, November.
    7. Nektarios A. Michail & Constantinos I. Massouras, 2014. "Back to Basics: Is Statistical Significance all that Matters?," Working Papers 2014-3, Central Bank of Cyprus.
    8. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, December.
    9. Altman, Morris, 2020. "A more scientific approach to applied economics: Reconstructing statistical, analytical significance, and correlation analysis," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 315-324.
    10. Meszaros, Sandor, 2008. "Theory testing (hypothesis testing) in agricultural economics," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 107, pages 1-13, March.
    11. Niclas Berggren & Mikael Elinder & Henrik Jordahl, 2008. "Trust and growth: a shaky relationship," Empirical Economics, Springer, vol. 35(2), pages 251-274, September.
    12. Zhimin Zhou & Xinyue Ye & Xiangyu Ge, 2017. "The Impacts of Technical Progress on Sulfur Dioxide Kuznets Curve in China: A Spatial Panel Data Approach," Sustainability, MDPI, vol. 9(4), pages 1-27, April.
    13. Rachel G. Childers, 2011. "Being One'S Own Boss: How Does Risk Fit In?," The American Economist, Sage Publications, vol. 56(1), pages 48-58, May.
    14. Ricardo Barradas & Ines Tomas, 2023. "Household indebtedness in the European Union countries: Going beyond the mainstream interpretation," PSL Quarterly Review, Economia civile, vol. 76(304), pages 21-49.
    15. Anupama Sen and Tooraj Jamasb, 2012. "Diversity in Unity: An Empirical Analysis of Electricity Deregulation in Indian States," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    16. Peter J. Veazie, 2015. "Understanding Statistical Testing," SAGE Open, , vol. 5(1), pages 21582440145, January.
    17. Thomas Mayer, 2012. "Ziliak and McCloskey's Criticisms of Significance Tests: An Assessment," Econ Journal Watch, Econ Journal Watch, vol. 9(3), pages 256-297, September.
    18. Günther Rehme, 2011. "Endogenous Policy And Cross‐Country Growth Empirics," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(2), pages 262-296, May.
    19. Xinyu (Jason) Cao, 2009. "Disentangling the influence of neighborhood type and self-selection on driving behavior: an application of sample selection model," Transportation, Springer, vol. 36(2), pages 207-222, March.
    20. Petersen, Verner C., 2005. "The otherworldly view of economics - and its consequences," Working Papers 2005-13, University of Aarhus, Aarhus School of Business, Department of Management.
    21. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Working Papers hal-03455978, HAL.

    More about this item

    Keywords

    Agribusiness;

    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:ags:agreko:345236. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aeasaea.html .

    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.