IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/29780.html
   My bibliography  Save this paper

Why inferential statistics are inappropriate for development studies and how the same data can be better used

Author

Listed:
  • Ballinger, Clint

Abstract

The purpose of this paper is twofold: 1) to highlight the widely ignored but fundamental problem of ‘superpopulations’ for the use of inferential statistics in development studies. We do not to dwell on this problem however as it has been sufficiently discussed in older papers by statisticians that social scientists have nevertheless long chosen to ignore; the interested reader can turn to those for greater detail. 2) to show that descriptive statistics both avoid the problem of superpopulations and can be a powerful tool when used correctly. A few examples are provided. The paper ends with considerations of some reasons we think are behind the adherence to methods that are known to be inapplicable to many of the types of questions asked in development studies yet still widely practiced.

Suggested Citation

  • Ballinger, Clint, 2011. "Why inferential statistics are inappropriate for development studies and how the same data can be better used," MPRA Paper 29780, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:29780
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/29780/1/MPRA_paper_29780.pdf
    File Function: original version
    Download Restriction: no

    References listed on IDEAS

    as
    1. Hoover,Kevin D., 2001. "Causality in Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521002882.
    2. Judea Pearl, 2003. "Statistics and causal inference: A review," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(2), pages 281-345, December.
    3. repec:cup:apsrev:v:88:y:1994:i:02:p:412-423_09 is not listed on IDEAS
    4. David A. Freedman & Stephen P. Klein & Jerome Sacks & Charles A. Smyth & Charles G. Everett, 1991. "Rejoinder," Evaluation Review, , vol. 15(6), pages 800-816, December.
    5. Hall, Peter A. & Franzese, Robert J., 1998. "Mixed Signals: Central Bank Independence, Coordinated Wage Bargaining, and European Monetary Union," International Organization, Cambridge University Press, vol. 52(03), pages 505-535, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    frequentist statistics; Bayesian statistics; causation; determinism; explanation; spatial autocorrelation; mulitple regression; international development; econometrics; comparative method; datasets; descriptive statistics; tabular analysis; visual analysis; maps; regession modeling; quantitative; qualitative; macrosociology; superpopulations; apparent populations; indeterminism; statistical assumptions;

    JEL classification:

    • B0 - Schools of Economic Thought and Methodology - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • P16 - Economic Systems - - Capitalist Systems - - - Political Economy of Capitalism
    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • F5 - International Economics - - International Relations, National Security, and International Political Economy
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    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:pra:mprapa:29780. 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: (Joachim Winter). General contact details of provider: http://edirc.repec.org/data/vfmunde.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.