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

Clint Ballinger ()

MPRA Paper from University Library of Munich, Germany

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.

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 (search for similar items in EconPapers)
JEL-codes: A11 B0 C10 C11 C12 C20 C21 C23 C3 C33 F5 O1 P16 (search for similar items in EconPapers)
Date: 2011-01-06
New Economics Papers: this item is included in nep-ecm, nep-hpe and nep-mic
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