Why Inferential Statistics are Inappropriate for Development Studies and How the Same Data Can be Better Used

23 Pages Posted: 4 Mar 2011

See all articles by Clint Ballinger

Clint Ballinger

affiliation not provided to SSRN

Date Written: March 2, 2011

Abstract

The purpose of this paper is twofold:

1) to highlight the widely ignored but fundamental problem of 'super-populations' 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 super-populations 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: inferential statistics, philosophy of the social sciences, methodology, frequentist statistics, superpopulations, determinism, Bayesian statistics, subjectivist statistics, econometrics, economic development, macro-comparative research, visual methods, descriptive statistics, tabular analysis

Suggested Citation

Ballinger, Clint, Why Inferential Statistics are Inappropriate for Development Studies and How the Same Data Can be Better Used (March 2, 2011). Available at SSRN: https://ssrn.com/abstract=1775002 or http://dx.doi.org/10.2139/ssrn.1775002

Clint Ballinger (Contact Author)

affiliation not provided to SSRN ( email )

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