Ballinger, Clint (2011): Why inferential statistics are inappropriate for development studies and how the same data can be better used.
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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.
|Item Type:||MPRA Paper|
|Original Title:||Why inferential statistics are inappropriate for development studies and how the same data can be better used|
|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|
|Subjects:||B - History of Economic Thought, Methodology, and Heterodox Approaches > B0 - General
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General
C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models; Multiple Variables > C33 - Models with Panel Data; Longitudinal Data; Spatial Time Series
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General
P - Economic Systems > P1 - Capitalist Systems > P16 - Political Economy
A - General Economics and Teaching > A1 - General Economics > A11 - Role of Economics; Role of Economists; Market for Economists
O - Economic Development, Technological Change, and Growth > O1 - Economic Development
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General
F - International Economics > F5 - International Relations and International Political Economy
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C20 - General
C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models; Multiple Variables
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C23 - Models with Panel Data; Longitudinal Data; Spatial Time Series
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
|Depositing User:||Dr. Clint Ballinger|
|Date Deposited:||05. Apr 2011 18:01|
|Last Modified:||12. Feb 2013 08:14|
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