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Statistical vs. Economic Significance in Economics and Econometrics: Further comments on McCloskey & Ziliak

  • Tom Engsted

    ()

    (School of Economics and Management, University of Aarhus and CREATES)

I comment on the controversy between McCloskey & Ziliak and Hoover & Siegler on statistical versus economic significance, in the March 2008 issue of the Journal of Economic Methodology. I argue that while McCloskey & Ziliak are right in emphasizing ’real error’, i.e. non-sampling error that cannot be eliminated through specification testing, they fail to acknowledge those areas in economics, e.g. rational expectations macroeconomics and asset pricing, where researchers clearly distinguish between statistical and economic significance and where statistical testing plays a relatively minor role in model evaluation. In these areas models are treated as inherently misspecified and, consequently, are evaluated empirically by other methods than statistical tests. I also criticise McCloskey & Ziliak for their strong focus on the size of parameter estimates while neglecting the important question of how to obtain reliable estimates, and I argue that significance tests are useful tools in those cases where a statistical model serves as input in the quantification of an economic model. Finally, I provide a specific example from economics - asset return predictability - where the distinction between statistical and economic significance is well appreciated, but which also shows how statistical tests have contributed to our substantive economic understanding.

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Paper provided by Department of Economics and Business Economics, Aarhus University in its series CREATES Research Papers with number 2009-17.

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Length: 24
Date of creation: 04 May 2009
Date of revision:
Handle: RePEc:aah:create:2009-17
Contact details of provider: Web page: http://www.econ.au.dk/afn/

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