It would appear that much debate among practically minded researchers in economics, social science, and in other fields, is rooted in (frequently) unstated assumptions about the underlying philosophical justification for the statistical procedures being debated. In this chapter, I try to provide a simple non-technical introduction to some long-standing debates about “metastatistical” questions, especially those that divide (some) “Bayesians” from (some) non-Bayesians while attempting to draw out some implications for the “practically minded non-Bayesian regression runner." Some of the issues which have prompted the most raucous debate in philosophical circles include: the meaning of “probability," the importance or unimportance of pre-designation (pre-specified research design), the role of “models," and the practical value of hypothesis testing and other common statistical practices. I discuss some of the links between these philosophical views and actual practice and consider two different case studies-one from medicine and another from labor economics.
CITATION STYLE
DiNardo, J. (2009). Introductory remarks on metastatistics for the practically minded non-bayesian regression runner. In Palgrave Handbook of Econometrics: Volume 2: Applied Econometrics (pp. 98–165). Palgrave Macmillan. https://doi.org/10.1057/9780230244405_3
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