David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Journal of Economic Methodology 2 (2):201-222 (1995)
Economists often try to make plausible inferences from a sizable empirical literature addressing a particular measurement, direction-of-effect, or testing issue. There are serious methodological problems associated with drawing such inferences. This article sets out some of these problems in order to make a case for their importance. After discussing these problems, the paper presents three case study examples of inference difficulties in specific literatures. It then proposes a new hypothesis about the time pattern of publication bias in empirical economics literatures. As support for this hypothesis, it presents evidence that ?reversals in findings? in empirical literatures in economics are not uncommon. Similarities are pointed out between the focus on inference problems in this paper, and the meta-analysis literatures in psychology and medical clinical trials.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Robert S. Goldfarb (1997). Now You See It, Now You Don't: Emerging Contrary Results in Economics. Journal of Economic Methodology 4 (2):221-244.
Peter Lipton (2004). Inference to the Best Explanation. Routledge/Taylor and Francis Group.
Jean-Baptiste Fleury (2012). The Evolving Notion of Relevance: An Historical Perspective to the 'Economics Made Fun' Movement. Journal of Economic Methodology 19 (3):303-316.
Bryan L. Boulier & Robert S. Goldfarb (1998). On the Use and Nonuse of Surveys in Economics. Journal of Economic Methodology 5 (1):1-21.
D. Turner (2000). The Functions of Fossils: Inference and Explanation in Functional Morphology. Studies in History and Philosophy of Science Part C 31 (1):193-212.
Daniel Nolan (2007). Contemporary Metaphysicians and Their Traditions. Philosophical Topics 35 (1-2):1-18.
P. D. Magnus (2008). Demonstrative Induction and the Skeleton of Inference. International Studies in the Philosophy of Science 22 (3):303 – 315.
William G. Lycan (2002). Explanation and Epistemology. In Paul K. Moser (ed.), The Oxford Handbook of Epistemology. Oxford University Press. 413.
Barbara Osimani (2013). Hunting Side Effects and Explaining Them: Should We Reverse Evidence Hierarchies Upside Down? [REVIEW] Journal of Evaluation in Clinical Practice (2):1-18.
Lloyd Humberstone (2004). Archetypal Forms of Inference. Synthese 141 (1):45 - 76.
Thomas Mayer (2000). Data Mining: A Reconsideration. Journal of Economic Methodology 7 (2):183-194.
Barbara Osimani (2013). Until RCT-Proven? On the Asymmetry of Evidence Requirements for Risk Assessment. Journal of Evaluation in Clinical Practice 19 (3):454-462.
Hans Rott (2011). Odd Choices: On the Rationality of Some Alleged Anomalies of Decision and Inference. Topoi 30 (1):59-69.
Added to index2012-02-20
Total downloads4 ( #260,003 of 1,102,634 )
Recent downloads (6 months)2 ( #183,726 of 1,102,634 )
How can I increase my downloads?