David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Journal of Economic Methodology 7 (2):183-194 (2000)
Data mining occurs because most economic hypotheses do not have a unique empirical interpretation but allow the econometrician much leeway in selecting conditioning variables, lags, functional forms, and sometimes the sample. The resulting problems are of interest not only to methodologists and philosophers concerned with how hypotheses are validated in the presence of some inevitable ad hocery but, also to readers of economics journals who have no interest in methodology but need to know whether to believe what they read. Since I focus on such mundane problems I make no claim of contributing to the deeper epistemological problems of relating empirical evidence to theory, and to the meaning of confirmation and disconfirmation when, say five of the eight specifications tested are consistent with the hypothesis and, three are not. Instead, I deal with a practical problem confronting a researcher who wants to persuade his readers but does not want to deceive them. He has fitted many regressions with varying results. How should he decide how many and which ones to report? This paper is therefore more about a problem in communicating results than about a problem in the philosophy of science. Hence, I use some common-sense notions, even though I cannot provide rigorous definitions for them.
|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
Roger E. Backhouse & Mary S. Morgan (2000). Introduction: Is Data Mining a Methodological Problem? Journal of Economic Methodology 7 (2):171-181.
Clinton A. Greene (2000). I Am Not, nor Have I Ever Been a Member of a Data-Mining Discipline. Journal of Economic Methodology 7 (2):217-230.
Kevin D. Hoover & Stephen J. Perez (2000). Three Attitudes Towards Data Mining. Journal of Economic Methodology 7 (2):195-210.
Dinah Payne & Cherie Courseault Trumbach (2009). Data Mining: Proprietary Rights, People and Proposals. Business Ethics 18 (3):241-252.
Aris Spanos (2000). Revisiting Data Mining: 'Hunting' with or Without a License. Journal of Economic Methodology 7 (2):231-264.
Steven Cook (2001). Observations on the Practice of Data-Mining: Comments on the JEM Symposium. Journal of Economic Methodology 8 (3):415-419.
Adrian R. Pagan & Michael R. Veall (2000). Data Mining and the Econometrics Industry: Comments on the Papers of Mayer and of Hoover and Perez. Journal of Economic Methodology 7 (2):211-216.
Herman T. Tavani (1999). Informational Privacy, Data Mining, and the Internet. Ethics and Information Technology 1 (2):137-145.
Herman T. Tavani (1999). KDD, Data Mining, and the Challenge for Normative Privacy. Ethics and Information Technology 1 (4):265-273.
P. X. Monaghan (2010). A Novel Interpretation of Plato's Theory of Forms. Metaphysica 11 (1):63-78.
Lita van Wel & Lambèr Royakkers (2004). Ethical Issues in Web Data Mining. Ethics and Information Technology 6 (2):129-140.
Dale Hample, Bing Han & David Payne (2010). The Aggressiveness of Playful Arguments. Argumentation 24 (4):405-421.
James A. Overton (2013). “Explain” in Scientific Discourse. Synthese 190 (8):1383-1405.
Added to index2012-02-20
Total downloads6 ( #224,641 of 1,410,161 )
Recent downloads (6 months)1 ( #155,015 of 1,410,161 )
How can I increase my downloads?