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Data Mining as an Industry

Citations

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Cited by:

  1. Chatelain, Jean-Bernard, 2010. "Can statistics do without artefacts?," MPRA Paper 42867, University Library of Munich, Germany.
  2. Kilpatrick, Henry E., Jr., 1998. "Some useful methods for measuring the benefits of social science research," Impact Assessment Discussion Papers 48290, CGIAR, International Food Policy Research Institute (IFPRI).
  3. A. Rashad Abdel†Khalik, 1986. "A critique of “Market reactions to mandated interest capitalization.†," Contemporary Accounting Research, John Wiley & Sons, vol. 2(2), pages 242-251, March.
  4. Adam Okulicz-Kozaryn, 2014. "‘Freedom From’ and ‘Freedom To’ Across Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(3), pages 1009-1029, September.
  5. Cheol‐Ho Park & Scott H. Irwin, 2010. "A reality check on technical trading rule profits in the U.S. futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(7), pages 633-659, July.
  6. Susan Feigenbaum & David M. Levy, 1996. "The Technological Obsolescence Of Scientific Fraud," Rationality and Society, , vol. 8(3), pages 261-276, August.
  7. Meisel, Stephan & Mattfeld, Dirk, 2010. "Synergies of Operations Research and Data Mining," European Journal of Operational Research, Elsevier, vol. 206(1), pages 1-10, October.
  8. Kilpatrick, Henry E., Jr., 1998. "Some useful methods for measuring the benefits of social science research," Impact assessments 5, International Food Policy Research Institute (IFPRI).
  9. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
  10. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
  11. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
  12. Ebersberger, Bernd & Galia, Fabrice & Laursen, Keld & Salter, Ammon, 2021. "Inbound Open Innovation and Innovation Performance: A Robustness Study," Research Policy, Elsevier, vol. 50(7).
  13. Julia Campos & Neil R. Ericsson, 1999. "Contructive data mining: modeling consumers' expenditure in Venezuela," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 226-240.
  14. Julia Campos & Neil R. Ericsson & David F. Hendry, 2005. "General-to-specific modeling: an overview and selected bibliography," International Finance Discussion Papers 838, Board of Governors of the Federal Reserve System (U.S.).
  15. Cefis, Elena & Coad, Alex & Lucini-Paioni, Alessandro, 2023. "Landmarks as lighthouses: firms' innovation and modes of exit during the business cycle," Research Policy, Elsevier, vol. 52(8).
  16. Alfredo Di Tillio & Marco Ottaviani & Peter Norman Sørensen, 2017. "Persuasion Bias in Science: Can Economics Help?," Economic Journal, Royal Economic Society, vol. 127(605), pages 266-304, October.
  17. Ashish Arora & Michelle Gittelman & Sarah Kaplan & John Lynch & Will Mitchell & Nicolaj Siggelkow & Brent Goldfarb & Andrew A. King, 2016. "Scientific apophenia in strategic management research: Significance tests & mistaken inference," Strategic Management Journal, Wiley Blackwell, vol. 37(1), pages 167-176, January.
  18. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
  19. Michael Cooper & Huseyin Gulen, 2006. "Is Time-Series-Based Predictability Evident in Real Time?," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1263-1292, May.
  20. Alex Coad & Stjepan Srhoj, 2020. "Catching Gazelles with a Lasso: Big data techniques for the prediction of high-growth firms," Small Business Economics, Springer, vol. 55(3), pages 541-565, October.
  21. repec:bla:jfinan:v:58:y:2003:i:5:p:1969-1996 is not listed on IDEAS
  22. J. Annaert & W. Van Hyfte, 2006. "Long-Horizon Mean Reversion for the Brussels Stock Exchange: Evidence for the 19th Century," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/376, Ghent University, Faculty of Economics and Business Administration.
  23. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.
  24. Edward L. Glaeser, 2006. "Researcher Incentives and Empirical Methods," NBER Technical Working Papers 0329, National Bureau of Economic Research, Inc.
  25. Fang, Jiali & Jacobsen, Ben & Qin, Yafeng, 2014. "Predictability of the simple technical trading rules: An out-of-sample test," Review of Financial Economics, Elsevier, vol. 23(1), pages 30-45.
  26. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
  27. Roodman, David, 2025. "Opinion on the Replication Debate over Heyes and Saberian (2019)," I4R Discussion Paper Series 227, The Institute for Replication (I4R).
  28. Frank T. Denton, 1990. "The Effects of Publication Selection on Test Probabilities and Estimator Distributions," Risk Analysis, John Wiley & Sons, vol. 10(1), pages 131-136, March.
  29. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
  30. Lutz Kilian & Clara Vega, 2011. "Do Energy Prices Respond to U.S. Macroeconomic News? A Test of the Hypothesis of Predetermined Energy Prices," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 660-671, May.
  31. David F. Hendry, 2024. "A Brief History of General‐to‐specific Modelling," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 1-20, February.
  32. Krämer Walter & Arminger Gerhard, 2011. "“True Believers” or Numerical Terrorism at the Nuclear Power Plant," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 608-620, October.
  33. Grahame Thompson, 1993. "Causality in economics: Rhetorical ethic or positivist empiric?," Quality & Quantity: International Journal of Methodology, Springer, vol. 27(1), pages 47-71, February.
  34. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
  35. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
  36. Christopher Winship & Xiaolin Zhuo, 2020. "Interpreting t-Statistics Under Publication Bias: Rough Rules of Thumb," Journal of Quantitative Criminology, Springer, vol. 36(2), pages 329-346, June.
  37. David Levy & Sandra Peart, 2006. "The fragility of a discipline when a model has monopoly status," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 19(2), pages 125-136, June.
  38. Bontempi, Maria Elena & Charemza, Wojciech & Makarova, Svetlana, 2025. "Economic uncertainty measures, experts and large language models," Journal of International Money and Finance, Elsevier, vol. 157(C).
  39. Todd Mitton, 2022. "Methodological Variation in Empirical Corporate Finance," The Review of Financial Studies, Society for Financial Studies, vol. 35(2), pages 527-575.
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