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Researcher Incentives and Empirical Methods

  • Edward L. Glaeser

Economists are quick to assume opportunistic behavior in almost every walk of life other than our own. Our empirical methods are based on assumptions of human behavior that would not pass muster in any of our models. The solution to this problem is not to expect a mass renunciation of data mining, selective data cleaning or opportunistic methodology selection, but rather to follow Leamer's lead in designing and using techniques that anticipate the behavior of optimizing researchers. In this essay, I make ten points about a more economic approach to empirical methods and suggest paths for methodological progress.

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File URL: http://www.nber.org/papers/t0329.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0329.

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Date of creation: Oct 2006
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Handle: RePEc:nbr:nberte:0329
Note: TWP
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  1. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-83, May.
  2. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
  3. Levine, Ross & Renelt, David, 1991. "A sensitivity analysis of cross-country growth regressions," Policy Research Working Paper Series 609, The World Bank.
  4. Edward E. Leamer, 1982. "Let's Take the Con Out of Econometrics," UCLA Economics Working Papers 239, UCLA Department of Economics.
  5. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
  6. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-27, February.
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