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Researcher Incentives and Empirical Methods

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  • Edward L. Glaeser

Abstract

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.

Suggested Citation

  • Edward L. Glaeser, 2006. "Researcher Incentives and Empirical Methods," NBER Technical Working Papers 0329, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0329
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    References listed on IDEAS

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    1. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-127, February.
    2. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    3. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
    4. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    5. Levine, Ross & Renelt, David, 1992. "A Sensitivity Analysis of Cross-Country Growth Regressions," American Economic Review, American Economic Association, vol. 82(4), pages 942-963, September.
    6. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
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    Cited by:

    1. Maximilian Kasy & Jann Spiess, 2024. "Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability," Economics Series Working Papers 1058, University of Oxford, Department of Economics.
    2. Alexander Frankel & Maximilian Kasy, 2022. "Which Findings Should Be Published?," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 1-38, February.
    3. Peace Karl E. & Yin JingJing & Rochani Haresh & Pandeya Sarbesh & Young Stanley, 2018. "A Serious Flaw in Nutrition Epidemiology: A Meta-Analysis Study," The International Journal of Biostatistics, De Gruyter, vol. 14(2), pages 1-10, November.
    4. Haeussler, Carolin, 2011. "Information-sharing in academia and the industry: A comparative study," Research Policy, Elsevier, vol. 40(1), pages 105-122, February.
    5. Maximilian Kasy & Jann Spiess, 2022. "Rationalizing Pre-Analysis Plans:Statistical Decisions Subject to Implementability," Economics Series Working Papers 975, University of Oxford, Department of Economics.
    6. Maximilian Kasy & Jann Spiess, 2022. "Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability," Papers 2208.09638, arXiv.org, revised Jul 2024.
    7. Simonetta LONGHI & Peter NIJKAMP & Jacques POOT, 2008. "Meta-Analysis Of Empirical Evidence On The Labour Market Impacts Of Immigration," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 27, pages 161-191.
    8. Tomas Havranek & Anna Sokolova, 2016. "Do Consumers Really Follow a Rule of Thumb? Three Thousand Estimates from 130 Studies Say "Probably Not"," Working Papers 2016/08, Czech National Bank.
    9. Stephan B. Bruns & David I. Stern, 2015. "Meta-Granger causality testing," CAMA Working Papers 2015-22, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Furman, Jeffrey L. & Jensen, Kyle & Murray, Fiona, 2012. "Governing knowledge in the scientific community: Exploring the role of retractions in biomedicine," Research Policy, Elsevier, vol. 41(2), pages 276-290.
    11. Stephan B. Bruns, 2016. "The Fragility of Meta-Regression Models in Observational Research," MAGKS Papers on Economics 201603, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    12. Nicola Lacetera & Lorenzo Zirulia, 2011. "The Economics of Scientific Misconduct," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 27(3), pages 568-603.
    13. Robert L. Obenchain & S. Stanley Young, 2017. "Local Control Strategy: Simple Analyses of Air Pollution Data Can Reveal Heterogeneity in Longevity Outcomes," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1742-1753, September.
    14. Marcel Fafchamps & Julien Labonne, 2017. "Do Politicians’ Relatives Get Better Jobs? Evidence from Municipal Elections," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 33(2), pages 268-300.
    15. Necker, Sarah, 2014. "Scientific misbehavior in economics," Research Policy, Elsevier, vol. 43(10), pages 1747-1759.

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    More about this item

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology

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