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Undergraduate Econometrics Instruction: Through Our Classes, Darkly

Listed author(s):
  • Joshua D. Angrist
  • Jörn-Steffen Pischke

The past half-century has seen economic research become increasingly empirical, while the nature of empirical economic research has also changed. In the 1960s and 1970s, an empirical economist’s typical mission was to “explain” economic variables like wages or GDP growth. Applied econometrics has since evolved to prioritize the estimation of specific causal effects and empirical policy analysis over general models of outcome determination. Yet econometric instruction remains mostly abstract, focusing on the search for “true models” and technical concerns associated with classical regression assumptions. Questions of research design and causality still take a back seat in the classroom, in spite of having risen to the top of the modern empirical agenda. This essay traces the divergent development of econometric teaching and empirical practice, arguing for a pedagogical paradigm shift.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 23144.

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Date of creation: Feb 2017
Publication status: published as Joshua D. Angrist & Jörn-Steffen Pischke, 2017. "Undergraduate Econometrics Instruction: Through Our Classes, Darkly," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 125-144, Spring.
Handle: RePEc:nbr:nberwo:23144
Note: CH ED HE LS PE
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  1. Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
  2. Matthew T. Panhans & John D. Singleton, 2015. "The Empirical Economist's Toolkit: From Models to Methods," Center for the History of Political Economy Working Paper Series 2015-3, Center for the History of Political Economy.
  3. Peter Arcidiacono & Esteban M. Aucejo & V. Joseph Hotz, 2016. "University Differences in the Graduation of Minorities in STEM Fields: Evidence from California," American Economic Review, American Economic Association, vol. 106(3), pages 525-562, March.
  4. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
  5. Stacy Berg Dale & Alan B. Krueger, 2002. "Estimating the Payoff to Attending a More Selective College: An Application of Selection on Observables and Unobservables," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1491-1527.
  6. Dougherty, Christopher, 2016. "Introduction to Econometrics," OUP Catalogue, Oxford University Press, edition 5, number 9780199676828.
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  12. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
  13. Arellano, M, 1987. "Computing Robust Standard Errors for Within-Groups Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 431-434, November.
  14. Joshua D. Angrist, 1998. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," Econometrica, Econometric Society, vol. 66(2), pages 249-288, March.
  15. repec:eee:macchp:v2-923 is not listed on IDEAS
  16. William E. Becker & William H. Greene, 2001. "Teaching Statistics and Econometrics to Undergraduates," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 169-182, Fall.
  17. Summers, Anita A & Wolfe, Barbara L, 1977. "Do Schools Make a Difference?," American Economic Review, American Economic Association, vol. 67(4), pages 639-652, September.
  18. Peter Arcidiacono & Esteban M. Aucejo & V. Joseph Hotz, 2016. "University differences in the graduation minorities in STEM fields: evidence from California," LSE Research Online Documents on Economics 64178, London School of Economics and Political Science, LSE Library.
  19. Yitzhaki, Shlomo, 1996. "On Using Linear Regressions in Welfare Economics," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 478-486, October.
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