Abstract
The widespread use of “Null hypothesis significance testing” and p-values in empirical work has come in for widespread criticism from many directions in recent years. Nearly all this literature and commentary has, understandably, focused on practice: how researchers use, and abuse, these methods and tools, and what they should do instead. Surprisingly, relatively little attention has been devoted to what to do about how we teach econometrics and applied statistics more generally. I suggest that it is possible to teach students how to practice frequentist statistics sensibly if the core concepts they are taught at the start are “coverage” and interval estimation. I suggest various tools that can be used to convey these concepts.
Invited paper for the Fifth International Econometric Conference of Vietnam, Ho-Chi-Minh City, Vietnam, 10–12 January 2022. All errors are my own.
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Notes
- 1.
Source: Wikimedia Commons. https://en.wikipedia.org/wiki/File:Pin_the_Tail_On_the_Donkey-example.jpg. Licensed under the Creative Commons Attribution 2.0 Generic license. The photograph has been trimmed slightly and the two arrows added; it is otherwise unchanged.
- 2.
Contrast this with the more traditional live classroom approach of using a computer simulation to illustrate the coverage properties of confidence intervals. While this is instructive and can be helpful, it is very dry and on its own is likely to go over heads of some students.
- 3.
Note that in the photograph of an actual play of Pin-the-Tail-on-the-Donkey above, some of the pinned tails have indeed missed the “playing area”.
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Schaffer, M.E. (2022). What’s Wrong with How We Teach Estimation and Inference in Econometrics? And What Should We Do About It?. In: Ngoc Thach, N., Kreinovich, V., Ha, D.T., Trung, N.D. (eds) Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics. ECONVN 2022. Studies in Systems, Decision and Control, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-030-98689-6_9
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