Why most published research is wrong

26 november, 2018 kl. 11:07 | Publicerat i Statistics & Econometrics | Kommentarer inaktiverade för Why most published research is wrong


After having mastered all the technicalities of regression analysis and econometrics, students often feel as though they are the masters of the universe. I usually cool them down with a required reading of Christopher Achen‘s modern classic Interpreting and Using Regression.

It usually get them back on track again, and they understand that

no increase in methodological sophistication … alter the fundamental nature of the subject. It remains a wondrous mixture of rigorous theory, experienced judgment, and inspired guesswork. And that, finally, is its charm.

And in case they get too excited about having learned to master the intricacies of proper significance tests and p-values, I ask them to also ponder on Achen’s warning:

Significance testing as a search for specification errors substitutes calculations for substantive thinking. Worse, it channels energy toward the hopeless search for functionally correct specifications and divert attention from the real tasks, which are to formulate a manageable description of the data and to exclude competing ones.

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