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What to Do about the “Cult of Statistical Significance”? A Renewable Fuel Application using the Neyman‐Pearson Protocol
Author(s) -
Wojan Timothy R.,
Brown Jason P.,
Lambert Dayton M.
Publication year - 2014
Publication title -
applied economic perspectives and policy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.4
H-Index - 49
eISSN - 2040-5804
pISSN - 2040-5790
DOI - 10.1093/aepp/ppu013
Subject(s) - protocol (science) , econometrics , statistical hypothesis testing , computer science , statistics , obstacle , power (physics) , economics , mathematics , geography , medicine , alternative medicine , pathology , physics , archaeology , quantum mechanics
This research adapts the Neyman‐Pearson testing protocol commonly used in biomedical research for ex post evaluation of the employment impacts of new ethanol bio‐refineries in the U.S. Great Plains and the Midwest. By calculating the power of the test, the suggested protocol may provide policy‐relevant information, even in the event of nonsignificant findings. The main obstacle to applying this protocol has been the need to posit an explicit alternative distribution, which runs counter to the empiricist tradition of mainstream econometrics. We resolve this problem by applying a data generating process with known parameters anchored to sample data to compute power.