What to Do about the "Cult of Statistical Significance"? A Renewable Fuel Application using the Neyman-Pearson Protocol

Timothy Wojan, Jason Brown and Dayton Lambert

Applied Economic Perspectives and Policy, 2014, vol. 36, issue 4, 674-695

Abstract: 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.

Date: 2014
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