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  Empirical Methods for the Law

Engel, C. (2018). Empirical Methods for the Law. Journal of Institutional and Theoretical Economics, 174, 5-23.

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 Creators:
Engel, Christoph1, Author           
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1Max Planck Institute for Research on Collective Goods, Max Planck Society, ou_2173688              

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Free keywords: normative claims, frequentist statistics, significance, power, structural equation model, finite mixture, Bayesian statistics, prediction, machine learning
 JEL: A12 - Relation of Economics to Other Disciplines
 JEL: C01 - Econometrics
 JEL: C11 - Bayesian Analysis: General
 JEL: C12 - Hypothesis Testing: General
 JEL: C18 - Methodological Issues: General
 JEL: C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
 JEL: H41 - Public Goods
 JEL: K00 - General
 JEL: K41 - Litigation Process
 Abstract: To their credit, empirical legal scholars try to live up to the highest methodological standards from the social sciences. But these standards do not always match the legal research question. This paper focuses on normative legal argument based on empirical evidence. Whether there is a normative problem, and whether legal intervention promises to mitigate the problem, requires a decision. If uncertainty cannot be completely removed, the legal decision-maker must weigh the risk of false positives against the risk of false negatives. This may call for an adjustment of the significance level. The fact that all legal choice is historically contingent, that legal problems tend to be ill-defined, and that strategic actors have an incentive to bias the generation of evidence defy frequentist statistics. Yet the law can capitalize on the adversarial principle. Competition among interested parties helps contain the strategic element and spurs the creative search for better evidence. This leads to suggestive, but institutionally contained empirical evidence.

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 Dates: 20182018
 Publication Status: Issued
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 Rev. Type: Peer
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Title: Journal of Institutional and Theoretical Economics
Source Genre: Journal
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Pages: - Volume / Issue: 174 Sequence Number: - Start / End Page: 5 - 23 Identifier: -