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Asymmetric Empirical Similarity

Joshua C. Teitelbaum

Georgetown University Law Center

July 19, 2013

Mathematical Social Sciences, Vol. 66, No. 3, pp. 346-351, 2013
Georgetown Public Law Research Paper No. 13-003

The paper suggests a similarity function for applications of empirical similarity theory in which the notion of similarity is asymmetric. I propose defining similarity in terms of a quasimetric. I suggest a particular quasimetric and explore the properties of the empirical similarity model given this function. The proposed function belongs to the class of quasimetrics induced by skewed norms. Finally, I provide a skewness axiom that, when imposed in lieu of the symmetry axiom in the main result of Billot et al. (2008), characterizes an exponential similarity function based on a skewed norm.

Number of Pages in PDF File: 18

Keywords: asymmetric distance, empirical similarity, quasimetric, skewed norm

JEL Classification: C44, D01, D80

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Date posted: January 22, 2013 ; Last revised: December 7, 2013

Suggested Citation

Teitelbaum, Joshua C., Asymmetric Empirical Similarity (July 19, 2013). Mathematical Social Sciences, Vol. 66, No. 3, pp. 346-351, 2013; Georgetown Public Law Research Paper No. 13-003. Available at SSRN: https://ssrn.com/abstract=2205040 or http://dx.doi.org/10.2139/ssrn.2205040

Contact Information

Joshua C. Teitelbaum (Contact Author)
Georgetown University Law Center ( email )
600 New Jersey Avenue NW
Washington, DC 20001
United States
202-661-6589 (Phone)
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References:  17
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