Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/97250 
Year of Publication: 
2013
Series/Report no.: 
Discussion Paper No. 1563
Publisher: 
Northwestern University, Kellogg School of Management, Center for Mathematical Studies in Economics and Management Science, Evanston, IL
Abstract: 
In many economic applications involving comparisons of multivariate distributions, supermodularity of an objective function is a natural property for capturing a preference for greater interdependence. One multivariate distribution dominates another according to the supermodular stochastic ordering if it yields a higher expectation than the other for all supermodular objective functions. We prove that this ordering is equivalent to one distribution being derivable from another by a sequence of elementary, bivariate, interdependence-increasing transformations, and develop methods for determining whether such a sequence exists. For random vectors resulting from common and idiosyncratic shocks, we provide non-parametric sufficient conditions for supermodular dominance. Moreover, we characterize the orderings corresponding to supermodular objective functions that are also increasing or symmetric. We use the symmetric supermodular ordering to compare distributions generated by heterogeneous lotteries. Applications to welfare economics, committee decision-making, insurance, finance, and parameter estimation are discussed.
Subjects: 
Interdependence
Supermodular
Correlation
Copula
Concordance
Mixture
Majorization
Tournament
Interdependence
Supermodular
Correlation
Copula
Concordance
Mixture
Majorization
Tournament
JEL: 
D63
D81
G11
G22
Document Type: 
Working Paper

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