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Integral of a correspondence

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In mathematics, the integral of a correspondence is a generalization of the integration of single-valued functions to correspondences.

The first notion of the integral of a correspondence is due to Aumann in 1965,[1] with a different approach by Debreu appearing in 1967.[2] Integrals of correspondences have applications in general equilibrium theory in mathematical economics,[3][4] random sets in probability theory,[5][6] partial identification in econometrics,[7] and fuzzy numbers in fuzzy set theory.[8]

Preliminaries

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Correspondences

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A correspondence is a function , where is the power set of . That is, assigns each point with a set .

Selections

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A selection of a correspondence is a function such that for every .

If can be seen as a measure space and as a Banach space , then one can define a measurable selection as an -measurable function[nb 1] such that for µ-allmost all .[5][nb 2]

Definitions

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The Aumann integral

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Let be a measure space and a Banach space. If is a correspondence, then the Aumann integral of is defined as

where the integrals are Bochner integrals.

Example: let the underlying measure space be , and a correspondence be defined as for all . Then the Aumman integral of is .

The Debreu integral

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Debreu's approach to the integration of a correspondence is more restrictive and cumbersome, but directly yields extensions of usual theorems from the integration theory of functions to the integration of correspondences, such as Lebesgue's Dominated convergence theorem.[3] It uses Rådström's embedding theorem to identify convex and compact valued correspondences with subsets of a real Banach space, over which Bochner integration is straightforward.[2]

Let be a measure space, a Banach space, and the set of all its convex and compact subsets. Let be a convex and compact valued correspondence from to . By Rådström's embedding theorem, can be isometrically embedded as a convex cone in a real Banach space , in such a way that addition and multiplication by nonnegative real numbers in induces the corresponding operation in .

Let be the "image" of under the embedding defined above, in the sense that is the image of under this embedding for every . For each pair of -simple functions , define the metric .

Then we say that is integrable if is integrable in the following sense: there exists a sequence of -simple functions from to which are Cauchy in the metric and converge in measure to . In this case, we define the integral of to be

where the integrals are again simply Bochner integrals in the space , and the result still belongs since it is a convex cone. We then uniquely identify the Debreu integral of as[5]

such that . Since every embedding is injective and surjective onto its image, the Debreu integral is unique and well-defined.

Notes

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  1. ^ Measurable in the sense of Bochner measurable: there exists a sequence of simple functions from to such that for µ-allmost all .
  2. ^ A stronger definition sometimes used requires to be measurable and for all . [4]

References

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  1. ^ Aumann, Robert J. (1965). "Integrals of Set-Valued Functions*". Journal of Mathematical Analysis and Applications. 12: 1–12. doi:10.1016/0022-247X(65)90049-1.
  2. ^ a b Debreu, Gérard (1967). "Integration of Correspondences". In Le Cam, Lucien; Neyman, Jerzy (eds.). Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume 2: Contributions to Probability Theory, Part 1. University of California Press. pp. 351–372. ISBN 978-0520366701.
  3. ^ a b Klein, Erwin; Thompson, Anthony C. (1984). Theory of Correspondences: Including Applications to Mathematical Economics. John Wiley & Sons. ISBN 0-471-88016-7.
  4. ^ a b Border, Kim; Aliprantis, Charalambos D. (2006). Infinite Dimensional Analysis: A Hitchhiker's Guide (3rd ed.). Springer-Verlag. ISBN 978-3540295860.
  5. ^ a b c Molchanov, Ilya (2017). Theory of Random Sets (2nd ed.). Springer-Verlag. ISBN 978-1852338923.
  6. ^ Molchanov, Ilya; Molinari, Francesca (2018). Random Sets in Econometrics (1st ed.). Cambridge University Press. ISBN 9781107121201.
  7. ^ Molinari, Francesca (2020). "Microeconometrics with partial identification". In Durlauf, Steven; Hansen, Lars Peter; Heckman, James; Matzkin, Rosa (eds.). Handbook of Econometrics, vol. 7. Elsevier. pp. 355–486. ISBN 9780444636492.
  8. ^ Zimmermann, Hans-Jürgen (2011). Fuzzy Set Theory - and Its Applications (4th ed.). Springer Science + Business. ISBN 978-0-7923-7435-0.