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Kenneth Joseph Arrow

Personal Information

Born January 1, 1921 (105 years old)
New York City, United States
Also known as: Kenneth J. Arrow
37 books
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46 readers

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Books

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Studies in linear and non-linear programming

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5

Contents : A theorem on convex polyhedral cones / Hirofumi Uzawa -- The Kuhn-Tucker theorem in concave programming / Hirofumi Uzawa -- Programming in linear spaces / Leonid Hurwicz -- A note on the Lagrangian saddle-points / Leonid Hurwicz and Hirofumi Uzawa -- Gradient method for concave programming, I: local results / Kenneth J. Arrow and Leonid Hurwicz -- Gradient method for concave programming, II: global stability in the strictly concave case / Hirofumi Uzawa -- Gradient method for concave programming, III: further global results and applications to resource allocation / Kenneth J. Arrow and Leonid Hurwicz -- An example of a modified gradient method for linear programming / Thomas Marschak -- Iterative methods for concave programming / Hirofumi Uzawa -- Gradient methods for constrained maxima, with weakened assumptions / Kenneth J. Arrow and Robert M. Solow -- An elementary method for linear programming / Hirofumi Uzawa -- Price speculation under certainty / Kenneth J. Arrow and Samuel Karlin -- A feasibility algorithm for one-way substitution in process analysis / Kenneth J. Arrow and Selmer M. Johnson -- Non-linear programming in economic development / Hollis B. Chenery and Hirofumi Uzawa.

Limited network connections and the distribution of wages

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"It is well-known that 50% or more of all jobs are obtained through informal channels i.e. connections to family or friends. As well, statistical studies show that observable individual factors account for only about 50% of the very wide variation in earnings. We seek to explain these two facts by assuming that the linking of workers and firms is mediated by limited network connections. The model implies that essentially similar workers can have markedly different wages and further that the inequality of wages is partly explained by variations in the sizes of workers' networks. Our results indicate that differences in the number of ties can induce substantial inequality and can explain roughly 15% of the unexplained variation in wages. We also show that reasonable differences in the average number of links between blacks and whites can explain the disparity in black and white income distributions"--Federal Reserve Board web site.