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Complementarity and aggregate implications of assortative matching : a nonparametric analysis

Author: Bryan S Graham; Guido Imbens; Geert Ridder; National Bureau of Economic Research.
Publisher: Cambridge, Mass. : National Bureau of Economic Research, ©2009.
Series: Working paper series (National Bureau of Economic Research), no. 14860.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This paper presents methods for evaluating the effects of reallocating an indivisible input across production units, taking into account resource constraints by keeping the marginal distribution of the input fixed. When the production technology is nonseparable, such reallocations, although leaving the marginal distribution of the reallocated input unchanged by construction, may nonetheless alter average output.  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Bryan S Graham; Guido Imbens; Geert Ridder; National Bureau of Economic Research.
OCLC Number: 318186237
Notes: "April 2009."
Description: 1 online resource (82 pages).
Series Title: Working paper series (National Bureau of Economic Research), no. 14860.
Responsibility: Bryan S. Graham, Guido W. Imbens, Geert Ridder.

Abstract:

This paper presents methods for evaluating the effects of reallocating an indivisible input across production units, taking into account resource constraints by keeping the marginal distribution of the input fixed. When the production technology is nonseparable, such reallocations, although leaving the marginal distribution of the reallocated input unchanged by construction, may nonetheless alter average output. Examples include reallocations of teachers across classrooms composed of students of varying mean ability. We focus on the effects of reallocating one input, while holding the assignment of another, potentially complementary, input fixed. We introduce a class of such reallocations -- correlated matching rules -- that includes the status quo allocation, a random allocation, and both the perfect positive and negative assortative matching allocations as special cases. We also characterize the effects of local (relative to the status quo) reallocations. For estimation we use a two-step approach. In the first step we nonparametrically estimate the production function. In the second step we average the estimated production function over the distribution of inputs induced by the new assignment rule. These methods build upon the partial mean literature, but require extensions involving boundary issues. We derive the large sample properties of our proposed estimators and assess their small sample properties via a limited set of Monte Carlo experiments.

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