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A simple framework for nonparametric specification testing

Author: Glenn Ellison; Sara Fisher Ellison; National Bureau of Economic Research.
Publisher: Cambridge, MA. : National Bureau of Economic Research, ©1998.
Series: Technical working paper series (National Bureau of Economic Research), technical working paper no. 234.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Abstract: This paper presents a simple framework for testing the specification of parametric conditional means. The test statistics are based on quadratic forms in the residuals of the null model. Under general assumptions the test statistics are asymptotically normal under the null. With an appropriate choice of the weight matrix, the tests are shown to be consistent and to have good local power. Specific  Read more...
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Additional Physical Format: Print version:
Ellison, Glenn, 1965-
Simple framework for nonparametric specification testing.
Cambridge, MA. : National Bureau of Economic Research, ©1998
(OCoLC)40266205
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Glenn Ellison; Sara Fisher Ellison; National Bureau of Economic Research.
OCLC Number: 70202302
Notes: "September 1998."
"Financial support from National Science Foundation grant SBR-95-15094 ... is acknowledged."
Reproduction Notes: Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. MiAaHDL
Description: 1 online resource (39 pages).
Details: Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
Series Title: Technical working paper series (National Bureau of Economic Research), technical working paper no. 234.
Other Titles: Simple framework for non-parametric specification testing
Responsibility: Glenn Ellison, Sara Fisher Ellison.

Abstract:

Abstract: This paper presents a simple framework for testing the specification of parametric conditional means. The test statistics are based on quadratic forms in the residuals of the null model. Under general assumptions the test statistics are asymptotically normal under the null. With an appropriate choice of the weight matrix, the tests are shown to be consistent and to have good local power. Specific implementations involving matrices of bin and kernel weights are discussed. Finite sample properties are explored in simulations and an application to some parametric models of gasoline demand is presented.

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