English, Article edition: Goodness-of-fit tests for functional data Federico A. Bugni; Peter Hall; Joel L. Horowitz; ...

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Bookmark: http://trove.nla.gov.au/version/26325
Physical Description
  • article
Language
  • English

Edition details

Title
  • Goodness-of-fit tests for functional data
Author
  • Federico A. Bugni
  • Peter Hall
  • Joel L. Horowitz
  • George R. Neumann
Physical Description
  • article
Notes
  • Economic data are frequently generated by stochastic processes that can be modelled as occurring in continuous time. That is, the data are treated as realizations of a random function (functional data). Sometimes an economic theory model specifies the process up to a finite-dimensional parameter. This paper develops a test of the null hypothesis that a given functional data set was generated by a specified parametric model of a continuous-time process. The alternative hypothesis is non-parametric. A random function is a form of infinite-dimensional random variable, and the test presented here a generalization of the familiar Cramér-von Mises test to an infinite dimensional random variable. The test is illustrated by using it to test the hypothesis that a sample of wage paths was generated by a certain equilibrium job search model. Simulation studies show that the test has good finite-sample performance. Copyright © The Author(s). Journal compilation © Royal Economic Society 2009
  • RePEc:ect:emjrnl:v:12:y:2009:i:s1:p:s1-s18
Language
  • English
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