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| ## Publications [#238053] of Federico Bugnisearch ideas.repec.org.
- Bugni, FA; Hall, P; Horowitz, JL; Neumann, GR,
*Goodness-of-fit tests for functional data*, The Econometrics Journal, vol. 12 no. SUPPL. 1 (July, 2009), pp. S1-S18, ISSN 1368-4221 [doi] (last updated on 2021/06/15)**Abstract:** 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. © Journal compilation © 2009 Royal Economic Society.
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