## 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.

Original language | English (US) |
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Pages (from-to) | S1-S18 |

Journal | Econometrics Journal |

Volume | 12 |

Issue number | SUPPL. 1 |

DOIs | |

State | Published - 2009 |

## Keywords

- Bootstrap
- Cramér-von Mises test
- Equilibrium search model
- Functional data analysis
- Hypothesis testing

## ASJC Scopus subject areas

- Economics and Econometrics