Consistent specification tests for semiparametric/nonparametric models based on series estimation methods Academic Article uri icon


  • This paper considers the problem of consistent model specification tests using series estimation methods. The null models we consider in this paper all contain some nonparametric components. A leading case we consider is to test for an additive partially linear model. The null distribution of the test statistic is derived using a central limit theorem for Hilbert-valued random arrays. The test statistic is shown to be able to detect local alternatives that approach the null models at the order of Op(n-1/2). We show that the wild bootstrap method can be used to approximate the null distribution of the test statistic. A small Monte Carlo simulation is reported to examine the finite sample performance of the proposed test. We also show that the proposed test can be easily modified to obtain series-based consistent tests for other semiparametric/nonparametric models. 2002 Elsevier Science B.V. All rights reserved.

published proceedings


author list (cited authors)

  • Li, Q., Hsiao, C., & Zinn, J.

citation count

  • 49

complete list of authors

  • Li, Q||Hsiao, C||Zinn, J

publication date

  • February 2003