A Specification Test Based on Convolution-Type Distribution Function Estimates for Non-Linear Autoregressive Processes

Kun Ho Kim, Hira L. Koul and Jiwoong Kim

A chapter in Essays in Honor of Joon Y. Park: Econometric Theory, 2023, vol. 45A, pp 187-206 from Emerald Group Publishing Limited

Abstract: This chapter proposes a test for a parametric specification of the autoregressive function of a given stationary autoregressive time series. This test is based on the integrated square difference between the empirical distribution function estimate and a convolution-type distribution function estimate of the stationary distribution function obtained from the autoregressive residuals. Some asymptotic properties of the proposed convolution-type distribution function estimate are studied when the model’s innovation density is unknown. These properties are in turn used to derive the asymptotic null distribution of the proposed test statistic. We also discuss some finite sample properties of the test statistic based on the block bootstrap methodology. A simulation study shows that the proposed test competes favorably with some existing tests in terms of the empirical level and power.

Keywords: Nonlinear autoregressive processes; integrated squared difference of the two d.f.’s; empirical and convolution d.f. estimators; block bootstrap; asymptotic power; empirical level and power; C12; C13; C14 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... 1-90532023000045A006
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-90532023000045a006

DOI: 10.1108/S0731-90532023000045A006

Access Statistics for this chapter

More chapters in Advances in Econometrics from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().