Koul, H.L. and Perera, I. (2021) A minimum distance lack-of-fit test in a Markovian multiplicative error model. Journal of Statistical Theory and Practice, 15 (2). 34. ISSN 1559-8608
Abstract
This paper proposes a lack-of-fit test for a parametric specification of the conditional mean function in a Markovian multiplicative error time series model. The proposed test is based on a minimized distance obtained using an integral of the square of a certain marked residual process. The asymptotic null distribution of the proposed test is model dependent and is not free from the underlying nuisance parameters. We propose a bootstrap method to implement the test and establish that the proposed bootstrap method is asymptotically valid. A finite sample simulation study that evaluates the empirical level and power is included. It compares the finite sample performance of the proposed test with several competing tests from the literature.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Grace Scientifc Publishing 2021. This is an author-produced version of a paper subsequently published in Journal of Statistical Theory and Practice. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Marked empirical processes; Bootstrap distribution |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Economics (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 23 Mar 2021 14:24 |
Last Modified: | 03 Mar 2022 01:38 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1007/s42519-021-00168-1 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:172482 |