DMCA
Specification Error Tests for Omitted Nonlinearity in Vector Error Correction Models
BibTeX
@MISC{Seo_specificationerror,
author = {Byeongseon Seo and Sokwon Kim and Qi Li and Joon Park and Peter Phillips For Invaluable},
title = {Specification Error Tests for Omitted Nonlinearity in Vector Error Correction Models},
year = {}
}
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Abstract
This paper considers the specification error tests for omitted nonlinearity in the long-run relationship of the vector error correction model with a null of the standard error correction model. We develop the test statistics for neglected nonlinearity by adding nonlinear functions of the regressors to the long-run relationship. Our test statistics can be calculated using the standard error correction model and its parameter estimates. The test statistics are shown to have the asymptotic standard distribution, and thus the proposed specification error tests can be carried out without inferential difficulty. The alternative distribution of the specification error tests is explored under the local drift and the smooth functional form. The Monte Carlo simulation reveals that the proposed tests have moderate finite sample performance in detecting nonlinear functional form. An economic application of the stock price-dividend relation is provided.
Keyphrases
omitted nonlinearity vector error correction model specification error test test statistic specification error standard error correction model long-run relationship monte carlo simulation reveals moderate finite sample performance asymptotic standard distribution local drift alternative distribution parameter estimate inferential difficulty nonlinear function smooth functional form nonlinear functional form stock price-dividend relation economic application
