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May 30, 2026Oxford Bulletin of Economics and Statistics0 citationsOpen Access

Inference on Common Trends in a Cointegrated Nonlinear SVAR

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JDJames A. DuffyXJXiyu Jiao

Key Points

  • This research aims to improve inference methods for identifying common stochastic trends in nonlinear cointegrated models.
  • Utilizes a modified version of the Breitung multivariate variance ratio test
  • Investigates a cointegrated CKSVAR system
  • Proves a LLN-type result for stable nonstationary autoregressive processes
  • The modified test provides accurate inferences for the number of common trends
  • Unmodified tests overestimate the number of common trends in nonlinear relationships
  • Employs a novel dual linear process approximation for analysis

Abstract

ABSTRACT We consider the problem of performing inference on the number of common stochastic trends when data is generated by a cointegrated CKSVAR (a two‐regime, piecewise affine SVAR; Mavroeidis, 2021), using a modified version of the Breitung (2002) multivariate variance ratio test that is robust to the presence of nonlinear cointegration (of a known form). To derive the asymptotics of our test statistic, we prove a fundamental LLN‐type result for a class of stable but nonstationary autoregressive processes, using a novel dual linear process approximation. We show that our modified test yields correct inferences regarding the number of common trends in such a system, whereas the unmodified test tends to infer a higher number of common trends than are actually present, when cointegrating relations are nonlinear.

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Cite This Study

Duffy et al. (2026) studied this question.

synapsesocial.com/papers/6a1a7f230307b78509431845https://doi.org/10.1111/obes.70078
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