Market Integration, Systemic Risk and Diagnostic Tests in Large Mixed Panels
50 Pages Posted: 7 Jan 2019
Date Written: November 15, 2018
This study investigates an AR (autoregressive)-filtered version of several conventional diagnostic tests for cross-sectional dependence in large mixed panels, including the adjusted LM test, the CD test, and the Schott test. We show that the modified tests asymptotically follow the standard normal distribution. The distinctive feature of these new tests is their simple implementation, even though the exact time series properties of each component of a mixed panel are unknown or unobservable in practice. Simulations show that the AR-filtered version of the CD test (CDAR) performs the best compared to the other testing procedures in finite sample and computation time, especially for those cases with large cross-sectional dimension. We also provide a new perspective on the role of CDAR statistic in an early warning indicator of market risk or crisis.
Keywords: autoregressive (AR) approximation, cross sectional dependence, diagnostic tests, CD and Schott tests, market integration and systemic risk
JEL Classification: C33, C53
Suggested Citation: Suggested Citation