Market Integration, Systemic Risk and Diagnostic Tests in Large Mixed Panels

50 Pages Posted: 7 Jan 2019

See all articles by Cindy S.H. Wang

Cindy S.H. Wang

Catholic University of Louvain (UCL); Peking University, HSBC Business School

Cheng Hsiao

University of Southern California - Department of Economics; National Taiwan University; National Bureau of Economic Research (NBER)

Hao-Hsiang Yang

National Tsing Hua University

Date Written: November 15, 2018

Abstract

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

Wang, Cindy S.H. and Hsiao, Cheng and Yang, Hao-Hsiang, Market Integration, Systemic Risk and Diagnostic Tests in Large Mixed Panels (November 15, 2018). Available at SSRN: https://ssrn.com/abstract=3305782 or http://dx.doi.org/10.2139/ssrn.3305782

Cindy S.H. Wang (Contact Author)

Catholic University of Louvain (UCL) ( email )

Place Montesquieu, 3
Louvain-la-Neuve, 1348
Belgium

Peking University, HSBC Business School ( email )

101, Section 2 Kuang Fu Road
Hsinchu, Taiwan 300
China

Cheng Hsiao

University of Southern California - Department of Economics ( email )

3620 South Vermont Ave. Kaprielian (KAP) Hall, 300
Los Angeles, CA 90089
United States

National Taiwan University

1 Sec. 4, Roosevelt Road
Taipei, 106
Taiwan

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Hao-Hsiang Yang

National Tsing Hua University

No. 101, Section 2, Guangfu Road, East District
Hsinchu, 300
Taiwan

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