Abstract

http://ssrn.com/abstract=1411432
 
 

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Bayesian Causal Effects in Quantiles: Accounting for Heteroscedasticity


Cathy W. S. Chen


Feng Chia University - Department of Statistics; Graduate Institute of Statistics & Actuarial Science, Feng Chia University

Richard H. Gerlach


University of Sydney

Jian-ming Wei


Graduate Institute of Statistics & Actuarial Science, Feng Chia University

May 28, 2009


Abstract:     
Testing for Granger non-causality over varying quantile levels could be used to measure and infer dynamic linkages, enabling the identification of quantiles for which causality is relevant, or not. However, dynamic quantiles in financial application settings are clearly affected by heteroscedasticity, as well as the exogenous and endogenous variables under consideration. GARCH-type dynamics are added to the standard quantile regression model, so as to more robustly examine quantile causal relations between dynamic variables. An adaptive Bayesian Markov chain Monte Carlo scheme, exploiting the link between quantile regression and the skewed-Laplace distribution, is designed for estimation and inference of the quantile causal relations, simultaneously estimating and accounting for heteroscedasticity. Dynamic quantile linkages for the international stock markets in Taiwan and Hong Kong are considered over a range of quantile levels. Specifically, the hypothesis that these stock returns are Granger-caused by the US market and/or the Japanese market is examined. The US market is found to significantly and positively Granger-cause both markets at all quantile levels, while the Japanese market effect was also significant at most quantile levels, but with weaker effects.

Number of Pages in PDF File: 21

Keywords: Bayesian, Granger non-causality in quantiles, Skewed-Laplace distribution, GARCH, Markov chain Monte Carlo

JEL Classification: C01, C11, C12

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Date posted: May 29, 2009  

Suggested Citation

Chen, Cathy W. S. and Gerlach, Richard H. and Wei, Jian-ming, Bayesian Causal Effects in Quantiles: Accounting for Heteroscedasticity (May 28, 2009). Available at SSRN: http://ssrn.com/abstract=1411432 or http://dx.doi.org/10.2139/ssrn.1411432

Contact Information

Cathy W. S. Chen
Feng Chia University - Department of Statistics ( email )
100 Wen Hwa Road
Taichung, 407
Taiwan
886 4 24517250 ext 4412 (Phone)
886 4 24517092 (Fax)
HOME PAGE: http://myweb.fcu.edu.tw/~chenws/
Graduate Institute of Statistics & Actuarial Science, Feng Chia University
100 Wenhwa Road
Talchung
Taiwan
886 4-24517250 ext 4412 (Phone)
886 4-2517092 (Fax)
HOME PAGE: http://myweb.fcu.edu.tw/~chenws/
Richard H. Gerlach
University of Sydney ( email )
Room 483, Building H04
University of Sydney
Sydney, NSW 2006
Australia
+ 612 9351 3944 (Phone)
+ 612 9351 6409 (Fax)
HOME PAGE: http://www.econ.usyd.edu.au/staff/richardg
Jian-ming Wei (Contact Author)
Graduate Institute of Statistics & Actuarial Science, Feng Chia University ( email )
100 Wen Hwa Road
Taichung, 407
Taiwan
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References:  31
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