Sparse seemingly unrelated regression modelling: Applications in finance and econometrics
A sparse seemingly unrelated regression (SSUR) model is proposed to generate substantively relevant structures in the high-dimensional distributions of seemingly unrelated regression (SUR) model parameters. The SSUR framework includes prior specifications, posterior computations using Markov chain Monte Carlo methods, evaluations of model uncertainty, and model structure searches. Extensions of the SSUR model to dynamic models embed general structure constraints and model uncertainty in dynamic models. The models represent specific varieties of models recently developed in the growing high-dimensional sparse modelling literature. Two simulated examples illustrate the model and highlight questions regarding model uncertainty, searching, and comparison. The model is then applied to two real-world examples in macroeconomics and finance, according to which its identified structures have practical significance.
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- George, Edward I. & Sun, Dongchu & Ni, Shawn, 2008. "Bayesian stochastic search for VAR model restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 553-580, January.
- Griffiths, W.E., 2001. "Bayesian Inference in the Seemingly Unrelated Regressions Models," Department of Economics - Working Papers Series 793, The University of Melbourne.
- Fama, Eugene F, 1981. "Stock Returns, Real Activity, Inflation, and Money," American Economic Review, American Economic Association, vol. 71(4), pages 545-65, September.
- Geske, Robert & Roll, Richard, 1983. " The Fiscal and Monetary Linkage between Stock Returns and Inflation," Journal of Finance, American Finance Association, vol. 38(1), pages 1-33, March.
- Carlos M. Carvalho & Hélène Massam & Mike West, 2007. "Simulation of hyper-inverse Wishart distributions in graphical models," Biometrika, Biometrika Trust, vol. 94(3), pages 647-659.
- Michael J. Daniels, 2002. "Bayesian analysis of covariance matrices and dynamic models for longitudinal data," Biometrika, Biometrika Trust, vol. 89(3), pages 553-566, August.
- C. M. Carvalho & J. G. Scott, 2009. "Objective Bayesian model selection in Gaussian graphical models," Biometrika, Biometrika Trust, vol. 96(3), pages 497-512.
- Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
- Dobra, Adrian & Hans, Chris & Jones, Beatrix & Nevins, J.R.Joseph R. & Yao, Guang & West, Mike, 2004. "Sparse graphical models for exploring gene expression data," Journal of Multivariate Analysis, Elsevier, vol. 90(1), pages 196-212, July.
- Lee, Bong-Soo, 1992. " Causal Relations among Stock Returns, Interest Rates, Real Activity, and Inflation," Journal of Finance, American Finance Association, vol. 47(4), pages 1591-603, September.
- Smith, M. & Kohn, R., 1998.
"Nonparametric Seemingly Unrelated Regression,"
Monash Econometrics and Business Statistics Working Papers
7/98, Monash University, Department of Econometrics and Business Statistics.
- Min, Chung-ki & Zellner, Arnold, 1993.
"Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates,"
Journal of Econometrics,
Elsevier, vol. 56(1-2), pages 89-118, March.
- Min, C.K. & Zellner, A., 1992. ""Bayesian and Non-Bayesian Methods for Combining Models and Forecasts with Applications to Forecasting International Growth Rates"," Papers 90-92-23, California Irvine - School of Social Sciences.
- Smith M. & Kohn R., 2002. "Parsimonious Covariance Matrix Estimation for Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1141-1153, December.
- Foschi, Paolo & Belsley, David A. & Kontoghiorghes, Erricos J., 2003. "A comparative study of algorithms for solving seemingly unrelated regressions models," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 3-35, October.
- Hao Wang & Mike West, 2009. "Bayesian analysis of matrix normal graphical models," Biometrika, Biometrika Trust, vol. 96(4), pages 821-834.
- Kontoghiorghes, E. J. & Clarke, M. R. B., 1995. "An alternative approach for the numerical solution of seemingly unrelated regression equations models," Computational Statistics & Data Analysis, Elsevier, vol. 19(4), pages 369-377, April.
- Foschi, Paolo & Kontoghiorghes, Erricos J., 2002. "Seemingly unrelated regression model with unequal size observations: computational aspects," Computational Statistics & Data Analysis, Elsevier, vol. 41(1), pages 211-229, November.
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