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Nonparametric Seemingly Unrelated Regression

This paper presnets a method for simultaneously estimating a system of nonparametric multiple regressions which may seem unrelated, but where the errors are potentially correlated between equations. We show that the prime advantage of estimating such a 'seemingly unrelated' system of nonparametric regressions is that substantially less observations can be required to obtain reliable functions estimates than if each of the regression equations was estimated separately and the correlation ignored.

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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 7/98.

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Length: 31 pages
Date of creation: 1998
Date of revision:
Handle: RePEc:msh:ebswps:1998-7
Contact details of provider: Postal: PO Box 11E, Monash University, Victoria 3800, Australia
Phone: +61-3-9905-2489
Fax: +61-3-9905-5474
Web page: http://www.buseco.monash.edu.au/depts/ebs/
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  1. Neil Shephard & Michael K Pitt, 1998. "Time Varying Covariances: A Factor Stochastic Volatility Approach (with discussion," Economics Series Working Papers 1998-W05, University of Oxford, Department of Economics.
  2. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
  3. 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.
  4. Mandy, David M. & Martins-Filho, Carlos, 1993. "Seemingly unrelated regressions under additive heteroscedasticity : Theory and share equation applications," Journal of Econometrics, Elsevier, vol. 58(3), pages 315-346, August.
  5. 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.
  6. Smith, Michael, 2000. "Modeling and Short-term Forecasting of New South Wales Electricity System Load," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 465-78, October.
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