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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|Date of creation:||1998|
|Date of revision:|
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- 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.
- Smith, M. & Kohn, R., .
"Nonparametric Regression using Bayesian Variable Selection,"
Statistics Working Paper
_009, Australian Graduate School of Management.
- Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
- 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.
- 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.
- repec:oxf:wpaper:1998-w05 is not listed on IDEAS
- 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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