An algorithm to estimate time-varying parameter SURE models under different types of restriction

Computational Statistics and Data Analysis

Volumn 42, Issue 3, 2003, Pages 363-383

  Orbe, Susan ^a   Ferreira, Eva ^a   Rodriguez Poo, Juan ^b  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

^b UNIVERSITY OF CANTABRIA   (Spain)

Author keywords

Constrained estimators; Cross restrictions; Nonparametric methods; Seasonal restrictions

Indexed keywords

ALGORITHMS; ITERATIVE METHODS; LINEAR SYSTEMS; PROBLEM SOLVING; REGRESSION ANALYSIS; TIME VARYING SYSTEMS;

NONPARAMETRIC METHODS;

COMPUTATIONAL METHODS;

NUMERICAL METHOD;

EID: 0037471363     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(02)00229-3     Document Type: Article

References (32)

1. Box, G.E., Tiao, G.C., 1973. Bayesian Inference in Statistical Analysis. Addison-Wesley, Reading, MA.
2. Chib, S., Greenberg, E., 1995. Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models. J. Econometrics, 68, 339-360.
3. Chow, G.C., 1984. Random and changing coefficients models. In: Griliches, Z., Intriligator M.D. (Ed.), Handbook of Econometrics, Vol. 2. North-Holland, New York, pp. 1213-1245.
4. Deaton, A., Muellbauer, J., 1980. Economics and Consumer Behavior. Cambridge University Press, Cambridge
5. Doran, H.E., Rambaldi, A.N., 1997. Applying linear time-varying constraints to econometric models: with an application to demand systems. J. Econometrics 79, 83-95.
6. Foschi, P., Kontoghiorghes, E.J., 2002. Seemingly unrelated regression model with unequal size observations: computational aspects. Comput. Statist. Data Anal. 41, 211-229.
7. Gamerman, D., Mignon, H.S., 1993. Dynamic hierarchical models. J. Roy. Statist. Soc. Ser. B 55, 629-642.
8. Gersovitz, M., Mackinnon, J., 1978. Seasonality in regression: An application of smoothness priors. J. Amer. Statist. Assoc. 73, 264-273.
9. Goldberger, A.S., 1991. A Course in Econometrics. Harvard University Press, Cambridge, MA.
10. Härdle W., 1990. Applied Nonparametric Estimation. Cambridge University Press, Cambridge.
11. Harvey, A.C., 1989. Forecasting Structural Time Series Models and the Kalman Filter. Cambridge University Press, Cambridge.
12. Hastie, T.J., Tibshirani, R.J., 1990. Generalized additive models. Monographs on Statistics and Applied Probability, Vol. 43 Chapman & Hall, London
13. Hausman, J.A., 1978. Specification tests in econometrics. Econometrica 46, 1251-1271.
14. Hylleberg, S., 1986. Seasonality in Regression. Academic Press, London
15. Jorgenson, D.W., 2000. Econometric Modeling of Producer Behavior. MIT Press, Cambridge.
16. Kontoghiorghes, K.J., Clarke, M.R., 1995. An alternative approach for the numerical of seemingly unrelated regression equation models. Comput. Statist. Data Anal., 19 (4), 369-377.
17. Lütkepohl, H., Herwatz, H., 1996. Specification of varying coefficients time series models via generalized flexible least squares. J. Econometrics 70, 261-290.
18. Min, C., Zellner, A., 1993. Bayesian and non-bayesian methods for combining models and forecasts with applications to forecasting international growth rates. J. Econometrics, 56, 89-118.
19. Nicholls, D.F., Pagan, A., 1985. Varying coefficient regression. In: Hannan, E.J., Krishnaiah, P.R., Rao, M.M. (Eds.), Handbook of Statistics, Vol. 5. North-Holland, Amsterdam, pp. 413-449.
20. Orbe, S., Ferreira, E., Rodriguez-Poo, J.M., 2000. A nonparametric method to estimate time varying coefficients under seasonal constraints. J. Nonparametric Statist. 12, 779-806.
21. Orbe, S., Ferreira, E., Rodriguez-Poo, J.M., 2001. Nonparametric estimation of time varying parameters undershape restrictions. Working Paper Biltoki 2001.02, Department of Econometrics and Statistics, University of the Basque Country, Spain. http://www.et.bs.ehu.es/biltoki/dt200102.shtml.
22. Robinson, P.M., 1989. Nonparametric estimation of time varying parameters. In Hackl P., (Ed.), Statistics Analysis and Forecasting of Economic Structural Change, Springer, Berlin pp. 253-264.
23. Sims, C.A., 1974. Seasonality in regression. J. Amer. Statist. Assoc. 69, 618-626.
24. Sing, B., Ullah, A., 1974. Estimation of seemingly unrelated regressions with random coefficients. J. Amer. Statist. Assoc. 69, 191-195.
25. Smith, M., Kohn, R., 2000. Nonparametric seemingly unrelated regression. J. Econometrics 98, 257-281.
26. Spall, J.C., 1990. Bayesian Analysis of Time Series and Dynamic Methods. Marcel Dekker, New York.
27. Spanos, A., 1986. Statistical Foundations of Econometric Modelling. Cambridge University Press, Cambridge.
28. Srivastava, V.K., Giles, D.E., 1987. Seemingly Unrelated Equation Models: Estimation and Inference. Marcel Dekker, New York, NY.
29. Staniswalis, J.G., 1989. The kernel estimate of a regression function in likelihood-based models. J. Amer. Statist. Assoc. 84, 276-283.
30. Wallis, K.F., 1969. Seasonal adjustment and relations between variables. J. Amer. Statist. Assoc. 69, 18-31.
31. Zellner, A., 1962. An efficient method of estimating seemingly unrelated regressions and tests of aggregation bias. J. Amer. Statist. Assoc. 57, 500-509.
32. Zellner, A., 1971. Introduction to Bayesian Inference in Econometrics. Wiley. New York.