Structural change and the combination of forecasts

Journal of Forecasting

Volumn 6, Issue 1, 1987, Pages 21-40

  Diebold, Francis X ^a   Pauly, Peter ^b  

^a FEDERAL RESERVE BOARD   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Forecast combination; Structural change; Varying parameter models

Indexed keywords

EID: 84984423763     PISSN: 02776693     EISSN: 1099131X     Source Type: Journal    
DOI: 10.1002/for.3980060103     Document Type: Article

References (37)

1. The combination of forecasts
2. Forecasting livestock prices with individual and composite methods
3. An analysis of transformations
4. A simple test for heteroskedasticity and random coefficient variation
5. Asymptotic distribution of the Hildreth‐Houck estimator
6. Some statistical results on the combination of forecasts
7. The combination of forecasts
8. Estimating structural models of seasonality
9. Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation
10. Combining competing forecasts of inflation using a bivariate ARCH model
11. The typical spectral shape of an economic variable
12. Experience with forecasting univariate time series and the combination of forecasts
13. Improved methods of combining forecasts
14. The use of outside information in econometric forecasting
15. A unified view of statistical forecasting procedures
16. Some estimators for a linear model with random coefficients
17. A note on studentizing a test for heteroskedasticity
18. The role of time series analysis in the evaluation of econometric models
19. Forecasting accuracy and the assumption of constancy
20. Averages of forecasts: some exact results
21. The role of macroeconometric models in forecasting and policy analysis in the U.S.
22. Spectral analysis of seasonal adjustment procedures
23. Distributed lags and unobserved components in economic time series
24. Indices of business; conditions
25. Statistics and economic theory
26. On the estimation of structural change: a generalization of the random coefficients regression model
27. Bayesian and Non‐Bayesian Analysis of Switching Regressions and Random Coefficient Models
28. Linear Prediction and Estimation Methods for Regression Models with Stationary Stochastic Coefficients;