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22 - A note on aggregation, disaggregation, and forecasting performance (2000)

Published online by Cambridge University Press:  24 October 2009

Arnold Zellner
Affiliation:
Professor, Emeritus of Economics and Statistics, Graduate School of Business, University of Chicago, Chicago, IL
Justin Tobias
Affiliation:
Department of Economics, University of California, Irvine, CA
Arnold Zellner
Affiliation:
University of Chicago
Franz C. Palm
Affiliation:
Universiteit Maastricht, Netherlands
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Publisher: Cambridge University Press
Print publication year: 2004

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References

Espasa, A. (1994), “Comment on ‘Time series analysis, forecasting and econometric modeling: the structural econometric modeling, time series analysis (SEMSTA) approach,’Journal of Forecasting 13, 234–5CrossRefGoogle Scholar
Garcia-Ferrer, A., Highfield, R. A., Palm, F. C., and Zellner, A. (1987), “Macroeconomic forecasting using pooled international data,” Journal of Business and Economic Statistics 5(1), 53–67; chapter 13 in this volumeGoogle Scholar
Geweke, J. (1986), “Exact inference in the inequality constrained normal linear regression model,” Journal of Applied Econometrics 1, 127–41CrossRefGoogle Scholar
Hong, C. (1979), “Forecasting real output growth rates and cyclical properties of models: a Bayesian approach,” PhD thesis, Department of Economics, University of Chicago
LeSage, J. P. (1990), “Forecasting turning points in metropolitan employment growth rates using Bayesian techniques,” Journal of Regional Science 30(4), 533–48; see chapter 21 in this volumeCrossRefGoogle Scholar
Min, C.-K. and Zellner, A. (1993), “Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates,” Journal of Econometrics, Annals 56, 89–118; chapter 17 in this volume; reprinted in Zellner, (1997)CrossRefGoogle Scholar
Palm, F. C. and Zellner, A. (1992), “To combine or not to combine? Issues of combining forecasts,” Journal of Forecasting 11, 687–701; reprinted in Zellner, (1997)CrossRefGoogle Scholar
Zellner, A. (1994), “Time series analysis, forecasting, and econometric modeling: the structural econometric modeling, time series analysis (SEMSTA) approach,” Journal of Forecasting 13, 215–33; chapter 4 in this volumeCrossRefGoogle Scholar
Zellner, A. (1997), Bayesian Analysis in Econometrics and Statistics: The Zellner View and Papers (Cheltenham, Edward Elgar)
Zellner, A. and Hong, C. (1989), “Forecasting international growth rates using Bayesian shrinkage and other procedures,” Journal of Econometrics, Annals 40, 183–202; chapter 14 in this volume; reprinted in Zellner, (1997)CrossRefGoogle Scholar
Zellner, A., C. Hong, and G. M. Gulati (1990), “Turning points in economic time series, loss structures, and Bayesian forecasting,” part VI in S. Geisser, J. S. Hodges, S. J. Press, and A. Zellner (eds.), Bayesian and Likelihood Methods in Statistics and Econometrics: Essays in Honor of George A. Barnard (Amsterdam, North-Holland), 371–89; chapter 15 in this volume
Zellner, A., Hong, C., and Min, C. (1991), “Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter, and pooling techniques,” Journal of Econometrics 49, 275–304; chapter 16 in this volume; reprinted in A. Zellner, Bayesian Analysis in Econometrics and Statistics: The Zellner View and Papers (Cheltenham, Edward Elgar)CrossRefGoogle Scholar
Zellner, A., J. Tobias, and H. Ryu (1998), “Bayesian method of moments analysis of time series models with an application to forecasting turning points in output growth rates,” H. G. B. Alexander Research Foundation, University of Chicago; [published in Estadistica 49–51 (152–157), 3–63]

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