Predictive Accuracy Gain from Disaggregate Sampling in ARIMA Models
We compare the forecast accuracy of autoregressive integrated moving average (ARIMA) models based on data observed with high and low frequency, respectively. We discuss how, for instance, a quarterly model can be used or predict one quarter ahead even if only annual data are available, and we compare the variance of the prediction error in this case with the variance if quarterly observations were indeed available. Results on the expected information gain are presented for a number of ARIMA models including models that describe the seasonally adjusted gross national product (GNP) series in the Netherlands. Disaggregation from annual to quarterly GNP data has reduced the variance of short-run forecast errors considerably, but furter disaggregation from quarterly to monthly data is found to hardly improve the accuracy of monthly forecasts.
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Volume (Year): 8 (1990)
Issue (Month): 4 (October)
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References listed on IDEAS
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- Geweke, John F, 1978. "Temporal Aggregation in the Multiple Regression Model," Econometrica, Econometric Society, vol. 46(3), pages 643-61, May.
- Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, vol. 26(3), pages 271-281, December.
- Nijman, T E & Palm, F C, 1986.
"The Construction and Use of Approximations for Missing Quarterly Observations: A Model-based Approach,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 4(1), pages 47-58, January.
- Nijman, T.E. & Palm, F.C., 1985. "The construction and use of approximations for missing quarterly observations : A model-based approach," Other publications TiSEM 22310454-d7c0-4639-b9a7-5, School of Economics and Management.
- repec:ner:tilbur:urn:nbn:nl:ui:12-153295 is not listed on IDEAS
- Nijman, T.E. & Palm, F.C., 1984.
"Missing observations in the dynamic regression model,"
Other publications TiSEM
4d689d7c-4d89-4ab6-b8c3-f, School of Economics and Management.
- Palm, Franz C & Nijman, Theo E, 1984. "Missing Observations in the Dynamic Regression Model," Econometrica, Econometric Society, vol. 52(6), pages 1415-35, November.
- Palm, F.C. & Nijman, Th., 1982. "Missing observations in the dynamic regression model," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
- Nijman, T.E., 1985. "Missing observations in dynamic macroeconomic modeling," Other publications TiSEM e37098ab-3c29-4f7c-b860-8, School of Economics and Management.
- repec:ner:tilbur:urn:nbn:nl:ui:12-154533 is not listed on IDEAS
- Lutkepohl, Helmut, 1984. "Linear transformations of vector ARMA processes," Journal of Econometrics, Elsevier, vol. 26(3), pages 283-293, December.
- Tiao, G. C. & Guttman, Irwin, 1980. "Forecasting contemporal aggregates of multiple time series," Journal of Econometrics, Elsevier, vol. 12(2), pages 219-230, February.
- Robert B. Litterman, 1983.
"A random walk, Markov model for the distribution of time series,"
84, Federal Reserve Bank of Minneapolis.
- Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-73, April.
- Rose, David E., 1977. "Forecasting aggregates of independent Arima processes," Journal of Econometrics, Elsevier, vol. 5(3), pages 323-345, May.
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