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Forecasting aggregates of independent Arima processes

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  • Rose, David E.

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  • Rose, David E., 1977. "Forecasting aggregates of independent Arima processes," Journal of Econometrics, Elsevier, vol. 5(3), pages 323-345, May.
    • Handle: RePEc:eee:econom:v:5:y:1977:i:3:p:323-345
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    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Pesaran, M. Hashem & Chudik, Alexander, 2014. "Aggregation in large dynamic panels," Journal of Econometrics, Elsevier, vol. 178(P2), pages 273-285.
    3. Thiago Carlomagno Carlo & Emerson Fernandes Marçal, 2016. "Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon," Applied Economics, Taylor & Francis Journals, vol. 48(50), pages 4846-4860, October.
    4. Francisco Dias & Maximiano Pinheiro & António Rua, 2018. "A bottom-up approach for forecasting GDP in a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 718-723, June.
    5. Barrera, Carlos, 2013. "El sistema de predicción desagregada: Una evaluación de las proyecciones de inflación 2006-2011," Working Papers 2013-009, Banco Central de Reserva del Perú.
    6. Hashem Pesaran, M., 2003. "Aggregation of linear dynamic models: an application to life-cycle consumption models under habit formation," Economic Modelling, Elsevier, vol. 20(2), pages 383-415, March.
    7. Bidarkota, Prasad V., 1998. "The comparative forecast performance of univariate and multivariate models: an application to real interest rate forecasting," International Journal of Forecasting, Elsevier, vol. 14(4), pages 457-468, December.
    8. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    9. Purkayastha, D. Das, 1995. "An exposition of the decomposition in a Controlled Autoregressive Integrated Segmented Moving Average (CARISMA) model," Economics Letters, Elsevier, vol. 48(1), pages 1-7, April.
    10. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    11. Colin Bermingham & Antonello D’Agostino, 2014. "Understanding and forecasting aggregate and disaggregate price dynamics," Empirical Economics, Springer, vol. 46(2), pages 765-788, March.
    12. Espasa, Antoni & Mayo-Burgos, Iván, 2013. "Forecasting aggregates and disaggregates with common features," International Journal of Forecasting, Elsevier, vol. 29(4), pages 718-732.
    13. Akman, Ibrahim & De Gooijer, Jan G., 1996. "Component extraction analysis of multivariate time series," Computational Statistics & Data Analysis, Elsevier, vol. 21(5), pages 487-499, May.
    14. Nijman, Theo E & Palm, Franz C, 1990. "Predictive Accuracy Gain from Disaggregate Sampling in ARIMA Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(4), pages 405-415, October.
    15. Widiarta, Handik & Viswanathan, S. & Piplani, Rajesh, 2009. "Forecasting aggregate demand: An analytical evaluation of top-down versus bottom-up forecasting in a production planning framework," International Journal of Production Economics, Elsevier, vol. 118(1), pages 87-94, March.
    16. Giacomo Sbrana & Andrea Silvestrini, 2012. "Comparing aggregate and disaggregate forecasts of first order moving average models," Statistical Papers, Springer, vol. 53(2), pages 255-263, May.
    17. Zeda Li & William W. S. Wei, 2024. "Measuring the advantages of contemporaneous aggregation in forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1308-1320, August.
    18. Sbrana, Giacomo & Silvestrini, Andrea, 2013. "Forecasting aggregate demand: Analytical comparison of top-down and bottom-up approaches in a multivariate exponential smoothing framework," International Journal of Production Economics, Elsevier, vol. 146(1), pages 185-198.
    19. Nijman, T.E. & Palm, F.C., 1987. "Predictive accuracy gain from disaggregate sampling in ARIMA-models," Other publications TiSEM 73cf32e2-d741-45a0-8b3e-f, Tilburg University, School of Economics and Management.
    20. Pesaran, M. H., 1999. "On Aggregation of Linear Dynamic Models," Cambridge Working Papers in Economics 9919, Faculty of Economics, University of Cambridge.

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