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Forecasting contemporaneous aggregates with stochastic aggregation weights


  • Brüggemann, Ralf
  • Lütkepohl, Helmut


Many contemporaneously aggregated variables have stochastic aggregation weights. We compare different forecasts for such variables, including univariate forecasts of the aggregate, a multivariate forecast of the aggregate that uses information from the disaggregated components, a forecast which aggregates a multivariate forecast of the disaggregate components and the aggregation weights, and a forecast which aggregates univariate forecasts of individual disaggregate components and the aggregation weights. In empirical illustrations based on aggregate GDP and money stock series, we find forecast mean squared error reductions when information in the stochastic aggregation weights is used.

Suggested Citation

  • Brüggemann, Ralf & Lütkepohl, Helmut, 2013. "Forecasting contemporaneous aggregates with stochastic aggregation weights," International Journal of Forecasting, Elsevier, vol. 29(1), pages 60-68.
  • Handle: RePEc:eee:intfor:v:29:y:2013:i:1:p:60-68 DOI: 10.1016/j.ijforecast.2012.05.007

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    References listed on IDEAS

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    More about this item


    Aggregation; Autoregressive process; Mean squared error;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models


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