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Forecasting Nonlinear Aggregates and Aggregates with Time-varying Weights

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  • Helmut Luetkepohl

Abstract

Despite the fact that many aggregates are nonlinear functions and the aggregation weights of many macroeconomic aggregates are timevarying, much of the literature on forecasting aggregates considers the case of linear aggregates with fixed, time-invariant aggregation weights. In this study a framework for nonlinear contemporaneous aggregation with possibly stochastic or time-varying weights is developed and different predictors for an aggregate are compared theoretically as well as with simulations. Two examples based on European unemployment and inflation series are used to illustrate the virtue of the theoretical setup and the forecasting results.

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Bibliographic Info

Paper provided by European University Institute in its series Economics Working Papers with number ECO2010/11.

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Date of creation: 2010
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Handle: RePEc:eui:euiwps:eco2010/11

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Keywords: Forecasting; stochastic aggregation; autoregression; moving average; vector autoregressive process;

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  1. David F. Hendry & Kirstin Hubrich, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 216-227, April.
  2. Kirstin Hubrich, 2004. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Computing in Economics and Finance 2004 230, Society for Computational Economics.
  3. Beyer, A. & Doornik, J.A. & Hendry, D.F., 2000. "Constructing Historical Euro-Zone Data," Economics Working Papers eco2000/10, European University Institute.
  4. Heather Anderson & Mardi Dungey & Denise R. Osborn & Farshid Vahid, 2007. "Constructing Historical Euro Area Data," CAMA Working Papers 2007-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  5. Helmut Lütkepohl, 2010. "Forecasting Aggregated Time Series Variables: A Survey," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2010(2), pages 1-26.
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Cited by:
  1. Brüggemann, Ralf & Lütkepohl, Helmut, 2013. "Forecasting contemporaneous aggregates with stochastic aggregation weights," International Journal of Forecasting, Elsevier, vol. 29(1), pages 60-68.
  2. Knotek, Edward S. & Zaman, Saeed, 2014. "Nowcasting U.S. Headline and Core Inflation," Working Paper 1403, Federal Reserve Bank of Cleveland.
  3. Colin Bermingham & Antonello D’Agostino, 2014. "Understanding and forecasting aggregate and disaggregate price dynamics," Empirical Economics, Springer, vol. 46(2), pages 765-788, March.

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