 Forecasting Nonlinear Aggregates and Aggregates with Time-varying WeightsJournal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), 2011, vol. 231, issue 1, 107-133 Abstract: Despite the fact that many aggregates are nonlinear functions and the aggregation weights of many macroeconomic aggregates are time-varying, 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. Keywords: Forecasting; stochastic aggregation; autoregression; moving average; vector autoregressive process; Forecasting; stochastic aggregation; autoregression; moving average; vector autoregressive process (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:jns:jbstat:v:231:y:2011:i:1:p:107-133 Access Statistics for this article Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik) is currently edited by Peter Winker More articles in Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik) from De Gruyter |
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