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Forecasting with balanced state space representations of multivariate distributed lag models
Author(s) -
Mittnik Stefan
Publication year - 1990
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980090302
Subject(s) - state space representation , multivariate statistics , autoregressive integrated moving average , lag , state space , econometrics , representation (politics) , singular value decomposition , state (computer science) , econometric model , competition (biology) , computer science , mathematics , time series , statistics , algorithm , computer network , ecology , politics , political science , law , biology
A procedure for estimating state space models for multivariate distributed lag processes is described. It involves singular value decomposition techniques and yields an internally balanced state space representation which has attractive properties. Following the specifications of a forecasting competition, the approach is applied to generate ex‐post forecasts for US real GNP growth rates. The forecasts of the estimated state space model are compared to those of twelve econometric models and an ARIMA model.