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Time series analysis: forecasting and control BOX JENKINS
Publisher: Prentice-Hall

Than the RMSFEs of the SPF forecasts. [7] base their models on time-series analysis and construct a moving average predictor [11], a weighted least squares predictor, and a Markov predictor. How time-series analysis can be used to conduct economic forecasts. We believe that the above findings contribute to the current discussion on the usefulness of DSGE models in policy oriented analyses. In this framework, forecasting uncertainty is reflected in the dispersion of actual outcomes relative to those forecasted (Hendry and Ericsson 2001). Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. A modernized new edition of one of the most trusted books on time series analysis. ``Time Series Analysis, Forecasting and Control''. (2007) point at an improved time series fit of. The increased availability of data, collected at frequent and regular intervals, also lends itself to time series analysis as well as closed-loop business strategies.