Abstract
A regression model from time series data allows us to identify performance drivers and forecast performance given specific predictor values, just as regression models from cross sectional data do. When decision makers want to forecast future performance, a time series of past performance is used to identify drivers and fit a model. A time series model can be used to identify drivers whose variation over time is associated with later variation in performance over time.
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© 2009 Springer Science+Business Media, LLC
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(2009). Model Building and Forecasting with Multicollinear Time Series. In: Business Statistics for Competitive Advantage with Excel 2007. Springer, New York, NY. https://doi.org/10.1007/978-0-387-74403-2_9
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DOI: https://doi.org/10.1007/978-0-387-74403-2_9
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-74402-5
Online ISBN: 978-0-387-74403-2
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