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Factor Decomposition of Economic Time Series Fluctuations — Economic and statistical models in harmony —

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The Practice of Time Series Analysis

Part of the book series: Statistics for Engineering and Physical Science ((ISS))

Abstract

In analyzing factors of economic time series fluctuations, it is important to compare, first of all, the characteristics between a macro-econometric model and a time series model in order to explain to what extent an economic theory should be utilized or how deeply a statistical theory should be taken in. With the macro-econometric model, we make much of the fact that movement of a variety of factors mainly concerning business fluctuations should be described deterministically with the aid of the economic theory. At the same time, the macro-econometric model is often used for the procedures including simulation for the purpose of measuring the effect of the fiscal and monetary policies, and no attention is paid to the time series structure of economic variables. On the other hand, with a general time series model, we need none of economic theories to analyze the time series structure of the data. Therefore the model is described stochastically and we make much of the prediction performance.1) Needless to say, there might actually be neither an econometric model ignoring the time series characteristics nor economic time series analysis neglecting the economic theories. The purpose of this chapter resides in the improvement of the time series model by taking in the economic knowledge expressed by an econometric model in analyzing economic data.

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© 1999 Springer-Verlag New York, Inc.

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Fukuda, K. (1999). Factor Decomposition of Economic Time Series Fluctuations — Economic and statistical models in harmony —. In: Akaike, H., Kitagawa, G. (eds) The Practice of Time Series Analysis. Statistics for Engineering and Physical Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2162-3_3

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  • DOI: https://doi.org/10.1007/978-1-4612-2162-3_3

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7439-1

  • Online ISBN: 978-1-4612-2162-3

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