Introduction

Helmut Lütkepohl

Chapter 1 in New Introduction to Multiple Time Series Analysis, 2005, pp 1-7 from Springer

Abstract: Abstract In making choices between alternative courses of action, decision makers at all structural levels often need predictions of economic variables. If time series observations are available for a variable of interest and the data from the past contain information about the future development of a variable, it is plausible to use as forecast some function of the data collected in the past. For instance, in forecasting the monthly unemployment rate, from past experience a forecaster may know that in some country or region a high unemployment rate in one month tends to be followed by a high rate in the next month. In other words, the rate changes only gradually. Assuming that the tendency prevails in future periods, forecasts can be based on current and past data.

Keywords: Forecast Error; Consumption Expenditure; Joint Distribution Function; Multiple Time Series; Univariate Time Series (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1007/978-3-540-27752-1_1

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