Short‐Term Analysis of Macroeconomic Time Series
Agustin Maravall provides an account of the statistical methodology used in analysing the present situation and predicting the short‐term future. The analysis of the present consists of removing seasonality and trend which increase the variability of the data. He then discusses short‐term forecasting and argues that overall, stochastic model‐based forecasting has now become standard and that the usual processes employed have to be extended to multi‐variate settings and that non‐linear extensions will be important. One of Maravall's principle focuses is on seasonal adjustment and while arguing that model‐based signal extraction with ARIMA type modes will continue to predominate, he regrets the widespread practice of issuing data that has already been seasonally corrected. He concludes by giving an example to illustrate his contention that short‐term methods may well be highly unreliable for long term analysis.
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