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Maximum entropy extreme-value seasonal adjustment

机译:最大熵极值季节性调整

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Some economic series in small economies exhibit meagre (i.e. non-positive) values, as well as seasonal extremes. For example, agricultural variables in countries with a distinct growing season may exhibit both of these features. Multiplicative seasonal adjustment typically utilises a logarithmic transformation, but the meagre values make this impossible, while the extremes engender huge distortions that render seasonal adjustments unacceptable. To account for these features, we propose a new method of extreme-value adjustment based on the maximum entropy principle, which results in replacement of the meagre values and extremes by optimal projections that utilise information from the available time series dynamics. This facilitates multiplicative seasonal adjustment. The method is illustrated in the New Zealand agricultural series.
机译:小型经济体中的某些经济系列表现出微弱(即非正值)的价值以及季节性的极端值。例如,生长季节不同的国家中的农业变量可能同时具有这两个特征。乘性季节性调整通常使用对数转换,但是微不足道的值使此操作不可能实现,而极端情况则会导致巨大的失真,从而使季节性调整无法接受。考虑到这些特征,我们提出了一种基于最大熵原理的极值调整新方法,该方法可通过利用来自可用时间序列动态信息的最佳投影来替代微薄值和极值。这有利于乘法季节性调整。新西兰农业系列对此方法进行了说明。

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