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Maximum entropy extreme‐value seasonal adjustment
Author(s) -
McElroy Tucker,
Penny Richard
Publication year - 2019
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/anzs.12262
Subject(s) - mathematics , multiplicative function , extreme value theory , econometrics , seasonality , series (stratigraphy) , seasonal adjustment , entropy (arrow of time) , principle of maximum entropy , statistics , climatology , mathematical analysis , paleontology , physics , variable (mathematics) , quantum mechanics , biology , geology
Summary 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.