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2019 год

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Increasing the accuracy of macroeconomic time series forecast by incorporating functional and correlational dependencies between them

Increasing the accuracy of macroeconomic time series forecast by incorporating functional and correlational dependencies between them

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The paper presents a parametric approach to forecasting vectors of macroeconomic indicators,which takes into account functional and correlation dependencies between them. It is asserted that this information allows to achieve a steady decrease in their mean-squared forecast error. The paper also provides an algorithm for calculating the general form of the corrected probability density function for each of modelled indicators. In order to prove the efficiency of the proposed method we conduct a rigorous simulation and empirical investigation.

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The paper presents a parametric approach to forecasting vectors of macroeconomic indicators,which takes into account functional and correlation dependencies between them. It is asserted that this information allows to achieve a steady decrease in their mean-squared forecast error. The paper also provides an algorithm for calculating the general form of the corrected probability density function for each of modelled indicators. In order to prove the efficiency of the proposed method we conduct a rigorous simulation and empirical investigation.

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Возрастное ограничение:
12+
Дата выхода на Литрес:
15 мая 2019
Дата написания:
2019
Объем:
19 стр.
Общий размер:
742 КБ
Общее кол-во страниц:
19
Правообладатель:
Синергия
Формат скачивания:
pdf

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