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Titlebook: Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation; Estela Bee Dagum,Silvia Bianconcini Book 2016 Springer International Pub

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楼主: Maculate
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Further Developments on the Henderson Trend-Cycle FilterUS Bureau of Census II-X11 and its variants, the X11/X12ARIMA. Major studies have been done on trend-cycle estimation during the last 20 years by making changes to the Henderson filters. The emphasis has been on determining the direction of the short-term trend for an early detection of a true turni
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The Effect of Seasonal Adjustment on Real-Time Trend-Cycle Predictionhodology reduce significantly revisions and turning point detection respect to the currently used by statistical agencies. The best choice of local time-varying bandwidth is the one obtained by minimizing the distance between the gain functions of the RKHS asymmetric and the symmetric filter to whic
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Linear Filters Seasonal Adjustment Methods: Census Method II and Its Variantsined with those of the ARIMA model extrapolations. An illustrative example of the seasonal adjustment with the X12ARIMA software default option is shown with the US New Orders for Durable Goods series. The illustrative example concentrates on the most important tables of this software that enable to assess the quality of the seasonal adjustment.
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Real Time Trend-Cycle Prediction of official statistical agencies, the new set of weights produces both smaller revisions and time delay to detect true turning points. The theoretical results are empirically corroborated with a set of leading, coincident, and lagging indicators of the US economy.
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The Effect of Seasonal Adjustment on Real-Time Trend-Cycle Predictiond with such nonparametric kernel filters. The seasonal adjustments compared are the two officially adopted by statistical agencies: X12ARIMA and TRAMO-SEATS applied to a sample of US leading, coincident, and lagging indicators.
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