Lecture_3_Decomposition_Falll_2009

# Lecture_3_Decomposition_Falll_2009 - 1 Lecture 3 Time...

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Lecture 3 Time Series Decomposition Read: (WK Ch 6) EC 413/513 Economic Forecast and Analysis (Professor Lee) 1

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This lecture is about: Time Series Decomposition method Y = T × S × C × I Trend Seasonality Cycle Irregular Component Procedures 1. MA and CMA ; Seasonality MA t = ( y t-2 + y t-1 + y t + y t+1 ) .. for quarterly data (Note: For monthly data, use 12 periods.) CMA t = (MA t + MA t+1 ) .. Centered Moving Average 2
Point : CMA t is the deseasonalized data. Why? SF t = Y t / CMA t .. Seasonal Factor (SF) SF 3 = Y 3 / CMA 3 = 20/15.25 = 1.31 SF 4 = Y 4 / CMA 4 = 12/15.75 = 0.76 ; It makes sense for the data of swimwear sales. SI (Seasonal Index) is the average of the seasonal factors (SF) for each quarter. 3

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4
CMAT (Centered Moving Average TREND ) We use a regression model, using CMA t . CMA t = a + b × t + error, t = 1,2,. .,T. .. CMA t is a fitted value from this regression. CMAT

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## This note was uploaded on 02/29/2012 for the course EC 513 taught by Professor Staff during the Fall '08 term at Alabama.

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Lecture_3_Decomposition_Falll_2009 - 1 Lecture 3 Time...

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