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Incorporating Seasonality

This guide delves into the incorporation of seasonality in time series analysis, focusing on quarterly data. We explore the modeling of seasonality alongside trends using dummy variables in EViews. Key models are presented, including those combining trend and seasonal factors, illustrated through mathematical representations. Learn to interpret these models effectively and understand the significance of seasonal components in forecasting. This comprehensive overview will equip you with the necessary tools to enhance your time series analysis and forecasting skills.

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Incorporating Seasonality

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  1. Incorporating Seasonality • Modeling seasonality with trend • Forecasting

  2. Seasonality • Data = Trend + Season (Quarter, say) + e * * * * * * * * * * * * I II III IV IV IV

  3. Defining Dummy Variables Eviews:@seas

  4. Seasonal Model - 1for Quarterly Data Yt = b0 + g1Q1t + g2Q2t + g3Q3t + et Note: Q4 is not included

  5. Interpretation of the Model

  6. Seasonal Model – 2for Quarterly Data Yt = g1Q1t + g2Q2t + g3Q3t + g4Q4t+et Note: b0 is not included

  7. Interpretation of the Model

  8. Model for Trend and Seasonality-1 Yt = b0 +b1 t +g1Q1t + g2Q2t + g3Q3t + et Note: Q4 is not included

  9. Interpretation of the Model

  10. Model for Trend and Seasonality-2 Yt = b1 t +g1Q1t + g2Q2t + g3Q3t + g4Q4t + et Note: b0 is not included

  11. Interpretation of the Model

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