EconHM28 - Question #1 You would like to predict cigarette...

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Question #1 You would like to predict cigarette consumption for the year 2005. You know that you can use exponential smoothing to create forecasts when the time series exhibits gradual (not a sharp) trend, has no cyclical effects, and has no seasonal effects, and when you are forecasting only one period beyond the existing data. You are given the data set on the cigarette consumption from 1965 to 2004. Answer the following questions. 1. From the scatter plot you can conclude that: o the series exhibits gradual (not a sharp) trend o the seriest exhibits a sharp change in trend o the series appears to have a cyclical component o the series does not appear to have a cyclical component o the series appears to have seasonal component o the series does not appear to have seasonal component o time series forecasting with exponential smoothing is appropriate o time series forecasting with exponential smoothing is not appropriate 2. 3. Using the smoothing constant of 0.8, the forecasted value for the cigarette consumption in 2005 is 2703.131459 Question #2 This question is based on the example on page 120 (slide 56) of your course packet. You are given the following quarterly data for hotel occupancy. We know that we need to drop one of the 4 seasons to run our regression - otherwise our model will suffer from perfect multicollinearity (or no intercept can be estimated). Drop the 4th Quarter like we do in the example in the course reader. Forecasting with Indicator Variables Using a model that includes indicator variables for the quarters, what is the test statistic for testing whether or not the second quarter has a significant effect on hotel occupancy? 5.741339555 What would be the predicted value for the second quarter of 1996 using this model?
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This note was uploaded on 02/11/2010 for the course ECON 203 taught by Professor Petry during the Spring '09 term at University of Illinois, Urbana Champaign.

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EconHM28 - Question #1 You would like to predict cigarette...

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