2 Economics Time Series Questions Excel or Eviews (Bid 6 Hours Bcz I need it

economics multi-part question and need the explanation and answer to help me learn.

2 Economics Time Series Questions Excel or Eviews (Bid 6 Hours Bcz I need it in 6 Hours)
Q6 and Q9 all parts
Requirements: All answers
Question 6
Barbara Lynch, the product manager for a line of skiwear produced by HeathCo
Industries, has been working on developing sales forecasts for the skiwear that is
sold under the Northern Slopes and Jacque Monri brands. She has had various
regression-based forecasting models developed (see Exercises 7 and 8 in Chapter 4
and Exercises 6 and 7 in Chapter 5). Quarterly sales for 1998 through 2007 are as
follows:
(c6p6)
Quarterly Sales ($000) at End-Month of Quarter
Year March June September December
1998 72,962 81,921 97,729 142,161
1999 145,592 117,129 114,159 151,402
2000 153,907 100,144 123,242 128,497
2001 176,076 180,440 162,665 220,818
2002 202,415 211,780 163,710 200,135
2003 174,200 182,556 198,990 243,700
2004 253,142 218,755 225,422 253,653
2005 257,156 202,568 224,482 229,879
2006 289,321 266,095 262,938 322,052
2007 313,769 315,011 264,939 301,479
a. Prepare a time-series plot of the data, and on the basis of what you see in the plot,
write a brief paragraph in which you explain what patterns you think are present in
the sales series.
b. Smooth out seasonal influences and irregular movements by calculating the cen-
tered moving averages. Add the centered moving averages to the original data you
plotted in part (a). Has the process of calculating centered moving averages been
effective in smoothing out the seasonal and irregular fluctuations in the data? Ex-
plain.
c. Determine the degree of seasonality by calculating seasonal indices for each quar-
ter of the year. Do this by finding the normalized average of the seasonal factors for
each quarter, where the seasonal factors are actual sales divided by the centered
moving average for each period. If you have done Exercise 7 in Chapter 5, explain
how these seasonal indices compare with the seasonality identified by the regres-
sion model.
d. Determine the long-term trend in the sales data by regressing the centered moving
average on time, where T = 1 for Mar-98. That is, estimate the values for b0 and b1
for the following model:
CMAT = b0 + b1(T)
Plot this equation, called the centered moving-average trend (CMAT), along with
the raw data and the CMA on the same plot developed in part (a).
e. Find the cycle factor (CF) for each quarter by dividing the CMA by the CMAT. Plot
the cycle factors on a new graph and project (CF) forward through Dec-08.
wil73648_ch06.qxd 11/6/08 10:28 AM Page 329
f. Develop a forecast for Ms. Lynch for the four quarters of 2008 by calculating the
product of the trend, the seasonal index, and the cycle factor. Given that actual sales
(in thousands of dollars) were 334,271, 328,982, 317,921, and 350,118 for quarters
1 through 4, respectively, calculate the RMSE for this model based only on the
2008 forecast period.
Question 9
The Bechtal Tire Company (BTC) is a supplier of automotive tires for U.S. car com-
panies. BTC has hired you to analyze its sales. Data from 1976Q1 through 2007Q4 are
given in the following table (in thousands of units):
wil73648_ch06.qxd 11/6/08 10:28 AM Page 332
Time-Series Decomposition 333
(c6p9) BTC Sales of Tires
Year Q1 Q2 Q3 Q4
1986 2,029 2,347 1,926 2,162
1987 1,783 2,190 1,656 1,491
1988 1,974 2,276 1,987 2,425
1989 2,064 2,517 2,147 2,524
1990 2,451 2,718 2,229 2,190
1991 1,752 2,138 1,927 1,546
1992 1,506 1,709 1,734 2,002
1993 2,025 2,376 1,970 2,122
1994 2,128 2,538 2,081 2,223
1995 2,027 2,727 2,140 2,270
1996 2,155 2,231 1,971 1,875
1997 1,850 1,551 1,515 1,666
1998 1,733 1,576 1,618 1,282
1999 1,401 1,535 1,327 1,494
2000 1,456 1,876 1,646 1,813
2001 1,994 2,251 1,855 1,852
2002 2,042 2,273 2,218 1,672
2003 1,898 2,242 2,247 1,827
2004 1,669 1,973 1,878 1,561
2005 1,914 2,076 1,787 1,763
2006 1,707 2,019 1,898 1,454
2007 1,706 1,878 1,752 1,560
a. Write a report to Bechtal Tire Company in which you explain what a time-series de-
composition analysis shows about its tire sales. Include in your discussion seasonal,
cyclical, and trend components. Show the raw data, the deseasonalized data, and
the long-term trend on one time-series plot. Also provide a plot of the cycle factor
with a projection through 2008.
b. In the last section of your report, show a time-series graph with the actual data and
the values that the time-series decomposition model would predict for each quarter
from 1986Q3 through 2007Q4, along with a forecast for 2008. If actual sales for
2008 were Q1 = 1,445.1, Q2 = 1,683.8, Q3 = 1,586.6, and Q4 = 1,421.3, what
RMSE would result from your 2008 forecast

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