Econ 325: Exam 3 Study Guide
1. Calculations you are expected to be able to make include:
a. MA, CMA, CMAT, CF, SF, SI, and anything else calculated during your homework.
2. Be prepared to answer questions similar to the following homework problems:
a. Chapter 6 Exercises: 1, 2, 3, 4, 6 a-f, 13
3. Time Series Decomposition
a. Write down the basic time series decomposition model.
i. Define all of your terms.
b. Write down the basic time series decomposition model using the specific
mathematical terms that we use to represent each of the variables in the model. That
is, write down the equation for your time series decomposition forecast.
i. Define all of your terms.
c. Give an intuitive (don’t simply describe the math) description of each of the
components of the model.
d. Explain the intuition behind the equation, and more generally, behind the time series
decomposition forecasting method.
e. List, describe, and draw a graph of each of the four component parts found in time
series data.
f. Graph a hypothetical time series that displays all of the four components.
g. Write an equation for a MAt assuming you have quarterly data.
h. What is the difference between the MA in this chapter (chapter 6) and the MA
discussed in chapter 3?
i. What is the difference between an MA in this chapter, and a centered moving average
(CMA)?
j. Are they ever equal?
k. When calculating centered moving-averages using a 12-period moving average, how
many data points are lost at the beginning of the series?
l. When calculating centered moving-averages using a 12-period moving average, how
many data points are lost at the end of the series?
m. Can a CMA be used to deseasonalize data? How?
n. Explain in detail how one would create a seasonal index.
i. Make sure to include all 4 steps and to include an equation for a step if
relevant.
o. What is a normalization in the context of the seasonal index?
i. Give the equation used to normalize your index.
p. What is the sum of the seasonal index numbers for monthly data?
q. How about for quarterly data?
r. Generally, what is the sum of the seasonal index numbers?
s. How would one use a seasonal index to estimate annual sales data if one knew sales
for the 1st quarter only?
t. How does one interpret a season index number? (For example, an index number of
0.8 for February.)
u. Explain graphically how one would estimate the long term trend component.
v. Explain using an equation how one would estimate the long term trend component.
w. What is the most difficult aspect of forecasting using time series decomposition?
x. Suggest a subjective technique for forecasting the cyclical factor in periods for which
you cannot simply calculate it (for example, periods which you are trying to forecast).
y. Suggest a quantitative technique for estimating the cyclical factor in periods for
which you cannot simply calculate it (for example, periods which you are trying to
forecast).
z. What is the major problem with using this technique?
aa. What is a “leading index?”
bb. What is a “coincident index?”
cc. What is a “lagging index?”
dd. Why would a “leading index” be of use to a forecaster?
ee. Suggest a third technique (different than the two above) for estimating the cyclical
factor based on your previous answer?
ff. What is the range of values that the cyclical factor can take?
gg. How do we calculate the cyclical factor?
hh. Over time, the cyclical factor will tend to oscillate around what number?
ii. What is the amplitude of a series?
jj. What is the periodicity of a series?
kk. What does a true cycle look like?
ll. How does one go about forecasting the irregular component in time series
decomposition?
mm. Is the irregular component always equal to 1?
nn. Explain how time series decomposition essentially involves combining 3 different
forecasts (and possibly a fourth).
oo. How far into the future can a forecast be made using the time series decomposition
model?
pp. What is the major advantage of the time series decomposition model?