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Summary and
Conclusions
1. The key idea behind regression analysis is the statistical dependence of one variable, the
dependent variable, on one or more other variables, the explanatory variables.
2. The objective of such analysis is to estimate and/or predict the mean or average value of the
dependent variable on the basis of the known or fixed values of the explanatory variables.
3. In practice the success of regression analysis depends on the availability of the appro-
priate data. This chapter discussed the nature, sources, and limitations of the data that
are generally available for research, especially in the social sciences.
4. In any research, the researcher should clearly state the sources of the data used in
the analysis, their definitions, their methods of collection, and any gaps or omissions
in the data as well as any revisions in the data. Keep in mind that the macroeconomic
data published by the government are often revised.
5. Since the reader may not have the time, energy, or resources to track down the data, the
reader has the right to presume that the data used by the researcher have been properly
gathered and that the computations and analysis are correct.
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Chapter 1
The Nature of Regression Analysis
29
EXERCISES
Year
U.S.
Canada
Japan
France
Germany
Italy
U.K.
1980
82.4
76.1
91.0
72.2
86.7
63.9
78.5
1981
90.9
85.6
95.3
81.8
92.2
75.5
87.9
1982
96.5
94.9
98.1
91.7
97.0
87.8
95.4
1983
99.6
100.4
99.8
100.3
100.3
100.8
99.8
1984
103.9
104.7
102.1
108.0
102.7
111.4
104.8
1985
107.6
109.0
104.2
114.3
104.8
121.7
111.1
1986
109.6
113.5
104.9
117.2
104.6
128.9
114.9
1987
113.6
118.4
104.9
121.1
104.9
135.1
119.7
1988
118.3
123.2
105.6
124.3
106.3
141.9
125.6
1989
124.0
129.3
108.0
128.7
109.2
150.7
135.4
1990
130.7
135.5
111.4
132.9
112.2
160.4
148.2
1991
136.2
143.1
115.0
137.2
116.3
170.5
156.9
1992
140.3
145.3
117.0
140.4
122.2
179.5
162.7
1993
144.5
147.9
118.5
143.4
127.6
187.7
165.3
1994
148.2
148.2
119.3
145.8
131.1
195.3
169.3
1995
152.4
151.4
119.2
148.4
133.3
205.6
175.2
1996
156.9
153.8
119.3
151.4
135.3
213.8
179.4
1997
160.5
156.3
121.5
153.2
137.8
218.2
185.1
1998
163.0
157.8
122.2
154.2
139.1
222.5
191.4
1999
166.6
160.5
121.8
155.0
140.0
226.2
194.3
2000
172.2
164.9
121.0
157.6
142.0
231.9
200.1
2001
177.1
169.1
120.1
160.2
144.8
238.3
203.6
2002
179.9
172.9
119.0
163.3
146.7
244.3
207.0
2003
184.0
177.7
118.7
166.7
148.3
250.8
213.0
2004
188.9
181.0
118.7
170.3
150.8
256.3
219.4
2005
195.3
184.9
118.3
173.2
153.7
261.3
225.6
17
Subtract from the current year’s CPI the CPI from the previous year, divide the difference by the
previous year’s CPI, and multiply the result by 100. Thus, the inflation rate for Canada for 1981 is
[(85
.
6
−
76
.
1)
/
76
.
1]
×
100
=
12
.
48% (approx.).
TABLE 1.3
CPI in Seven
Industrial Countries,
1980–2005
(1982–1984
=
100)
Source:
Economic Report of the
President,
2007, Table 108,
p. 354.
1.1. Table 1.3 gives data on the Consumer Price Index (CPI) for seven industrialized
countries with 1982–1984
=
100 as the base of the index.
a.
From the given data, compute the inflation rate for each country.
17
b.
Plot the inflation rate for each country against time (i.e., use the horizontal axis for
time and the vertical axis for the inflation rate).
c.
What broad conclusions can you draw about the inflation experience in the seven
countries?
d.
Which country’s inflation rate seems to be most variable? Can you offer any
explanation?
1.2.
a.
Using Table 1.3, plot the inflation rate of Canada, France, Germany, Italy, Japan,
and the United Kingdom against the United States inflation rate.
b.
Comment generally about the behavior of the inflation rate in the six countries
vis-à-vis the U.S. inflation rate.
c.
If you find that the six countries’ inflation rates move in the same direction as the
U.S. inflation rate, would that suggest that U.S. inflation “causes” inflation in the
other countries? Why or why not?
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