Real GDP in the U.S., 1979-83
annual rate
5100
5050
5000
4950
4900
4850
4800
4750
4700
4650
4600
79.1
79.3
79.2
80.1
79.4
80.3
80.2
81.1
80.4
81.3
81.2
82.1
81.4
Yea r/Quarter
Source: Bureau of Economic Analysis
82.3
82.2
83.1
82.4
83.3
83.2
83.4
Types of graphs
•Scatter diagram: A graph of the value of one
variable against the value of another variable
•Time-series graph: A graph that measures
time on the x-axis and the variable or
variables of interest on the y-axis.
•Cross-section graph: A graph that shows the
values of a variable for different groups in the
population at a point in time.
Disp osable Income and Consumptio n in th e U.S., 1959-99
7000
www.bea.gov
6000
1991
1999
5000
4000
3000
2000
Scatter diagram
1959
1000
1000
2000
3000
4000
5000
6000
Disp osable Income (billions o f 1996 dollar s)
7000
Alumni Giving Rates and Acceptance Rates
70
115 U.S. universities
60
Giving%
50
40
30
20
10
0
0
10
20
30
40
50
60
70
80
Acceptance%
Source: U.S. News and World Report
90
100
Recessions are
shaded
Median Income of Females
Full-Time, Year-Round
199 6 dolla rs
25000
24500
24000
23500
23000
22500
22000
21500
1978
1981
1984
1987
YEAR
Source: Economic Report of the President
1990
1993
1996
Median Income of Young Men, 1965-2002
(in 2000 dollars)
All men, Ages 22-34
Black men, Ages 22-34
$35,000
$30,000
$25,000
$20,000
01
99
20
97
19
95
19
93
19
91
19
19
89
19
87
19
85
19
83
19
81
79
19
77
19
75
19
19
73
19
71
19
69
19
67
19
65
$15,000
19
2000 dollars
$40,000
Year
Source: Authors’ calculations using the March Demographic
Files of the Current Population Survey
Unemployment rates in industrialized countries, May
2000
Austria
3.8
Belgium
10.1
Britain
5.7
Canada
6.6
COUNTRY
France
9.8
Germany
9.6
Italy
11.2
Japan
4.8
Spain
Crosssection
graph
Sweden
U.S.
2.0
14.1
4.7
4.1
4.0
Source: The Economist
6.0
8.0
10.0
12.0
Unemployment rate (percent)
14.0
16.0
Median Income of Full-Time Workers
1996 dollars
40000
35000
30000
25000
20000
15000
Males
10000
FEMALES
1978 1981 1984 1987 1990 1993 1996
Yea r
Source: Economic Report of the President
Marriage Rates for Women, Ages 22-34
(Income measured in 2000 dollars)
Source: Author's calculation from March CPS files
90
Percentage
80
70
60
50
40
1977
1982
1987
1992
1997
2001
Year
Income less than $9,999
Income greater than $35,000
Relationships among variables
•Variables X and Y have a positive or direct
relationship if, ceteris paribus, they move in
the same direction.
•Variables X and Y have a negative or inverse
relationship if, ceteris paribus, they move in
opposite directions.
•The relationship between X and Y is linear if
it can be described by a straight line.
Distance traveled in 5 hours
(miles)
300
200
0
40
60
Speed (MPH)
Recovery time (MINUTES)
30
20
0
100
200
400
Distance sprinted
(Yards)
Time partying (Hours)
5
0
5
Time studying
(Hours)
Linear graphs
Advertising
($1,000’s per Mo.)
0
2
3
6
7
11
12
Sales
($1,000’s per Mo.)
40
46
49
58
61
73
76
The Jewelry Mart
We want to describe the (causal)
relationship between sales and advertising
using a simple linear equation—because,
as it turns out, the relationship is linear
•Let Y denote sales per month (in
$1,000’s)
•Let X denote advertising per month (in
$1,000’s)
Thus we have:
Y = f(X)
Where Y is the dependent variable and X is the
independent (explanatory variable)
Sales ($1,000’s per mo.)
76
73
E
49
46
40
A
0
2 3
F
B
11 12
Now we want to
describe the
relationship by a linear
equation like this:
Y = a + bX
Where a is the intercept and b is the
slope coefficient.
Y
a>0
a=0
0
X
a<0
VerticalChange
Rise Y
Slope 


Horizontal Change Run X
Y
a
b>0
b=0
b<0
0
X
Sales ($1,000’s per mo.)
Now let’s compute the
slope of this line
76
73
E
49
46
40
A
F
B
Notice that a = $40
0
2 3
11 12
Moving from point A to
B (or from point E to
F), the vertical change
is $3 and the horizontal
change is $1. Thus our
slope is equal to 3
Rise
Y
3
Slope 

 3
Run
X
1
Interpretation: A $1,000 increase in monthly advertising
expenditures will result in a $3,000 increase in monthly
jewelry sales(and vice-versa), other things being equal.
Thus we have:
Y = 40 + 3X
Suppose that the management of
the Jewelry Mart have set a
monthly sales target of $64,000.
How much advertising is
necessary to meet the target?
Y = 40 + 3X
Hence:
64 = 40 + 3X
 24 = 3X
X=8
The Jewelry Mart needs to spend $8,000
per month on advertising to achieve the
sales target.