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Some Techniques ofSome Techniques ofEconomic AnalysisEconomic Analysis
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics• Use of diagrams in economics
O
Entertainment
Exp
endi
ture
(£)
Individual’s income (£)
Food
Effect of a rise in incomeEffect of a rise in income
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics
• Representing statistics
• Use of diagrams in economics
• Representing statistics
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics
• Representing statistics– time-series data
• Use of diagrams in economics
• Representing statistics– time-series data
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1UK Unemployment and economic growth: 1998 Q1 – 2002 Q1U
ne
mp
loym
en
t (m
illio
ns)
1998 1999 2000 2001 2002
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1UK Unemployment and economic growth: 1998 Q1 – 2002 Q1U
ne
mp
loym
en
t (m
illio
ns)
1998 1999 2000 2001 2002
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1UK Unemployment and economic growth: 1998 Q1 – 2002 Q1U
ne
mp
loym
en
t (m
illio
ns)
1998 1999 2000 2001 2002
Ec
on
om
ic g
row
th (%
)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1UK Unemployment and economic growth: 1998 Q1 – 2002 Q1U
ne
mp
loym
en
t (m
illio
ns)
1998 1999 2000 2001 2002
Ec
on
om
ic g
row
th (%
)
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
Cross-section data:The distribution of UK pre-tax income
Cross-section data:The distribution of UK pre-tax income
0
10
20
30
40
50
60
Poorest 20% Next 20% Middle 20% Next 20% Richest 20%
Per
cen
tag
e o
f to
tal
ho
use
ho
ld i
nco
me
Cross-section data:The distribution of UK pre-tax income
Cross-section data:The distribution of UK pre-tax income
Cross-section data:The distribution of UK pre-tax income
Cross-section data:The distribution of UK pre-tax income
1977
42%42%
4%4%
10%10%
18%18%
26%26%
Cross-section data:The distribution of UK pre-tax income
Cross-section data:The distribution of UK pre-tax income
2000/1
15%15%
7%7%
2%2%51%51%
25%25%
1977
42%42%
4%4%
10%10%
18%18%
26%26%
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
– graphical presentation
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
– graphical presentation
0
25
50
75
100
0 10 000 20 000 30 000 40 000 50 000 60 000
Kg
pu
rch
ase
d p
er
yea
r
Consumer income (£ per year)
ConsumerConsumerincome (£)income (£)
Kg purchasedKg purchasedper yearper year
05 000
10 00015 00020 000
10254570
100
Using graphs with different scales: scale 1Using graphs with different scales: scale 1
0
25
50
75
100
0 10 000 20 000 30 000 40 000 50 000 60 000
Consumption of a foodstuff(per person)
Kg
pu
rch
ase
d p
er
yea
r
Consumer income (£ per year)
ConsumerConsumerincome (£)income (£)
Kg purchasedKg purchasedper yearper year
05 000
10 00015 00020 000
10254570
100
Using graphs with different scales: scale 1Using graphs with different scales: scale 1
0
100
200
300
400
0 5000 10 000 15 000 20 000
Kg
pu
rch
ase
d p
er
yea
r
Consumer income (£ per year)
ConsumerConsumerincome (£)income (£)
05 000
10 00015 00020 000
Kg purchasedKg purchasedper yearper year
10254570
100
Using graphs with different scales: scale 2Using graphs with different scales: scale 2
0
100
200
300
400
0 5000 10 000 15 000 20 000
Kg
pu
rch
ase
d p
er
yea
r
Consumer income (£ per year)
Consumption of a foodstuff(per person)
ConsumerConsumerincome (£)income (£)
05 000
10 00015 00020 000
Kg purchasedKg purchasedper yearper year
10254570
100
Using graphs with different scales: scale 2Using graphs with different scales: scale 2
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
– graphical presentation
– absolute and proportional values
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
– graphical presentation
– absolute and proportional values
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
– graphical presentation
– absolute and proportional values
– questions of distribution
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
– graphical presentation
– absolute and proportional values
– questions of distribution
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
– graphical presentation
– absolute and proportional values
– questions of distribution
– real and nominal values
• Use of diagrams in economics
• Representing statistics– time-series data
– cross-section data
• Getting a true picture from statistics– selective use of data
– graphical presentation
– absolute and proportional values
– questions of distribution
– real and nominal values
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Index numbers– constructing an index
• Index numbers– constructing an index
Constructing an index:UK manufacturing and service industry output: 1995 = 100
Constructing an index:UK manufacturing and service industry output: 1995 = 100
Constructing an index:UK manufacturing and service industry output: 1995 = 100
Constructing an index:UK manufacturing and service industry output: 1995 = 100
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Index numbers– constructing an index – using index numbers to measure
percentage changes
• Index numbers– constructing an index – using index numbers to measure
percentage changes
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index– use of weighted averages
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index– use of weighted averages
Constructing a weighted average indexConstructing a weighted average index
Constructing a weighted average indexConstructing a weighted average index
Constructing a weighted average indexConstructing a weighted average index
Constructing a weighted average indexConstructing a weighted average index
Constructing a weighted average indexConstructing a weighted average index
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index– use of weighted averages
• Functional relationships
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index– use of weighted averages
• Functional relationships
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index– use of weighted averages
• Functional relationships– simple linear functions
• as a table• as a graph• as an equation
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index– use of weighted averages
• Functional relationships– simple linear functions
• as a table• as a graph• as an equation
Graph of the saving function: S = 0.2YGraph of the saving function: S = 0.2Y
National income(£bn per year)
Total saving(£bn per year)
01020304050
02468
10
Sa
vin
g (£
bn)
National income (£bn)
a
a
S = 0.2Y
0
2
4
6
8
10
12
14
0 10 20 30 40 50
National income(£bn per year)
Total saving(£bn per year)
01020304050
02468
10
Sa
vin
g (£
bn)
National income (£bn)
b
b
S = 0.2Y
0
2
4
6
8
10
12
14
0 10 20 30 40 50
Graph of the saving function: S = 0.2YGraph of the saving function: S = 0.2Y
National income(£bn per year)
Total saving(£bn per year)
01020304050
02468
10
Sa
vin
g (£
bn)
National income (£bn)
c
c
S = 0.2Y
0
2
4
6
8
10
12
14
0 10 20 30 40 50
Graph of the saving function: S = 0.2YGraph of the saving function: S = 0.2Y
National income(£bn per year)
Total saving(£bn per year)
01020304050
02468
10
S = 0.2Y
Sa
vin
g (£
bn)
National income (£bn)
def d
e
f
0
2
4
6
8
10
12
14
0 10 20 30 40 50
Graph of the saving function: S = 0.2YGraph of the saving function: S = 0.2Y
0
2
4
6
8
10
12
14
16
0 1 2 3 4 5
x y
012345
a
a
Y = 4 + 2x 4 6 8101214
y
x
Graph of the function: y = 4 + 2xGraph of the function: y = 4 + 2x
0
2
4
6
8
10
12
14
16
0 1 2 3 4 5
x y
012345
b
b
4 6 8101214
y
x
Y = 4 + 2x
Graph of the function: y = 4 + 2xGraph of the function: y = 4 + 2x
0
2
4
6
8
10
12
14
16
0 1 2 3 4 5
x y
012345
c
c
4 6 8101214
y
x
Y = 4 + 2x
Graph of the function: y = 4 + 2xGraph of the function: y = 4 + 2x
0
2
4
6
8
10
12
14
16
0 1 2 3 4 5
x y
012345
def
d
4 6 8101214
y
x
e
fY = 4 + 2x
Graph of the function: y = 4 + 2xGraph of the function: y = 4 + 2x
0
2
4
6
8
10
12
14
16
0 1 2 3 4 5
x y
012345
4 6 8101214
y
x
1
cd
c
d
2
Y = 4 + 2x
Graph of the function: y = 4 + 2xGraph of the function: y = 4 + 2x
SOME TECHNIQUES OF ECONOMIC ANALYSISSOME TECHNIQUES OF ECONOMIC ANALYSIS
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index– use of weighted averages
• Functional relationships– simple linear functions
• as a table• as a graph• as an equation
– non-linear functions
• Index numbers– constructing an index – using index numbers to measure
percentage changes– price index– use of weighted averages
• Functional relationships– simple linear functions
• as a table• as a graph• as an equation
– non-linear functions
0
5
10
15
20
25
30
0 1 2 3 4 5 6
x y
0123456
a
a
4132025282928
y
x
Graph of the function: y = 4 + 10x – x2Graph of the function: y = 4 + 10x – x2
0
5
10
15
20
25
30
0 1 2 3 4 5 6
y
x
x y
0123456
b 4132025282928
b
Graph of the function: y = 4 + 10x – x2Graph of the function: y = 4 + 10x – x2
0
5
10
15
20
25
30
0 1 2 3 4 5 6
y
x
x y
0123456
c
4132025282928
c
Graph of the function: y = 4 + 10x – x2Graph of the function: y = 4 + 10x – x2
0
10
20
30
40
50
60
70
80
90
100
110
0 1 2 3 4 5 6 7
Q C
01234567
a
a
20263444567086
104
y
x
A total cost function: C = 20 + 5Q + Q2A total cost function: C = 20 + 5Q + Q2
0
10
20
30
40
50
60
70
80
90
100
110
0 1 2 3 4 5 6 7
b
y
x
Q C
01234567
b20263444567086
104
A total cost function: C = 20 + 5Q + Q2A total cost function: C = 20 + 5Q + Q2
0
10
20
30
40
50
60
70
80
90
100
110
0 1 2 3 4 5 6 7
c
y
x
Q C
01234567
c
20263444567086
104
A total cost function: C = 20 + 5Q + Q2A total cost function: C = 20 + 5Q + Q2
0
10
20
30
40
50
60
70
80
90
100
110
0 1 2 3 4 5 6 7
y
x
Q C
01234567
abcdefgh
20263444567086
104
cb
d
a
e
f
g
hA total cost function: C = 20 + 5Q + Q2A total cost function: C = 20 + 5Q + Q2
Q C
01234567
d
d
20263444567086
104
y
x
1
11
0
10
20
30
40
50
60
70
80
90
100
110
0 1 2 3 4 5 6 7
A total cost function: C = 20 + 5Q + Q2A total cost function: C = 20 + 5Q + Q2
DIFFERENTIATIONDIFFERENTIATION
• Elementary differentiation
– the rules
• Finding the maximum or minimum point of a curve
– differentiating the equation
– setting it equal to zero
• Is it a maximum or a minimum?
– differentiating a second time
• Elementary differentiation
– the rules
• Finding the maximum or minimum point of a curve
– differentiating the equation
– setting it equal to zero
• Is it a maximum or a minimum?
– differentiating a second time
-25
-20
-15
-10
-5
0
5
10
15
20
0 1 2 3 4 5 6 7 8 9 10
Q 0 1 2 3 4 5 6 7 8 9 10 -20 -9 0 7 12 15 16 15 12 7 0
A total profit function:= –20 + 12Q – Q 2A total profit function:= –20 + 12Q – Q 2
Q
Q 0 1 2 3 4 5 6 7 8 9 10 -20 -9 0 7 12 15 16 15 12 7 0
d / dQ = 0
Q
-25
-20
-15
-10
-5
0
5
10
15
20
0 1 2 3 4 5 6 7 8 9 10
A total profit function:= –20 + 12Q – Q 2A total profit function:= –20 + 12Q – Q 2
DIFFERENTIATIONDIFFERENTIATION
• Elementary differentiation
– the rules
• Finding the maximum or minimum point of a curve
– differentiating the equation
– setting it equal to zero
• Is it a maximum or a minimum?
– differentiating a second time
– the second derivative test
• Elementary differentiation
– the rules
• Finding the maximum or minimum point of a curve
– differentiating the equation
– setting it equal to zero
• Is it a maximum or a minimum?
– differentiating a second time
– the second derivative test
Un
em
plo
yme
nt (
%)
Unemployment
1989 1990 1991 1992
4
5
6
7
8
9
10
11
12
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3-10
-5
0
5
10
15When is good news really good?When is good news really good?
Un
em
plo
yme
nt (
%)
Ra
te of ch
ang
e in un
emplo
ymen
t (%)
Unemployment
Rate of changein unemployment
1989 1990 1991 1992
4
5
6
7
8
9
10
11
12
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3-10
-5
0
5
10
15When is good news really good?When is good news really good?
Un
em
plo
yme
nt (
%)
Ra
te of ch
ang
e in un
emplo
ymen
t (%)
Unemployment
Rate of changein unemployment
1989 1990 1991 1992
4
5
6
7
8
9
10
11
12
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3-10
-5
0
5
10
15When is good news really good?When is good news really good?