Some Techniques Of Economic Analysis
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Some Techniques of Economic Analysis
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Use of diagrams in economics
Effect of a rise in income Entertainment
Expenditure (£)
Food
O Individual’s income (£)
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Use of diagrams in economics • Representing statistics
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Use of diagrams in economics • Representing statistics – time-series data
Unemployment (millions)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1
1998
1999
2000
2001
2002
Unemployment (millions)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1
1998
1999
2000
2001
2002
Economic growth (%)
Unemployment (millions)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1
1998
1999
2000
2001
2002
Economic growth (%)
Unemployment (millions)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1
1998
1999
2000
2001
2002
SOME TECHNIQUES OF ECONOMIC ANALYSIS • 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
Percentage of total household income
60 50 40 30 20 10 0 Poorest 20%
Next 20%
Middle 20%
Next 20%
Richest 20%
Cross-section data: The distribution of UK pre-tax income
1977 42% 4% 10%
18% 26%
Cross-section data: The distribution of UK pre-tax income
2000/1
1977 42%
2%
51%
4%
7% 10% 15% 18% 26%
25%
SOME 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
SOME 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
Kg purchased per year
100
Using graphs with different scales: scale 1
75
50
25
Consumer income (£)
Kg purchased per year
0 5 000 10 000 15 000 20 000
10 25 45 70 100
0 0
10 000
20 000
30 000
40 000
Consumer income (£ per year)
50 000
60 000
Kg purchased per year
100
Using graphs with different scales: scale 1 Consumption of a foodstuff (per person)
75
50
25
Consumer income (£)
Kg purchased per year
0 5 000 10 000 15 000 20 000
10 25 45 70 100
0 0
10 000
20 000
30 000
40 000
Consumer income (£ per year)
50 000
60 000
Kg purchased per year
400
Using graphs with different scales: scale 2
300
200
Consumer income (£)
Kg purchased per year
0 5 000 10 000 15 000 20 000
10 25 45 70 100
100
0 0
5000
10 000
15 000
Consumer income (£ per year)
20 000
Kg purchased per year
400
Using graphs with different scales: scale 2
300
200
Consumer income (£)
Kg purchased per year
0 5 000 10 000 15 000 20 000
10 25 45 70 100 Consumption of a foodstuff (per person)
100
0 0
5000
10 000
15 000
Consumer income (£ per year)
20 000
SOME 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
SOME 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
SOME 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
SOME TECHNIQUES OF ECONOMIC ANALYSIS • 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
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Index numbers – constructing an index – using index numbers to measure percentage changes
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Index numbers – constructing an index – using index numbers to measure percentage changes – price index
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Index numbers – constructing an index – using index numbers to measure percentage changes – price index – use of weighted averages
Constructing a weighted average index
Constructing a weighted average index
Constructing a weighted average index
Constructing a weighted average index
Constructing a weighted average index
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Index numbers – constructing an index – using index numbers to measure percentage changes – price index – use of weighted averages
• Functional relationships
SOME 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
Graph of the saving function: S = 0.2Y
14
National income Total saving (£bn per year) (£bn per year)
12
a
Saving (£bn)
10 8 6
0 10 20 30 40 50
0 2 4 6 8 10
S = 0.2Y
4 2 0
a 0
10
20
30
National income (£bn)
40
50
Graph of the saving function: S = 0.2Y
14
National income Total saving (£bn per year) (£bn per year)
12
Saving (£bn)
10
b
8 6
0 10 20 30 40 50
0 2 4 6 8 10
S = 0.2Y
4
b
2 0 0
10
20
30
National income (£bn)
40
50
Graph of the saving function: S = 0.2Y
14
National income Total saving (£bn per year) (£bn per year)
12 10
Saving (£bn)
c 8 6
0 10 20 30 40 50
0 2 4 6 8 10
S = 0.2Y
c
4 2 0 0
10
20
30
National income (£bn)
40
50
Graph of the saving function: S = 0.2Y
14
National income Total saving (£bn per year) (£bn per year)
12
Saving (£bn)
10
d e f
8 6
0 10 20 30 40 50
0 2 4 6 8 10
S = 0.2Y
f
e d
4 2 0 0
10
20
30
National income (£bn)
40
50
y
Graph of the function: y = 4 + 2x 16 14
a
12 10 8
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
6 4
a
2 0 0
1
2
3
4
5
x
y
Graph of the function: y = 4 + 2x 16 14 12
b
10 8 6
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
b
4 2 0 0
1
2
3
4
5
x
y
Graph of the function: y = 4 + 2x 16 14 12
c
10 8
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
c
6 4 2 0 0
1
2
3
4
5
x
y
Graph of the function: y = 4 + 2x 16 14 12 10
d e f
8
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
f
e d
6 4 2 0 0
1
2
3
4
5
x
y
Graph of the function: y = 4 + 2x 16 14 12
c d
10 8
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
d c
2 1
6 4 2 0 0
1
2
3
4
5
x
SOME 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
y
Graph of the function: y = 4 + 10x – x2 30
25
20
15
a
10
a
5
x
y
0 1 2 3 4 5 6
4 13 20 25 28 29 28
0 0
1
2
3
4
5
6
x
y
Graph of the function: y = 4 + 10x – x2 30
25
20
15
b b
10
5
x
y
0 1 2 3 4 5 6
4 13 20 25 28 29 28
0 0
1
2
3
4
5
6
x
y
Graph of the function: y = 4 + 10x – x2 30
25
c
20
15
c
10
5
x
y
0 1 2 3 4 5 6
4 13 20 25 28 29 28
0 0
1
2
3
4
5
6
x
y
A total cost function: C = 20 + 5Q + Q2 110 100 90 80 70 60
a
50 40 30
a
20 10
Q
C
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
0 0
1
2
3
4
5
6
7
x
y
A total cost function: C = 20 + 5Q + Q2 110 100 90 80 70 60
Q
C
50
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
b
40
b
30 20 10 0 0
1
2
3
4
5
6
7
x
y
A total cost function: C = 20 + 5Q + Q2 110 100 90 80 70 60
Q
C
50
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
40
c
c
30 20 10 0 0
1
2
3
4
5
6
7
x
y
A total cost function: C = 20 + 5Q + Q2 110
h
100
g
90 80
f
70
e
60 50
a b c d e f g h
d
40
c
30
a
20
b
10
Q
C
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
0 0
1
2
3
4
5
6
7
x
y
A total cost function: C = 20 + 5Q + Q2 110 100 90 80
d
70 60 50
Q
C
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
11 1
d
40 30 20 10 0 0
1
2
3
4
5
6
7
x
DIFFERENTIATION • 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
Π
A total profit function: Π = –20 + 12Q – Q 2 20 15 10 5 0 0
1
2
3
4
5
6
7
8
9
-5 -10 -15 -20 -25
Q Π
0 1 -20 -9
2 0
3 4 5 6 7 8 7 12 15 16 15 12
9 10 7 0
10
Q
Π
A total profit function: Π = –20 + 12Q – Q 2 20
dΠ / dQ = 0
15 10 5 0 0
1
2
3
4
5
6
7
8
9
-5 -10 -15 -20 -25
Q Π
0 1 -20 -9
2 0
3 4 5 6 7 8 7 12 15 16 15 12
9 10 7 0
10
Q
DIFFERENTIATION • 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
When is good news really good? 12
15
11 10
Unemployment (%)
10 9
5
8 0
7 Unemployment
6
-5
5 4
-10 Q1
Q2
Q3
1989
Q4
Q1
Q2
Q3
1990
Q4
Q1
Q2
Q3
1991
Q4
Q1
Q2
1992
Q3
When is good news really good? 12
15
11
10
Unemployment (%)
10 9
5
8 0
7 Unemployment
6
-5
5 4
-10 Q1
Q2
Q3
1989
Q4
Q1
Q2
Q3
1990
Q4
Q1
Q2
Q3
1991
Q4
Q1
Q2
1992
Q3
Rate of change in unemployment (%)
Rate of change in unemployment
When is good news really good? 12
15
11
10
Unemployment (%)
10 9
5
8 0
7 Unemployment
6
-5
5 4
-10 Q1
Q2
Q3
1989
Q4
Q1
Q2
Q3
1990
Q4
Q1
Q2
Q3
1991
Q4
Q1
Q2
1992
Q3
Rate of change in unemployment (%)
Rate of change in unemployment
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Use of diagrams in economics
Effect of a rise in income Entertainment
Expenditure (£)
Food
O Individual’s income (£)
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Use of diagrams in economics • Representing statistics
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Use of diagrams in economics • Representing statistics – time-series data
Unemployment (millions)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1
1998
1999
2000
2001
2002
Unemployment (millions)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1
1998
1999
2000
2001
2002
Economic growth (%)
Unemployment (millions)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1
1998
1999
2000
2001
2002
Economic growth (%)
Unemployment (millions)
UK Unemployment and economic growth: 1998 Q1 – 2002 Q1
1998
1999
2000
2001
2002
SOME TECHNIQUES OF ECONOMIC ANALYSIS • 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
Percentage of total household income
60 50 40 30 20 10 0 Poorest 20%
Next 20%
Middle 20%
Next 20%
Richest 20%
Cross-section data: The distribution of UK pre-tax income
1977 42% 4% 10%
18% 26%
Cross-section data: The distribution of UK pre-tax income
2000/1
1977 42%
2%
51%
4%
7% 10% 15% 18% 26%
25%
SOME 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
SOME 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
Kg purchased per year
100
Using graphs with different scales: scale 1
75
50
25
Consumer income (£)
Kg purchased per year
0 5 000 10 000 15 000 20 000
10 25 45 70 100
0 0
10 000
20 000
30 000
40 000
Consumer income (£ per year)
50 000
60 000
Kg purchased per year
100
Using graphs with different scales: scale 1 Consumption of a foodstuff (per person)
75
50
25
Consumer income (£)
Kg purchased per year
0 5 000 10 000 15 000 20 000
10 25 45 70 100
0 0
10 000
20 000
30 000
40 000
Consumer income (£ per year)
50 000
60 000
Kg purchased per year
400
Using graphs with different scales: scale 2
300
200
Consumer income (£)
Kg purchased per year
0 5 000 10 000 15 000 20 000
10 25 45 70 100
100
0 0
5000
10 000
15 000
Consumer income (£ per year)
20 000
Kg purchased per year
400
Using graphs with different scales: scale 2
300
200
Consumer income (£)
Kg purchased per year
0 5 000 10 000 15 000 20 000
10 25 45 70 100 Consumption of a foodstuff (per person)
100
0 0
5000
10 000
15 000
Consumer income (£ per year)
20 000
SOME 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
SOME 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
SOME 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
SOME TECHNIQUES OF ECONOMIC ANALYSIS • 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
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Index numbers – constructing an index – using index numbers to measure percentage changes
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Index numbers – constructing an index – using index numbers to measure percentage changes – price index
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Index numbers – constructing an index – using index numbers to measure percentage changes – price index – use of weighted averages
Constructing a weighted average index
Constructing a weighted average index
Constructing a weighted average index
Constructing a weighted average index
Constructing a weighted average index
SOME TECHNIQUES OF ECONOMIC ANALYSIS • Index numbers – constructing an index – using index numbers to measure percentage changes – price index – use of weighted averages
• Functional relationships
SOME 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
Graph of the saving function: S = 0.2Y
14
National income Total saving (£bn per year) (£bn per year)
12
a
Saving (£bn)
10 8 6
0 10 20 30 40 50
0 2 4 6 8 10
S = 0.2Y
4 2 0
a 0
10
20
30
National income (£bn)
40
50
Graph of the saving function: S = 0.2Y
14
National income Total saving (£bn per year) (£bn per year)
12
Saving (£bn)
10
b
8 6
0 10 20 30 40 50
0 2 4 6 8 10
S = 0.2Y
4
b
2 0 0
10
20
30
National income (£bn)
40
50
Graph of the saving function: S = 0.2Y
14
National income Total saving (£bn per year) (£bn per year)
12 10
Saving (£bn)
c 8 6
0 10 20 30 40 50
0 2 4 6 8 10
S = 0.2Y
c
4 2 0 0
10
20
30
National income (£bn)
40
50
Graph of the saving function: S = 0.2Y
14
National income Total saving (£bn per year) (£bn per year)
12
Saving (£bn)
10
d e f
8 6
0 10 20 30 40 50
0 2 4 6 8 10
S = 0.2Y
f
e d
4 2 0 0
10
20
30
National income (£bn)
40
50
y
Graph of the function: y = 4 + 2x 16 14
a
12 10 8
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
6 4
a
2 0 0
1
2
3
4
5
x
y
Graph of the function: y = 4 + 2x 16 14 12
b
10 8 6
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
b
4 2 0 0
1
2
3
4
5
x
y
Graph of the function: y = 4 + 2x 16 14 12
c
10 8
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
c
6 4 2 0 0
1
2
3
4
5
x
y
Graph of the function: y = 4 + 2x 16 14 12 10
d e f
8
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
f
e d
6 4 2 0 0
1
2
3
4
5
x
y
Graph of the function: y = 4 + 2x 16 14 12
c d
10 8
x
y
0 1 2 3 4 5
4 6 8 10 12 14
Y = 4 + 2x
d c
2 1
6 4 2 0 0
1
2
3
4
5
x
SOME 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
y
Graph of the function: y = 4 + 10x – x2 30
25
20
15
a
10
a
5
x
y
0 1 2 3 4 5 6
4 13 20 25 28 29 28
0 0
1
2
3
4
5
6
x
y
Graph of the function: y = 4 + 10x – x2 30
25
20
15
b b
10
5
x
y
0 1 2 3 4 5 6
4 13 20 25 28 29 28
0 0
1
2
3
4
5
6
x
y
Graph of the function: y = 4 + 10x – x2 30
25
c
20
15
c
10
5
x
y
0 1 2 3 4 5 6
4 13 20 25 28 29 28
0 0
1
2
3
4
5
6
x
y
A total cost function: C = 20 + 5Q + Q2 110 100 90 80 70 60
a
50 40 30
a
20 10
Q
C
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
0 0
1
2
3
4
5
6
7
x
y
A total cost function: C = 20 + 5Q + Q2 110 100 90 80 70 60
Q
C
50
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
b
40
b
30 20 10 0 0
1
2
3
4
5
6
7
x
y
A total cost function: C = 20 + 5Q + Q2 110 100 90 80 70 60
Q
C
50
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
40
c
c
30 20 10 0 0
1
2
3
4
5
6
7
x
y
A total cost function: C = 20 + 5Q + Q2 110
h
100
g
90 80
f
70
e
60 50
a b c d e f g h
d
40
c
30
a
20
b
10
Q
C
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
0 0
1
2
3
4
5
6
7
x
y
A total cost function: C = 20 + 5Q + Q2 110 100 90 80
d
70 60 50
Q
C
0 1 2 3 4 5 6 7
20 26 34 44 56 70 86 104
11 1
d
40 30 20 10 0 0
1
2
3
4
5
6
7
x
DIFFERENTIATION • 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
Π
A total profit function: Π = –20 + 12Q – Q 2 20 15 10 5 0 0
1
2
3
4
5
6
7
8
9
-5 -10 -15 -20 -25
Q Π
0 1 -20 -9
2 0
3 4 5 6 7 8 7 12 15 16 15 12
9 10 7 0
10
Q
Π
A total profit function: Π = –20 + 12Q – Q 2 20
dΠ / dQ = 0
15 10 5 0 0
1
2
3
4
5
6
7
8
9
-5 -10 -15 -20 -25
Q Π
0 1 -20 -9
2 0
3 4 5 6 7 8 7 12 15 16 15 12
9 10 7 0
10
Q
DIFFERENTIATION • 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
When is good news really good? 12
15
11 10
Unemployment (%)
10 9
5
8 0
7 Unemployment
6
-5
5 4
-10 Q1
Q2
Q3
1989
Q4
Q1
Q2
Q3
1990
Q4
Q1
Q2
Q3
1991
Q4
Q1
Q2
1992
Q3
When is good news really good? 12
15
11
10
Unemployment (%)
10 9
5
8 0
7 Unemployment
6
-5
5 4
-10 Q1
Q2
Q3
1989
Q4
Q1
Q2
Q3
1990
Q4
Q1
Q2
Q3
1991
Q4
Q1
Q2
1992
Q3
Rate of change in unemployment (%)
Rate of change in unemployment
When is good news really good? 12
15
11
10
Unemployment (%)
10 9
5
8 0
7 Unemployment
6
-5
5 4
-10 Q1
Q2
Q3
1989
Q4
Q1
Q2
Q3
1990
Q4
Q1
Q2
Q3
1991
Q4
Q1
Q2
1992
Q3
Rate of change in unemployment (%)
Rate of change in unemployment
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