THEMES AND CAPSTONE UNITS
17: History, instability, and growth
18: Global economy
21: Innovation
22: Politics and policy
UNIT 13
ECONOMIC FLUCTUATIONS
AND UNEMPLOYMENT
HOW ECONOMIES FLUCTUATE BETWEEN BOOMS
AND RECESSIONS AS THEY ARE CONTINUOUSLY
HIT BY GOOD AND BAD SHOCKS
• Fluctuations in the total output of a nation (GDP) affect unemploy-
ment, and unemployment is a serious hardship for people.
• Economists measure the size of the economy using the national
accounts: these measure economic fluctuations and growth.
• Households respond to shocks by saving, borrowing, and sharing to
smooth their consumption of goods and services.
• Due to limits on people’s ability to borrow (credit constraints) and their
weakness of will, these strategies are not sufficient to eliminate shocks
to their consumption.
• Investment spending by firms (on capital goods) and households (on new
housing) fluctuates more than consumption.
Losing your job hurts. It causes stress. Following the global financial crisis
in 2008, unemployment went up, as did the number of searches for
antistress medication on Google. By plotting the increase in search
intensity against the increase in the unemployment rate in the different
states of the US (Figure 13.1), we see that states that had a larger increase in
the unemployment rate between 2007 and 2010, also had a larger increase
in searches for antistress medication. This suggests that higher unemploy-
ment is related to higher stress. We say the two are correlated.
The upward-sloping line summarizes the data by finding the line that
best fits the scatter of points. This is called a line of best fit or a linear
regression line. When a line of best fit is upward sloping, it means that
higher values of the variable on the horizontal axis (in this case the rise in
unemployment) are associated with higher values of the variable on the ver-
tical axis (in this case, the increase in Google searches for antistress
medication).
An impending storm
545
reverse causality A two-way causal
relationship in which A affects B
and B also affects A.
linear regression line The best-
fitting line through a set of data.
Many kinds of evidence show that being unemployed or fearing
unemployment is a major source of unhappiness for people. It ranks
alongside major disease and divorce as a stressful life event.
Economists have estimated that becoming unemployed produces more
unhappiness than is measured solely by the loss of earnings from being out
of work. Economists Andrew Clark and Andrew Oswald have measured
the effect of important life events on how happy people claim to be when
they are asked. In 2002, they calculated that the average British person
would need to be compensated by £15,000 ($22,500) per month after losing
their job in order to be as happy as they were when they were employed.
This is considerably larger than the loss of earnings (which at the time were
£2,000 per month on average).
The compensation needed to restore wellbeing is an enormous amount,
much greater than the monetary loss associated with a spell of unemploy-
ment. The reason is that unemployment dramatically reduces self-esteem
and leads to a much greater reduction in happiness. As we saw in Unit 1,
wellbeing depends on more than just income.
Correlation may not be causation
Can we draw the conclusion from the data in Figure 13.1 that higher
unemployment causes higher stress? Maybe we have it the wrong way
round, and actually Google searches cause unemployment. Economists call
this reverse causality. We can rule this out because it is unlikely that indi-
vidual Google searches on the side effects of antidepressants could cause an
increase in unemployment at the state level. Yet there are other possible
explanations for this pattern.
A natural disaster like Hurricane Katrina (https://tinyco.re/7393966) in
the US state of Louisiana in 2005 could have triggered an increase in both
stress and unemployment. This is an example where a third factor—in this
case, the weather—might account for the positive correlation between
searches for antidepressants and unemployment. It warns us to be careful in
concluding that an observed correlation implies a causal relationship
between variables.
Andrew E. Clark and Andrew J.
Oswald. 2002. ‘A Simple Statistical
Method for Measuring How Life
Events Affect Happiness’
(https://tinyco.re/7872100). Inter-
national Journal of Epidemiology
31 (6): pp. 1139–1144.
The Spurious Correlations website
shows how dangerous it is to draw
a conclusion from correlation.
James Fletcher. 2014. ‘Spurious
Correlations: Margarine Linked to
Divorce?’ (https://tinyco.re/
6825314). BBC News.
South Dakota
North Dakota
Virginia
California
Nevada
Connecticut
Kentucky
Idaho
Line of best fit
0
1
2
3
4
5
6
7
8
9
10
−5 −4 −3 −2 −1 0 1 2 3 4 5
Change in Google Stress Index (2007–2010)
Ch
an
ge
in
un
em
pl
oy
m
en
tr
at
e
(%
,2
00
7–
20
10
)
Figure 13.1 Changes in unemployment and wellbeing during the financial crisis:
Evidence from the US states (2007–2010).
View this data at OWiD https://tinyco.re/
8246287
Yann Algan, Elizabeth Beasley, Florian
Guyot, and Fabrice Murtin. 2014. ‘Big
Data Measures of Human Well-Being:
Evidence from a Google Stress Index on
US States’. Sciences Po Working Paper.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
546
correlation A statistical association
in which knowing the value of one
variable provides information on
the likely value of the other, for
example high values of one
variable being commonly observed
along with high values of the other
variable. It can be positive or neg-
ative (it is negative when high
values of one variable are observed
with low values of the other). It
does not mean that there is a
causal relationship between the
variables. See also: causality, cor-
relation coefficient.
logarithmic scale A way of measuring a quantity based on the
logarithm function, f(x) = log(x). The logarithm function
converts a ratio to a difference: log (a/b) = log a – log b. This is
very useful for working with growth rates. For instance, if
national income doubles from 50 to 100 in a poor country and
from 1,000 to 2,000 in a rich country, the absolute difference in
the first case is 50 and in the second 1,000, but log(100) –
log(50) = 0.693, and log(2,000) – log(1,000) = 0.693. The ratio in
each case is 2 and log(2) = 0.693.
To establish a causal relationship between variables, economists devise
experiments (https://tinyco.re/8046664) (like those in Unit 4) or exploit
natural experiments (like the comparison of East and West Germany in
Unit 1 or the estimate of the size of employment rents in Unit 6).
In Exercise 13.1, we show you a tool that you can use to examine your
ideas about how the overall wellbeing in a country can be compared with
wellbeing in other countries. What is your recipe for a better life in your
country? How important do you think unemployment is? Do other things
matter more or just as much—for example, good education, clean air, a high
level of trust among citizens, high income, or not too much inequality?
In this unit, we learn about why economies go through upswings, during
which unemployment falls, and downswings, during which it rises. We
focus on the total spending (by households, firms, the government and
people outside the home economy) on the goods and services produced by
people employed in the home economy.
EXERCISE 13.1 THE OECD BETTER LIFE INDEX
The Better Life Index (https://tinyco.re/2887644), was created by the
Organization for Economic Cooperation and Development (OECD). It lets
you design a measure of the quality of life in a country by deciding how
much weight to put on each component of the index.
1. Should a better life index include the following elements: income,
housing, jobs, community, education, environment, civic engagement,
health, life satisfaction, safety, and work-life balance? For each of these
elements, explain why or why not.
2. Use the Better Life Index tool to create your own better life index for
the country where you are living. How does this country score on the
topics that are important to you?
3. Rank the countries in the database using your own newly created
better life index, and compare it with a ranking based exclusively on
income.
4. For both of these indices, choose two countries with contrasting
rankings and briefly suggest why this may be the case.
••13.1 GROWTH AND FLUCTUATIONS
Economies in which the capitalist revolution has taken place have grown
over the long run, as illustrated in the hockey stick charts for GDP per
capita in Unit 1.
But growth has not been smooth. Figure 13.2
shows the case of the British economy, for which
data over a long period is available. The first chart
shows GDP per person (per capita) of the popula-
tion from 1875. This is part of the hockey stick
graph from Unit 1. The chart next to it shows the
same data but plots the natural logarithm (‘log’)
of GDP per capita. This is a way of presenting the
ratio scale that we used in Unit 1.
The OECD is an international
organization based in Paris, with 35
member countries, most with high
levels of GDP per capita. It was
formed in 1948 to facilitate
postwar reconstruction in Western
Europe. The OECD is an important
source of internationally
comparable statistics on economic
and social performance.
13.1 GROWTH AND FLUCTUATIONS
547
gross domestic product (GDP) A measure of the market value
of the output of final goods and services in the economy in a
given period. Output of intermediate goods that are inputs to
final production is excluded to prevent double counting.
See the Einstein at the end of this section to explore the relationship
between plotting the log of a variable and the use of a ratio scale on the ver-
tical axis.
By looking at the graph in levels of GDP per capita in the left-hand panel
of Figure 13.2, it is hard to tell whether the economy was growing at a
steady pace, accelerating, or decelerating over time. Transforming the data
into natural logs in the right-hand panel allows us to answer the question
about the pace of growth more easily. For example, for the period after the
First World War, a straight line from 1921 to 2019 fits the data well. For a
graph in which the vertical axis represents the log of GDP per capita, the
slope of the line (the dashed black line) represents the average annual
growth rate of the series. Immediately we notice that growth was steady
from 1921 to 2019 (with a little uptick during the Second World War). You
can see that a line drawn through the log series from 1875 to 1914 is flatter
than the line from 1921, indicating that the growth rate was lower.
We will explore long-run growth further in
Units 16 and 17. In this unit we focus on
fluctuations. These are the deviations from the
dotted black line showing the long-run growth
rate in Figure 13.2.
The top panel of Figure 13.3 plots the annual
growth rate of UK GDP between 1875 and 2020.
Since we want to focus on the size of the economy and how it changes from
year to year, we will examine total GDP rather than GDP per capita.
0
5,000
10,000
15,000
20,000
25,000
18
75
18
90
19
05
19
20
19
35
19
50
19
65
19
80
19
95
20
10
20
25
Year
Re
al
G
D
P
pe
rc
ap
ita
(£
,f
ac
to
rc
os
t)
8
8.5
9
9.5
10
10.5
18
75
18
90
19
05
19
20
19
35
19
50
19
65
19
80
19
95
20
10
20
25
Year
Lo
g
of
re
al
G
D
P
pe
rc
ap
ita
Figure 13.2 UK GDP per capita (1875–2014).
See more https://tinyco.re/4301124
See more https://tinyco.re/4309811
Ryland Thomas and Nicholas Dimsdale.
(2017). ‘A Millennium of UK Data’
(https://tinyco.re/0223548). Bank of
England OBRA dataset; UK Office for
National Statistics. (2021). ‘Gross
domestic product (Average) per head,
CVM market prices: SA’
(https://tinyco.re/9074553).
1. Annual growth rate after 1921
In the right-hand panel, the slope of the
line (the dashed black line) represents
the average annual growth rate from
1921 to 2020. It was 2.0% per annum.
We can see that growth was steady.
2. Annual growth rate 1875 to 1914
A line drawn through the log series
from 1875 to 1914 is flatter than the
line from 1921. The average growth
rate in that period was only 0.9% per
annum.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
548
Business cycle
peak
Business cycle
trough
−12
−10
−8
−6
−4
−2
0
2
4
6
8
10
12
G
D
P
gr
ow
th
(%
)
1918
End of WW1
1929
Start of
the Great
Depression
2008
Start of
the global
financial
crisis
0
2
4
6
8
10
12
14
16
18
75
18
80
18
85
18
90
18
95
19
00
19
05
19
10
19
15
19
20
19
25
19
30
19
35
19
40
19
45
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
Year
U
ne
m
pl
oy
m
en
tr
at
e
(%
)
Figure 13.3 UK GDP growth and unemployment rate (1875–2020).
See more https://tinyco.re/5022375
Ryland Thomas and Nicholas Dimsdale.
(2017). ‘A Millennium of UK Data’
(https://tinyco.re/0223548). Bank of
England OBRA dataset; UK Office for
National Statistics. (2021). UK Economic
Accounts time series (https://tinyco.re/
3387553).
1. UK GDP growth and unemployment
The panels show UK GDP growth and
the unemployment rate for the period
1875–2020.
2. Peaks and troughs
The arrows highlight the peak and
trough of a business cycle during the
late 1980s and early 1990s.
3. The global financial crisis
In the twenty-first century, the 2008 fin-
ancial crisis followed a period in which
fluctuations were limited.
4. Downturns and unemployment
We can see that downturns in the busi-
ness cycle are associated with rising
unemployment. In the business cycle of
the early 1990s, unemployment
continued to rise for a time after the
growth rate began to rise.
13.1 GROWTH AND FLUCTUATIONS
549
recession The US National Bureau of Economic Research
defines it as a period when output is declining. It is over once
the economy begins to grow again. An alternative definition is
a period when the level of output is below its normal level,
even if the economy is growing. It is not over until output has
grown enough to get back to normal. The latter definition has
the problem that the ‘normal’ level is subjective.
business cycle Alternating periods
of faster and slower (or even neg-
ative) growth rates. The economy
goes from boom to recession and
back to boom. See also: short-run
equilibrium.
It is clear from the ups and downs of the series
in Figure 13.3 that economic growth is not a
smooth process. We often hear about economies
going through a boom or a recession as growth
swings from positive to negative, but there is no
standard definition of these words. The National
Bureau of Economic Research (NBER)
(https://tinyco.re/3195217), a US organization,
defines it like this: ‘During a recession, a signi-
ficant decline in economic activity spreads across
the economy and can last from a few months to more than a year.’ An
alternative definition says that an economy is in recession during a period
when the level of output is below its normal level. So we have two defini-
tions of recession:
• NBER definition: output is declining. A recession is over once the eco-
nomy begins to grow again.
• Alternative definition: the level of output is below its normal level, even if
the economy is growing. A recession is not over until output has grown
enough to get back to normal.
There is a practical problem with the second definition: it is a matter of
judgement, and sometimes controversy, over what an economy’s normal
output would be (we return to this issue in later units, where we will see
that ‘normal output’ is often defined as that consistent with stable inflation).
The movement from boom, to recession, and back to boom is known as
the business cycle. In Figure 13.3 you will notice that in addition to the
yearly change in GDP, in which recessions measured by negative growth
seem to happen about twice every 10 years, there are less frequent episodes
of much larger fluctuations in output. In the twentieth century, the big
downward spikes coincided with the end of the First and Second World
Wars, and with the economic crisis of the Great Depression. In the twenty-
first century, the global financial crisis followed a period in which
fluctuations were limited.
In the lower part of Figure 13.3 you can see that the unemployment rate
varies over the business cycle. During the Great Depression, unemployment
in the UK was higher than it had ever been, and it was particularly low
during the World Wars.
EXERCISE 13.2 DEFINING RECESSIONS
A recession can be defined as a period when output is declining, or as a
period when the level of output is below normal (sometimes referred to as
its ‘potential level’). Look at this article (https://tinyco.re/2305833),
especially Figures 5, 6, and 7, to find out more.
1. Consider a country that has been producing a lot of oil and suppose
that from one year to the next its oil wells run out. The country will be
poorer than previously. According to the two definitions above, is it in a
recession?
2. Does knowing whether a country is in recession make a difference to
policymakers whose job it is to manage the economy?
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
550
QUESTION 13.1 CHOOSE THE CORRECT ANSWER(S)
The following is the graph of the natural log of UK real GDP per capita
between 1875 and 2020:
y = 0.0156x −21.4576
R2 = 0.9445
7.5
8.0
8.5
9.0
9.5
10.0
10.5
11.0
18
75
18
90
19
05
19
20
19
35
19
50
19
65
19
80
19
95
20
10
Year
Lo
g
of
re
al
G
D
P
pe
rc
ap
ita
Based on this information, which of the following statements is
correct?
The graph shows that real GDP per capita in the UK in 1955 was
about £8,000.
The slope of the best-fit straight line is the average annual growth
rate.
The graph shows that the average growth rate was lower in the
decades after 1921 than in the decades before 1918.
The graph of real GDP per capita plotted using a ratio scale would
look very different to the graph above.
EINSTEIN
Ratio scales and logarithms
In Unit 1, we made frequent use of a ratio or log scale on the vertical axis
to display long-run data. For example, we used ratio scales with the units
doubling in Figure 1.1b and rising tenfold in Figure 1.2. The ratio scale
is also called a logarithmic (or log) scale. We can write a scale where the
tick marks on the vertical axis double like this:
Or a scale where they rise tenfold, like this:
The first is called a logarithmic scale in base 2; the second is in base 10.
As we saw in the charts in Unit 1, if the data forms a straight line on a
ratio (logarithmic) scale, then the growth rate is constant. A different
method of using this property of logarithms is to first convert the data
into natural logs and then plot it on a scale that is linear in logs.
13.1 GROWTH AND FLUCTUATIONS
551
Exponential trend (y)
GDP per capita
y = e0.02033x − 30.81
R2 = 0.9805
4,096
8,192
16,384
32,768
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
Year
Re
al
G
D
P
pe
rc
ap
ita
(£
,f
ac
to
rc
os
t)
Figure 13.4a The ratio scale and an exponential function.
See more https://tinyco.re/5401123
Linear trend (y)
Log of GDP per capita
y = 0.0203x − 30.8127
R2 = 0.9805
8.5
9.0
9.5
10.0
10.5
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
Year
Lo
g
of
G
D
P
pe
rc
ap
ita
Figure 13.4b The linear scale in natural logs and a linear function.
See more https://tinyco.re/7221043
Natural logs use base e, where e is a number (approximately 2.718) that
has mathematically useful properties.
We can use a calculator or a spreadsheet program to convert levels
into natural logs. As you can see, when applied to this data, it converts
the curved line in Figure 13.2 in the left-hand panel into one that is
almost a straight line in the right-hand one.
Using the chart functions in Microsoft Excel helps illustrate the rela-
tionship between plotting the data with a ratio scale on the vertical axis
(Figure 13.4a, which uses the doubling or base 2 scale) and transforming
the data into natural logs and plotting on a linear scale (in logs) on the
axis (Figure 13.4b). Note that the tick marks double from 4,096 to 8,192
to 16,384 in Figure 13.4a and rise from 8.5 to 9 to 9.5 in Figure 13.4b.
In each chart, a line appears alongside the data series. Using Excel, we
created Figure 13.4a by selecting Analysis/Trendline, and then selecting
‘Exponential’. Excel finds the line or curve that best fits the data points:
since the scale is a ratio scale, a straight line is displayed. The equation of
the line is given. Other spreadsheet or graphing software offers similar
features.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
552
Okun’s law The empirical
regularity that growth of GDP is
negatively correlated with the rate
of unemployment. See also: Okun’s
coefficient.
Okun’s coefficient The change in
the unemployment rate in
percentage points predicted to be
associated with a 1% change in
GDP. For example, an Okun coeffi-
cient of -0.4 means that a fall in
output of 1% is predicted to be
associated with a rise in the
unemployment rate of 0.4
percentage points. See also: Okun’s
law.
We can see that the exponential function uses what is called base e in
contrast to base 2 (doubling) or base 10 (increasing tenfold). The
exponent on e tells us the compound annual growth rate of the series: it
is 0.0203 × 100 = 2.03% per annum.
In Figure 13.4b, if we use Excel to select the ‘Fit a linear function’
option, a straight line appears. This time, we see an equation for a
straight line with intercept 8.8032 and slope 0.0203. Now the slope of
the line tells us the exponential, or equivalently, the compound annual
growth rate of the series: 0.0203 × 100 = 2.03% per annum.
In summary:
• When a data series is plotted, either using a ratio scale or by
transforming the data into natural logs, and the outcome is
approximately linear, it means that the growth rate of the series is
approximately constant. This constant growth rate is called an
exponential growth rate.
• The exponential growth rate (known also as the compound annual
growth rate or CAGR) is the slope of the line when the natural
logarithm of the data series is plotted.
• Notice the persistent deviation of the British economy from the trend
line following the 2008 financial crisis.
•13.2 OUTPUT GROWTH AND CHANGES IN
UNEMPLOYMENT
We saw in Figure 13.3 that unemployment goes down in booms and up in
recessions.
Figure 13.5 shows the relationship between output and unemployment
fluctuations, known as Okun’s law. Arthur Okun, an advisor to US
President Kennedy, noticed that when a country’s output growth was high,
unemployment tended to decrease. Okun’s law has been a strong and stable
empirical relationship in most economies since the Second World War.
Figure 13.5 plots the change in the unemployment rate (vertical axis) and
the growth rate of output (horizontal axis) for six countries: lower output
growth is clearly associated with a larger increase in unemployment. In
each country chart, there is a downward-sloping line that best fits the
points. In the US, for example, the slope of the line implies that, on average,
a 1% fall in output raises the unemployment rate by roughly 0.37
percentage points. We say that Okun’s coefficient is –0.37 in the US.
The dot labeled 2009 in each graph in Figure 13.5 shows the changes in
real GDP and unemployment that occurred from 2008 to 2009, during the
recession that followed the global financial crisis. We can see that in 2009,
all four of the advanced economies experienced their worst output con-
traction in 50 years. As predicted by Okun’s law, unemployment rose in
Spain, Japan, and the US.
In each of these three countries, however, the increase in unemployment
was higher than Okun’s law predicted: the red dot is well above the black
line of best fit. Germany looks very different: Okun’s law predicted a rise in
unemployment of 1.50 percentage points in Germany but, as the red dot
shows, German unemployment hardly changed in 2009. An economic
policymaker would surely want to know how Germany managed to protect
jobs in the face of the largest decline in the economy’s output in 50 years.
Edward S. Knotek, II, 2007. ‘How
useful is Okun’s law?’ Economic
review (Kansas City), 92(4), p. 73.
13.2 OUTPUT GROWTH AND CHANGES IN UNEMPLOYMENT
553
A rise in the
unemployment
rate
A fall in
wellbeing
A fall in
output
We will see why this occurred later in this unit. Our Einstein at the end of
this section shows how to predict the rise in unemployment associated with
a change in GDP using Okun’s relationship.
Brazil and Malaysia also experienced contractions in output and
increases in unemployment in 2009. However, like most developing eco-
nomies, they were hit less hard by the crisis than the advanced economies.
Also, Malaysia had experienced a much worse contraction during the East
Asian crisis in 1998, when growth was –7.4%—bad enough that it would
not fit on our chart.
We can summarize the relationship between output, unemployment, and
wellbeing like this:
EXERCISE 13.3 OKUN’S LAW
1. Look at the regression lines (the lines of best fit) in Figure 13.5. What
prediction does the regression line show for unemployment when the
economy is not growing? Are the results the same for all the countries?
2. Assume that the population in the economy is growing. Can you use
this assumption to provide an explanation for your results in question
1? What else might explain the differences between countries?
y = −0.1869x + 0.4188
R2 = 0.1991
2009
−2
0
2
4
6
−6 −10 4 9
Germany (1971–2019)
y = −0.3147x + 1.2821
R2 = 0.2726
2009
−2
0
2
4
6
−6 −10 4 9
Spain (1961–2019)
y = −0.02x + 0.0845
R2 = 0.0685
2009
−2
0
2
4
6
−6 −10 4 9
Japan (1961–2019)
Ch
an
ge
in
un
em
pl
oy
m
en
tr
at
e
(p
er
ce
nt
ag
e
po
in
ts
)
y = −0.3671x + 1.0827
R2 = 0.5957
2009
−2
0
2
4
6
−6 −10 4 9
US (1961–2019)
y = −0.1192x + 0.4225
R2 = 0.2281
2009
−2
0
2
4
6
−6 −10 4 9
Brazil (1990–2013)
y = −0.0511x + 0.3172
R2 = 0.4707
2009
−2
0
2
4
6
−6 −10 4 9
Malaysia (1990–2013)
Real GDP growth (%)
Figure 13.5 Okun’s law for selected economies.
OECD. 2021. OECD Statistics
(https://tinyco.re/9377362); The World
Bank. 2021. World Development
Indicators (https://tinyco.re/9263826).
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
554
QUESTION 13.2 CHOOSE THE CORRECT ANSWER(S)
The following graph shows the relationship between real GDP growth
and change in unemployment for the US between 1961 and 2019.
y = −0.3671x + 1.0827
R2 = 0.596
2009
−2
0
2
4
6
−6 −1 0 4 9
US (1961–2019)
Real GDP growth (%)
Ch
an
ge
in
un
em
pl
oy
m
en
tr
at
e
(p
er
ce
nt
ag
e
po
in
ts
)
The equation shown is the regression result for the best-fitting line.
Based on this information, which of the following statements is
correct?
The unemployment rate remains stable when there is zero real GDP
growth.
Okun’s coefficient for the US is 1.0827.
From the regression result, policy makers can be sure that a 1%
increase in real GDP next year will definitely lead to a fall in the
unemployment rate of 0.37 percentage points.
With real GDP falling by 2.8% in 2009, the predicted rise in the
unemployment rate would have been 2.11 percentage points.
13.2 OUTPUT GROWTH AND CHANGES IN UNEMPLOYMENT
555
aggregate output The total output
in an economy, across all sectors
and regions.
EINSTEIN
Okun’s law
The Okun’s law relationship is defined as:
Δut is the change in unemployment rate at time t, (GDP growtht) is the
real GDP growth at time t, α is the intercept value, and β is a coefficient
indicating the predicted effect of real GDP growth on changes in the
unemployment rate. Okun’s law is an empirical linear relationship that
associates the percentage change in GDP from the previous year with
the change in the unemployment rate from the previous year in
percentage points. The coefficient β, called Okun’s coefficient, is
generally found to be negative, suggesting that a positive real GDP
growth will be associated with a fall in the unemployment rate.
The estimated Okun’s law relationship for Germany, for the period
1971–2019, has coefficients β = –0.19 and α = 0.42.
When we estimate a line of best fit, we also measure the R-squared
(R2), which is a statistic that lies between 0 and 1. It measures how
closely the observed data fits the line that we draw through them, with 1
being a perfect fit, and 0 representing no observable relationship
between the observations and the prediction. In our case, the R2 statistic
measures how well Okun’s law approximates the data for real GDP
growth and unemployment changes. The R2 statistic is 0.20 for Germany
for the period 1971–2019, which is much lower than for the estimated
Okun’s law equation for the US, which is 0.60.
To work out the predicted percentage change in unemployment for
Germany in 2009 using the Okun’s law equation, we simply plug in the
value of real GDP growth for Germany in 2009 and solve the equation as
follows:
Okun’s law predicts that the fall in GDP of 5.7% in 2009 in Germany
should have been associated with an increase in unemployment by 1.50
percentage points.
13.3 MEASURING THE AGGREGATE ECONOMY
Economists use what are called aggregate statistics to describe the economy
as a whole (known as the aggregate economy, meaning simply the sum of its
parts brought together).
In Figure 13.5, aggregate output (GDP) is the output of all producers in
a country, not just those of some region, firm, or sector. Recall from Unit 1
that Diane Coyle, an economist who specializes in how we measure GDP,
describes it as:
Everything from nails to toothbrushes, tractors, shoes, haircuts,
management consultancy, street cleaning, yoga teaching, plates,
bandages, books, and the millions of other services and products in
the economy.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
556
national accounts The system used
for measuring overall output and
expenditure in a country.
value added For a production
process this is the value of output
minus the value of all inputs (called
intermediate goods). The capital
goods and labour used in produc-
tion are not intermediate goods.
The value added is equal to profits
before taxes plus wages.
The national accounts are statistics published by national statistical
offices that use information about individual behaviour to construct a
quantitative picture of the economy as a whole. There are three different
ways to estimate GDP:
• Spending: The total spent by households, firms, the government, and
residents of other countries on the home economy’s products.
• Production: The total produced by the industries that operate in the
home economy. Production is measured by the value added by each
industry: this means that the cost of goods and services used as inputs to
production is subtracted from the value of output. These inputs will be
measured in the value added of other industries, which prevents double-
counting when measuring production in the economy as a whole.
• Income: The sum of all the incomes received, comprising wages, profits,
the incomes of the self-employed, and taxes received by the government.
The relationship between spending, production, and incomes in the eco-
nomy as a whole can be represented as a circular flow: the national
accounts measurement of GDP can be taken at the spending stage, the pro-
duction stage, or the income stage. If accurate measurement were possible,
the total of expenditure, output, and incomes in a year would be the same
so the point at which the measurement is taken would not matter.
Households and firms both receive income and spend it. Figure 13.6
shows the circular flow between households and firms (ignoring the role of
government and purchases from and sales abroad for now).
In the model of the economy in Figure 1.12, we looked at the physical
flows among households, firms, and the biosphere instead of the circular
flow of income. In Unit 20, we look at how the interaction of households
and firms with the biosphere can be measured.
GDP can be defined according to any of these three perspectives.
The three methods for measuring GDP are best understood using a very
simple economy comprising just three industries. The economy produces a
single good, cotton shirts, which are sold to consumers for $100. The shirt
industry buys cloth for $80, which in turn buys cotton from the raw cotton
industry for $50. The final product or GDP of this economy is equal to
$100 because that is the value of the sale to the final consumer.
GDP can also be measured by the value added by each industry: the raw
cotton industry’s value added is equal to the value of its output, which is $50,
In eighteenth century France, a
group of economists, called the
Physiocrats, studied the economy
and compared the way it func-
tioned to the circular flow of blood
in the human body. This was a
forerunner to how we think today
about the circular flow in the eco-
nomy that allows us to calculate
GDP. Money flows from the
spender to the producer, from the
producer to its employees or
shareholders, and then is spent
again on further output, continuing
the cycle.
EXPENDITURE ($)
Money spent on goods and services
VALUE ADDED BY FIRMS ($) = INCOME ($)
Income received as wages and profits
from the production of goods and services
labour force
FIRMS HOUSEHOLDS
goods, services
Figure 13.6 The circular flow model: Three ways to measure GDP.
13.3 MEASURING THE AGGREGATE ECONOMY
557
imports (M) Goods and services
produced in other countries and
purchased by domestic households,
firms, and the government.
exports (X) Goods and services
produced in a particular country
and sold to households, firms and
governments in other countries.
because it purchases no inputs; the cloth industry’s value added is 80 − 50
= $30; and the shirt industry’s value added is 100 − 80 = $20. The total value
added in the economy is $100, exactly equal to the value of final production
and equal to total final expenditure.
Incomes are received as wages and profits. Across all industries in the
economy, wages plus profits will be equal to the value of final production
(which is equal to the total value added).
Therefore, GDP can be defined according to any of these three
perspectives. But we have to be careful in the definition because, while it is
always the case that one person’s expenditure is another person’s income,
globalization means that often the two people are in different countries.
This is the case with imports and exports: someone in China may buy rice
from someone in Japan, implying that the expenditure is Chinese while the
income is Japanese.
How do we account for these transactions? Since GDP is defined as
domestic product, it counts as Japanese GDP because the rice was produced
(and sold) by Japan. So exports are included in GDP because they are part of
domestic production, but imports are not because they are produced else-
where. For this reason, GDP is defined to include exports and exclude imports:
• as the value added of domestic production, or as expenditure on
domestic production
• as income due to domestic production
The circular flow model in Figure 13.6 considered only households and
firms, but the government, and the public services the government provides,
can be incorporated in a similar way. Households receive some goods and
services that are supplied by the government, for which they do not pay at
the point of consumption. A good example is primary school education.
The consumption and production of these services can be visualized
using the circular flow model:
• Households to government: Households pay taxes.
• Government to households: These taxes pay for the production of public
services used by households.
In this way the government can be seen as another producer, like a firm—
with the difference that the taxes paid by a particular household pay for
public services in general, and do not necessarily correspond to the services
received by that household. In Unit 19, we will look at how the payment of
taxes and the receipt of public services or benefits varies across households.
Since public services are not sold in the market, we also have to make a
further assumption: that the value added of government production is equal
to the amount it costs the government to produce.
So we can say that if, for example, citizens on average pay $15,000 per
year in taxes (the expenditure), that is $15,000 of revenues to the govern-
ment (the income), which uses it to produce $15,000 worth of public goods
and services (the value added).
The fact that expenditure, output, and incomes are all equal means that
we can use any one of these perspectives to help us understand the others.
We described recessions as periods of negative output growth. But this
means they must also be periods of negative expenditure growth (output
will only decline if people are buying less). Often, we can even say that
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
558
consumption (C) Expenditure on
consumer goods including both
short-lived goods and services and
long-lived goods, which are called
consumer durables.
investment (I) Expenditure on
newly produced capital goods
(machinery and equipment) and
buildings, including new housing.
inventory Goods held by a firm
prior to sale or use, including raw
materials, and partially-finished or
finished goods intended for sale.
output declines because people are buying less. This is very useful because
we know a lot about what determines expenditure, which in turn helps us
to understand recessions, as we will see in Unit 14.
•13.4 MEASURING THE AGGREGATE ECONOMY: THE
COMPONENTS OF GDP
Figure 13.7 shows the different components of GDP from the expenditure
side, as measured in the national accounts for economies on three different
continents: the US, the Eurozone, and China.
Consumption (C)
Consumption includes the goods and services purchased by households.
Goods are normally tangible things. Goods like cars, household appliances,
and furniture that last for three years or more are called durable goods;
those that last for shorter periods are non-durable goods. Services are
things that households buy that are normally intangible, such as
transportation, housing (payment of rent), gym membership, and medical
treatment. Household spending on durable goods like cars and household
equipment is counted in consumption in the national accounts, although as
we will see, in economic terms the decision to buy these long-lasting items
is more like an investment decision.
From the table in Figure 13.7 we see that in the advanced countries, con-
sumption is by far the largest component of GDP, close to 56% in the
Eurozone and 68% in the US. This contrasts with China, where final con-
sumption of households accounts for 37% of GDP.
Investment (I)
This is the spending by firms on new equipment and new commercial
buildings; and spending on residential structures (the construction of new
housing).
Investment in the unsold output that firms produce is the other part of
investment that is recorded as a separate item in the national accounts. It is
called the change in inventories or stocks. Including changes in stocks is
essential to ensuring that when we measure GDP by the output method
(what is produced), it is equal to GDP measured by the expenditure method
(what is spent, including investment by firms in unsold inventories).
Investment represents a much lower share of GDP in OECD countries,
roughly one-fifth of GDP in the US and the Eurozone. In contrast, invest-
ment accounts for almost half of GDP in China.
US Eurozone (19 countries) China
Consumption (C) 68.4% 55.9% 37.3%
Government spending (G) 15.1% 21.1% 14.1%
Investment (I) 19.1% 19.5% 47.3%
Change in inventories 0.4% 0.0% 2.0%
Exports (X) 13.6% 43.9% 26.2%
Imports (M) 16.6% 40.5% 23.8%
Figure 13.7 Decomposition of GDP in 2013 for the US, the Eurozone, and China.
OECD. 2015. OECD Statistics
(https://tinyco.re/9377362); The World
Bank. 2015. World Development
Indicators (https://tinyco.re/9263826).
OECD reports a statistical discrepancy
for China equal to -3.1% of GDP.
13.4 MEASURING THE AGGREGATE ECONOMY: THE COMPONENTS OF GDP
559
government spending (G) Expend-
iture by the government to
purchase goods and services. When
used as a component of aggregate
demand, this does not include
spending on transfers such as
pensions and unemployment bene-
fits. See also: government transfers
government transfers Spending by
the government in the form of
payments to households or indi-
viduals. Unemployment benefits
and pensions are examples.
Transfers are not included in gov-
ernment spending (G) in the
national accounts. See also: gov-
ernment spending (G)
trade balance Value of exports
minus the value of imports. Also
known as: net exports. See also:
trade deficit, trade surplus.
trade deficit A country’s negative
trade balance (it imports more than
it exports). See also: trade surplus,
trade balance.
trade surplus A country’s positive
trade balance (it exports more than
it imports). See also: trade deficit,
trade balance.
aggregate demand The total of the
components of spending in the eco-
nomy, added to get GDP: Y = C + I +
G + X – M. It is the total amount of
demand for (or expenditure on)
goods and services produced in the
economy. See also: consumption,
investment, government spending,
exports, imports.
Government spending on goods and services (G)
This represents the consumption and investment purchases by the govern-
ment (consisting of central and local government, often called ‘general
government’). Government consumption purchases are of goods (such as
office equipment, software, and cars) and services (such as wages of civil
servants, armed services, police, teachers, and scientists). Government
investment spending is on the building of roads, schools, and defence
equipment. Much of government spending on goods and services is for
health and education.
Government transfers in the form of benefits and pensions, such as
Medicare in the US, or social security benefits in Europe, are not included
in G because households receive them as income: when they are spent, they
are recorded in C or I. It would be double-counting to record this spending
in G too.
The share of government spending on goods and services is slightly
higher in Europe (21.1%) than in the US (15.1%). Remember, this excludes
transfers (such as benefits and pensions). The greater difference in the role
of the government between Europe and the US comes from those transfers.
In 2012, total government spending including transfers was 57% of GDP in
France, compared to 40% of GDP in the US.
Exports (X)
Domestically produced goods and services that are purchased by house-
holds, firms, and governments in other countries.
Imports (M)
Goods and services purchased by households, firms, and governments in
the home economy that are produced in other countries.
Net exports (X−M)
Also called the trade balance, this is the difference between the values of
exports and imports (X – M).
In 2010, the US had a trade deficit of 3.4% of GDP and China had a trade
surplus of 3.6% of GDP. The trade balance is a deficit if the value of exports
minus the value of imports is negative; it is called a trade surplus if it is
positive.
GDP (Y)
To calculate GDP, which is the aggregate demand for what is produced in
the country, we add the purchases by those in other countries (exports) and
subtract the purchases by home residents of goods and services produced
abroad (imports). Taking China as an example, its GDP is the aggregate
demand for China’s output, which includes its exports less its imports.
Working with national accounts data is a way of learning about the eco-
nomy, and an easy way to do this is to use the Federal Reserve Economic
Data (FRED) (https://tinyco.re/3965569). To learn more about the country
where you live and how it compares to other countries, try Exercise 13.4
for yourself.
In most countries, private consumption spending makes up the largest
share of GDP (see Figure 13.7 to check). Investment spending accounts for
a much smaller share (China’s very high level of investment, shown in
Figure 13.7, is exceptional). We use the data in the national accounts to
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
560
calculate how much each component of expenditure contributes towards
GDP fluctuations.
The equation below shows how GDP growth can be broken down into
the contributions made by each component of expenditure. We can see that
the contribution of each component to GDP growth depends on both the
share of GDP that the component makes up and its growth over the
previous period.
The table in Figure 13.8 shows the contributions of the components of
expenditure to US GDP growth. The data is for 2009, in the middle of the
recession caused by the global financial crisis. We can see that:
• Although investment makes up less than one-fifth of US GDP, it was
much more important in accounting for the contraction in the economy
than the fall in consumption spending.
• Although consumption makes up about 70% of US GDP, the effect of
investment on GDP was more than three times larger.
• In contrast to consumption and investment, government expenditure
contributed positively to GDP growth. The US government used fiscal
stimulus to prop up the economy whilst private sector demand was
depressed.
• Net exports also contributed positively to GDP, which reflects both the
stronger performance of emerging economies in the aftermath of the
crisis and the collapse in import demand that accompanied the
recession.
Shortcomings of GDP as a measure
Three things need to be kept in mind when using the concept of GDP:
1. It is a conventional measure of the size of an economy: We examined what
GDP includes in Unit 1. In Unit 20, the concept of green growth
accounting is introduced, which shows how to calculate the size of the
economy and its growth taking into account environmental degradation.
2. Distinguish aggregate GDP from GDP per capita: This is especially import-
ant when discussing growth. In this section, the focus has been on GDP
GDP Consumption Investment Government spending Net exports
2009 −2.8 −1.06 −3.52 0.64 1.14
Figure 13.8 Contributions to percentage change in real GDP in the US in 2009.
Federal Reserve Bank of St. Louis. 2015.
FRED (https://tinyco.re/3965569). Note
that in the national accounts, govern-
ment investment is counted as
government spending and not invest-
ment.
13.4 MEASURING THE AGGREGATE ECONOMY: THE COMPONENTS OF GDP
561
and the contributions of the different components of demand to its
growth. In other contexts, the relevant concept is a per capita measure.
To see the difference, note that GDP in the UK grew by 7% between
2007 and 2015 but GDP per capita grew by only 0.8%. The explanation
is that there was a large increase in immigration.
3. GDP per capita is a flawed measure of living standards: Recall from Unit 1
that Robert Kennedy’s 1968 speech at the University of Kansas
(https://tinyco.re/9533853) highlighted these flaws (search for ‘Gross
National Product’ in the text).
EXERCISE 13.4 HOW TO USE FRED
If you want real-time macroeconomic data on the
German unemployment rate or China’s output growth,
you do not need to learn German and Chinese, or
struggle to get to grips with national archives, because
FRED does it for you! FRED is a comprehensive up-to-
date data source maintained by the Federal Reserve
Bank of St Louis in the US, which is part of the US
central banking system. It contains the main macroeco-
nomic statistics for almost all developed countries
going back to the 1960s. FRED also allows you to create
your own graphs and export data into a spreadsheet.
To learn how to use FRED to find macroeconomic
data, follow these steps:
• Visit the FRED website (https://tinyco.re/5104028).
• Use the search bar and type ‘Real Gross Domestic
Product’ (GDP) and the name of a major global eco-
nomy. Select the annual series for real (constant
prices) GDP for this country. This is clearly labelled
as ‘Real Gross Domestic Product’ for your chosen
country.
• Click the ‘Edit graph’ button, above the top-right
corner of the graph.
• Click the ‘Add line’ button. Search for the annual
series for nominal (current prices) GDP. This is
labelled as simply ‘Gross Domestic Product’ for your
chosen country. Add this series to your graph.
• You can use the ‘Edit graph’ button to modify the
frequency of your data, if it is not annual.
You can also watch this short tutorial (https://tinyco.re/
3209844) to understand how FRED works.
Use the graph you created to answer these
questions:
1. What is the level of nominal GDP in your chosen
country this year?
2. FRED tells you that the real GDP is chained in a
specific year (this means that it is evaluated in terms
of constant prices for that year). Note that the real
GDP and the nominal GDP series cross at one point.
Why does this happen?
From the FRED graph, keep only the real GDP series.
You can remove a data series by using the graph editing
tool. FRED shows recessions in shaded areas for the US
economy using the NBER definition, but not for other
economies. For other economies, assume that a
recession is defined by two consecutive quarters of neg-
ative growth. In the graph editing tool, change the units
of your series, and select ‘Percentage change from Year
Ago’. The series now shows the percentage change in
real GDP.
3. How many recessions has your chosen economy
undergone over the years plotted in the chart?
4. What are the two biggest recessions in terms of
length and magnitude?
Now add to the graph the quarterly unemployment rate
for your chosen economy (click on ‘Add data series’
under the graph and search for ‘Unemployment’ and
your chosen country name).
5. How does the unemployment rate react during the
two main recessions you have identified?
6. What was the level of the unemployment rate during
the first and the last quarter of negative growth for
those two recessions?
7. What do you conclude about the link between
recession and the variation in unemployment?
Note: To make sure you understand how these FRED
graphs are created, you may want to extract the data
into a spreadsheet, and create a graph showing the
growth rate of real GDP and the evolution of the
unemployment rate since 1948 for the US economy.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
562
shock An exogenous change in
some of the fundamental data used
in a model.
QUESTION 13.3 CHOOSE THE CORRECT ANSWER(S)
Which of the following statements is correct regarding measuring
GDP?
GDP can be measured either as the total spending on domestically
produced goods and services, or the total value added in domestic
production, or the sum of all incomes received from domestic pro-
duction.
Information about exports but not imports is necessary to calculate
GDP.
Government production is not included in the GDP.
The value added of government production is computed using the
price that public goods and services are sold at in the market.
QUESTION 13.4 CHOOSE THE CORRECT ANSWER(S)
Which of the following would increase GDP?
A decline in imports, holding all other components of GDP constant.
An increase in remittances paid to domestic residents by relatives
living abroad.
An increase in government spending.
A decline in exports.
••13.5 HOW HOUSEHOLDS COPE WITH FLUCTUATIONS
Economies fluctuate between good and bad times. So far we have studied
industrialized economies, but this is equally true in economies based on
agriculture. Figure 13.9a illustrates fluctuations in production in the largely
agrarian British economy between 1550 and 1700. Just as we divided GDP
into different components from the expenditure side, we can also divide it
into different sectors on the production side. Figure 13.9a shows the
growth rate of real GDP and of the three main sectors: agriculture,
industry, and services. Follow the analysis in Figure 13.9a to see how the
agricultural sector drove fluctuations in GDP.
Figure 13.9b shows the growth rates of real GDP and agriculture in
India since 1960. In 1961 agriculture comprised 43% of the economy, which
had declined to 18% in 2020. Partly due to modern farming methods,
agriculture in modern India is not as volatile as it was in Britain before
1700. But it remains nearly twice as volatile as GDP as a whole.
To help us to think about the costs and causes of economic fluctuations,
we begin with an agrarian economy. In an economy based on agricultural
production, the weather—along with war and disease—is a major cause of
good and bad years. The term shock is used in economics to refer to an
unexpected event, for example, extreme weather or a war. As we know,
people think about the future and usually they anticipate that unpredictable
events may occur. They also act on these beliefs. In a modern economy, this
is the basis of the insurance industry. In an agrarian economy, households
also anticipate that both bad luck and good harvests can occur.
How do households cope with fluctuations that can cut their income in
half from one season to the next?
13.5 HOW HOUSEHOLDS COPE WITH FLUCTUATIONS
563
Industry ServicesAgriculture GDP
−60
−40
−20
0
20
40
60
15
50
15
60
15
70
15
80
15
90
16
00
16
10
16
20
16
30
16
40
16
50
16
60
16
70
16
80
16
90
17
00
Year
G
ro
w
th
ra
te
(%
)
Figure 13.9a The role of agriculture in the fluctuations of the aggregate economy in
Britain (1550–1700).
Agriculture GDP
−15
−10
−5
0
5
10
15
20
19
60
19
70
19
80
19
90
20
00
20
10
20
20
Year
G
ro
w
th
ra
te
(%
)
Figure 13.9b The role of agriculture in the fluctuations of the aggregate economy in
India (1961–2020).
View this data at OWiD https://tinyco.re/
0436267
The World Bank. 2021. World
Development Indicators
(https://tinyco.re/9263826).
View this data at OWiD https://tinyco.re/
2907345
Stephen Broadberry, Bruce M. S.
Campbell, and Alexander Klein. 2015.
British Economic Growth, 1270–1870.
Cambridge: Cambridge University Press.
1. GDP growth between 1550 and 1700
The figure shows the growth rate of
real GDP and its three main sectors at
this time.
2. Agriculture
Clearly the agricultural sector is much
more volatile than other sectors.
3. Industry
In this period the average difference in
the output of the agricultural sector
from one year to the next is three times
larger than that of the industrial
sector …
4. Services
… and more than 10 times larger than
that of the services sector.
5. Agriculture drove fluctuations in GDP
Between 1552 and 1553, the
agricultural sector expanded by 41%
and GDP rose by 17%. In the next year
the agricultural sector contracted by
16% and the economy shrank by 8%.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
564
self-insurance Saving by a house-
hold in order to be able to maintain
its consumption when there is a
temporary fall in income or need
for greater expenditure.
co-insurance A means of pooling
savings across households in order
for a household to be able to
maintain consumption when it
experiences a temporary fall in
income or the need for greater
expenditure.
altruism The willingness to bear a
cost in order to benefit somebody
else.
We can distinguish between two situations:
• Good or bad fortune strikes the household: For example, when disease
affects a family’s animals, or when a family member who plays an
important role in farming is injured.
• Good or bad fortune strikes the economy as a whole: For example, when
drought, disease, floods, a war, or an earthquake affects a whole area.
Household shocks
People use two strategies to deal with shocks that are specific to their
household:
• Self-insurance: Households that encounter an unusually high income in
some period will save, so that when their luck reverses, they can spend
their savings. As we saw in Unit 10, they may also borrow in bad times if
they can, depending on how credit-constrained they are. It is called self-
insurance because other households are not involved.
• Co-insurance: Households that have been fortunate during a particular
period can help a household hit by bad luck. Sometimes this is done
among members of extended families or among friends and neighbours.
Since the mid-twentieth century, particularly in richer countries, co-
insurance has taken the form of citizens paying taxes, which are then
used to support individuals who are temporarily out of work, called
unemployment benefits.
Informal co-insurance among family and friends is based on both
reciprocity and trust: you are willing to help those who have helped you in
the past, and you trust the people who you helped to do the same in return.
Altruism towards those in need is also usually involved, although co-insur-
ance can work without it.
These strategies reflect two important aspects of household preferences:
• People prefer a smooth pattern of consumption: As we saw in Unit 10, they
dislike consumption that fluctuates as a result of bad or good shocks
such as injury or good harvests. So they will self-insure.
• Households are not solely selfish: They are willing to provide support to
each other to help smooth the effect of good and bad luck. They often
trust others to do the same, even when they do not have a way of
enforcing this. Altruistic and reciprocal preferences remain important
even when co-insurance takes the form of a tax-supported unemploy-
ment benefit, because these are among the motives for supporting the
public policies in question.
Economy-wide shocks
Co-insurance is less effective if the bad shock hits everyone at the same
time. When there is a drought, flood, or earthquake, it is more difficult for
an agrarian economy to protect the wellbeing of the people who are
affected. For example, it is not usually possible to store produce from a
bumper harvest long enough to get through the next bad harvest, which
may take several years to arrive.
But when these shocks hit, co-insurance may be even more necessary, as
community survival requires that less badly hit households help the worst-
hit households. In farming economies of the past that were based in volatile
‘New Cradles to Graves’
(https://tinyco.re/8856321). The
Economist. Updated 8 September
2012.
Michael Naef and Jürgen Schupp
report comparisons between
surveys and experiments using
trust. Michael Naef and Jürgen
Schupp. 2009. ‘Measuring Trust:
Experiments and Surveys in
Contrast and Combination’
(https://tinyco.re/3956674). IZA
Discussion Paper No. 4087.
13.5 HOW HOUSEHOLDS COPE WITH FLUCTUATIONS
565
climates, people practised co-insurance based on trust, reciprocity, and
altruism. These are norms, like the fairness norm we discussed in Unit 4,
and they probably emerged and persisted because they helped people to
survive in these regions that were often hit by bad weather shocks. Recent
research suggests that they seem to have persisted even after climate had
become largely unimportant for economic activity.
The evidence for this is that people in the regions with high year-to-year
variability in rainfall and temperature during the past 500 years now
display high levels of trust, and have more modern day co-insurance insti-
tutions such as unemployment benefit payments and government assistance
for the disabled and poor.
EXERCISE 13.5 HEALTH INSURANCE
1. Think about the health insurance system in your country. Is this an
example of co-insurance or self-insurance?
2. Can you think of other examples of both co-insurance and self-insur-
ance? In each case, consider what kinds of shocks are being insured
against and how the scheme is financed.
QUESTION 13.5 CHOOSE THE CORRECT ANSWER(S)
Figure 13.9a (page 564) plots the growth rate of real GDP, as well as
the growth rates of the agricultural, industrial, and service sectors
between 1550 and 1700 in Britain.
Which of the following statements can be deduced from the graph?
The average growth rate of the agricultural sector was higher than
that of the service sector for the period shown.
The growth rate of the industrial sector was more volatile than that
of the service sector.
The agricultural sector largely drove fluctuations in GDP.
The recession around 1560 was caused by contractions in all three
sectors.
13.6 WHY IS CONSUMPTION SMOOTH?
A basic source of stabilization in any economy comes from the desire of
households to keep the level of their consumption of goods and services
constant. Keeping a steady level of consumption means households have to
plan. They think about what might happen to their income in the future,
and they save and borrow to smooth the bumps in income. This is the self-
insurance we discussed above.
We have seen that this behaviour occurs in agrarian societies faced by
weather and war shocks, but modern households also try to smooth their
consumption. One way to visualize this behaviour is to focus on predictable
events. A young person thinking about life can imagine getting a job, then
enjoying a period of working life with income higher than the starting
salary, followed by years in retirement when income is lower than during
working life.
As we saw in Unit 10, people prefer to smooth their consumption
because there are diminishing marginal returns to consumption at any
Ruben Durante. 2010. ‘Risk,
Cooperation and the Economic
Origins of Social Trust: An
Empirical Investigation’
(https://tinyco.re/7674543).
Sciences Po Working Paper.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
566
given time. So having a lot of consumption later and little now, for example,
is worse than having some intermediate amount of consumption in the two
periods (Figure 10.3a).
The person contemplating a future promotion and planning their
spending would be in a position similar to Julia in Unit 10 (Figure 10.2),
who had limited funds in the present but knew she would have more later,
and consequently was interested in moving some of her future buying
power to the present by borrowing. The model of decision making for the
individual that we introduced in Unit 3 and Unit 10 is the basis for thinking
about consumption throughout a person’s life. It predicts that, although
income fluctuates throughout our lives, our desired consumption is
smoother.
We can use Figure 13.10 to visualize an individual’s tendency to smooth
consumption expenditure. In this simple example, before starting work, the
individual’s income and consumption expenditure are the same—we
assume, for example, that parents support their children until the children
start work. Follow the analysis in Figure 13.10 to see their income and con-
sumption over time.
A notable feature of Figure 13.10 is that consumption changes before
income does.
Like a family in an agrarian economy that begins saving for a daughter’s
dowry before she is old enough to marry, the individual shown in Figure
13.10 anticipates receiving higher income after a promotion, and adjusts
consumption upward ahead of time. As we have seen in Unit 10, this
assumes that the individual can borrow. Maybe it is possible to convince
In
co
m
e,
c
on
su
m
pt
io
n
Time
Start work Promotion Retirement
Running down
savings
Accumulating savings
and repaying debt
Borrowing
Path of income
Path of consumption
Figure 13.10 Consumption smoothing through our lifetime.
1. Income over time
The blue line shows the path of income
over time: it starts low, rises when the
individual is promoted and falls at
retirement.
2. Consumption expenditure
This is the red line. It is smooth (flat)
from the point at which the individual
first gets a job.
3. The individual borrows while young
At this time income is low. The indi-
vidual saves and repays the debt when
older and earning more, and finally
runs down savings after retirement,
when income falls again.
13.6 WHY IS CONSUMPTION SMOOTH?
567
the bank that the job is secure and prospects are good. If so, the individual
can probably get a mortgage now, and live in a more comfortable house
with a higher standard of living than would be the case if long-term earn-
ings were to remain at the starting salary. The labels on Figure 13.10 show
that the individual borrows while young and income is low, saves and
repays the debt when older and earning more, and finally runs down
savings after retirement, when income falls again.
The model of decision making highlights the desire of households for a
smooth path of consumption. We next ask what happens when something
unexpected occurs to disturb the lifetime consumption plan. What if the
individual shown in the figure encounters an unexpected income shock?
The consumption-smoothing model suggests that:
• The individual will make a judgement: This will be about whether the
shock is temporary or permanent.
• If the shock is permanent: We should adjust the red line in Figure 13.10 up
or down to reflect the new long-run level of consumption that the indi-
vidual adopts, consistent with the new pattern of forecast income.
• If the shock is temporary: Little will change. A temporary fluctuation in
income has almost no effect on the lifetime consumption plan, because it
makes only a small change to lifetime income.
To summarize, when individuals and households behave in the way shown
in Figure 13.10, shocks to the economy will be dampened because spending
decisions are based on long-term considerations. They aim to avoid
fluctuations in consumption even when income fluctuates.
What limits a household’s consumption smoothing? Many individuals
and households are not able to make or implement long-term consumption
plans. Making plans can be difficult because of a lack of information. Even
if we have information, we may not be able to use it to predict the future
with confidence. For example, it is often very hard to judge whether a
change in circumstances is temporary or permanent.
There are three other things that constrain the ways in which house-
holds can smooth their consumption when faced with income shocks. The
first two concern limits on self-insurance, the third is a limit on co-insur-
ance:
• Credit constraints or credit market exclusion: Introduced in Unit 10, this
restricts a family’s ability to borrow in order to sustain consumption
when income has fallen.
• Weakness of will: A characteristic of human behaviour that leads people
to be unable to carry out the plans—for example, saving in anticipation
of a negative income shock—that they know would make them better
off.
• Limited co-insurance: So that those with a fall in income cannot expect
much support in sustaining their incomes from others more fortunate
than them.
Credit constraints
As we saw in Unit 10, the amount a family can borrow is limited,
particularly if it is not wealthy. Households with little money cannot
borrow at all, or only at extraordinarily high interest rates. Thus the people
who most need credit to smooth their consumption are often unable to do
In Portfolios of the Poor: How the
World’s Poor Live on $2 a Day,
Daryl Collins, Jonathan Morduch,
Stuart Rutherford, and Orlanda
Ruthven show how poor house-
holds manage finances to avoid
literally living hand-to-mouth.
‘Smooth Operators’
(https://tinyco.re/7009658). The
Economist. Updated 14 May 2009.
Some of the stories can be read
online (https://tinyco.re/8070650).
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
568
so. The credit constraints and credit market exclusion discussed in Units 10
and 12 help explain why borrowing is often not possible.
Figure 13.11 shows the reaction of two different types of households to
an anticipated rise in income. Households that are able to borrow as much
as they like are in the top panel. Credit-constrained households that are
unable to get a loan or take out a credit card are in the bottom panel. Follow
the analysis in Figure 13.11 to see how the two households react to two key
events:
1. News is received that income will rise at a predictable time in the future
(for example, a promotion or a bequest).
2. The household’s income actually rises (the promotion happens, the
inheritance comes through).
We can think about these decisions using the two-period model of
borrowing and lending from Unit 10, shown in Figure 13.12. First consider
a household that receives the same income, y, this period and next period,
indicated by the endowment point A in Figure 13.12. The interest rate is r
In
co
m
e,
c
on
su
m
pt
io
n
Consumption-smoothing households
Time
News about rise in
future income received
Actual income rises
Repaying debt
Borrowing
In
co
m
e,
c
on
su
m
pt
io
n
Consumption-constrained households
Time
News about rise in
future income received
Actual income rises
Path of income
Path of consumption
Figure 13.11 Consumption when credit constraints bind: An anticipated rise in
income.
1. Income over time
The blue lines on the figure show that
the path of income over time is the
same in both households.
2. Consumption smoothing
The red line in the top panel shows
that, in a consumption-smoothing
household, consumption changes
immediately once the household
receives the news.
3. The effect of credit constraints
On the other hand, a credit-constrained
household that cannot borrow has to
wait until the income arrives before
adjusting its standard of living.
13.6 WHY IS CONSUMPTION SMOOTH?
569
so if the household can borrow and save, then it can choose any point on
the budget constraint, which has the slope −(1 + r). The budget constraint is
another term for the frontier of the feasible set with the slope of −(1 + r)
which we used in Unit 10.
In
co
m
e,
c
on
su
m
pt
io
n
la
te
r (
$)
Income, consumption now ($)
y′0
0
c′ y
y
c′
A′
A′′
A
IC1
IC2 Household’s endowment following the
temporary income shock; its pattern of
consumption if it cannot borrow
Household’s initial endowment
and pattern of consumption
Household’s pattern of
consumption following the
temporary income shock
if it can borrow
Slope = –(1 + r)
Figure 13.12 Credit-constrained and unconstrained households: An unanticipated
temporary fall in income.
1. Same income in both periods
Consider a household that receives the
same income, y, this period and next
period, indicated by the endowment
point A.
2. An unconstrained household
The interest rate is r so if the household
can borrow and save, then it can
choose any point on the budget con-
straint, which has the slope −(1 + r).
3. Preference for smoothing
Assume that the household prefers to
consume the same amount each
period, shown by the point A where the
indifference curve is tangent to the
budget constraint.
4. A negative shock
Now suppose that the household
experiences an unexpected negative
temporary shock to its income this
year, such as a bad harvest, which
lowers this year’s income to y′, leaving
expected income next year unaffected
at y.
5. The budget constraint
If it can borrow and save, then its
budget constraint has a slope of −(1 + r)
and passes through point A′.
6. The highest indifference curve
The highest curve that touches this
budget constraint does so at point A″,
showing that the household prefers to
smooth consumption, consuming c′ in
both periods. The household borrows c′
− y′ now and repays (1 + r)(c′ − y′) next
period following the shock.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
570
weakness of will The inability to
commit to a course of action
(dieting or foregoing some other
present pleasure, for example) that
one will regret later. It differs from
impatience, which may also lead a
person to favour pleasures in the
present, but not necessarily act in a
way that one regrets.
We learn from this example that:
• Without borrowing or lending, the endowment point and pattern of
consumption coincide.
• Compared with the smoothing household, the credit-constrained house-
hold consumes less this period and more next period.
We can also see that the indifference curve that passes through A′ (not
shown) is lower than the one that passes through A″. So the household that
can smooth consumption by borrowing is better off than the credit-
constrained household.
A temporary change in income affects the current consumption of
credit-constrained households more than it does that of the unconstrained.
Weakness of will
In Figure 13.13, an individual learns that income is going to fall in the
future. This could be because of retirement or job loss. It could also be
because the individual is becoming pessimistic. Perhaps the newspapers
predict an economic crisis. In the top panel of Figure 13.13 we again show a
household behaving in a forward-looking manner to smooth consumption.
The bottom panel shows a household with weakness of will that con-
sumes all its income today even though it implies a large reduction in
consumption in the future.
This feature of human behaviour is familiar to many of us. We often lack
willpower.
The problem of not being able to save obviously differs from the
problem of not being able to borrow: saving is a form of self-insurance and
doesn’t involve anyone else.
HOW ECONOMISTS LEARN FROM FACTS
My diet starts tomorrow
Economists have conducted experiments to test for behaviour that
would help to explain why we don’t save even when we can. For
example, Daniel Read and Barbara van Leeuwen conducted an
experiment with 200 employees at firms in Amsterdam. They asked
them to choose today what they thought they would eat next week. The
choice was between fruit and chocolate.
When asked, 50% of subjects replied that they would eat fruit next
week. But, when next week came, only 17% actually chose to eat fruit.
The experiment shows that, although people may plan to do something
that they know will be beneficial (eat fruit, save money), when the time
comes they often don’t do it.
Read: Daniel, and Barbara van Leeuwen. 1998. ‘Predicting Hunger:
The Effects of Appetite and Delay on Choice’. Organizational Behavior
and Human Decision Processes 76 (2): pp. 189–205.
13.6 WHY IS CONSUMPTION SMOOTH?
571
Limited co-insurance
Most households lack a network of family and friends who can help out in
substantial ways over a long period when a negative income shock occurs. As
we have seen, unemployment benefits provide this kind of co-insurance—the
citizens who turn out to be lucky in one year insure those who are unlucky.
But in many societies the coverage of these policies is very limited.
A vivid demonstration of the value of smoothing through co-insurance
is the experience of Germany during the drastic reduction in income
experienced by that economy in 2009 (see Figure 13.5). When the demand
for firms’ products fell, workers’ hours of work were cut, but as a result of
both government policy and agreements between firms and their employ-
ees, very few Germans lost their jobs, and many of those at work were still
paid as if they were working many more hours than they did. The result
was that although aggregate income fell, consumption did not—and
unemployment did not increase.
OECD. 2010. Employment Outlook
2010: Moving Beyond the Jobs
Crisis (https://tinyco.re/5607435).
In
co
m
e,
c
on
su
m
pt
io
n
Consumption-smoothing households
Time
News about fall in
future income received
Actual income falls
News about fall in
future income received
Actual income falls
Running down savings or borrowing
Path of income
Path of consumption
Saving
In
co
m
e,
c
on
su
m
pt
io
n
Households with ‘weakness of will’
Time
Figure 13.13 Consumption when households are weak-willed: An anticipated fall in
income.
1. The path of income
The blue lines in the figure show that
income follows the same path in both
sets of households.
2. Consumption smoothing
The red line in the top panel shows the
consumption path for a consumption-
smoothing household. When it receives
news of the imminent fall in income, it
immediately starts saving to
supplement consumption when income
falls.
3. A weak-willed household
In contrast, the weak-willed household
does not react to the news, and keeps
consumption high until income falls.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
572
But most empirical evidence shows that credit constraints, weakness of
will, and limited co-insurance mean that, for many households, a change in
income results in an equal change in consumption. In the case of a negative
income shock such as the loss of a job, this means that the income shock
will now be passed on to other families who would have produced and sold
the consumption goods that are now not demanded.
We will see in the next unit how the initial shock in income may be
multiplied (or amplified) by the fact that families are limited in their ability
to smooth their consumption. This in turn helps us understand the business
cycle and how policymakers may or may not help to manage it.
EXERCISE 13.6 CHANGES IN INCOME, CHANGES IN CONSUMPTION
Consider a credit-constrained household type and a consumption
smoothing household type.
1. For each household type, use a figure with time on the horizontal axis
and income and consumption on the vertical axis to explain the rela-
tionship between the change in income and the change in consumption
when income returns to normal after an unexpected temporary
decline.
2. Based on this analysis, explain the predicted relationship between
temporary changes in income and consumption for an economy with a
mixture of the two household types.
QUESTION 13.6 CHOOSE THE CORRECT ANSWER(S)
Figure 13.12 (page 570) shows the consumption choice of a consumer
over two periods. His initial endowment is (y, y), that is, an income y in
both periods, which is depicted by point A. If possible, the consumer
prefers to consume the same amount in both periods. The interest rate
is r.
Now assume that there has been a temporary shock such that the
income in period 1 is reduced to y′, while the period 2 income is expec-
ted to return to y. Assume that a credit-constrained consumer is not
able to borrow at all. Based on this information, which of the following
statements is correct?
If the consumer is credit-constrained, then he will consume less in
period 2 than he would have done without the temporary shock.
If the consumer is not credit-constrained, then he will be able to
borrow to consume the same amount as he would have done in
both periods without the temporary shock.
If the consumer is not credit-constrained, then he will borrow y − c′
in period 1 in order to smooth out his consumption in the two
periods.
If the consumer is not credit-constrained, then he will consume c′ in
both periods such that c′ = y − (c′ − y′)(1 + r) (income minus
repayment in period 2).
Empirical evidence shows that,
even when income changes in
predictable ways, consumption
responds. Tullio Jappelli and Luigi
Pistaferri. 2010. ‘The Consumption
Response to Income Changes’
(https://tinyco.re/3409802).
VoxEU.org.
13.6 WHY IS CONSUMPTION SMOOTH?
573
QUESTION 13.7 CHOOSE THE CORRECT ANSWER(S)
The following diagram shows the path of income for a household that
receives news about an expected rise and fall in future income at the
depicted times.
In
co
m
e,
c
on
su
m
pt
io
n
Time
t = 1
News about rise
in future income received
t = 2
Actual
income
rises
t = 3
News about fall
in future income received
t = 4
Actual
income
falls
Path of income
Assume that the household prefers to smooth out its consumption if it
can. Based on this information, which of the following statements is
correct?
If the household is not credit-constrained, then it will consume the
same level after t = 1.
If the household is credit-constrained and has ‘weakness of will’,
then its consumption will match precisely its income path.
If the household is not credit-constrained but has ‘weakness of will’,
then it will borrow at t = 1 and save at t = 3.
If the household is credit-constrained but does not have ‘weakness
of will’, then it will borrow at t = 1 and save at t = 3.
•••13.7 WHY IS INVESTMENT VOLATILE?
Households tend to smooth their consumption spending when they can, but
there is no similar motivation for a firm to smooth investment spending.
Firms increase their stock of machinery and equipment and build new prem-
ises whenever they see an opportunity to make profits. But, unlike eating and
most other consumption expenditures, investment expenditures can be
postponed. There are several reasons why this is likely to produce clusters of
investment projects at some times, while few projects at other times.
In Unit 2, we saw how firms responded to profit opportunities in the
Industrial Revolution by innovating. This helps explain why investment
occurs in waves. When an innovation like the spinning jenny is introduced,
firms using the new technology can produce output at lower cost or
produce higher-quality output. They expand their share of the market.
Firms that fail to follow may be forced out of business because they are
unable to make a profit using the old technology. But new technology
means that firms must install new machines. As firms do this, there is an
investment boom. This will be amplified if the firms producing the
machinery and equipment need to expand their own production facilities to
meet the extra demand expected.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
574
In this case, investment by one firm pushes other firms to invest: if they
don’t, they may lose market share or even be unable to cover their costs and
eventually have to leave the industry. But investment by one firm can also pull
other firms to invest by helping to increase their market and potential profits.
An example of push investment is the hi-tech investment boom in the
US. From the mid-1990s, new information and communications techno-
logy (ICT) was introduced into the US economy on a large scale. Figure
13.14 shows the sustained growth of investment in new technologies
through the second half of the 1990s.
As we saw in Unit 11, investment in new technology can lead to a stock
market bubble and over-investment in machinery and equipment. The
chart shows in green the behaviour of the US stock market index on which
hi-tech companies are listed. This is the Nasdaq index, introduced in
Unit 11.
The index rose strongly from the mid-1990s to an all-time peak in 1999
as stock market investors’ confidence in the profitability of new tech firms
grew. Investment in IT equipment (the red line) grew rapidly as a result of
this confidence, but dropped sharply following the collapse in confidence
that caused the fall of the stock market index. This suggests that over-
investment in machinery and equipment had occurred: investment did not
begin growing again until 2003. Robert Shiller, the economist, argued that
the Nasdaq index was driven high by what he called ‘irrational exuberance’,
as you might recall from Unit 11. Beliefs in the future of hi-tech led not
only to share prices rising to levels that were unsustainable, but also to
excessive investment in machinery and equipment in the hi-tech sector.
Credit constraints are another reason for the clustering of investment
projects and the volatility of aggregate investment. In a buoyant economy,
profits are high and firms can use these profits to finance investment
projects. Access to external finance from sources outside the firm is also
easier: in the US hi-tech boom, for example, the expansion of the Nasdaq
exchange reflected the appetite of investors to provide finance by buying
shares (stocks) in firms in the emerging ICT industries.
To understand how one firm’s investment can induce another firm to
invest, think of a local economy comprising of just two firms. Firm A’s
machinery and equipment are not fully used, so the firm can produce more
Robert Shiller has explained in a
VoxEU podcast (https://tinyco.re/
9820978) how animal spirits
contribute to the volatility of
investment.
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
20
17
20
18
20
19
20
20
−50
−40
−30
−20
−10
0
10
20
30
40
50
60
Growth of investment in new technologies (%) Growth of nominal GDP (%)
Growth of Nasdaq index (%) Years of recession (from NBER)
Year
Pe
rc
en
ta
ge
gr
ow
th
Figure 13.14 Investment in new technologies and the dotcom bubble (1991–2020).
US Bureau of Economic Analysis. 2021.
Fixed Assets Accounts Tables
(https://tinyco.re/7765843). Note: the
series are in current US dollars. Nasdaq
value is the yearly average of the close
price value of the Nasdaq. Investment in
new technologies is the investment in
information processing equipment,
computers and peripheral equipment,
communication equipment,
communication structure, and IPPR
investments for software,
semiconductors, and other electronic
components and computers.
13.7 WHY IS INVESTMENT VOLATILE?
575
capacity utilization rate A measure
of the extent to which a firm,
industry, or entire economy is
producing as much as the stock of
its capital goods and current
knowledge would allow.
if it hires more employees. But there is not enough demand to sell the
products it would produce. This situation is called low capacity utiliz-
ation. The owners of Firm A have no incentive to hire more workers or to
install additional machinery (that is, to invest).
Firm B has the same problem. Because of low capacity utilization, profits
are low for both. Thus when we think about both firms together we have a
vicious circle:
If the owners of both A and B decide to invest and hire at the same time,
they would employ more workers, who would spend more, increasing the
demand for the products of both firms. The profits of both would rise, and
we have a virtuous circle:
These two circles highlight the role of expectations of future demand,
which depend on the behaviour of other actors. A game similar to those
studied in Unit 4 can illustrate how to get out of the vicious circle and into
the virtuous one. As in every game, we specify:
• The actors: The two firms.
• The actions that they can take: Invest, or do not invest.
• The information they have: They decide simultaneously, so they do not
know what the other has done.
• The payoff: The profits resulting from each of the four pairs of actions
that they could possibly take.
Low
expectations of
future demand
Little spending
by firms
or workers
Low capacity
utilization and
low profits
No incentive
to invest
or hire
Figure 13.15 Negative expectations of future demand create a vicious circle.
Firms invest
and hire
High capacity
utilization and
high profits
Higher spending
by firms and
workers
High demand
for the firm’s
products
Figure 13.16 Positive expectations of future demand create a virtuous circle.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
576
Nash equilibrium A set of
strategies, one for each player in
the game, such that each player’s
strategy is a best response to the
strategies chosen by everyone else.
The four possible outcomes of the interaction and the payoffs are given in
Figure 13.17.
From this figure you can see what happens when the virtuous (both
invest) and vicious (neither invest) circles occur. Note what happens if one
of the firms invests but the other does not. If Firm A invests and B does not
(the upper-right cell in the figure) then A pays to install new equipment and
premises, but because the other firm did not invest there is no demand for
the products that the new capacity could produce; so A makes a loss. But
had B known that A would invest, then B would have made higher profits
by investing as well (getting 100 rather than only 80). On the other hand,
had B known that A was not going to invest, then it would have done better
to also not invest.
In this game, the two firms will do better if they do the same thing, and
the best outcome is when both firms invest. This is another reason that
investment tends to fluctuate a lot. If owners of firms think that other firms
will not invest, then they will not invest, confirming the pessimism of the
other owners. This is why the vicious circle is self-reinforcing. The virtuous
circle is self-reinforcing for the same reason. Optimism about what other
firms will do leads to investment, which sustains the optimism.
There are two Nash equilibria in this game (upper-left and lower-
right). To find the Nash equilibria use the ‘dot’ and ‘circle’ method of Unit 4,
beginning with A’s best responses to B’s choices. If B invests, A’s best
response is also to invest so a dot goes into the upper-left cell. If B does not
invest, A chooses also not to invest so we place a dot in the bottom right-
hand cell. Notice that A does not have a dominant strategy. Now, we
consider B’s best responses. If A invests, B’s best response is to invest and if
A does not invest, B chooses not to invest. The circles showing B’s best
responses coincide with the dots: B also does not have a dominant strategy.
Where the dots and circles coincide, there are Nash equilibria.
The Nash equilibrium (lower-right) in which both firms have low
capacity utilization and low hiring and investment is not Pareto efficient,
because there is a change in which both make higher profits, namely if both
firms decide to invest. This situation is like the driving on the right or left
side of the road game, discussed in Unit 4, or the interaction described in
Figure 4.15 concerning specialization in different crops, or global climate
change described in Figure 4.17b. These are all called coordination games.
B invests B does not invest
B’s profit
100
100
80
–40
–40
80
10
10
A
do
es
n
ot
in
ve
st
A
in
ve
st
s
A’
s
pr
ofi
t
Figure 13.17 Investment decisions as a coordination game.
13.7 WHY IS INVESTMENT VOLATILE?
577
COORDINATION GAME
A game in which there are two
Nash equilibria and in which one
may be Pareto superior to the other
is called a coordination game.
• Driving on the right or the left is
a coordination game in which
neither equilibrium is
preferable to either player.
• In the crop specialization
coordination game in Unit 4
(Figure 4.15), specialization in
the ‘right’ crops (a different crop
for the two farmers, which their
land is more suited for) is better
for both than the ‘wrong
specialization’.
• In the investment coordination
game (Figure 13.17), an out-
come in which both invest is
better for both than neither
investing.
The name is very apt here because to make the move from the vicious to
the virtuous circle, the firms have to coordinate in some way (both agree to
invest) or develop optimistic beliefs about what the other will do. This kind
of optimism is often called business confidence, and it has a major role in
the fluctuations in the economy as a whole. As we will see in the next unit,
under some circumstances, government policy can also help shift an eco-
nomy from the Pareto-inefficient outcome to the Pareto-efficient outcome.
We can generalize the argument about the role of coordination in
investment to say that investment spending by firms will respond positively
to the growth of demand in the economy. Once an increase in aggregate
spending on home’s production of goods and services (that is, on C + I + G
+ X – M) occurs, this helps to coordinate the forward-looking plans of firms
about their future capacity needs, and stimulates investment spending.
Figure 13.18 illustrates the relationship between the growth of aggregate
demand (excluding investment), business confidence, and investment for
the Eurozone. The business confidence indicator moves closely with
aggregate demand (excluding investment) and investment.
Therefore we would expect the data from the national accounts to
confirm that consumption spending is smoother and investment spending
more volatile than GDP in the economy as a whole.
As expected, Figures 13.19a and 13.19b show that investment is much
more volatile than consumption in two rich countries (the UK and the US)
and two middle-income countries (Mexico and South Africa). The upward
and downward spikes in the red series for investment are larger than those
for the green series for consumption.
A close look at the charts for the rich countries also shows that, as
predicted, consumption is less volatile than GDP. The black peaks and
troughs for GDP are larger than the green ones for consumption. This is
less evident in the middle-income countries, perhaps because households
are more credit-constrained and therefore are less able to borrow in order
to smooth their consumption.
−15
−10
−5
0
5
10
−30
−20
−10
0
10
20
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
20
17
20
18
20
19
20
20
Year
G
ro
w
th
ra
te
(%
)
In
du
st
ri
al
co
nfi
de
nc
e
In
di
ca
to
r
(a
nn
ua
la
ve
ra
ge
)
Growth of demand (C + G + X – M) (left axis)
Growth of investment (I) (left axis)
Industrial confidence indicator (right axis)
Figure 13.18 Investment and business confidence in the Eurozone (1996–2020).
Eurostat. 2021. Confidence Indicators by
Sector. Federal Reserve Bank of St. Louis.
2021. FRED (https://tinyco.re/3965569).
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
578
How volatile is government spending? Unlike investment, government
spending (the G in the national accounts) does not respond to innovation or
fluctuate with business confidence. We would predict it to be less volatile
than investment. And net exports? The demand for exports will fluctuate
with the business cycle in other countries, and will be affected more by the
booms and recessions of the countries that are large export markets. Find
out about the volatility of government spending and net exports by
consulting FRED.
GDP Private Consumption Gross Investment
−20
−15
−10
−5
0
5
10
15
20
G
ro
w
th
ra
te
(%
)
UK
−20
−15
−10
−5
0
5
10
15
20
1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020
Year
G
ro
w
th
ra
te
(%
)
US
Figure 13.19a Growth rates of consumption, investment, and GDP in the UK and US,
per cent per annum (1956–2020).
View this data at OWiD https://tinyco.re/
2841924
View this data at OWiD https://tinyco.re/
2684283
Federal Reserve Bank of St. Louis.
2021. FRED (https://tinyco.re/3965569).
13.7 WHY IS INVESTMENT VOLATILE?
579
EXERCISE 13.7 CONSULTING FRED
For your own country, use data from FRED
(https://tinyco.re/5104028) to construct charts for the
growth rate of real GDP, consumption, investment, net
exports, and government expenditure.
For example, for the US these series are,
respectively: ‘Real Gross Domestic Product’ (GDPC1),
‘Personal Consumption Expenditures’ (PCE), ‘Gross
Private Domestic Investment’ (GDPI), ‘Net Exports of
Goods and Services’ (NETEXP), ‘Government Consump-
tion Expenditures and Gross Investment’ (GCE). For PCE,
GDPI, NETEXP and GCE, you simply need to add ‘Real’ to
get the equivalent series in real terms. For all these
series, you should find the equivalent ones for your own
country.
You can watch this short tutorial (https://tinyco.re/
3209844) to understand how FRED works.
1. How has government expenditure evolved in your
own country throughout the period for which data is
available?
2. Comment on the relationship between the growth
rate of output and government spending during this
period.
3. Describe the volatility of government spending and
net exports relative to that of GDP and suggest an
explanation for the patterns you observe.
GDP Private Consumption Gross Investment
−30
−20
−10
0
10
20
30
40
50
60
G
ro
w
th
ra
te
(%
)
Mexico
−20
−15
−10
−5
0
5
10
15
20
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020
Year
G
ro
w
th
ra
te
(%
)
South Africa
Figure 13.19b Growth rates of consumption, investment, and GDP in Mexico and
South Africa (1961–2020).
View this data at OWiD https://tinyco.re/
1934774
View this data at OWiD https://tinyco.re/
9278475
OECD. 2021. OECD Statistics
(https://tinyco.re/9377362); The World
Bank. 2021. World Development
Indicators (https://tinyco.re/9263826).
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
580
inflation An increase in the general
price level in the economy. Usually
measured over a year. See also:
deflation, disinflation.
deflation A decrease in the general
price level. See also: inflation.
QUESTION 13.8 CHOOSE THE CORRECT ANSWER(S)
Consider a local economy comprising of just two firms, Firm A and Firm
B. Currently both firms have low capacity utilization. The following
table shows the profits (or losses if negative) when the firms invest or
do not invest:
Firm B invests Firm B does
not invest
Firm B’s profit
150
100
80
–20
–40
60
40
20Fir
m
A
d
oe
s
no
t i
nv
es
t
Fi
rm
A
in
ve
st
s
Fi
rm
A
’s
p
ro
fit
Based on this information, which of the following statements is
correct?
Investing is a dominant strategy for both firms.
The only Nash equilibrium is for both firms to invest.
Firm A investing and Firm B not investing is a Pareto-inefficient
Nash equilibrium.
To achieve the Pareto-efficient Nash equilibrium, the firms have to
coordinate in some way or develop business confidence.
••13.8 MEASURING THE ECONOMY: INFLATION
In Figures 13.20a and 13.20b we repeat the graphs from Figure 13.3,
showing the growth rate of GDP and the unemployment rate in the UK
from 1875 to 2020.
In Figure 13.20c, we show the rate of inflation over this period.
Inflation is an increase in the general price level in the economy, usually
measured over a year. For the British economy, inflation ranges from a low
level, with prices actually falling (called deflation) for much of the inter-
war period before and after the Great Depression, to a peak of nearly 25%
per annum in 1975.
Previously we saw that the downward spikes of economic crises were
associated with upward spikes of unemployment; we now see that inflation
was especially low in the 1930s and especially high in the 1970s. The peak
in inflation followed the first of two oil price shocks (1973 and 1979) that
were major disturbances to the global economy.
Figure 13.21 shows average rates of inflation in different regions of the
world, and how they have changed over time. Upward spikes in inflation have
tended to occur in periods of economic crisis, but the general trend worldwide
since the 1970s has been a decline in inflation rates. The figure also shows that
inflation tends to be higher in poor than in rich countries. For instance, since
13.8 MEASURING THE ECONOMY: INFLATION
581
2000, inflation has averaged 6.0% in sub-Saharan Africa and 6.6% in south
Asia, in contrast to only 2.2% in the high-income OECD countries.
What is inflation?
Take your favourite chocolate bar. If its price goes up during the year from
50p to 55p, how do you know that is a symptom of inflation in the economy?
It could just be that the chocolate bar has become more expensive relative to
everything else, as a result of a rightward shift in the demand curve or a
leftward shift in the supply curve of the kind we studied in Unit 8. To see
what has happened to prices across the economy, take a giant shopping basket
and fill it with every product and service that you buy in January. Has the
1918
End of WWI
1929
Start of Great
Depression
1945
End of WWII
1970s
2008
Start of global
financial crisis
−12
−10
−8
−6
−4
−2
0
2
4
6
8
10
12
18
75
18
80
18
85
18
90
18
95
19
00
19
05
19
10
19
15
19
20
19
25
19
30
19
35
19
40
19
45
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
Year
G
D
P
gr
ow
th
(%
)
Figure 13.20a UK GDP growth (1875–2020).
See more https://tinyco.re/5644921
Ryland Thomas and Nicholas Dimsdale.
(2017). ‘A Millennium of UK Data’
(https://tinyco.re/0223548). Bank of
England OBRA dataset; UK Office for
National Statistics. (2021). UK Economic
Accounts time series (https://tinyco.re/
3387553).
1918
End of WWI
1929
Start of Great
Depression
1945
End of WWII
1970s
2008
Start of global
financial crisis
0
2
4
6
8
10
12
14
16
18
75
18
80
18
85
18
90
18
95
19
00
19
05
19
10
19
15
19
20
19
25
19
30
19
35
19
40
19
45
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
Year
U
ne
m
pl
oy
m
en
tr
at
e
(%
)
Figure 13.20b UK unemployment rate (1875–2020).
See more https://tinyco.re/7644132
Ryland Thomas and Nicholas Dimsdale.
(2017). ‘A Millennium of UK Data’
(https://tinyco.re/0223548). Bank of
England OBRA dataset; UK Office for
National Statistics. (2021). UK Economic
Accounts time series (https://tinyco.re/
3387553).
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
582
consumer price index (CPI) A
measure of the general level of
prices that consumers have to pay
for goods and services, including
consumption taxes.
price of this same giant basket increased when you check the prices in
January the following year? And what about the baskets of other people?
The Consumer Price Index (CPI) measures the general level of prices
that consumers have to pay for goods and services, including consumption
taxes. The basket of goods and services is chosen to reflect the spending of a
typical household in the economy. For this reason, the change in the CPI, or
CPI inflation, is often considered to measure changes in the ‘cost of living’.
The CPI is based on what consumers actually buy. It includes the prices
of food and drink, housing, clothing, transportation, recreation, education,
communications, medical care, and other goods and services. The goods
and services in the basket are weighted according to the fraction of house-
hold spending they account for. The CPI excludes exports, which are
consumed by foreign residents, but includes imports, which are consumed
by households in the home economy. The change in the CPI over the past
year is commonly used as a measure of inflation.
1918
End of WWI
1929
Start of Great
Depression
1945
End of WWII 1970s
2008
Start of global
financial crisis
−20
−10
0
10
20
30
18
75
18
80
18
85
18
90
18
95
19
00
19
05
19
10
19
15
19
20
19
25
19
30
19
35
19
40
19
45
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
Year
CP
Ii
nfl
at
io
n
(%
)
Figure 13.20c UK inflation rate (1875–2020).
See more https://tinyco.re/3201694
Ryland Thomas and Nicholas Dimsdale.
(2017). ‘A Millennium of UK Data’
(https://tinyco.re/0223548). Bank of
England OBRA dataset; UK Office for
National Statistics. (2021). UK Economic
Accounts time series (https://tinyco.re/
3387553).
−5
0
5
10
15
20
25
30
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
Year
CP
Ii
nfl
at
io
n
(%
)
East Asia & Pacific
Middle East & North Africa
High Income: OECD
South Asia
Latin American and Caribbean
Sub-Saharan Africa
Figure 13.21 Inflation levels and volatility in high- and low-income economies.
View this data at OWiD https://tinyco.re/
3937469
The World Bank. 2021. World
Development Indicators
(https://tinyco.re/9263826).
13.8 MEASURING THE ECONOMY: INFLATION
583
GDP deflator A measure of the
level of prices for domestically
produced output. This is the ratio of
nominal (or current price) GDP to
real (or constant price) GDP.
The GDP deflator is a price index like the CPI, but it tracks the change
in prices of all domestically produced final goods and services. Instead of a
basket of goods and services, the GDP deflator tracks the price changes of
the components of domestic GDP, that is, of C + I + G + X – M (the GDP
deflator includes exports, which are produced by the home economy, but
excludes imports, which are produced abroad).
The GDP deflator can also be expressed as the ratio of nominal (or
current price) GDP to real (or constant price) GDP. The GDP deflator series
is most commonly used to transform a nominal GDP series into a real GDP
series. As we saw in Section 1.2 and Unit 1’s Einstein section, the real GDP
series shows how the size of the home economy changes over time, taking
into account changes in the price of domestically produced goods and
services.
EXERCISE 13.8 MEASURING INFLATION
Go to the Office for National Statistics (ONS) website (https://tinyco.re/
5469853), scroll to ‘2. The shopping basket’ and answer these questions:
1. How does a national statistical authority such as the ONS in the UK
construct a giant representative shopping basket for the whole popula-
tion?
2. If inflation this year is 2.5%, then what is the current price of the
representative shopping basket that cost £100 last year?
The official national inflation rate does not necessarily reflect your own
personal inflation rate. If you want to calculate your own personal
inflation rate and how it deviates from the national one, some national
statistics agencies offer a personal inflation calculator, such as Statistics
Netherlands (https://tinyco.re/0093731) or Statistics South Africa
(https://tinyco.re/7543547). Your own office of national statistics may also
have a personal inflation calculator.
3. Using a personal inflation calculator, calculate your personal inflation
rate and comment on how and why it differs from the official inflation
rate for your country.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT
584
EXERCISE 13.9 THE CPI AND THE GDP DEFLATOR
1. Use the data from FRED (https://tinyco.re/5104028) to construct charts
for annual real GDP growth (GDPC1), the unemployment rate
(UNRATE), and the inflation rate (CPIAUCSL. Hint: how is the inflation
rate calculated from the Consumer Price Index?) for the US. Select the
period from 1960 until the most recent year available. In addition,
download the data for the US GDP deflator (search for GDPDEF). Make
sure your series are all in annual frequency. You can change the
frequency by using the ‘Edit graph’ button, above the top-right corner
of your graph. You can watch this short tutorial (https://tinyco.re/
3209844) to understand how FRED works.
Use the data you downloaded to answer the following questions
(remember that the CPI is calculated from the price of goods consumed in
the home country, while the GDP deflator is calculated from the price of
the goods produced in the home country):
2. The main difference in the evolution of the series for the CPI and the
GDP deflator takes place in 1974–75 and 1979–1982. What could
explain this pattern? (Hint: think about the likely impact of an oil crisis
on the price of imported goods and, in particular, on your own
transport and fuel bills.)
3. What do you notice about the evolution of unemployment and inflation
in the early 1980s?
4. Now construct the same charts for your own country. Write a brief
report on the evolution of inflation, unemployment, and the real GDP
growth rate over the same period.
13.9 CONCLUSION
In this unit, we have introduced two essential tools for understanding the
economy: the national accounts used to measure aggregate economic
activity, and a set of models that allow us to organize the data in ways that
illuminate economic fluctuations. Economists are often asked to provide
forecasts about the future development of the economy, and they use both
data and models to do this. We have learned in this unit that households
and firms make forecasts when deciding on their spending.
In the following two units, we focus on government policy. We shall see
that in order to make good forecasts and good policies, the government and
central bank need to take into account how households and firms think
about the future and what may disrupt their plans.
13.9 CONCLUSION
585
Concepts introduced in Unit 13
Before you move on, review these definitions:
• Recession
• Okun’s law
• Circular flow of production, income, and spending
• Aggregate demand and its components: Y, C, I, G, X, M
• Government transfer payments
• Self-insurance and co-insurance
• Capacity utilization rate
• Investment as a coordination game
• Inflation, CPI, and GDP deflator
13.10 REFERENCES
Consult CORE’s Fact checker for a detailed list of sources.
Ball, Laurence, Daniel Leigh and Prakash Loungani. 2017. ‘Okun’s Law: Fit
at 50?’ (https://tinyco.re/5970004). Journal of Money, Credit and
Banking 49 (7): pp. 1413-1441
Ball, Laurence, Davide Furceri, Daniel Leigh and Prakash Loungani. 2019.
‘Does One Law Fit All? Cross-Country Evidence on Okun’s Law’
(https://tinyco.re/7744920). Open Economies Review 30: pp. 841-874
Carlin, Wendy and David Soskice. 2015. Macroeconomics: Institutions,
Instability, and the Financial System. Oxford: Oxford University Press.
Chapters 1 and 10.
Clark, Andrew E., and Andrew J. Oswald. 2002. ‘A Simple Statistical
Method for Measuring How Life Events Affect Happiness’
(https://tinyco.re/7872100). International Journal of Epidemiology
31 (6): pp. 1139–1144.
Collins, Daryl, Jonathan Morduch, Stuart Rutherford, and Orlanda
Ruthven. 2009. Portfolios of the Poor (https://tinyco.re/8070650).
Princeton: Princeton University Press.
Durante, Ruben. 2010. ‘Risk, Cooperation and the Economic Origins of
Social Trust: An Empirical Investigation’ (https://tinyco.re/7674543).
Sciences Po Working Paper.
Fletcher, James. 2014. ‘Spurious Correlations: Margarine Linked to
Divorce?’ (https://tinyco.re/6825314). BBC News.
Jappelli, Tullio, and Luigi Pistaferri. 2010. ‘The Consumption Response to
Income Changes’ (https://tinyco.re/3409802). VoxEU.org.
Naef, Michael, and Jürgen Schupp. 2009. ‘Measuring Trust: Experiments
and Surveys in Contrast and Combination’ (https://tinyco.re/
3956674). IZA discussion Paper No. 4087.
OECD. 2010. Employment Outlook 2010: Moving Beyond the Jobs Crisis
(https://tinyco.re/5607435).
Shiller, Robert. 2009. ‘Animal Spirits’ (https://tinyco.re/9820978).
VoxEU.org podcast. Updated 14 August 2009.
The Economist. 2009. ‘Smooth Operators’ (https://tinyco.re/7009658).
Updated 14 May 2009.
The Economist. 2012. ‘New Cradles to Graves’ (https://tinyco.re/8856321).
Updated 8 September 2012.
UNIT 13 ECONOMIC FLUCTUATIONS AND UNEMPLOYMENT