Download Lecture 1 The Facts of Growth

Lecture 1: Macroeconomics Third Year
• Overview of course
– Intermediate level macroeconomic theory course
– Basic text is “Macroeconomics – 5th edition” by
Olivier Blanchard
– Course outline at www.kennethcreamer.co.za
– Lecture 1-7 Kenneth Creamer (Thursday 8:00
FNB33)
– Lecture 8-14 Chris Malikane Creamer (Thursday
8:00 FNB33)
– Evaluation: Tests 18 August and 29 September,
plus Exam
• Growth Theory – understanding the drivers of
long-run economic growth
• The role of expectations in macroeconomic
theory
• Open economy analysis – including analysis of
various exchange rate regimes
• The conduct of Monetary and Fiscal Policy
Growth Theory – The facts of growth
1.
2.
3.
4.
Distinguishing the short-run and the long-run
Measuring the standard of living
Growth across time and space
A formal framework for understanding
growth
1.Short run vs. Long-run
• Important to distinguish the determination of
output in the short and medium run—where
fluctuations dominate—from the determination of
output in the long run—where growth dominates.
• Cycle vs. trend
• Traditional demand management through fiscal
and monetary policy is concerned with countercyclical short- to medium- run stabilisation
• Growth theory is about growth trends (and the
determinants of growth) in the longer run
•Growth is the steady increase in aggregate output
over time.
2. Measuring the Standard of
Living
Growth is linked to the standard of living.
Furthermore, comparisons over time or across countries is output per person (GDP
per capita) rather than output itself.
The straightforward method of taking a country’s GDP expressed in that country’s
currency, and then using the current exchange rate to express it in terms of dollars
does not always work for two reasons:
– Firstly, the exchange rates varies (as the Rand strengthens from R10/$ to R7/$ it
is not correct to simply state that South Africa’s standard of living (reflected in a
GDP of R2-trillion) has increased from U2$200-bn to around US$285-bn in a short
time period..
– Secondly, the prices of basic goods is much lower in poorer countries than in rich
countries, in fact “the lower a country’s GDP per capita the lower the prices of
food and basic services” and hence the standard of living is not quite as low as
that implied by a direct comparison of the GDP per capita data (e.g. in 2006 USA
US$44 000 GDP p.c. vs. India US$790 GDP p.c. would be a 55x higher standard of
living)
Measuring the Standard of Living
• What method do economists use to compare more accurately the standard
of living across countries?
• Economists develop a common set of prices for all countries – known as
purchasing power parity (PPP) adjusted GDP and GDP per capita.
•Example of the effect: For 2006, once a common set of prices is used for
food and basic goods in India and the US, the US GDP p.c. is 12x larger than
the GDP p.c. in India. This is because the amount of money that Indian’s
spend on food and basic goods is re-priced at a common PPP level of
US$3666 p.c. (instead of US$790)
•Process of construction of PPP adjusted GDP.
• International dollar prices are constructed and outlined in the “Penn World
Tables.” (Penn stands for the University of Pennsylvania, where the project
is taking place.)
• Led by three economists—Irving Kravis, Robert Summers, and Alan
Heston, who have constructed PPP series not only for consumption (as per
the US - India example) but, more generally, for GDP and its components,
going back to 1950, for most countries in the world.
Growth and happiness (across
countries)
• See Fig.1 – there is broadly a positive correlation
across countries between GDP p.c. (at PPP prices)
and % of people surveyed who are happy or very
happy (late 1990’s survey), further specific
conclusions:
• Countries with very low happiness – difficult political
transitions
• Amongst rich countries (GDP p.c. > US$20 000)
there is little relation between income and happiness
• Caveat: cross-cultural comparisons of happiness are
inherently difficult
Fig.1 – positive correlation between
GDP p.c. and happiness
Growth and happiness (within countries)
• Within the US between 1975 and 1996 GDP p.c.
increased by over 60% BUT, there was basically no
change in the distribution of happiness (Table 1)
• YET, rich people self report a higher level of
happiness than poor people (Table 2)
Growth and happiness (within countries)
Table 1
Distribution of Happiness in the United
States Over Time
(Percent)
1975
1996
Very happy
32
31
Pretty happy
55
58
Not too happy
13
11
Table 2
Income Level
Distribution of Happiness in the United
States Across Income Groups (Percent)
Top Quarter
Bottom Quarter
Very happy
37
16
Pretty happy
57
53
Not too happy
6
31
3. Growth in Rich Countries since
1950





There has been a large increase in output per person (See table
10.1)
There has been evidence of convergence of output per person
across countries – emerging economies grow faster and thus the
gap in GDP p.c. has been closing between many rich and poor
countries.
Real output per capita has increased by a factor of 3.2 since 1950
in the United States, by a factor of 4.4 in France, and by a factor of
11.2 in Japan.
These numbers show what is sometimes called the force of
compounding
NOTE: A policy that leads to a 1% increase in growth rate every
year for 40 years (e.g. 6% growth instead of 5% growth) leads to a
standard of living that is 48% higher than it would have been
(1.0140 – 1 = 48%) (China vs. Africa – divergence)
Table 10-1 The Evolution of Output per Person in Four Rich Countries
since 1950
Annual Growth Rate
Output per Person (%)
1950–2004
Real Output per
Person (2000 dollars)
1950
2004
2004/1950
France
3.3
5,920
26,168
4.4
Japan
4.6
2,187
24,661
11.2
United Kingdom
2.7
8,091
26,762
3.3
United States
2.6
11,233
36,098
3.2
Average
3.5
6,875
28,422
3.9
Note on Logarithmic scale
• The characteristic of a logarithmic scale is that
the same proportional increase in a variable is
represented by the same distance on the
vertical axis. (whereas linear scale shows units
at a constant distance)
• This is useful in measuring growth to avoid the
appearance of highly concave time series, e.g.
where 3% growth from a base of R2-trn in the
first year = R60-bn, but by year 100 is
2(1,03)100 = R38,4-trn (see Figs A2.1 and A2.2)
Growth in Rich Countries since 1950
(cont.)
• Countries with lower levels of output per
person in 1950 have typically grown faster
(See Fig.10.2)
• The convergence of levels of output per capita
across countries extends to the set of OECD
countries.
Figure 10 - 2
Growth Rate of GDP per
Person since 1950
versus GDP per Person
in 1950, OECD Countries
Countries with lower levels of
output per person in 1950 have
typically grown faster.
The convergence of levels of output per capita across countries
is not specific to the four countries we are looking at, it also
extends to the set of OECD countries.
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Growth trends across many countries –
evidence of convergence?
• There is no clear evidence of convergence across all countries
from 1960 to the present (See Fig.10.3)
• OECD – there is clear evidence of convergence as countries
with lower levels of output per person have typically
grown faster
• Asia – countries have generally shown convergence as they
have high growth rates for lower initial levels of output per
person
• Africa – no evidence of convergence, that is, countries with
initially low levels of output have not shown positive growth (in
fact have often shown negative growth in GDP p.c.)
Figure 10 - 3
Growth Rate of GDP per
Person since 1960
versus GDP per Person
in 1960 (2000 dollars) for
70 Countries
There is no clear relation
between per person the growth
rate of output since 1960 and
the level of output per person in
1960.
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Growth over a longer period
• There is agreement among economic historians about the main economic evolutions
over the last 2,000 years:
– From the end of the Roman Empire to roughly the year 1500, there was
essentially no growth of output per person in Europe.
– From about 1500 to 1700, growth of output per person turned positive, about
0.1% per year. It increased to 0.2% per year from 1700 to 1820.
– This period of stagnation of output per person is often called the Malthusian era.
Europe was in a Malthusian trap, unable to increase its output per person.
Malthus argued that any increase in output would lead to a decrease in mortality,
leading to an increase in population until output per person was back at its initial
level.
– On the scale of human history, the growth of output per capita is a recent
phenomenon – post Industrial Revolution.
Note on Growth Theory vs.
Development Economics
• Growth theory takes many of the institutions of a
country e.g. legal system, form of government,
etc. as given
• Development economics seeks to ascertain what
institutional reform would assist in creating an
environment for sustained growth
• David Landes Wealth and Poverty of Nations
using a close historical analysis of institutions to
explain why some countries are rich and some
countries are poor. (“Developmental State”)
4. A formal framework for
understanding growth
• To think about the facts presented in the previous
sections, we use the framework of analysis
developed by Robert Solow, from MIT, in the late
1950s. Particularly:
– What determines growth?
– What is the role of capital accumulation?
– What is the role of technological progress?
Aggregate production function
• The aggregate production function is a specification of
the relation between aggregate output and the inputs
in production.
• Y = F(K,N)
• Y = aggregate output.
• K = capital — the sum of all the machines, plants,
and office buildings in the economy.
• N = labor — the number of workers in the
economy.
• The function F, which tells us how much output is
produced for given quantities of capital and labor,
is the aggregate production function.
State of technology
• The aggregate production function depends on the state of
technology. The higher the state of technology, the higher
the output that can be achieved from a given K and a given
N.
• The state of technology can be narrowly understood
as a set of blue prints defining the range of products
and the techniques available to produce them.
• A wider definition of the state of technology would
include the way in which the economy is organised,
the internal organisation of firms and the legal and
political systems (or institutions) e.g. the legal
protection of intellectual property to reward, protect
and encourage invention and innovation.
Returns to Scale
• Constant returns to scale is a property of the
economy in which, if the scale of operation is
doubled—that is, if the quantities of capital
and labor are doubled—then output will also
double.
• 2Y=F(2K,2N), or
• xY=F(xK,xN)
Returns to Factors
• What happens where the quantity of one
factor of production is increased and the other
factors is held constant?
• Decreasing returns to capital – where
increases in capital (given fixed labour) leads
to smaller and smaller increases in output
• Decreasing returns to labour – where
increases in labour (given fixed capital) leads
to smaller and smaller increases in output
Output per worker and Capital per worker
• Constant returns to scale implies that we can rewrite
the aggregate production function as (where x = 1/N):
Y
 K N
K 
 F  ,   F  ,1
 N N
N 
N
• The amount of output per worker, Y/N depends on
the amount of capital per worker, K/N.
– As capital per worker increases, so does output per
worker – known as a process of capital accumulation
of capital deepening. See Fig.10.4
Output per worker and Capital per worker
• Increases in output per worker (Y/N) can come
from increases in capital per worker (K/N), but
at a decreasing rate
• In Fig 10.4 the increase in capital per worker
AB = CD, but the increase in output per worker
A’B’>C’D’.
• This is due to the fact of decreasing returns to
capital where the quantity of labour is fixed
Figure 10 - 4
Output and Capital per
Worker
Increases in capital per worker
lead to smaller and smaller
increases in output per worker.
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Sources of Growth
– Firstly, increases in output per worker (Y/N) (or
output per person - if the ratio of workers to the
population remains constant) can come from capital
accumulation – i.e. increase in capital per worker
(K/N) (move along the production function)
• Secondly, increases in output per worker (Y/N) can
come from technological progress that shifts the
production function and leads to more output per
worker given capital per worker.
– See Fig.10.5 where an improvement in technology shifts the
production function up from F(K/N,1) to F(K/N,1)’ , leading to an
increase in output per worker for a given level of capital per worker.
Figure 10 - 5
The Effects of an
Improvement in the
State of Technology
An improvement in technology
shifts the production function
up, leading to an increase in
output per worker for a given
level of capital per worker.
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Conclusion
• These two factors play very different roles in the growth process:
– Capital accumulation by itself cannot sustain growth due to the
decreasing returns to capital. As a result larger and larger
increases in capital per worker would be required and the
economy would not be unwilling to save and invest sufficiently
to sustain such capital accumulation. Savings play an
important role in determining the level of output per person,
but do not determine the growth rate or output. (Chapter 11)
– Sustained growth requires sustained technological progress.
The economy’s rate of growth of output per person is
eventually determined by the economy’s rate of technological
progress both narrowly defined (in terms of R&D, patents and
Education and Training) and broadly defined (in terms of
broader social and government institutions (Chapter 12 and 13)