Transcript Lecture 4: Productivity, Output, and Unemployment in the Short Run

Lecture 4: Productivity, Output, and Unemployment
in the short-run and long-run
• Key issues
• The short-run response of employment to technological
progress is ambiguous – increases in productivity
sometimes decrease unemployment and sometimes
increase unemployment
• In the medium to long-run increases in productivity are
associated with lower unemployment
• Technological progress leads to structural change – job
creation and job destruction (“Creative destruction” has
distribution effects)
• Why some countries experience technological progress and
others do not depends on institutions such as property
rights
Structure of lecture
1. Technological progress and AS and AD (in the
short-run)
2. Productivity and the natural rate of
unemployment (in the long-run)
3. Distribution effects of technological change
4. Institutions and technological change
1. Technological progress in short-run: Production Function
A production function with technological progress can be written as:
Y  F ( K, AN )
Leaving aside matters concerning capital, then:
Y  AN
Output is produced using only labor, N, and each worker produces A units of output.
Increases in A represent technological progress.
A has two interpretations:
1.A indicates the state of technology
2.A indicates the degree of labour productivity i.e. Y/N
Furthermore, employment is equal to output divided by productivity:
N=Y/A
That is, given a certain level of output, an increase in productivity decreases the level
of employment needed to produce such output.
Key question: When productivity increases does output (Y) increase enough to avoid
a decrease in employment (N) (s-r: answer is ambiguous; l-r: answer is yes)
Technological Progress, AS and AD, in the short-run
•Recall the basic structure of the aggregate supply and aggregate
demand model (Fig 13.1):
– Output (Y) is determined by the intersection of the aggregate supply
curve and the aggregate demand curve. (At Y there is equilibrium in
labour, goods and financial markets)
– The aggregate supply relation gives the price level for a given level
of output. Upward sloping (YP) as an increase in output leads to
an increase in employment, which leads to an increase in nominal
wages and an increase in the price level.
– The aggregate demand relation gives output for a given price level.
Downward sloping (YP) as an increase in the price level leads to
a decrease in the demand for output i.e. on increase in prices leads
to a decrease in real money stock (M/P) resulting in higher interest
rates, decreased demand and decreased output.
Technological Progress, Aggregate Supply,
and Aggregate Demand
Figure 13 - 1
Aggregate Supply and
Aggregate Demand for a
Given Level of Productivity
The aggregate supply curve is
upward sloping: An increase in
output leads to an increase in
the price level. The aggregate
demand curve is downward
sloping: An increase in the
price level leads to a decrease
in output.
What happens to AS-AD if productivity (A) increases?
• AS curve shifts DOWN (Fig 13.2) – as the effect of
productivity increase is to decrease the amount of
labour needed to produce a unit of output (reducing
costs), therefore prices are reduced at each level of
output and AS
• AD curve shifts UP or DOWN – depending on what
triggered the increase in productivity:
– Case 1: wide implementation of new technology AD as demand
increases at the given price level due to consumption increases on
prospect of future growth, investment increases due to prospect of
higher future profits (exogenous change in productivity)
– Case 2: more efficient use of existing labour and technology (or
downsizing due to trade) AD which may lead to reduced
consumption
Technological Progress, Aggregate Supply,
and Aggregate Demand
Figure 13 - 2
The Effects of an Increase in
Productivity on Output in
the Short Run
An increase in productivity
shifts the aggregate supply
curve down. It has an
ambiguous effect on the
aggregate demand curve,
which may shift either to the left
or to the right. In this figure, we
assume that it shifts to the
right.
The effect of technological progress on
output and employment
• As per Fig13.2 even in Case 1 where technological progress
leads to increased supply and demand and there is an
unambiguous increase in equilibrium output (i.e. low costs
and high demand lead to Y), it is not clear what happens to
employment (as N = Y/A)
• % change in employment (N) = % change in output (Y) - %
change in productivity (A)
• Condition employment will increase if % ΔY > %ΔA (i.e. if
productivity increases by 2% then output must increase by at
least 2% to avoid a decrease in employment)
• Conclusion: in the short-run an increase in productivity may
or may not lead to an increase in employment (theory does
not settle the issue)
The Empirical Evidence in the short-run
• Fig 13.3 plots productivity growth and
output growth in the US from 1960 to
2005
• It shows a strong positive relation
between output growth and productivity
growth
• Also generally ΔY>ΔA which should be
positive for employment levels
The Empirical Evidence (short-run)
Figure 13 - 3
Labor Productivity and
Output Growth in the
United States since 1960
There is a strong positive
relation between output growth
and productivity growth. But the
causality runs from output
growth to productivity growth,
not the other way around.
The Empirical Evidence (short-run)
• But, empirically there is a problem as in the shortrun the causal relationship runs from output growth
to productivity growth (not from productivity
growth to output growth)
• As demand rises firms use existing labour more
intensively and there is higher productivity (but this
is not due to the introduction of a new exogenous
technology) (referred to as “labour hoarding” during
bad times)
• Conclusion: The empirical finding is ambiguous –
sometimes in the short-run an increase in
productivity leads to increased output and
employment (and sometimes it does not)
2. Productivity and the Natural Rate of Unemployment (long-run)
• Key question: Is the medium to long-run natural rate of unemployment
affected by productivity changes?
• A naïve argument is that of Technological unemployment—a concept
associated with the technocracy movement during the Great Depression
(and Luddites and Saboteurs)—that unemployment comes from the
introduction of machinery.
• In its crudest form, the argument that technological progress must lead to
unemployment is false, as there have been large increases in the standard
of living and in employment in advanced countries during the 20th century
e.g. US and Japan have had highest productivity growth and lowest levels
of unemployment in OECD.
• A more sophisticated version of the argument cannot, however, be
dismissed so easily. That is that perhaps periods of fast technological
progress are associated with a higher natural rate of unemployment, and
periods of slower technological progress are associated with a lower
natural rate of unemployment. (To answer this, it is useful to analyse how
price setting and wage setting are effected by changes in productivity.)
Price Setting and Wage Setting Revisited
• Consider price setting:
– From Y=AN, each worker produces A units of output i.e. producing 1
unit of output requires 1/A workers.
– If the nominal wage is equal to W, the nominal cost of producing one
unit of output is therefore equal to (1/A) W = W/A.
– If firms set their price equal to 1+ times cost, the price level is given
by:
W
Price setting P  (1   )
A
– It can be seen that an increase in productivity (A) reduces costs,
which has the effect of decreasing the price level (P) given the
nominal wage (W)
Price Setting and Wage Setting
Consider wage setting:
Wages are typically set to reflect the increase in productivity over time (i.e. if
productivity has been rising by 2% a year for some time wage increases will
rise by 2% per year):
Wage setting W  A P F (u, z )
e
e
Wages depend on the following factors:
– Workers care about real wages, not nominal wages, so
wages depend positively on the (expected) price level, Pe.
– Wages depend negatively on the the unemployment rate
(u)
– Wages depend on institutional factors (z)
– Wages also depend positively on the expected level of
productivity, Ae.
Price-setting (Fig 13.4)
• The natural rate of unemployment is determined by price
setting and wage setting relations
• A condition of the natural rate is that expectations are correct
i.e. Pe = P and Ae =A
• The price setting equation can be reorganised as follows:
W
Price setting P  (1   )
A
W
A

P 1 
• As A increases, the real wage paid by firms, W/P, increases
one for one with productivity, A i.e. higher productivity (A)
means lower prices set by firms (P), given the nominal wage
(W), therefore, the real wage (W/P) rises .
• This is outlined in Fig 13.4 where shift from A to A’ leads to a
rise in real wages (but no change in the natural rate of
unemployment)
The Natural Rate of Unemployment
Figure 13 - 4
The Effects of an Increase in
Productivity on the Natural
Rate of Unemployment
An increase in productivity
shifts both the wage and the
price-setting curves by the
same proportion and thus has
no effect on the natural rate.
Wage-setting (Fig 13.4)
• Under the condition that expectations are correct,
then Pe=P and Ae=A, the wage-setting equation
becomes:
Wage setting W  A P F (u, z )
e
e
W
 AF (u, z)
P
• The real wage (W/P) depends on both the level of
productivity and the unemployment rate.
• In Fig 13.4 the real wage (W/P) is a decreasing
function of the unemployment rate i.e. as u
therefore W/P 
• If A rises to A’ then the real wage (W/P) rises for any
given natural rate
Response to a rise in A (Fig 13.4)
• Suppose A increases by 3%, so A’ = 1.03 x A
• The real wage (W/P) increases by 3%, this is implied by the
A
upward shift in the price setting curve given by: W
P

1 
• The wage setting curve also shifts up 3% at a given natural rate
W
of u, and W/P increases as per:
P
 AF (u, z)
• At B’ both curves shift up proportionally and the real wage is
higher by 3% and the natural rate of unemployment remains the
same (Fig13.4)
• Conclusion: A 3% rise in productivity leads firms to reduce
price by 3%, leading to 3% increase in real wages (due to price
setting and confirmed by wage setting), with natural rate of
unemployment unchanged
Empirical Evidence (long-run)
• Theoretical result: the long-run natural rate of
unemployment does not depend on the level of
productivity (nor on the rate of productivity
growth)
• Empirical reality: a positive relationship appears
to be present between productivity growth and
the level of long-run employment
– See Fig.13.5 which indicates that in the US decades of
higher productivity growth are associated with a lower
unemployment rate (1940’s, 50’s and 60’s) and low
productivity growth results in higher unemployment
(1970’s and 80’s)
Empirical Evidence (long-run)
Figure 13 - 5
Productivity Growth and
Unemployment— Averages
by Decade, 1890 to 2000
There is little relation between the
10-year averages of productivity
growth and the 10-year averages
of the unemployment rate. If
anything, higher productivity
growth is associated with lower
unemployment.
Empirical Evidence (long-run)
• Measurement issues:
• Difficult to measure the natural rate of unemployment (as
it is not observable) solution: use the actual average rate
of unemployment over decades – this is a satisfactory
approximation because the actual rate of unemployment
moves around the natural rate
• Measuring average productivity growth over a decade
takes care of labour hoarding, as productivity gains due to
increased use of existing labour may be significant in the
short-run, changes in labour hoarding are unlikely to
impact on productivity growth over a decade
Empirical Evidence (long-run)
• How does theory explain the inverse relationship between
productivity growth (A) and unemployment (u)t i.e. high
productivity growth (A) leads to lower natural rate of
unemployment (u)
• As follows:
– It takes time for expectations to adjust to the reality of
productivity growth
– As a result in the context of a slow down in productivity growth
- slow expectations adjustment means that workers keep
asking for wage increases that are too high for the new lower
rate of productivity growth (leading to lower levels of
employment i.e. Au)
– Or in reverse, if there is an increase in productivity growth,
slow expectations adjustment means that workers do not
upwardly adjust their salary increases (leading to higher levels
of employment Au)
Empirical Evidence (long-run)
• If price expectations are correct (Pe = P)
• But productivity expectations are NOT correct
(Ae≠A)
• Then the implied price-setting and wage setting
relations are given by:
W
A
Price setting:

P
1 
W
 A e F(u.z)
P
Wage setting:
e
• If productivity
growth
declines
then
A

increases for some time by more than A (Ae>A)
Empirical Evidence (long-run)
• If (Ae>A) i.e. expectations adjust slowly to reduced
productivity growth then the wage setting relation shifts
up by more than the price setting relation (equilibrium
shifts from B to B’ in Fig 13.6 resulting in an increase in
the natural rate of unemployment from un to un’)
• The natural rate of unemployment will remain high until
expectations of productivity have adjusted to the new
reality (where Ae=A)
• Conclusion: after the slowdown in productivity growth
workers ask for larger wage increases than firms are
able to give, leading to a rise in unemployment. As
expectations adjust unemployment will fall back to its
original level.
Empirical Evidence (long-run)
Figure 13 - 6
The Effects of a Decrease in
Productivity Growth on the
Unemployment Rate When
Expectations of Productivity
Growth Adjust Slowly
If it takes time for workers to
adjust their expectations of
productivity growth, a slowdown
in productivity growth will lead to
an increase in the natural rate for
some time.
Summary of findings (short-run and long-run)
– In the short run, the response of employment to
technological progress is ambiguous – increases in
productivity sometimes decrease unemployment and
sometimes increase unemployment. (See slide on the the
US Jobless Recovery in early 2000’s)
– In the medium to long-run, there is an inverse relation.
Lower productivity growth leads to higher unemployment
and higher productivity growth leads to lower
unemployment.
– So where do fears of technological unemployment come
from? They must be based in structural change – the
change in the structure of the economy induced by
technological progress, a process which produces
“winners and losers”
The New Economy, the U.S. Expansion of the 1990s,
and the Jobless Recovery of the Early 2000s
By the end of 2001, the recession in the U.S. was over, and output growth was positive in
2002 and 2003. But unemployment continued to increase. The recovery was dubbed the
jobless recovery. This was because output growth (Y) – in the context of high productivity
growth (A) - was not sufficient to reduce unemployment N=Y/A). Output growth was
stunted by the loss of confidence in the “new economy” which meant there was no boom
in consumption or investment.
Table 1 Selected U.S. Macroeconomic Variables, United States, 1996-2003
1996
1997
1998
1999
2000
2001
2002
2003
GDP growth (%)
3.6
4.4
4.2
4.4
3.7
0.5
2.2
3.1
Unemployment rate (%)
5.4
4.9
4.5
4.2
4.0
4.8
5.8
6.0
Inflation rate (GDP deflator, %)
1.9
1.9
1.1
1.4
2.2
2.4
1.5
1.7
Labor productivity (%)
1.8
2.2
2.2
2.4
2.6
0.7
3.9
3.4
3. Distribution effects and technological change
Joseph Schumpeter characterised the process of growth as a
process of creative destruction – new goods are developed,
making old ones obsolete, new techniques of production are
introduced. This is the process of structural change – a process
that has distributional consequences – as some industries (and
some people) are winners and others are losers
Churning is another the term used to describe how new techniques
of production require new skills and make old skills less useful.
(Coined by Robert McTeer in his book “The Churn: The Paradox of
Progress” (1993))
The Increase in Wage Inequality
• For those in growing sectors (winning industries rising on the winds of new
technology) – or those with the rights skills (skills appropriate to the new
technologies) – technological progress leads to higher wages. But for those in
declining sectors and with outdated skills – technological change means lower
wages or even job loss.
• As a result - technological change is the reason for the large increase in wage
inequality in the United States during the last 25 years. In particular those with
access to higher levels of education are able to access jobs in growing sectors
and have appropriate skills for the new technology driving these sectors. (See
Fig 13.7 which shows the evolution of wages in the US be education level form
1973 to 2005)
– At the low end of the education ladder, both the relative and the absolute
wage of workers has declined
– At the high end, the relative wage of those with an advanced degree has
increased by 25% since the early 1980s.
The Increase in Wage Inequality
Figure 13 - 7
Evolution of Relative Wages,
by Education Level, 1973 to
2005
Since the early 1980s, the
relative wages of workers with a
low education level have fallen;
the relative wages of workers
with a high education level have
risen.
The Causes of Increased Wage Inequality
• Wage inequality in the US is driven by the steady increase in
demand for high skilled workers relative to low skilled workers
(which is exacerbated by the fact that the growth in supply of
skilled workers has failed to keep pace with the growth in
demand)
• This relative growth in relative demand for skilled workers is
driven by:
– International trade: Firms that hire low-skilled workers
usually go abroad to find this source of labor (reducing
demand for low skilled workers).
– Skill-biased technological progress: New machines
and productive methods require high-skill workers with
better education (increasing demand for high skilled
workers). (this trend is present across all sectors)
Will wage inequality continue to steadily
increase in the US?
• The future may be different from the recent past where wage
inequality is concerned:
– The trend in relative demand may slow down. (as
computers become easier to use and accessible by low
skilled workers and replace high skilled workers)
– Technological progress is not exogenous. R&D will be
incentivised to lead to technology that is less skills biased
to take advantage of low-skill low-wage workers
– The relative supply of high-skill versus low-skill workers is
not exogenous. There is a high incentive to gain skills but
public policy must ensure adequate basic education and
financial access to higher education.
4. Institutions and technological change
For poor countries, technological progress is more a process of imitation than a process of
innovation.
But some developing countries (e.g. China) have succeeded in this process of stimulating
technological progress, but others have failed (e.g. most African countries, such a Kenya
where PPP adjusted GDP is 1/30th of the US and A is 1/15th the US level.)
Why do poor countries (like Kenya) not adopt the technological knowledge that is readily
available in the world and closing the technological gap that exists.
Most economists believe that the main source of the problem, for poor countries in general
lies in poor institutions.
What institutions do economists have in mind? At a broad level, the protection of property
rights may well be the most important. Few individuals are going to create firms, introduce
new technologies, and invest, if they expect that profits will be either appropriated by the
state, extracted in bribes by corrupt bureaucrats, or stolen by other people in the economy.
(this argument risks being ahistorical as it neglects the damaging effects of imperialism and
colonialism and the unfair establishment of property rights associated with colonialism, also
there are geo-political factors eg island economies, landlocked economies, climate change)
Institutions and output
• Fig 13.8 shows a strong positive relationship between the
degree of protection from expropriation (protection of
property rights) and GDP per person across various
countries from 1985 to 1995
• Findings:
– low protection of property rights is associated with
low GDP per person (e.g. Zaire and Haiti)
– high protection of property rights is associated with
high GDP per person (e.g. US, Norway)
• See further examples of North vs. South Korea and
effects of market-oriented reforms in China
Institutions and technological change
Figure 13 - 8
Protection from
Expropriation and GDP per
Person
There is a strong positive relation
between the degree of protection
from expropriation and the level
of GDP per person.
The Importance of Institutions:
North and South Korea
50 years after Korea was divided into two countries the GDP per
person was 10 times higher in South Korea
than in North Korea.
This was the result of South Korea’s capitalist organization of the
economy versus North Korea’s nationalized industries and centralized
planning by the state. There were no private property rights for
individuals. The result was the decline of the industrial sector and the
collapse of agriculture. The lesson is sad but transparent: Institutions
matter very much for growth.
The Importance of Institutions:
North and South Korea
Figure 1
PPP GDP per Person,North and South Korea, 1950 to 1998
What Is Behind Chinese Growth?
In 1978, an agricultural reform was put in place, allowing farmers, after
satisfying a quota due to the state, to sell their production on rural
markets.
Outside of agriculture, state firms were given increasing autonomy over
their production decisions, and market mechanisms and prices were
introduced for an increasing number of goods. Private entrepreneurship
was encouraged, often taking the form of “Town and Village Enterprises,”
collective ventures guided by a profit motive. Tax advantages and special
agreements were used to attract foreign investors.
Despite poor establishment of property rights and an inefficient banking
system China’s economy continues to grow.
Conclusion
• What types of institutions are important to fostering technological progress
– Political system where state cannot expropriate property of citizens
(highly politicised issue)
– Good judicial system to resolve disputes between state and individual
and between individuals
– Laws against insider trading to promote confidence in the stock market
– Clear and well enforced patent laws to promote R&D
– Good anti-trust (competition) laws to protect competitive markets and
avoid monopolies that have few incentives to introduce innovations
• Conclusion – it is difficult to start the virtuous circle of higher
GDP growth and better institutions, particularly as the causality
runs both ways and low GDP leads to less protection form
expropriation and makes the building of correct institutions
(which are costly) more difficult