Growth and Development
# 4
9 March 2016
Growth or development?
Are growth and development the same phenomenon (synonyms)?
If not, how can we first define the underlying concepts and then measure different but undeniably related phenomena?
Growth is a quantitative phenomenon
even within the pre-industrial economy
Development is a form of growth driven by a
structural change
The Kuznets’ approach
Simon Kuznets regarded growth as a merely quantitative phenomenon, whilst stressing the relevance of
structural changes produced within economic systems (“modern
economic growth”, or development):
productivity increase as a result of a
different structure of the economy
The economic structure
To understand growth and development we use a dynamic model in which
(macro)sectors are responsible for varying shares - in terms of
employment and output/income
In fact, Kuznets [1962] explains
productivity variations in terms of sectoral/structural changes:
Agriculture, industry and services
Economy
as a three-sector system
Economies consist of a wide array of activities and the structure of economic activities vary as the
economy develops (otherwise, simply grows…) Economists classify activities on the basis of a
macro distinction [Fisher, 1939; Clark, 1940]
Agriculture-primary: farming, fishing, forestry Industry-secondary: manufacturing, mines,
construction, gas, water, electricity
Services-tertiary: all other activities (not goods)
Old sectors, new sectors
(to build up a bi-sectoral growth model)
Although it might seem a simple effort, dividing an economic system in three
macro-sectors was a major achievement It helps understand in what measure
productivity improvements, if any, are related to which specific sector
If “old sectors”, slowly increasing in terms of productivity, decline whilst “new and innovative sectors” emerge
with a net productivity gain for the whole!
A three-sector model: USA
What does the model suggest?
The Kuznets model suggests a positive
correlation between changes of labour force in sectors and productivity/income
As a general rule, as the labour force in
agriculture declines the shares in industry and services increase
A negative relationship between the level of per capita income and the share of the labour
force in agriculture
Thus, escaping from poverty require the
reallocation of labour away from agricolture
The structural change
(working population-labour forces by sectors)
1871 1911 1961 1871 1911 1961 1871 1911 1961
USA 52,7 31,4 8,1 26,5 30,3 29,0 20,7 38,3 62,9 Great
Britain
15,3 8,8 3,6 47,1 51,6 47,4 37,6 39,6 48,9 Germany 46,7
(1882)
36,8 14,8 35,5
(1882)
40,9 48,9 17,8
(1882)
22,2 36,3 France 48,9
(1856)
42,0 19,7 25,6
(1856)
32,4 26,5 25,5
(1856)
25,6 53,8 Italy 61,8
(1881)
59,1 30,0 20,5
(1881)
23,6 39,8 17,7
(1881)
17,3 30,2 Japan 73,5 65,4 31,2 26,5
(+
services)
14,9 29,2 - 19,8 39,6
Agriculture Industry Services
The structural change
(output/income by sectors)
1871 1911 1961 1871 1911 1961 1871 1911 1961
USA 22,2 18,9 4,3 21,8 27,5 35,7 56,0 53,6 59,8 Great
Britain
15,0 6,0 4,0 40,0 34,0 38,0 45,0 60,0 58,0 Germany 36,0
(1882)
25,0 6,0 32,0
(1882)
43,0 46,0 32,0
(1882)
32,0 48,0 France 41,9
(1856)
31,7 9,0 35,5
(1856)
39,3 39,0 22,6
(1856)
29,0 52,0 Italy 59,0 46,0 15,0 17,0 21,0 31,0 24,0 33,0 54,0 Japan 45,2
(1885)
36,7 14,0 14,7
(1885)
23,4 37,3 40,1
(1885)
39,9 48,7
Agriculture Industry Services
What does the empirical evidence actually say?
Some emerging economies suffer a persistent lack of efficiency
as a high percentage of working population in agriculture matches a low level of output
(1961: F, I, J)
Pooling cross-sectional observations on GDP per capita and labour force confirms a
positive correlation between living standard and sectoral allocation in industry and
services, negative in agriculture
Labour force allocation and income per capita
agriculture industry services
R2 0.795 0.349 0.782
How did Kuznets explain that?
The “modern economic growth” depends on structural changes in the economy and
society:
in firms (size, forms), workers’ skills,
consumptions (higher income/living standard) in productivity levels (decreasing costs per unit) in terms of constant population growth and
income (against Malthus prophecies)
and of modernization of societies and values in global inequality levels as the West expands
Measuring growth,
measuring development
Since October 1947 the standard measure of growth has been GDP (per capita)
In the wake of the Keynesian revolution But GDP is a relatively rough indicator of
very complex phenomena
Human Development Index (HDI)
Since 1990 UNs introduced HDI [Sen] to measure development as the result of capabilities and choices
Human Development Index
HDI is a composite index relating longevity (population), education (skills) and
output/income as a form of material wellbeing (
The average of three indicators:
life expectancy at birth
education (now MYS mean years of schooling + EYS expected years of schooling)
income per capita
Taking inequality into account
Inequality-adjusted Human Development Index (I-HDI) is a more recent indicator (2010) introduced to take into account inequality
as inequality could limit the growth potential negatively affecting capabilities and skills, as well as longevity within certain groups criticisms: an egalitarian bias?
In fact, HDI estimates suggest that has a predictive value of future growth
Human Development Index (1870-1991)
1870 1913 1950 1973 1991
Italy 0,288 0,453 0,656 0,794 0,861
United Kingdom
0,493 0,637 0,757 0,822 0,864
Germany 0,450 0,601 0,734 0,819 0,873
France 0,456 0,599 0,720 0,824 0,880
Holland 0,475 0,639 0,774 0,841 0,874
Sweden 0,474 0,633 0,771 0,845 0,876
Spain 0,289 0,409 0,616 0,786 0,866
Japan 0,236 0,452 0,663 0,825 0,892
USA 0,499 0,873 0,795 0,854 0,897
National income accounts
# 5
8 March 2016
Aggregate output
National income and product accounts
measure the aggregate output, or
income (aggregate means total): GDP and were introduced in the mid-1940s
after major contributions by Kuznets and Richard Stone in the 1930s
time (historical) series prior to 1947
have been retrospectively estimated
GDP: production and income
The measure of aggregate output is called the gross domestic product (GDP),
referring to the product within a nation regardless of the producer’s nationality whilst the gross national product (GNP) is
defined as the product made by residents even outside the country
GDP and GNP tend to be by and large
similar, with exceptions when large sums are invested abroad (Norway, Kuwait)
The construction of GDP
To understand how GDP is constructed we can use a simple example, a very
simplified two-firm economy, as a way to define it and calculate it
Steel Company (Firm 1) Revenues from sales $100 Expenses $ 80
Wages $80
Profit $ 20
Car Company (Firm 2) Revenues from sales $200 Expenses $170
Wages $70
Profit $ 30
How to calculate GDP in our two- firm economy?
Would you define aggregate output as the sum of the values of all the goods
produced?
steel ($100) plus car ($200)? So $300?
Or would you define aggregate output as the value of cars (the final goods),
equal to $200?
The right answer is $200. Why?
Because steel is an intermediate good
Avoid double counting!
An intermediate good like steel goes into the production of the final good (cars)
$300 would imply a double counting!
steel + cars would entail counting more than once the same good or value
Hence, the first definition of GDP:
GDP is the value of the final goods and services produced in the economy
during a given period (usually, one year) It would be confirmed in case of a merger
The value added approach to GDP
The value added means exactly what a firm actually does:
the value added by a firm is defined as the value of its production minus the value of intermediate goods
That’s a second way of thinking about GDP (and constructing it):
GDP is the sum of value added in the
economy during a given period
From the production side to the income side
May one think of GDP from a different perspective? Is it just production? Or
may one look at it even from the income side?
actually, wages and profits are paid for getting their own income
Revenues going to pay workers and capital are specific components of GDP, called labour income and profit income
Calculating GDP as income
In our two-firm economy as a whole labour income is equal to $150 ($80 + $70) and capital income (profits) is equal to $50 ($20 + $30)
Steel Company (Firm 1) Revenues from sales $100 Expenses $ 80
Wages $80
Profit $ 20
Car Company (Firm 2) Revenues from sales $200 Expenses $170
Wages $70
Profit $ 30
A third definition of GDP (and its composition)
GDP is the sum of incomes in the economy during a given period
And who has got the larger slice of the cake? Capital or labour?
In our example labour gets 75% and capital 20%: is it realistic?
The composition of GDP in the USA, 1966 and 2006
1960 2006
Labour income 66% 64%
Capital income 26% 29%
Indirect taxes 8% 7%
US labour income: a sharp decline in
the last decades, 1947-2011
Nominal and real GDP
U.S. GDP was worth $17,419 billion in
2014 compared to $526 billion in 1960, but was US output really 13.11 times higher?
Much of the increase reflects an increase in prices rather than in quantities
This leads to the distinction between nominal and real GDP as prices are
monetary values susceptible to inflation or deflation (money/goods and services)
Why do we need real values?
Nominal GDP is the sum of final goods and services at current prices, not constant Thus, GDP increases over time depend on
two simple facts:
the production of most goods increases over time
the prices of most goods also increase over time
To measure and compare output over time we must eliminate the effect of prices
How to construct the real GDP?
The real GDP is the sum of the quantities of goods and services multiplied by constant prices, not current
Problems in practice: there is more than one good (cars), differences in qualities and
technological progress (hedonic pricing)
Quantities of cars
Prices of cars Nominal GDP Real GDP in 2000 dollars
1999 10 $20,000 $200,000 $240,000
2000 12 $24,000 $288,000 $288,000
2001 13 $26,000 $338,000 $312,000
Comparing the US GDP over time adjusted for inflation, 1960-1997
By construction, nominal GDP is equal to real GDP ($1993) US national
accounts are constructed in chained prices in order to
overcome problems of relative prices and their
weight
The real GDP allows to catch long-
run and cyclical phenomena
GDP per capita
One must be careful when comparing countries different in size and population
One has to calculate the ratio of real GDP to the population in order to get real
comparisons – GDP per capita
China GDP is $10,354.80 billion (2014), compared to Switzerland, $685,4 billion (2013): more than 15 times
But China GDP per capita is $6.807 (2013) whilst Switzerland GDP per capita is $84.815 (2013), that is Swiss are 12.45 times richer than Chinese!
May we get a better measure of differences by countries?
How to avoid exchange rate variations (volatility) and even distortions?
Cassel [1918] elaborated a method to compare per capita income in different countries:
The Purchasing Power Parity (PPP)
to estimate what the exchange rate between two
currencies would have to be if the currencies were at par with the respective purchasing power
Another way to have a purchasing power adjustment is the Geary-Khamis dollar (the "international dollar") [1970, 1972]
The Big Mac Index (The Economist)
GDP: level versus growth rate
GDP growth is constructed as follows (Yt – Yt-1)/Yt-1
where Y is GDP and t is the year to which real GDP is referred to
Can we infer longer term trends?
US real GDP growth rate, 1940-2014
Unemployment and inflation
# 6
9 March 2016
Macroeconomic variables
GDP is a measure of aggregate economic activity
But two other variables are relevant when gauging how an economy is performing:
unemployment rate and inflation rate Unemployment rate is a measure of
inefficient use of resources
Inflation affects income distribution and leads to a higher level of uncertainty distorting decisions about the future
The unemployment rate
Employment rate is the number of people who have a job
Unemployment rate is the number of people
who do not have a job but are looking for one The labour force is the sum of employment and
unemployment
L = N + U
labour force = employment + unemployment u = U/L
unemployment rate = unemployment/labour force
To calculate
the unemployment rate is hard
Assessing whether one is unemployed is rather harder
Two conditions must be met:
i) not having a job and ii) looking for one but the latter condition is harder to assess Computing unemployment rate is not a
trivial exercise as its actual level affects income and consumptions
but human capital and skills as well!
How to cope with difficulties
Unemployment is a rather elusive
phenomenon as one can look for a job for a certain time, but one can be discouraged and give up if one do not meet a job for a long time (discouraged workers)
Unemployed is only who is looking for a job, otherwise is not in the labour force any
more = participation rate
The unemployment rate in the long run, USA (1890-2014)
Very poor estimates of the unemployment rate
before 1940 (and even afterwards)
A number of cyclical
variation according to economic fluctuations, even though jobless recoveries are
becoming a more
frequent phenomenon May we actually compare
estimates in the long run? Just partially
Labour force
and the participation rate
As the participation rate – the ratio of the labour force to the total population - could vary even significantly the unemployment rate will be positively correlated
As a slow growing economy a higher
unemployment rate is associated with a lower participation rate
Discouraged workers will be high in such a case or in case of inefficient labour market (young, minorities, unskilled)
Female participation rate in OECD
countries and other economies, 2010
Self-employment seems to confirm specific labour market arrangements (in Europe)
Can the labour market influence the unemployment rate?
Europe as late as 2014 shows a certain variance in labour
markets and GDP growth rate There is a more marked tendency
to long term U rate than in the USA
Why do we care for unemployment?
Unemployment is a measure of economic distress or labour market inefficiency
(bad regulation)
It has a certain predictive value on the
macroeconomic performance in the short run A high U level means less income and less
consumptions, but it affect expectations and investment decisions as well
It influences also human capital: i) skills and ii) financial and psychological suffering
How do we cope with the underground economy?
When we notice a very high U rate (or long term U forms or amongst the young) we have to ask how unemployed actually survive?
generous unemployment benefits?
We can have two answers:
a specific family structure exerting a “buffer”
transferring income within its components a large underground economy, illegal or not
paying taxes but producing income!
The inflation rate
Inflation is a sustained rise in the general level of prices – the price level
Deflation, symmetrically, is the opposite: a decrease in the price level (or negative inflation rate)
Inflation – as well as deflation – affects
consumption, saving and investment decisions with a real outcome on the economy
(production level)
it has a distortive effect on relative prices (think of a specific asset inflation, such as properties)
Inflation origins
Inflation is usually related to three factors:
i) monetary/fiduciary inflation provoked by central banks or an inflation of payment means (France, 1793; Germany, 1921-23) as a form of financial profligacy
ii) cost-push inflation – or supply shocks – as a result of full employment or major shocks (Oil Shock, 1973)
iii) demand-pull inflation as a result of changes in demand side spending (WWs, international demand for specific goods) or Phillips’ Curve (increase in wages)
Inflation, hyperinflation, deflation in
Europe in the 1910s-1940s
Connecting unemployment and inflation: the Phillips Curve
Phillips [1958] observed an inverse
relationship between the unemployment rate and the inflation rate
Friedman [1968] maintained that it was true only in the short run, as inflationary trends would have eroded employment increases in the medium- and long-term assuming it was too simplistic a model:
Stagflation in the 1970s did not confirm
Phillips’ model as grew both inflation and U
so, no single curve will fit the data
The Phillips Curve
Growth and unemployment
A.M. Okun [1962] observed a certain relation between economic growth – expansionary or recessionary cycles – and unemployment rate, albeit with a margin of “noise”
The unemployment rate depends on
growth but some frictions can operate slowing down the pace of jobs creation whilst the economy recovery, and vice versa
Okun’s law:
USA, 1960-1998 and 1950-2015
An imperfect relationship as, for instance, productivity could affect the output
The Okun’s law is much more a
“rule of thumb”, a rather noisy correlation as recent data show
Crescita del Pil (%) Variazione del tasso di disoccupazione
