the norwegian economy norwegian life and society (norint0500) thomas von brasch: [email protected]
TRANSCRIPT
The Norwegian EconomyNORWEGIAN LIFE AND SOCIETY (NORINT0500)
Thomas von Brasch: [email protected]
Thomas von Brasch: [email protected]
Plan for the lecture
• Wealth and productivity in Norway– The Norwegian Productivity Puzzle
• Other statistical facts about Norway• Current macroeconomic situation
– Four important stabilising mechanisms
Thomas von Brasch: [email protected]
How wealthy is Norway?
Thomas von Brasch: [email protected]
National income per capita,Current prices, Norway=1
Thomas von Brasch: [email protected]
Why are we so wealthy?
6
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Sources of wealth
19701974
19781982
19861990
19941998
20022006
20102014
0
0.5
1
1.5
2
2.5
3
3.5
Disposable real income per capita
Productivity - oil
Productivity - non oil
Terms of trade
Balance of income and current transfers
Hours worked/Population
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Reasons to worry?
1970-1994 1995-2004 2005-2014-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
Productivity - oilProductivity - non oilTerms of tradeBalance of income and current transfersHours worked/Population
Thomas von Brasch: [email protected]
Contributions to labour productivity growth
1970-1994 1995-2004 2005-20140
0.5
1
1.5
2
2.5
3
TFPCapital intensity
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Main drivers of TFP
• Human capital– Level of education– ICT knowledge
• Research and development
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Level of education
Johansson, Å. et al. (2013), “Long-Term Growth Scenarios”, OECD Economics Department Working Papers, No. 1000, OECD Publishing. http://dx.doi.org/10.1787/5k4ddxpr2fmr-en
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PISA 2012
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ICT knowledge
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ICT knowledge
OECD (2014), Measuring the Digital Economy: A New Perspective, OECD Publishing. http://dx.doi.org/10.1787/9789264221796-en
Thomas von Brasch: [email protected]
ICT knowledge
OECD (2014), Measuring the Digital Economy: A New Perspective, OECD Publishing. http://dx.doi.org/10.1787/9789264221796-en
Thomas von Brasch: [email protected]
R&D and productivity growth (1986 - 2008)
0.0 0.5 1.0 1.5 2.0 2.5-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
TFP annual % change
R&D/GDP
MFP growth=-0.18+0.497(R&D/GDP)t-statistic: 2.08**
Thomas von Brasch: [email protected]
The Norwegian Puzzle
• “There is a puzzle about Norway. How did it succeed in reaching one of the highest living standards among OECD countries from a relatively poor ranking in 1970?”(p. 18)
• “Productivity is high, real growth rates have been respectable, overall TFP growth is better than in many countries with higher R&D spending, and industry has by and large managed to survive a changing world and a strong exchange rate” (p. 129)
Source: OECD (2007), Economic Surveys: Norway, January (2).
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Labour productivity
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4
NorwayNorway, Mainland
BelgiumNetherlands
DenmarkFrance
GermanySwedenAustria
SpainFinland
ItalyUnited Kingdom
IcelandGreece
PortugalEstoniaPoland
GDP per hour, relative to USA in 2013. Converted to USD using economy wide purchasing power parities. Sources: OECD og SSB.
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Productivity and Purchasing Power Parities• Productivity refers to the volume of
outputs relative to the volume of inputs
• But the value of production is measured in different currencies
• How should the value of production be compared across countries?
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Productivity and Purchasing Power Parities• Purchasing Power Parities compares
price levels between countries:
• They are essential when comparing productivity between countries
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Impact from industry composition on productivity• Assume that two countries produce
two goods and that the prices of the two goods are the same in both countries at both time periods
• The Purchasing Power Parity between the two countries is then
• Relative productivity is then measured by
=
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Impact from industry composition on productivity• Assume further that country is a
large oil exporter and that the oil price increases. Value added in constant prices will then increase most in country .
• Even if nothing has happened with productivity, the increase in oil prices will result in an increased of measured productivity:
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Productivity (in time and space)
16
20
24
28
32
36
40
44
16
20
24
28
32
36
40
44
1980 1985 1990 1995 2000 2005 2010
Norway Denmark Sweden USAGermany France Finland
Sources: OECD og EUKLEMS. Gross product per hour. USD, basic prices. All industries except oil and electronics.
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R&D: controlling for industry composition
PO
L
SV
K
ES
P
ITA
HU
N
PR
T
NO
R
CZ
E
IRL
GB
R
NL
D
AU
S
SV
N
BE
L
ES
T
FR
A
AU
T
DE
U
US
A
DN
K
JPN
SW
E
KO
R
FIN
01
23
45
%
U
na
dju
ste
d b
usi
ne
ss R
&D
inte
nsi
ty
Ad
just
ed
bu
sin
ess
R&
D in
ten
sity
Business R&D intensity, OECD average
Andrews, Criscuolo, 2013, Knowledge-based capital, innovation and resource Allocation, OECD Economic Policy Papers (4)
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The Norwegian Puzzle
• Not that low R&D investments• Not as productive as previously
believed• Not as puzzling after all
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Break
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Can one compare productivity between
countries with different industry structures?
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Sectoral composition and productivity• Example:
– Country produces 1 banana per hour– Country produces 2 apples per hour
• Which country is most productive?
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Sectoral composition and productivity• Split production in three categories
A. Products made by both country and B. Products made by country onlyC. Products made by country only
• Productivity comparisons across countries relates to A
• But, how large is the common set of production?
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Equal sectoral composition?
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
NLD
LVA
POL
GBR
FRA
EST
FIN
SWE
ITA
AUT
ESP
BEL
DEU
IRL
IS
DNK
Common production relative to total production, Manufacturing, 2013.
Source: Eurostat, PRODCOM database 2013. Average of the shares for Norway and the comparison country. ISO country codes.
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Equal sectoral composition? Norway vs. Denmark
NOR DNK Product0,072 0 Unwrought aluminium alloys 0,058 0 Offshore vessels0,057 0 Fitting out services of ships and floating platforms and structures0,037 0 Design and assembly of automated production plants0,037 0 Repairing of ships, boats and floating structures 0,035 0 Frozen whole salt water fish0,025 0,012 Other structures principally of sheet: other0,021 0,003 Fresh or chilled fish fillets and other fish meat without bones0,019 0,013 Fresh or chilled cuts, of beef and veal0,019 0,001 Frozen fish fillets0,380 0,029
0 0,138 Generating sets, wind-powered0 0,029 Medicaments containing corticosteroid hormones0 0,028 Medicaments containing insulin but not antibiotics,
0,007 0,028 Fresh or chilled pig meat 0,001 0,024 Weirs, sluices, lock-gates, and other maritime structures0,004 0,022 Other food preparations n.e.c.
0 0,021 Enzymes; prepared enzymes 0,005 0,018 Articles of iron or steel, n.e.s.0,002 0,017 Other articles of plastics or other materials0,005 0,017 Beer made from malt 0,024 0,342
Shares of production, 2013
Source: Eurostat, PRODCOM database 2013. ISO country codes.
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How can we increase productivity?
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1. Produce more electronics
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Produce more electronics?
Kilde: OECD STAN ISIC REV. 4, Industry d26 for USA.
Development relative to overall GDP. USA.
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2. Fire people with a disability
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Productivity – not at any price• Policies directed at increasing
productivity should be based on what is an overall gain for society, not only by the gain in productivity.
• Public policies to raise productivity in private businesses should be based on the existence of market failure, e.g., – Monopoly– Polution
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Future productivity growth
40
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Employment
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Implications for productivity: envelope calculation• Public employment share is expected
to rise from 30% to between 40 and 50% in 2060
• Change in overall productivity growth= (change in employment share) x (difference in productivity growth)= (50%-30%) x (0,5%-2%) = -0,3 (percentage points)
• Is this a problem?
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Other statistical facts about Norway
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Gender gap index
• Economic Participation and opportunity– E.g., Female labour force participation,
income etc. relative to male.
• Educational attainment– E.g., female literacy rate, enrolment rate
etc.
• Health and survival– Female healthy life expectancy over
male value
• Political empowerment– Females at ministerial level over male
value
World Economic Forum: http://www3.weforum.org/docs/GGGR14/GGGR_CompleteReport_2014.pdf
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Gender gap index
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Women at work
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Women at work
https://www.regjeringen.no/no/dokumenter/meld-st-46-20122013/id733259/?ch=2
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Wise women
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Inequality: Gini coefficient = A/(A+B)
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Inequality (Gini coefficient)
Source: https://en.wikipedia.org/wiki/Economic_inequality
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Employment and labour force participation rates 2012
https://www.regjeringen.no/no/dokumenter/meld-st-46-20122013/id733259/?ch=2
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Thomas von Brasch: [email protected]
Current macroeconomic situation
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Output gap in Norway
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Stabiliser 1: Government policy – «budgetary rule»
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Stabiliser 2: The Central Bank of Norway
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Stabiliser 2: The Central Bank of Norway
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Why do we have so low interest rates?
𝑟∗
Savings
Investments
Real interest rate,
Thomas von Brasch: [email protected]
Why do we have so low interest rates?
Savings
Investment slump
Real interest rate,
𝑟∗
Thomas von Brasch: [email protected]
Why do we have so low interest rates?
Savings glut
Investment slump
Real interest rate,
𝑟∗
Thomas von Brasch: [email protected]
Stabiliser 3: Wage negotiations
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Stabiliser 4: Exchange rate
http://www.economist.com/news/finance-and-economics/21674775-currency-pegs-are-still-fashion-some-are-creaking-pegs-under-pressure?frsc=dg%7Cd
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Stabiliser 4: Exchange rate
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Contributions to future GDP growth
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Summary
• Norway – Wealthy– «Equal» in many respects– Highly educated– No productivity puzzle– Different sectoral composition sector
compared with many other European countries
• 4 important short run stabilising mechanisms