NORWAY’S PRODUCTIVITY PERFORMANCE -AN OECD PERSPECTIVE
Alain de Serres and Naomitsu Yashiro Economics Department, OECD
Productivity Symposium 9 December 2013
Oslo, Norway
Outline of presentation
• Productivity performance in a cross-country perspective: controlling for the contribution of natural resources
• The direct contribution of physical and human capital
• The role of knowledge-based capital and its growing importance as a source of productivity
• The role of resource reallocation within and across firms
• Summing-up
2
Norway’s advantage in per capita income is less pronounced when export value of petroleum production is excluded
Growth performance indicators for Norway
Gap to upper half of OECD countries
3 -20
-15 -10 -5 0 5 10 15 20 25 30 35 40 45 50
Per cent GDP per capita (Mainland) GDP per hour worked (Mainland) GDP per capita
4
Differences in MFP growth rates from including natural resources as a production factor
-3 -2 -1 0 1 2 3 4
1986 1991 1996 2001 2006
Di ff er en ce in p er cen tag e po in ts
Time
Brandt, N., P. Schreyer and V. Zipperer (2013), “Productivity Measurement with Natural Capital”, OECD Economics Department Working Papers, No.
1092, OECD Publishing.
5
The decline in GDP growth is more than accounted for by the reduction in the contribution from natural resource
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0
GMFP Labour Capital Natural Capital
GDP
Norway
1986 - 1999 2000 - 2008
The Norwegian economy appears to have successfully (so far) substituted produced capital for natural capital
Outline of presentation
• Productivity performance in a cross-country perspective: controlling for the contribution of natural resources
• The direct contribution of physical and human capital to
• The role of knowledge-based capital and its growing importance as a source of productivity
• The role of resource reallocation within and across firms
• Summing-up
6
Using a simple framework to shed light on the sources of Norway’s performance
• A simple econometric analysis based on the Solow framework as developed by Mankiw, Romer and Weil (1992) and which considers physical and human capital.
• Per capita income level is a function of investments rate in physical capital, level of human capital and the rate of population growth:
• This function is estimated from a panel of 20 OECD countries between 1980-2010. Estimation includes country and time fixed effects and controls for first-order serial correlation.
• GDP per capita for Norway corresponds to mainland GDP
7
Dependent variable: log
of per capita GDP (1) (2) (3) (4)
Physical capital 0.1951*** 0.2004*** 0.1997*** 0.1895***
(0.0173) (0.0184) (0.0184) (0.0202) Human capital 0.2304*** 0.1857*** 0.2031*** 0.1932***
(0.0658) (0.0680) (0.0657) (0.0660) Population growth 0.0131 0.0193 0.0228 0.0186
(0.0193) (0.0212) (0.0206) (0.0229) R&D intensity 0.0234*** 0.0211*** 0.0204**
(0.0084) (0.0081) (0.0084)
Trade intensity 0.0350**
(0.0169)
0.0848***
(0.0157)
R Squared 0.9994 0.9995 0.9995 0.9995
Number of observation 599 561 561 546
Index of market and supplier access
Both human and physical capital contributes significantly to per capita income.
A large portion of per capita income gap is found in the country fixed effect
Contribution to deviation of GDP per capita against 20 OECD country average (2000-2010)
9 -0.5
-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
Country fixed effect Population
Human capital Physical capital Actual GDP per capita Predicted GDP capita Deviation to OECD average (% points)
Norway’s advantage in physical capital has been declining since the mid-1990s
-6 -4 -2 0 2 4 6 8 10 12 14 16
Percentage of GDP
Norway's advantage in investment rate Norway minus other countries
DNK FIN NLD SWE USA
Norway’s investment rate covers only non-oil sector
The advantage in human capital has remained stable
11 -1
-0.5 0 0.5 1 1.5 2 2.5
Adjusted average years of schooling
Norway's advantage in Human Capital Norway minus other countries
DNK FIN NLD SWE USA
Based on mean years of schooling without adjustment for quality or compositional effect of labour force
Norway is out-performing other Nordic countries in what can be loosely interpreted as MFP
-0.2 -0.1 0 0.1 0.2 0.3 0.4
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
gap vis-a-vis OECD average
Country Fixed effects and residuals of standard Solow regression
DNK FIN NOR SWE USA
Even on the basis of mainland GDP (i.e. excluding the export value of oil)
Outline of presentation
• Productivity performance in a cross-country perspective: controlling for the contribution of natural resources
• The direct contribution of physical and human capital
• The role of knowledge-based capital and its growing importance as a source of productivity
• The role of resource reallocation within and across firms
• Summing-up
13
An important factor missing from the basic Solow
framework: Knowledge-based capital
15
Investment in KBC is becoming increasingly important in rich OECD countries
0.0 0.5 1.0 1.5 2.0 2.5
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
The ratio of KBC to Physical capital investments
Denmark Finland Germany Ireland Netherlands Sweden
United Kingdom Norway
United States
Norway’s ICT related R&D is small compared to other Nordic countries
R&D expenditure in information industries (Percentage of GDP)
Information industries includes ISIC Rev.4 Division 26 (Manufacture of computer, electronic and optical products) and Section J (Information and communication), consisting of Divisions 58-60 (Publishing and broadcasting industries), 61 (Telecommunications) and 62-63 (Computer programming and information service activities).
Dependent variable: log
of per capita GDP (1) (2) (3) (4)
Physical capital 0.1951*** 0.2004*** 0.1997*** 0.1895***
(0.0173) (0.0184) (0.0184) (0.0202) Human capital 0.2304*** 0.1857*** 0.2031*** 0.1932***
(0.0658) (0.0680) (0.0657) (0.0660) Population growth 0.0131 0.0193 0.0228 0.0186
(0.0193) (0.0212) (0.0206) (0.0229) R&D intensity 0.0234*** 0.0211*** 0.0204**
(0.0084) (0.0081) (0.0084)
Trade intensity 0.0350**
(0.0169)
0.0848***
(0.0157)
R Squared 0.9994 0.9995 0.9995 0.9995
Number of observation 599 561 561 546
Index of market and supplier access
The augmented Solow regression indicates a significant and positive contribution by R&D to per capita income
17
-0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
Country fixed effect R&D
Human capital Physical capital Actual GDP per capita Predicted GDP capita
Country fixed effects remains the dominant explanatory factor even after R&D in added
Contribution to deviation of GDP per capita against 20 OECD country average (2000-2010)
Deviation to OECD average (% points)
19
Some contribution of R&D is embodied in country fixed effects due to its low time variance
USA
CHE
IRL
NLD CAN NOR_MAIN
AUT AUS
DNK
GBR
BEL SWE
DEU
FIN FRA
JPN ITA
ESP
NZL PRT
-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03
Country fixed effects in the Solow regression
R&D intensity (average deviation from OECD mean, 2000-2010)
Country fixed effect and R&D intensity
FE=-0.00037 + 6.40567 * R&D t = 3.27
-0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
Other country fixed effects Country fixed effect explained by R&D Population Human capital Physical capital Actual GDP per capita Predicted GDP capita
The R&D component in country fixed effects reveals the sizable contribution by R&D in income gap
Contribution to deviation of GDP per capita against 20 OECD country average (2000-2010)
Deviation to OECD average (% points)
21
The difference in R&D intensity can explain up to half of Norway’s productivity gap vis-à-vis the United States
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4
1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
NOR base
NOR R&D included
NOR base + R&D in fixed effect
USA base
USA R&D included
USAbase + R&D in fixed effect
10%
points 22%
points
Country Fixed effects and residuals of Solow models Norway vs the U.S.
Gap vis-a-viz OECD countries
Outline of presentation
• Productivity performance in a cross-country perspective: controlling for the contribution of natural resources
• The direct contribution of physical and human capital
• The role of knowledge-based capital and its growing importance as a source of productivity
• The role of resource reallocation within and across firms
• Summing-up
22
Making the most out of ICT investment requires changes in business practices within firms
Vast body of research has underscored the importance of investment in ICT for innovation in services
– ICT-using services made a significant contribution to productivity gains in the 2000s (Jorgensen, Ho and Stiroh, 2008) ...
– …and account for a good portion of the gaps in productivity and growth performance between US and Europe (Van Ark, O’Mahoney and Timmer, 2008)
Conditions for ICT to generate efficiency gains within firms:
– Adapting business practices and providing workforce training is required to get most of ICT investment: Organisational capital (Brynjolfsson and Hitt, 2003)
– Studies comparing US and UK firms (operating in the UK) have attributed better performance of US firms to higher tendency to undertake
organisational changes (Crespi, Criscuolo and Haskell, 2007)
23
0 2 4 6 8 10 12
Percentage of GDP
Other Economic competencies Organisational capital
Innovative Property Software
Norway’s KBC investment is relatively less intensive and is less oriented toward ICT and organisational capital
Investment in KBC as percentage of GDP (Year 2010, except Norway)
25
Norway businesses appear to be overall well connected but may not invest much to adapt practices
0 10 20 30 40 50 60 70 80
Share in total enterprises (%)
Enterprises who have ERP software package to share information between different functional areas
Enterprises using
automated data exchange with other ICT systems outside the own
enterprise
Enterprises having received orders via computer mediated networks
The use of ICT in enterprises
Source: Eurostat
Making the most out of KBC requires efficient reallocation of resources across firms
Varying use of intangible assets at the firm level is reflected in heterogeneity in productivity
Investment in new ideas entails large fixed costs, low marginal costs:
Source of increasing returns to scale
To fully reap scale effect new firms or firms with new ideas need to be able to raise production rapidly and hence attract tangible resources (capital and labour)
Resources must flow from low-productivity to high-productivity firms
Static and dynamic allocative efficiency
27
OECD countries differ in their ability to allocate labour to the most productive firms
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8
Covariance across firms between firm size and labour productivity Log points; selected OECD Countries, 2005
Manufacturing Services
Policy factors include product market regulation, the cost of bankruptcy legislation employment protection legislation and barriers to competition in financial markets.
Dynamic allocative efficiency: do resources flow to innovative firms?
Source: Andrews, Criscuolo and Menon (2013). The chart shows the estimated coefficient from a firm level regression of log(capital stock) on the log(patent stock), controlling from firm fixed effects and country*sector*time fixed effects.
The difference between the coefficients for SWE & USA and ITA & ESP is statistically significant .
Efficient reallocation mechanism underpin the implementation and commercialisation of new ideas in SWE and the US.
But it is much more difficult for innovative firms to attract capital in ITA and ESP.
29
The ability of innovative firms to attract tangible resources is influenced by policy environment I
Norway
Norway Norway
Norway
Maximum (Portugal)
Maximum (Sweden)
Maximum (Poland)
Maximum (Czech Rep.)
Maximum (Switzerland)
Minimum (United States)
Minimum (Greece)
Minimum (United Kingdom)
Minimum (Norway)
Minimum (Slovak Rep.)
0.0 0.5 1.0 1.5 2.0 2.5 3.0
Stringency of Employment Protection Legislation
Access to Early Stage VC Stringency of Product Market Regulation
Judicial inefficiency Stock market capitalization
%
The estimated impact of various policies on the responsiveness of the firm employment to patenting
Additional labour attracted by a firm that raises its patent stock by 10%
The ability of innovative firms to attract tangible resources is influenced by policy environment II
Norway
Norway
Norway
Maximum (Portugal)
Maximum (Sweden)
Maximum
(Czech Rep.) Maximum
(Slovak Rep.)
Maximum (Italy) Minimum
(United States)
Minimum (Greece)
Minimum
(Norway) Minimum
(United Kingdom)
Minimum (Norway)
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5
Stringency of Employment Protection Legislation
Access to Early Stage VC Judicial inefficiency Barriers to Trade &
Investment
Cost of Bankruptcy Legislation for Entrepreneurs
%
The estimated impact of various policies on the responsiveness of the firm investment to patenting
Additional capital attracted by a firm that raises its patent stock by 10%
Summing up
Relatively good productivity performance, even after controlling for oil production/exports
MFP growth has been maintained in the face of slowing GDP
Comparable MFP levels to other Nordics but a 20 per cent gap vis-à-vis US levels
Gap in innovation – as proxied by R&D – may account for between one-fifth to one-half of this gap
Boosting innovation – especially in services -- may require stronger investment in KBC:
Norway appears to be lagging in particular in ICT investment, but also organisational capital
Regulatory barriers to competition in telecom and energy (gas) sectors are high by OECD standards
Improving skills level to facilitate adapting to changes in technology
• Thank you
• Additional material
33
Norway’s trade intensity (adjusted for size) is relatively low by international standards
AUS AUT
BEL
CAN CHE
CHL CZE
DNK DEU
ESP EST
FIN
FRA GBR
GRC HUN IRL
ISL
ISR ITA
JPN KOR
LUX
MEX NLD
NOR
NZL
POL PRT
SVK
SVN
SWE
TUR
USA
Regression line (excluding Luxembourg)
0 50 100 150 200 250 300
2 2.5 3 3.5 4 4.5 5 5.5
goods and services trade as a share of GDP (%)
log(GDP) (value, measured in PPP, 2005 million USD)
Norway is no more disadvantaged than Sweden in terms of distance and access to markets.