The “Smart Public Intangibles (SPINTAN)”
Project: Main Findings and Policy
Implications
Matilde Mas
Universitat de València and IVIE
Joint meeting of the Working Party on Industry Analysis (WPIA) and the
Working Party on Globalisation of Industry (WPGI)
OECD, Paris, October 11th 2016
The Objective of the SPINTAN project is to identify and measure public
sector intangible capital which allows us to evaluate its role as a driver of
firm-industry-country economic growth. It develops new insights on the
role of public sector knowledge creation which can be relevant for the
European innovation and growth policy agenda.
At the most practical level, its goal is to complete the coverage of the
sources of growth information already existing for the market economy (EU
KLEMS (FP 6th), COINVEST (FP 7th), INDICSER (FP 7th), INNODRIVE
(FP 7th) and INTAN-Invest) including the Public Sector, making possible
the generation of total economy growth accounts with intangibles as
productive assets.
OBJETIVES
2
INDEX
1. Identification: Framework
2. Empirical Measurement: Investment
3. Empirical Measurement: From Investment to Capital
Services
4. Implications for Economic growth
5. Additional Policy Implications
OBJETIVES
3
Starting point:
Corrado, C., Hulthen, C., and D. Sichel (2005): «Measuring Capital and
technology: An expanded framework», Measuring Capital in the New
Economy, University of Chicago Press.
Corrado, C., Hulten, J., and D. Sichel (2009): «Intangible capital and US
economic growth», The Review of Income and Wealth 55(3), 661-685.
Corrado, C., Haskel, J. and C. Jona-Lasinio (2014): Smart Public
Intangibles: SPINTAN Framework and Measurement (Spintan, Mimeo)
Corrado, C., Jäger, K. and C. Jona-Lasinio (eds.) (2015): Measuring
intangible capital in the Public sector (Spintan, Mimeo)
Expected Final Output:
SPINTAN Manual
1. FRAMEWORK
4
1. Industry Coverage
Table 1: SPINTAN industries of interest
1. FRAMEWORK
5
2. Industries vs. Institutional sector
Figure 1: Enterprise types in the SNA: Groups according to control (private, public) and
ability to charge economically significant prices (market, nonmarket)
1. FRAMEWORK
6
3. CHS
CHS type of asset: market vs. nonmarket
Table 2: Knowledge capital in a total economy
1. FRAMEWORK
7
1. FRAMEWORK
8
Figure 2: UNESCO Framework for statistics on cultural domains
Main Pillars:
1. Expenditure based approach
2. Reproducibility
3. “Updatability”
4. Homogeneity: Comparability across countries
5. Consistency with National Accounts
*Based on Iommi, M. and C. Jona-Lasinio (2015): Measuring public sector
investment in intangible asset: Main achievements and open issues,
(Spintan, Mimeo)
2. EMPIRICAL MEASUREMENT: INVESTMENT*
9
Two different strategies for:
1. New Intangible assets (NewIA)
o Design
o Market research and advertising
o Organisational Capital
o Training
2. Assets already included in the SNA/ESA (NAIA)
o Computer software and databases
o Research and development
o Mineral exploration
o Entertainment, literary and artistic originals
2. EMPIRICAL MEASUREMENT: INVESTMENT
10
1. New Intangible assets (NewIA)
o Expenditures for NewIA are currently considered expenditure to
purchase intermediate inputs
oNo output produced for own use is recorded (in NA only final output for own
final use is included in the production boundary)
oBoth, the production and the use of the purchased component are registered
in NA data
o We have to produce our estimates of the own account
component
o We have no reasons to change NA estimates of total output and
total expenditure
o We want to change the type of use (from intermediate
consumption to GFCF)
2. EMPIRICAL MEASUREMENT: INVESTMENT
11
1. New Intangible assets (NewIA)
1.1 Purchased intermediate inputs
o Main source: Use tables
o Data on total expenditure is required for each product that
relates to NewIA for the industry/sector
o Assumptions on how much of each expenditure might be
considered GFCF
o Use tables usually available with delay (t-3)
2. EMPIRICAL MEASUREMENT: INVESTMENT
12
1. New Intangible assets (NewIA)
1.2 Own Account Component
o Standard Approach: to value it at the costs of production, i.e. the
sum of compensation of employees, intermediate consumption
and the cost of capital (consumption of fixed capital and, only for
market producers, net operating surplus)
o For Organisational Capital it can be estimated using data from
LFS-SES integrated with data from the OECD survey on
compensation in the public sector for the O84 industry
o We deem that own-account production of design, advertising and
market research in the non-market sector is negligible
2. EMPIRICAL MEASUREMENT: INVESTMENT
13
2. National Accounts Intangibles Assets (NAIA)
o Include both, purchased and own-account component
o Usually data are not available at the level of detail that we need
(i.e. cross-classified by asset, industry and sector)
o Quite likely that there is no GFCF in Mineral Explorations and
Originals in the non-market component of the industries of
interest to Spintan.
o We need to produce estimates of GFCF in Computer software
and Databases and in Research and Development cross-
classified by industry and by sector that are consistent with the
available national accounts data on GFCF.
o Very few countries provide also data on GFCF by institutional
sector for IPP (and some components)
2. EMPIRICAL MEASUREMENT: INVESTMENT
14
Deflation. Options for SPINTAN
o Producing our own hedonic price indexes, IPP and input-based
deflator for all countries (it would be nice but a little bit too
demanding)
o Use NA GFCF deflators for NAIA and output/value added deflators
for NewIA
o Current SPINTAN estimates:
o NA deflators
o The same deflator for purchased and own account organisational capital
2. EMPIRICAL MEASUREMENT: INVESTMENT
15
US outperforms the EU in market and non- market intangible
investment . Heterogeneity within EU-15. Sweden and UK in
top positions. The four peripheral countries at the tail end.
Figure 3: Share of GFCF on intangible assets over total GDP. EU15 and US. Average
2006-2010 (percentages)
Source: Eurostat, INTAN-Invest, SPINTAN and own elaboration.
a) Market sector b) Non-market sector
10.8
8.48.3
7.57.47.37.16.96.8
6.36.36.26.16.0
5.2
4.54.54.3
2.1
0
2
4
6
8
10
12
UnitedStates
Sweden
UnitedKingdom
Belgium
Denmark
France
Finland
Slovenia
Netherlands
EU15
CzechRepublic
Germany
Austria
Luxembourg
Ireland
Spain
Portugal
Italy
Greece
EU15 average = 6.3%
2.5
1.6
1.3
1.11.1
0.90.90.90.90.90.80.80.70.70.7
0.6
0.4
0.20.2
0.0
0.5
1.0
1.5
2.0
2.5
3.0
UnitedStates
Sweden
UnitedKingdom
Italy
Netherlands
Austria
Portugal
Finland
EU15
Belgium
CzechRepublic
Germany
Ireland
France
Denmark
Slovenia
Spain
Greece
Luxembourg
EU15 average = 0.9%
In R&D the gap with US is larger in the non-market sector
Figure 5: Share of GFCF on R&D over total GDP. EU15 and US. Average 2006-2010
(percentages)
Source: Eurostat, INTAN-Invest, SPINTAN and own elaboration.
a) Market sector b) Non-market sector
2.2 2.1
2.0
1.6 1.6
1.4
1.1 1.1 1.1 1.1 1.0
0.8
0.8 0.7
0.6 0.6 0.5 0.5
0.1
0.0
0.5
1.0
1.5
2.0
2.5
Sweden
Finland
UnitedStates
Germany
Austria
Denmark
France
Luxembourg
Belgium
EU15
Slovenia
UnitedKingdom
CzechRepublic
Netherlands
Ireland
Spain
Italy
Portugal
Greece
EU15 average = 1.06%
0.9
0.8
0.6
0.5
0.5
0.4 0.4 0.4
0.3 0.3 0.3
0.2
0.2 0.2 0.2
0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
UnitedStates
Sweden
Austria
Portugal
Italy
CzechRepublic
Denmark
Finland
Germany
EU15
Belgium
Netherlands
UnitedKingdom
France
Spain
Slovenia
EU15 average = 0.29%
UK leads the ranking in organizational capital investment
over GDP in the market sector, while US tops the non-market
sector.
Figure 6: Share of GFCF on organisational capital over total GDP. EU-15 and US.
Average 2006-2010 (percentages)
Source: Eurostat, Intan-INVEST, SPINTAN and own elaboration.
a) Market sector b) Non-market sector
2.9
2.42.3
2.1
1.9
1.8
1.61.6
1.51.51.41.41.31.3
1.01.00.9
0.7
0.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
UnitedKingdom
UnitedStates
Belgium
Netherlands
France
Sweden
Slovenia
EU15
Austria
Portugal
Finland
Ireland
CzechRepublic
Germany
Luxembourg
Italy
Denmark
Spain
Greece
EU15 average = 1.6%
0.4
0.3
0.2
0.2
0.10.1
0.10.10.10.10.10.10.10.10.10.1
0.0
0.00.0
0.0
0.1
0.1
0.2
0.2
0.3
0.3
0.4
0.4
0.5
UnitedStates
Belgium
Italy
Netherlands
France
Sweden
Greece
EU15
Ireland
Finland
Austria
UnitedKingdom
Denmark
Portugal
Slovenia
CzechRepublic
Germany
Spain
Luxembourg
EU15 average = 0.1%
Denmark (followed by US) is the leader in investment in
training in the market sector and UK in the non-market
sector. US is above the EU-15 average.
Figure 7: Share of GFCF on training over total GDP. EU-15 and US. Average 2006-
2010 (percentages)
Source: Eurostat, INTAN-Invest, SPINTAN and own elaboration.
0.8
0.5
0.4
0.3
0.3
0.20.20.2
0.10.10.10.10.10.10.10.10.00.00.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
UnitedKingdom
Ireland
UnitedStates
Germany
EU15
CzechRepublic
Belgium
Finland
Sweden
Netherlands
Slovenia
Italy
France
Portugal
Greece
Luxembourg
Austria
Denmark
Spain
EU15 average = 0.3%
a) Market sector b) Non-market sector
1.3
1.1
1.0
0.90.9
0.80.8
0.80.80.7
0.7
0.60.50.50.50.5
0.40.4
0.0
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Denmark
UnitedStates
UnitedKingdom
France
Germany
Netherlands
Luxembourg
EU15
Austria
Ireland
Sweden
Slovenia
CzechRepublic
Italy
Belgium
Finland
Portugal
Spain
Greece
EU15 average = 0.8%
oWe need capital stock and capital services data for Growth
Accounting analysis
oThe Perpetual Inventory Method (PIM) is used to obtain
intangible capital stock figures.
oContrary to standard NA practices, a rate of return is
imputed to public capital.
oSo we need:
o A set of depreciation rates
o To select a rate of return for public capital (tangible and intangible)
3. EMPIRICAL MEASUREMENT:
FROM INVESTMENT TO CAPITAL SERVICES
20
21
Table 3: Depreciation rates for intangible assets
3. EMPIRICAL MEASUREMENT:
FROM INVESTMENT TO CAPITAL SERVICES
Rate of return
o It is now accepted that public capital should be assigned a net return
that goes beyond the NA practices of considering only the depreciation
component measured by the consumption of fixed capital.
o It is recommended to use a rate of return for the non-market economy
different from the market.
o The lack of statistical data providing cross-referenced information for
both industrial and institutional sectors is a major hurdle to
appropriately measure public capital.
o For this reason, the most consistent approach is to use an exogenous
rate of return.
o Since public investment crowds out both private consumption and
private investment, one logical choice is to use a combination of the
opportunity cost of both of them.
o The final option has been to select the Social Rate of Time Preference
(SRTP) for SPINTAN rate of return
22
3. EMPIRICAL MEASUREMENT:
FROM INVESTMENT TO CAPITAL SERVICES
4. IMPLICATIONS FOR ECONOMIC GROWTH
GROWTH ACCOUNTING
23
Figure 8: Contributions to labour productivity growth. Non-farm market sector, 1998-
2013 (percentages)
-2
-1
0
1
2
3
AT DE ES FI FR IT NL UK US EU
Labour composition Non ICT ICT Intangibles TFP GDP
Source: Corrado, Haskel, Jona-Lasinio, Iommi and O’Mahony (2016).
4. IMPLICATIONS FOR ECONOMIC GROWTH
GROWTH ACCOUNTING
24
Figure 9: Contributions to labour productivity growth. Non-market sector, 1998-2013
(percentages)
-2
-1
0
1
2
3
AT DE ES FI FR IT NL UK US EU
Labour composition Non ICT ICT Intangibles TFP GDP
Source: Corrado, Haskel, Jona-Lasinio, Iommi and O’Mahony (2016).
Corrado, C., Haskel, J. and C. Jona-Lasinio: “Spillovers from public intangibles” (Mimeo,
Spintan)
o Evidence of spillovers from public sector R&D to productivity in the market sector.
o Their findings suggest a rate of return of around 50% to public sector R&D spending.
o They also find that market sector investments in non-R&D intangible capital generate
spillovers to productivity.
o They do not find evidence that non-market non-R&D intangible investment has
spillover benefits to the market sector.
Schiersch, A. and M. Gornig Intangible Capital: “Complement or Substitute in the
Creation of Public Goods?” (Mimeo, Spintan)
o First analysis of the elasticity of substitution between intangible capital and other
inputs for public sector in Europe
o Intangible capital is only weakly substitutable with other inputs; but also not fully
complementary
MORE RESEARCH IS NEEDED, together with expanding and updating already existing
databases (EUKLEMS, INTAN_Invest) complementary to SPINTAN.
4. IMPLICATIONS FOR ECONOMIC GROWTH
ECONOMETRIC RESULTS
25
On Health and Education as societal intangible assets
SPINTAN sees education and health services as producing a societal asset that should
be included in saving and wealth
Serrano, L., Soler, A. and Hernández, L: “Fiscal consolidation and crisis in the EU: exploring long-
run supply-side effects through education” (SPINTAN Working Paper nº 7)
o Fiscal consolidation might affect negatively educational attainment but with the crisis,
job opportunities for young people drastically decrease. This reduces the opportunity
cost of studying, extending schooling, reducing dropout rates and fostering human
capital accumulation. All in all, the latter positive effects seem to dominate any
negative long-run supply-side effect.
José Manuel Pastor, Lorenzo Serrano “The research output of universities and its determinants:
quality, intangible investments, specialisation and inefficiencies” (SPINTAN Working Paper nº 5)
o Intangibles are determinants of the research productivity of the European HEIs.
There are important efficiency differences in research activity across countries but
there seems to be a wide margin for the EU to substantially increase research output
without having to assign additional resources, lower the quality or change the field of
science.
5. ADDITIONAL POLICY IMPLICATIONS
26
Intangibles and fiscal consolidation
Pellens, M., Peters, B., Rammer, C. And G. Licht: “Public Investment in R&D in reaction to economic
crises – a longitudinal study for OECD countries” (SPINTAN, Working Paper nº 16)
o Whereas European innovation leaders and non-EU countries pursue a counter-cyclical
strategy, innovation followers and moderate innovators behave pro-cyclical. This leads
to an increasing innovation gap in Europe.
o There is no evidence that economic crises systematically affect the composition of
public R&D spending along different thematic areas or by beneficiaries.
Goerlich, F.J. and L. Hernández “Fiscal consolidation and income distribution” (SPINTAN Working
Paper nº 7)
o If in-kind transfers are added there are no relative inequality effects of fiscal
consolidations in countries where public sector cuts have been deeper. Reason:
primary incomes have fallen far more than the cuts in public services provided to
citizens. Individual national experiences vary, but in-kind public transfers have been
highly redistributive also during the crisis.
5. ADDITIONAL POLICY IMPLICATIONS
27
On Organizational Capital (OC)
Beckmann, L., Huttl, A., O’Mahony, M., Schultz, E. and L. Stokes: “Intangible Investment and Hospital
Performance” (SPINTAN, Mimeo)
OC is associated with enhanced hospital performance when broad measures are
employed that include both general managers and clinical practitioners with some
managerial responsibilities. Personnel with clinical responsibilities appear to be important
in generating the types of long term improvements that are associated with organisational
capital.
Bryson, A., Stokes, L., and D. Wilkinson: “The role of intangibles in school performance: a case study
for England” (SPINTAN, Mimeo)
o Same approach for OC for schools as for hospitals, identifying staff in leadership roles.
These measures of OC are positively associated with school performance. Schools
judged outstanding at inspection appear to have a higher % staff engaged in broader
leadership roles.
Squicciarini, M., and L. Marcolin: “Knowledge-based capital and global value chains: the role of
organisational capital”
5. ADDITIONAL POLICY IMPLICATIONS
28
The “Smart Public Intangibles (SPINTAN)”
Project: Main Findings and Policy
Implications
Matilde Mas
Universitat de València and IVIE
Joint meeting of the Working Party on Industry Analysis (WPIA) and the
Working Party on Globalisation of Industry (WPGI)
OECD, Paris, October 11th 2016

Working Party on Industry Analysis (WPIA)

  • 1.
    The “Smart PublicIntangibles (SPINTAN)” Project: Main Findings and Policy Implications Matilde Mas Universitat de València and IVIE Joint meeting of the Working Party on Industry Analysis (WPIA) and the Working Party on Globalisation of Industry (WPGI) OECD, Paris, October 11th 2016
  • 2.
    The Objective ofthe SPINTAN project is to identify and measure public sector intangible capital which allows us to evaluate its role as a driver of firm-industry-country economic growth. It develops new insights on the role of public sector knowledge creation which can be relevant for the European innovation and growth policy agenda. At the most practical level, its goal is to complete the coverage of the sources of growth information already existing for the market economy (EU KLEMS (FP 6th), COINVEST (FP 7th), INDICSER (FP 7th), INNODRIVE (FP 7th) and INTAN-Invest) including the Public Sector, making possible the generation of total economy growth accounts with intangibles as productive assets. OBJETIVES 2
  • 3.
    INDEX 1. Identification: Framework 2.Empirical Measurement: Investment 3. Empirical Measurement: From Investment to Capital Services 4. Implications for Economic growth 5. Additional Policy Implications OBJETIVES 3
  • 4.
    Starting point: Corrado, C.,Hulthen, C., and D. Sichel (2005): «Measuring Capital and technology: An expanded framework», Measuring Capital in the New Economy, University of Chicago Press. Corrado, C., Hulten, J., and D. Sichel (2009): «Intangible capital and US economic growth», The Review of Income and Wealth 55(3), 661-685. Corrado, C., Haskel, J. and C. Jona-Lasinio (2014): Smart Public Intangibles: SPINTAN Framework and Measurement (Spintan, Mimeo) Corrado, C., Jäger, K. and C. Jona-Lasinio (eds.) (2015): Measuring intangible capital in the Public sector (Spintan, Mimeo) Expected Final Output: SPINTAN Manual 1. FRAMEWORK 4
  • 5.
    1. Industry Coverage Table1: SPINTAN industries of interest 1. FRAMEWORK 5
  • 6.
    2. Industries vs.Institutional sector Figure 1: Enterprise types in the SNA: Groups according to control (private, public) and ability to charge economically significant prices (market, nonmarket) 1. FRAMEWORK 6
  • 7.
    3. CHS CHS typeof asset: market vs. nonmarket Table 2: Knowledge capital in a total economy 1. FRAMEWORK 7
  • 8.
    1. FRAMEWORK 8 Figure 2:UNESCO Framework for statistics on cultural domains
  • 9.
    Main Pillars: 1. Expenditurebased approach 2. Reproducibility 3. “Updatability” 4. Homogeneity: Comparability across countries 5. Consistency with National Accounts *Based on Iommi, M. and C. Jona-Lasinio (2015): Measuring public sector investment in intangible asset: Main achievements and open issues, (Spintan, Mimeo) 2. EMPIRICAL MEASUREMENT: INVESTMENT* 9
  • 10.
    Two different strategiesfor: 1. New Intangible assets (NewIA) o Design o Market research and advertising o Organisational Capital o Training 2. Assets already included in the SNA/ESA (NAIA) o Computer software and databases o Research and development o Mineral exploration o Entertainment, literary and artistic originals 2. EMPIRICAL MEASUREMENT: INVESTMENT 10
  • 11.
    1. New Intangibleassets (NewIA) o Expenditures for NewIA are currently considered expenditure to purchase intermediate inputs oNo output produced for own use is recorded (in NA only final output for own final use is included in the production boundary) oBoth, the production and the use of the purchased component are registered in NA data o We have to produce our estimates of the own account component o We have no reasons to change NA estimates of total output and total expenditure o We want to change the type of use (from intermediate consumption to GFCF) 2. EMPIRICAL MEASUREMENT: INVESTMENT 11
  • 12.
    1. New Intangibleassets (NewIA) 1.1 Purchased intermediate inputs o Main source: Use tables o Data on total expenditure is required for each product that relates to NewIA for the industry/sector o Assumptions on how much of each expenditure might be considered GFCF o Use tables usually available with delay (t-3) 2. EMPIRICAL MEASUREMENT: INVESTMENT 12
  • 13.
    1. New Intangibleassets (NewIA) 1.2 Own Account Component o Standard Approach: to value it at the costs of production, i.e. the sum of compensation of employees, intermediate consumption and the cost of capital (consumption of fixed capital and, only for market producers, net operating surplus) o For Organisational Capital it can be estimated using data from LFS-SES integrated with data from the OECD survey on compensation in the public sector for the O84 industry o We deem that own-account production of design, advertising and market research in the non-market sector is negligible 2. EMPIRICAL MEASUREMENT: INVESTMENT 13
  • 14.
    2. National AccountsIntangibles Assets (NAIA) o Include both, purchased and own-account component o Usually data are not available at the level of detail that we need (i.e. cross-classified by asset, industry and sector) o Quite likely that there is no GFCF in Mineral Explorations and Originals in the non-market component of the industries of interest to Spintan. o We need to produce estimates of GFCF in Computer software and Databases and in Research and Development cross- classified by industry and by sector that are consistent with the available national accounts data on GFCF. o Very few countries provide also data on GFCF by institutional sector for IPP (and some components) 2. EMPIRICAL MEASUREMENT: INVESTMENT 14
  • 15.
    Deflation. Options forSPINTAN o Producing our own hedonic price indexes, IPP and input-based deflator for all countries (it would be nice but a little bit too demanding) o Use NA GFCF deflators for NAIA and output/value added deflators for NewIA o Current SPINTAN estimates: o NA deflators o The same deflator for purchased and own account organisational capital 2. EMPIRICAL MEASUREMENT: INVESTMENT 15
  • 16.
    US outperforms theEU in market and non- market intangible investment . Heterogeneity within EU-15. Sweden and UK in top positions. The four peripheral countries at the tail end. Figure 3: Share of GFCF on intangible assets over total GDP. EU15 and US. Average 2006-2010 (percentages) Source: Eurostat, INTAN-Invest, SPINTAN and own elaboration. a) Market sector b) Non-market sector 10.8 8.48.3 7.57.47.37.16.96.8 6.36.36.26.16.0 5.2 4.54.54.3 2.1 0 2 4 6 8 10 12 UnitedStates Sweden UnitedKingdom Belgium Denmark France Finland Slovenia Netherlands EU15 CzechRepublic Germany Austria Luxembourg Ireland Spain Portugal Italy Greece EU15 average = 6.3% 2.5 1.6 1.3 1.11.1 0.90.90.90.90.90.80.80.70.70.7 0.6 0.4 0.20.2 0.0 0.5 1.0 1.5 2.0 2.5 3.0 UnitedStates Sweden UnitedKingdom Italy Netherlands Austria Portugal Finland EU15 Belgium CzechRepublic Germany Ireland France Denmark Slovenia Spain Greece Luxembourg EU15 average = 0.9%
  • 17.
    In R&D thegap with US is larger in the non-market sector Figure 5: Share of GFCF on R&D over total GDP. EU15 and US. Average 2006-2010 (percentages) Source: Eurostat, INTAN-Invest, SPINTAN and own elaboration. a) Market sector b) Non-market sector 2.2 2.1 2.0 1.6 1.6 1.4 1.1 1.1 1.1 1.1 1.0 0.8 0.8 0.7 0.6 0.6 0.5 0.5 0.1 0.0 0.5 1.0 1.5 2.0 2.5 Sweden Finland UnitedStates Germany Austria Denmark France Luxembourg Belgium EU15 Slovenia UnitedKingdom CzechRepublic Netherlands Ireland Spain Italy Portugal Greece EU15 average = 1.06% 0.9 0.8 0.6 0.5 0.5 0.4 0.4 0.4 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 UnitedStates Sweden Austria Portugal Italy CzechRepublic Denmark Finland Germany EU15 Belgium Netherlands UnitedKingdom France Spain Slovenia EU15 average = 0.29%
  • 18.
    UK leads theranking in organizational capital investment over GDP in the market sector, while US tops the non-market sector. Figure 6: Share of GFCF on organisational capital over total GDP. EU-15 and US. Average 2006-2010 (percentages) Source: Eurostat, Intan-INVEST, SPINTAN and own elaboration. a) Market sector b) Non-market sector 2.9 2.42.3 2.1 1.9 1.8 1.61.6 1.51.51.41.41.31.3 1.01.00.9 0.7 0.0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 UnitedKingdom UnitedStates Belgium Netherlands France Sweden Slovenia EU15 Austria Portugal Finland Ireland CzechRepublic Germany Luxembourg Italy Denmark Spain Greece EU15 average = 1.6% 0.4 0.3 0.2 0.2 0.10.1 0.10.10.10.10.10.10.10.10.10.1 0.0 0.00.0 0.0 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 0.5 UnitedStates Belgium Italy Netherlands France Sweden Greece EU15 Ireland Finland Austria UnitedKingdom Denmark Portugal Slovenia CzechRepublic Germany Spain Luxembourg EU15 average = 0.1%
  • 19.
    Denmark (followed byUS) is the leader in investment in training in the market sector and UK in the non-market sector. US is above the EU-15 average. Figure 7: Share of GFCF on training over total GDP. EU-15 and US. Average 2006- 2010 (percentages) Source: Eurostat, INTAN-Invest, SPINTAN and own elaboration. 0.8 0.5 0.4 0.3 0.3 0.20.20.2 0.10.10.10.10.10.10.10.10.00.00.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 UnitedKingdom Ireland UnitedStates Germany EU15 CzechRepublic Belgium Finland Sweden Netherlands Slovenia Italy France Portugal Greece Luxembourg Austria Denmark Spain EU15 average = 0.3% a) Market sector b) Non-market sector 1.3 1.1 1.0 0.90.9 0.80.8 0.80.80.7 0.7 0.60.50.50.50.5 0.40.4 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Denmark UnitedStates UnitedKingdom France Germany Netherlands Luxembourg EU15 Austria Ireland Sweden Slovenia CzechRepublic Italy Belgium Finland Portugal Spain Greece EU15 average = 0.8%
  • 20.
    oWe need capitalstock and capital services data for Growth Accounting analysis oThe Perpetual Inventory Method (PIM) is used to obtain intangible capital stock figures. oContrary to standard NA practices, a rate of return is imputed to public capital. oSo we need: o A set of depreciation rates o To select a rate of return for public capital (tangible and intangible) 3. EMPIRICAL MEASUREMENT: FROM INVESTMENT TO CAPITAL SERVICES 20
  • 21.
    21 Table 3: Depreciationrates for intangible assets 3. EMPIRICAL MEASUREMENT: FROM INVESTMENT TO CAPITAL SERVICES
  • 22.
    Rate of return oIt is now accepted that public capital should be assigned a net return that goes beyond the NA practices of considering only the depreciation component measured by the consumption of fixed capital. o It is recommended to use a rate of return for the non-market economy different from the market. o The lack of statistical data providing cross-referenced information for both industrial and institutional sectors is a major hurdle to appropriately measure public capital. o For this reason, the most consistent approach is to use an exogenous rate of return. o Since public investment crowds out both private consumption and private investment, one logical choice is to use a combination of the opportunity cost of both of them. o The final option has been to select the Social Rate of Time Preference (SRTP) for SPINTAN rate of return 22 3. EMPIRICAL MEASUREMENT: FROM INVESTMENT TO CAPITAL SERVICES
  • 23.
    4. IMPLICATIONS FORECONOMIC GROWTH GROWTH ACCOUNTING 23 Figure 8: Contributions to labour productivity growth. Non-farm market sector, 1998- 2013 (percentages) -2 -1 0 1 2 3 AT DE ES FI FR IT NL UK US EU Labour composition Non ICT ICT Intangibles TFP GDP Source: Corrado, Haskel, Jona-Lasinio, Iommi and O’Mahony (2016).
  • 24.
    4. IMPLICATIONS FORECONOMIC GROWTH GROWTH ACCOUNTING 24 Figure 9: Contributions to labour productivity growth. Non-market sector, 1998-2013 (percentages) -2 -1 0 1 2 3 AT DE ES FI FR IT NL UK US EU Labour composition Non ICT ICT Intangibles TFP GDP Source: Corrado, Haskel, Jona-Lasinio, Iommi and O’Mahony (2016).
  • 25.
    Corrado, C., Haskel,J. and C. Jona-Lasinio: “Spillovers from public intangibles” (Mimeo, Spintan) o Evidence of spillovers from public sector R&D to productivity in the market sector. o Their findings suggest a rate of return of around 50% to public sector R&D spending. o They also find that market sector investments in non-R&D intangible capital generate spillovers to productivity. o They do not find evidence that non-market non-R&D intangible investment has spillover benefits to the market sector. Schiersch, A. and M. Gornig Intangible Capital: “Complement or Substitute in the Creation of Public Goods?” (Mimeo, Spintan) o First analysis of the elasticity of substitution between intangible capital and other inputs for public sector in Europe o Intangible capital is only weakly substitutable with other inputs; but also not fully complementary MORE RESEARCH IS NEEDED, together with expanding and updating already existing databases (EUKLEMS, INTAN_Invest) complementary to SPINTAN. 4. IMPLICATIONS FOR ECONOMIC GROWTH ECONOMETRIC RESULTS 25
  • 26.
    On Health andEducation as societal intangible assets SPINTAN sees education and health services as producing a societal asset that should be included in saving and wealth Serrano, L., Soler, A. and Hernández, L: “Fiscal consolidation and crisis in the EU: exploring long- run supply-side effects through education” (SPINTAN Working Paper nº 7) o Fiscal consolidation might affect negatively educational attainment but with the crisis, job opportunities for young people drastically decrease. This reduces the opportunity cost of studying, extending schooling, reducing dropout rates and fostering human capital accumulation. All in all, the latter positive effects seem to dominate any negative long-run supply-side effect. José Manuel Pastor, Lorenzo Serrano “The research output of universities and its determinants: quality, intangible investments, specialisation and inefficiencies” (SPINTAN Working Paper nº 5) o Intangibles are determinants of the research productivity of the European HEIs. There are important efficiency differences in research activity across countries but there seems to be a wide margin for the EU to substantially increase research output without having to assign additional resources, lower the quality or change the field of science. 5. ADDITIONAL POLICY IMPLICATIONS 26
  • 27.
    Intangibles and fiscalconsolidation Pellens, M., Peters, B., Rammer, C. And G. Licht: “Public Investment in R&D in reaction to economic crises – a longitudinal study for OECD countries” (SPINTAN, Working Paper nº 16) o Whereas European innovation leaders and non-EU countries pursue a counter-cyclical strategy, innovation followers and moderate innovators behave pro-cyclical. This leads to an increasing innovation gap in Europe. o There is no evidence that economic crises systematically affect the composition of public R&D spending along different thematic areas or by beneficiaries. Goerlich, F.J. and L. Hernández “Fiscal consolidation and income distribution” (SPINTAN Working Paper nº 7) o If in-kind transfers are added there are no relative inequality effects of fiscal consolidations in countries where public sector cuts have been deeper. Reason: primary incomes have fallen far more than the cuts in public services provided to citizens. Individual national experiences vary, but in-kind public transfers have been highly redistributive also during the crisis. 5. ADDITIONAL POLICY IMPLICATIONS 27
  • 28.
    On Organizational Capital(OC) Beckmann, L., Huttl, A., O’Mahony, M., Schultz, E. and L. Stokes: “Intangible Investment and Hospital Performance” (SPINTAN, Mimeo) OC is associated with enhanced hospital performance when broad measures are employed that include both general managers and clinical practitioners with some managerial responsibilities. Personnel with clinical responsibilities appear to be important in generating the types of long term improvements that are associated with organisational capital. Bryson, A., Stokes, L., and D. Wilkinson: “The role of intangibles in school performance: a case study for England” (SPINTAN, Mimeo) o Same approach for OC for schools as for hospitals, identifying staff in leadership roles. These measures of OC are positively associated with school performance. Schools judged outstanding at inspection appear to have a higher % staff engaged in broader leadership roles. Squicciarini, M., and L. Marcolin: “Knowledge-based capital and global value chains: the role of organisational capital” 5. ADDITIONAL POLICY IMPLICATIONS 28
  • 29.
    The “Smart PublicIntangibles (SPINTAN)” Project: Main Findings and Policy Implications Matilde Mas Universitat de València and IVIE Joint meeting of the Working Party on Industry Analysis (WPIA) and the Working Party on Globalisation of Industry (WPGI) OECD, Paris, October 11th 2016

Editor's Notes

  • #6 Since the intention is to expand the existing intangibles framework, we continue to treat the current scope of GDP as our production possibilities frontier. In other words, while we consider nonmarket production by public and nonprofit institutions, nonmarket production by households is excluded
  • #7 Investment activities of the general government and nonprofit institutions (NPI) are the focus of Spintan. Many NPI are considered market producers according to the System of National Accounts (SNA) because they are able to charge “economically significant” prices. NPI = NPISH + NPIPP (nonprofit institutions with pricing power). Example: educational institutions can be public or private, and among the later while most are nonprofit institutions some are classified as market producers. The distinction is important (imputation of a return)
  • #8 (2) Public Sector information = information and content that is produced and/or collected by a public body as part of its public task (statistical info, meteorological data, geographical, business…). It is typically stored in databases. (7) OC should take into consideration not only managers but also professional employees in using the labour cost approach to estimate OC in the public sector (8) It is proposed a new methodology to estimate investment in training at the industry and country level for 2011-2012 mainly based on PIAAC, expanding the types of training to include not only the direct cost but also the opportunity cost of training (=the foregone earnings of workders and output of production when the individual is in training 4. Cultural Assets= public intangible assets whose services are used in production in cultural domains (as defined by UNESCO) dominated or influenced by the public and nonmarket sectors.
  • #22 The rate for software is from EUKLEMS (a bit slower than CHS). The rate for mineral exploration is the US BEA rate. The others are, in general, similar (even the same) as CHS