1 R&D efforts during crisis and beyond: Some lessons from NEMESIS simulations Arnaud Fougeyrollas, Pierre Haddad, Boris le Hir, Pierre le Mouël et Paul.

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R&D efforts during crisis and beyond: Some lessons from

NEMESIS simulations

Arnaud Fougeyrollas, Pierre Haddad, Boris le Hir, Pierre le Mouël et Paul Zagamé

WIOD CONFERENCE VIENNA- May 26-28, 2010

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Outline

1. The NEMESIS model

2- R&D policies are useful during crisis

3- A new scenario for 3% Barcelona objective

4- Increasing R&D effort: doubling FP8

5- Redeployment of European budget towards R&D

6- Conclusions

3

1-The NEMESIS Model:

1.1-General dynamicPhysico Economic interdependancies

NEMESISCore economic

model

Energy/EnvironmentModule

Regional Module(Gives results for NUTS 2

regions)

Agriculture module(Detailed agriculture production

function)

Land-Use module-Transport

- Urban- Agriculture

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1- The NEMESIS Model

1.1-General dynamic Intersectoral Economic Interdependancies: up to

Knowledge (30 sectors)

Price and substitution effects on final demand Exchange of goods and services for production (input-output)

Intermediary CapitalKnowledge spillovers

Strong heterogeneity of sectors from a dynamic point of view (employment, knowledge, Environment, Energy…)

Economic track: the result of strong interdependancies of most progressive sectors (I.C.I, biotechnologies, and less ones (some services, agriculture)

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1-The NEMESIS Model

1.1-General dynamicMacro-sectoral (hybrid)

Bottom-up sector approach: GDP, revenues are the sum of sectors

Top down: macro Economic Saving Consumption arbitrage

Hybrid result: dynamic loop is generally sectoral: productions, prices, investment, employment, revenues but with a macroeconomic feedback by consumption

Complex result for the dynamic

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1- The NEMESIS Model

1.1-General DynamicInternational interdependancies

27 distinct models for EuropeSimplified models for Areas of rest of the

WorldInternational exchanges of goods and servicesInternational knowledge spillovers

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1- The NEMESIS Model

1.2- Econometric based mechanismsEconometrics

Mainly on chronological data or panel data (sectors, countries)

Based on implicit maximisation behaviour, (utility profit) but not on explicit maximization conditions and with a choice of relationship based on econometric criteria

Then different from applied general equilibrium approach that is based on:Maximization CalibrationEqilibrium on every market

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1- The NEMESIS Model

1.2-Econometric based mechanismsA compromise theory /data

Applied modelling is always a « compromise » between :TheoryData and facts

The compromise for econometric modelling is nearer data and facts than general equilibrium one

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1- The NEMESIS Model

1.2- Econometric based mechanisms

InconvenientsCan be rejected by strict orthodoxyNo explicit utility functions and then

impossibility to calculate surplisses variations associated to policies

Dependant on statistics availability that is not case for G.E.M. aprroach that is calibrated

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1- The NEMESIS Model

1.2-Econometric based mechanisms

AdvantagesModelling is more based on data recent

tendencies and in this sense « more realistic »Allow forecasts and easier link with the present

conjoncture conditions for the start of Baseline Allow easier adaptation to specific mechanisms

(pricing for zero marginal cost activities)

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1- The NEMESIS Model

1.2-Econometric based mechanismsAdvantages (following)

Structure more « flexible » allowing easy removal of mechanismsMore adaptable to heterodox theoriesSuited for prospective of « break through

scenario ».

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1- The NEMESIS Model

1.3-The central rôle of « knowledge economics »

Three main variables

R&D expenditures and R&D stocksSpillovers and technical Knowledge

(T.K.)Human capital

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1- The NEMESIS Model

1.4. Externalities and knowledge spillovers

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KNOW

Foreign Public R&D StockR&D Stocks of Foreign

SectorsPublic R&D Stock

R&D Stock of Other Sectors

R&D Stock of the Sector

Technology Flow MatricesTechnology Flows

Matrices

R&D StockR&D Expenditures Decay

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1- The NEMESIS Model

= elasticity for KNOW performance

– increasing with R&D intensity in the sector i and the country j

with14

ij

ij

ijij Y

Rf 0'

1.5-Sectoral and national results for knowledge performance

KNOW

KNOW

Y

Yij

.

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1- The NEMESIS Model

1.5-Sectoral and national results for R&D performance

But sectoral knowledge spillovers very heterogeneous

- Emitting sources- Reception

Then for sectors and countries– Identity for private rate of return– Heterogeneity of social rate of return

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16

1- The NEMESIS Model

1.6-The use of NEMESISEnergyEnvironment, GHG, other pollutionsAgriculture and land useR&D and knowledge Economics:

3% barcelona FP (7-8) New National Action Plan for R&D

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2- R&D policies are useful during crisis

2.1- R&D effort is lowering during crisis (procyclical):Countercyclical view:

Need for efficiency Opportunity cost Bental and Piled (1960) François Lloyd Ellis (2003)

But majority for pro-cyclical view: Financial contraints Demand driven François Lloyd Ellis (2009)

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2- R&D policies are useful during crisis

2.2- The durability of crisis Short term effects of crisis: DG ECFIN (Fall

prospect)

GDP Employment GDP Employment GDP Employment

Trend (growth rate) 2.7% 1.4% 1.6% -0.4% 1.8% -0.3% Crisis (growth rate) 0.8% 1.2% -4.1% -2.3% 0.7% -1.2% Cumulartive GAP (%) 1.9% 0.2% 7.6% 2.1% 8.7% 3.0%

2008 2009 2010

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2- R&D policies are useful during crisis

2.2- The durability of crisis Evolution of GDP in pre- and post-crisis forecast

scenarios Evolution of GDP (Billion € 2000)

9000

10000

11000

12000

13000

14000

15000

16000

17000

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

Forecast before Crise New forecast

(1)

(2)

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2- R&D policies are useful during crisis

In the new forecast, NEMESIS is constrained in 2008, 2009 and 2010 to reproduce DG ECFIN GDP prospects.

After 2010, NEMESIS shows that the effects of crisis are durable: The GDP gap increases up to 2025 and after

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2- R&D policies are useful during crisis

2.2- The durability of crisis Average growth rates of production in

pre- and post-crisis forecast scenarios

Pre-Crisis Post-Crisis Pre-Crisis Post-Crisis Pre-Crisis Post-Crisis Pre-Crisis Post-Crisis Pre-Crisis Post-CrisisAgriculture 0.0% -0.4% -0.4% -1.6% -0.2% 0.1% 0.7% 1.0% 0.5% 0.6%Energy 1.5% 0.3% -1.3% -6.9% 0.6% -2.3% 2.4% 2.6% 1.2% 1.0%Intermediate goods 4.3% 2.7% 2.1% -7.9% 1.7% -2.2% 2.4% 3.9% 2.1% 2.0%Equipment goods 4.7% 2.5% 2.2% -11.0% 1.9% -0.8% 2.6% 4.0% 2.3% 2.3%Final consumption goods 2.3% 1.4% 1.3% -3.8% 1.1% -1.2% 1.7% 2.2% 1.4% 1.2%Construction 4.8% 0.5% 0.8% -17.6% 1.9% 1.1% 2.7% 3.0% 2.2% 1.3%Distribution 2.3% 1.2% 1.5% -3.9% 1.5% -0.1% 2.4% 2.4% 1.9% 1.7%Transports 3.2% 2.1% 1.9% -5.2% 1.8% -0.3% 2.7% 3.4% 2.3% 2.3%Communications 2.8% 2.0% 2.0% -2.2% 1.8% -0.5% 2.8% 2.9% 2.2% 2.0%Bank, finance, insurance 2.8% 2.0% 2.0% -2.2% 1.8% -0.5% 2.8% 2.9% 2.2% 2.0%Other market services 2.4% 1.3% 1.5% -3.5% 1.4% -0.7% 2.5% 2.6% 1.9% 1.7%Non market services 1.8% 2.1% 1.2% 1.2% 1.7% 1.5% 2.4% 2.1% 2.1% 2.0%Total 2.9% 1.7% 1.5% -5.4% 1.5% -0.4% 2.4% 2.8% 2.0% 1.8%

2016-20252008 2009 2010 2011-2015

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2- R&D policies are useful during crisis

2.2- The durability of crisis Evolution of employment in pre- and post-

crisis forecast scenarios

Evolution of employment (Millions)

202

207

212

217

222

227

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

Forecast before Crise New forecast

(1)

(2)

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2- R&D policies are useful during crisis

2.2- The durability of crisis

Evolution of Employment is different than for GDP: The employment gap of 2010 is half filled in 2015

The lowering of wages during crisis allows a growth richer in employment during the economic recovery

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2- R&D policies are useful during crisis

2.3- The research for economic

recoveryPost-Crisis scenario with countercyclical

R&D (3):Increase of R&D effort up to 3% GDP in 2020Additional R&D financed mainly by private sector

such as to reach 2% private financing in 2020

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2- R&D policies are useful during crisis

2.3- The research for economic recovery Evolution of GDP (Billion € 2000)

9000

10000

11000

12000

13000

14000

15000

16000

17000

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

Forecast before Crise New forecast Counter-cyclical scenario

(1)

(2)

(3)

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2- R&D policies are useful during crisis

2.3- The research for economic

recovery43% of GDP gap is filled in 2025but GDP growth is faster and GDP gap

reduced compared to the post-crisis scenario without counter-cyclical R&D

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2- R&D policies are useful during crisis

2.3- The research for economic recovery

Evolution of employment (Millions)

202

207

212

217

222

227

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

Forecast before Crise New forecast Counter-cyclical scenario

(1)

(2)

(3)

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2- R&D policies are useful during crisis

2.3- The research for economic recovery

The employment Gap is almost filled in 2015.The reduction of wages during crising

stimulates employment, the increase in R&D effort boosts growth: Economic recovery is rich in jobs creation

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3- A new scenario for Barcelona 3% objective

Former assessment in 2002 for EU15

Extension to new member States

New agenda

Crisis

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3- A new scenario for Barcelona 3% objective

RD effort in new Barcelona 3% scenario

0.016

0.018

0.02

0.022

0.024

0.026

0.028

0.03

0.032

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

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3- A new scenario for Barcelona 3% objective

GDP and its counterparts in the 2002 assessment for EU15

-4%

-3%

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

11%

12%

13%

14%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

GDP (1) Investment (2) Final Consumption (3)

Employment (4) Exports (5) Imports (6)

(1)

(2)

(3)

(4)

(6)

(5)

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3- A new scenario for Barcelona 3% objective

GDP and its counterparts in the new Barcelona scenario for EU27

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

GDP (1) Investment (2) Final Consumption (3)

Employment (4) Exports (5) Imports (6)

(5)

(3)

(1)

(4)

(2)

(6)

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3- A new scenario for Barcelona 3% objective

Crisis reduces R&D efforts in the model in 2009

The new assessment shows less deficits in the first phase due to low inflationary pressure in reason of: High unemployment rate Low production capacity utilisation rate

In the long term the major driver for GDP growth are first exportations and second final consumption It was the reverse in the former assessment The lowering of wages during crisis stimulates external

competitiveness but hampers final consumption

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4- Increasing R&D effort : doubling the

FP8 (1/4)4.1- Characteristics of the FP:

Small share of R&D effort of the European countries: 0.054% of EU GDP in 2009 Up to potentially 0.076% in 2013

(according to the F.P. 7 financial scheme)

1.9% for total R&D effort

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4- Increasing R&D effort : doubling the FP8

(2/4)4.1- Characteristics of the FP But generates strong incentives (crowding-in

effects):

Networks effects

Best practices transfer

High productivity

Then doubling FP in 2020

FP will be 0,15% of EU G.D.P.

The total R&D effort raises by 0,18% of G.D.P. (1/6 of

Barcelona effort)

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4- Increasing R&D effort : doubling the FP8 (3/4)

4.2-Economic consequences

-0.75%

-0.50%

-0.25%

0.00%

0.25%

0.50%

0.75%

1.00%

1.25%

1.50%

1.75%

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

GDP (1) Investment (2) Consumption (3)

Employment (4) Exports (5) Imports (6)

(1)

(2)

(3)

(4)

(5)

(6)

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5- Redeployment of European budget towards

R&D5.1- Redeploying part of CAP direct supports ( ≈ 16%) towards the FP in order to double it leads to an increase of G.D.P and employment:

1.2% additional GDP in 2025

1 million (0.48%) more jobs in 2025

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5- Redeployment of European budget towards R&D

5.2-But with important adjustment costs for agriculture:

Production -0,14Arable land -0,46Employment -2,3Revenu -2,45

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GDP

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6- Conclusion

R&D policies seem to be more adapted to today economic situation deeply impacted by the crisis:Pulling up the European economy while

inducing only limited deficits and inflationary pressures

A better way out of the crisis with a fast catching up of employment and a lower one of G.D.P., compared to their potential level before crisis

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6- Conclusion

The implementation of other structural policies like GHG reduction could also give more breathing space for increasing the R&D effort incentive policies: ex. recycling of the auctionning revenus of the EUTS permits

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6- Conclusion

The results presented here are macro economic at EU level

The different results at a detailed level or countries and sectors highly differenciated regarding the R&D efforts and knowledge spillovers are interesting

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6- Conclusion

The future developments of modelling are on:

The use of new databases (EU-KLEMS and WIOD for productivities, input output tables in order to make new estimations

Deepening of externalities and Knowledge spillovers General purpose technologies (ICT,…) International spillovers

New simulations on R&D policies

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6- Conclusion

• The main message for WIOD is :

– The feasibility of simulations of a detailed interdependent econometric system

– The need for new databases and the first results of WIOD will be welcome

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6- Conclusion

Thank you for your attention!

[email protected]@ecp.fr

[email protected]