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

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 Zagamé WIOD CONFERENCE VIENNA- May 26-28, 2010

2. Outline • 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 dynamic Physico Economic interdependancies Energy/Environment Module Regional Module (Gives results for NUTS 2 regions) NEMESIS Core economic model Land-Use module -Transport - Urban - Agriculture Agriculture module (Detailed agriculture production function)

4. 1- The NEMESIS Model 1.1-General dynamic • IntersectoralEconomicInterdependancies: up to Knowledge • (30 sectors) • Price and substitution effects on final demand • Exchange of goods and services for production (input-output) • Intermediary • Capital • Knowledgespillovers • Strongheterogeneity of sectorsfrom a dynamic point of view (employment, knowledge, Environment, Energy…) • Economictrack: the result of stronginterdependancies of most progressive sectors (I.C.I, biotechnologies, and lessones (some services, agriculture)

5. 1-The NEMESIS Model 1.1-General dynamic • Macro-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

6. 1- The NEMESIS Model 1.1-General Dynamic • International interdependancies • 27 distinct models for Europe • Simplified models for Areas of rest of the World • International exchanges of goods and services • International knowledge spillovers

7. 1- The NEMESIS Model 1.2- Econometric based mechanisms • Econometrics • 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 • Calibration • Eqilibrium on every market

8. 1- The NEMESIS Model 1.2-Econometric based mechanisms • A compromise theory /data • Applied modelling is always a « compromise » between : • Theory • Data and facts • The compromise for econometric modelling is nearer data and facts than general equilibrium one

9. 1- The NEMESIS Model 1.2- Econometric based mechanisms • Inconvenients • Can be rejected by strict orthodoxy • No 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

10. 1- The NEMESIS Model 1.2-Econometric based mechanisms • Advantages • Modelling 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)

11. 1- The NEMESIS Model 1.2-Econometric based mechanisms • Advantages (following) • Structure more « flexible » allowing easy removal of mechanisms • More adaptable to heterodox theories • Suited for prospective of « break through scenario ».

12. 1- The NEMESIS Model 1.3-The central rôle of « knowledge economics » • Three main variables • R&D expenditures and R&D stocks • Spillovers and technical Knowledge (T.K.) • Human capital

13. 1- The NEMESIS Model 1.4. Externalities and knowledge spillovers

14. 1- The NEMESIS Model 1.5-Sectoral and national results for knowledge performance • = elasticity for KNOW performance • increasing with R&D intensity in the sector i and the country j with

15. 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

16. 1- The NEMESIS Model 1.6-The use of NEMESIS • Energy • Environment, GHG, other pollutions • Agriculture and land use • R&D and knowledge Economics: • 3% barcelona • FP (7-8) • New National Action Plan for R&D

17. 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)

18. 2- R&D policies are useful during crisis • 2.2- The durability of crisis • Short term effects of crisis: DG ECFIN (Fall prospect)

19. 2- R&D policies are useful during crisis • 2.2- The durability of crisis • Evolution of GDP in pre- and post-crisis forecast scenarios

20. 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

21. 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

22. 2- R&D policies are useful during crisis • 2.2- The durability of crisis • Evolution of employment in pre- and post-crisis forecast scenarios

23. 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

24. 2- R&D policies are useful during crisis • 2.3- The research for economic recovery • Post-Crisis scenario with countercyclical R&D (3): • Increase of R&D effort up to 3% GDP in 2020 • Additional R&D financed mainly by private sector such as to reach 2% private financing in 2020

25. 2- R&D policies are useful during crisis • 2.3- The research for economic recovery

26. 2- R&D policies are useful during crisis • 2.3- The research for economic recovery • 43% of GDP gap is filled in 2025 • but GDP growth is faster and GDP gap reduced compared to the post-crisis scenario without counter-cyclical R&D

27. 2- R&D policies are useful during crisis • 2.3- The research for economic recovery

28. 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

29. 3- A new scenario for Barcelona 3% objective • Former assessment in 2002 for EU15 • Extension to new member States • New agenda • Crisis

30. 3- A new scenario for Barcelona 3% objective

31. 3- A new scenario for Barcelona 3% objective GDP and its counterparts in the 2002 assessment for EU15

32. 3- A new scenario for Barcelona 3% objective GDP and its counterparts in the new Barcelona scenario for EU27

33. 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

34. 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 4- Increasing R&D effort : doubling the FP8 (1/4)

35. 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) 4- Increasing R&D effort : doubling the FP8 (2/4)

36. 4.2-Economic consequences 4- Increasing R&D effort : doubling the FP8 (3/4)

37. 5.1- 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 5- Redeployment of European budget towards R&D 37

38. 5- Redeployment of European budget towards R&D 5.2-But with important adjustment costs for agriculture: • Production -0,14 • Arable land -0,46 • Employment -2,3 • Revenu -2,45

39. GDP

40. 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

41. 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

42. 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

43. 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

44. 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

45. 6- Conclusion Thank you for your attention! afougey@ecp.fr lemouelp@ecp.fr Paul.zagame@ecp.fr