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This project is co-funded
by the European Union
WP10 Macro-economic Modelling
Project Meeting, 9-10 February 2016
Venue: Brussels
Arnaud Fougeyrollas, Pierre Le Mouël and Paul Zagamé, SEURECO
Content
• How can we progress towards the assessment with NEMESIS:
1. Some general remarks
2. State of the art of model
3. Main modifications
4. Main concerns
• Open Discussion
2
General remarks
• Deliverables reveal an important work of bibliography and research
• For the commitments rationale and solution, for the impact channel, for
indicators
• Documents that can be useful for policy makers and scientists
• Some did try to make an advancement towards NEMESIS : Human Capital,
Finance
• How to progress in the next steps
3
General remarks
Commitment
Rationale
Solution Main Impact
Channel
Results of
Indicators
Model
Modifications
Simulations Socio-
Economic
impacts
4
State of the Art of NEMESIS
• All innovation comes from knowledge variation
Δ Knowledge Innovations
5
State of the Art of NEMESIS
Innovations
Price
Quality
6
Internal and external Demand
State of the Art of NEMESIS
Pure Macro Dynamic
Intersectoral Dynamic
Macro
Sectoral
Results
7
Sectoral Growth
State of the Art of NEMESIS: General Scheme
8
State of the Art of NEMESIS: Calibration
• R&D Decision:
• Endogenous
• Exogenous (Hall & Toads, 2000, Guellec & Van Pottelsberghe, 2004, Aerts &
Schmidt, 2008
• Elasticity of supply ε of scientists
• Spillovers matrix (DEMETER project - Meijers and Verspagen 2010) and
SIMPATIC project - Mohnen and Belderbos, 2013)
• β Coefficient (Hall, Mairesse, Mohnen, 2009)9
State of the Art of NEMESIS: Effects
• All effects pass by variation of :
• R&D real increase
• Finance conditions
• R&D decisions
• Supply of scientists and Human Capital
• Supply of capital goods for R&D
• Knowledge spillovers
• β economic performance
10
Main modifications: Variables
• Knowledge
• R&D
• Human Capital
11
Main modifications:¨Parameters
• ε (elasticity of supply for scientists)
• Spillovers
• β (economic performance of knowledge)
12
Main modifications: Behavioural equations
• R&D decision (Finance)
• Other innovative assets demand
13
Main modifications: Extension to other assets
• ICT
• Other intangibles (Training, software...)
• Extension allowed by new databases (INTAN-invest) and
the work of C. Corrado, J. Haskel & C. Jona Lasinio (2014)
14
Main modifications/commitments
• Looking at this table :
15
R&D Human Capital
and ε
Spillovers Knowledge Performance Economic
Results
Commitment
Main modifications: Commitments 1,2,3 of WP1
• Developping scientific and human capabilities, fostering knowledge
alliances between education and business to develop new curicula
addressing innovation and skill gaps and particularly e-skills for
innovation
• Major impact on human capital skills for scientists in general : Human
capital, ε and then on R&D ; impacts on e-skills
• Derived effect on spillovers
• On Knowledge (Patents)
16
Main modifications: Commitments 10,11,12 (Finance)
• Major impacts on R&D decision and then on additionality
and leverage
• An interesting case, the RSFF: How the reduction of risk
modifies the R&D decision and then the leverage effect?
17
Main concerns
1. Some commitments have very few or no credible quantitative approach, what can
we do with the qualitative results
2. Some commitments have quantitative results richer than the simplified
mechanisms of models (number of publication or patents) : how to proceed to not
loose this richness, and to reagregate all these results to fit with the NEMESIS
mechanisms
18
Main concerns
3. Some commitments have a too coarse granularity to be directly expoited by NEMESIS, for
instance the sectoral aspects. How to allocate and differentiate the parameters between
the sectors. The use of the theory to make this “split”
4. The case studies:
• Is the case studied important enough to give macro-results?
• How case studies could give more general insights to be used in modelling?
5. Overlaping and colinearity
• Intra-commitments
• Inter commitments
19
Main concerns
6. Modification of the Model:
• Variables
• parameters
• behavioural equations
7. Degree of implementation of the commitments ?
20