1. Geographic Macro and Regional (GMR) Model for EU Policy Impact Analysis of Intangible Assets and Growth Attila Varga Péter Járosi Tamás Sebestyén PTE KTK KRTI

2. Development policy instruments Knowledge-based development policy Policy instruments: –Promoting firms’ technological potential (start-up and investment supports, tax credits, low interest rate loans or venture capital) –Local technological environment support (R&D promotion: universities and private firms, human capital improvement, support of public-private interactions in innovation, financing physical infrastructure building)

3. GMR: Geographic Macro and Regional Modelling

4. Why should geography be incorporated into development policy impact modeling? Geography and policy effectiveness: 1. Interventions happen at a certain point in space and the impacts appear there / spill over to proximate locations to a considerable extent. 2. The initial impacts could significantly be amplified/reduced by short run agglomeration effects. 3. Cumulative long run process resulting from migration of K and L: - further amplification/reduction of the initial impacts in the region - the spatial structure of the economy (K, L, Y, w) might eventually change in a significant manner. 4. Different spatial patterns of interventions might result in significantly different growth and convergence/divergence patterns.

5. Why „regional”

6. Why „macro”?

7. GMR-Eurozone The particular model developed for the Eurozone NUTS 2 regions includes: –a KPF model (to model: 1 and 2) –an SCGE model (for 3) –a macro DSGE model (for 4)

8. Introduction Antecedents: –Empirical modeling framework (Varga 2006) –EcoRet model (Schalk, Varga 2004, Varga, Schalk 2004) –GMR-Hungary model (Varga, Schalk, Koike, Járosi, Tavasszy 2008) –Dynamic KPF model for EU regions (Varga, Pontikakis, Chorafakis, 2009)

9. Outline Model structure –The KPF model –The SCGE model –Dynamism and macro effects: macro DSGE model (QUEST III) Policy simulations

10. The role of the KPF model To generate initial TFP changes as a result of technology policy interventions NOT for forecasting but for impact analysis

11. Equations in the TFP block

12. The TFP equation

13. Require the integration of TFP with the SCGE and MACRO models BUT: –How strong these processes are? –What are the economic impacts on the regions? –What are the macro (EU level) economic impacts?

14. The role of the SCGE model To generate dynamic TFP changes that incorporate the effects of agglomeration externalities on labor-capital migration Agglomeration effects depend on: - centripetal forces: local knowledge (TFP) - centrifugal forces: transport cost, congestion To calculate the spatial distribution of L, I, Y, w for the period of simulation

15. The SCGE model C-D production function, cost minimization, utility maximization, interregional trade, migration Equilibrium: - short run (regional equilibrium) - long run (interregional equilibrium)

16. Main characteristics of the SCGE model NOT for historical forecasting The aim: to study the spatial effects of shocks (technology policy intervention) Without interventions: it represents full spatial equilibrium - regional and interregional (no migration) Shock: interrupts the state of equilibrium, the model describes the gradual process towards full spatial equilibrium

17. The role of the MACRO model Regional technology policy impacts depend to a large extent on macro level variables (fiscal/monetary policy shocks, exchange rates, international trade etc.) Dynamising the (static) SCGE model

18. The MACRO model The QUEST III Dynamic stochastic general equilibrium (DSGE) model for the EURO area A-spatial model Macro effects of exogenous TFP shocks Baseline: TFP growth without interventions Policy simulations: describe the effects of TFP changes on macro variables

19. Regional and national level short run and long run effects of TFP changes induced by regional technology policy interventions 1. Intervention in any region changes regional TFP level 2. „Short run” effect: - price of the good decreases - decreasing demand for both L and K (substitution effect - SE) - increasing regional and interregional demand for the good increases demand for L and K (output effect - OE) - if OE>SE: increased regional demand increases wages and utility levels of consumers in the region 3. „Long run” effects: increasing utility levels induces labor migration into the region (until congestion does not prevail) followed by capital migration - resulting in a further increase in TFP - and finally a changed spatial economic structure 4. Macroeconomic variables reflect the long run equilibrium TFP level resulting from dynamic agglomeration effects

20. Policy Models, Procedures State of Equilibrium MACRO model Dynamic supply and demand side effects Regional SCGE model Agglomeration effects on regional and interregional variables Regional KPF model Regional TFP effects Policy intervention A CB Dynamic impact on macroeconomic variables Dynamic impact on regional economic variables

21. Data, software environment The model is build for the NUTS 2 regions of the EURO zone Regional KPF model estimated in SpaceStat The complex model is programmed and run in MATLAB Easy to run/make simulation changes with an Excel interface The regional model is large considering that equilibriums have to be found for 144 interconnected (interregional trade and migration) regions A simulation with 20 periods needs the computer time of about 20 minutes

22. Regional R&D policy impact assessment: The EU FP6 program EURO zone 144 NUTS 2 regions (QUEST constraint) Interventions: 2003-2007

31. Policy implications

32. Policy implications (cont.)