European Commission Directorate General for Enterprise and Industry, Directorate B. WorldScan & MIRAGE. Model structure and application

Transcription

1 European Commission Directorate General for Enterprise and Industry, Directorate B WorldScan & MIRAGE Model structure and application EPC LIME Working Group Modelling Workshop 3 rd May 2007, Brussels Peter Wobst & Isabel Grilo, ENTR-B2

2 Outline CGE simulation models: Characteristics and structure* WorldScan: Particular model characteristics Applications: The example of R&D expenditure Access and applicability A common interface for model development and application: The example of MIRAGE & GSE * Adapted from presentation by Sherman Robinson at DG ENTR on 23/04/2007 2

3 Computable General Equilibrium simulation models: Characteristics Simulation laboratory for counterfactual analysis Decomposition of policy packages (complementarities, synergies, sequencing) Structural models used for structural change issues such as investment, trade liberalization, productivity growth, world energy prices, environmental policies, etc. Deep structural models: agents, technologies, markets, institutions, signals, motivation, and behavior Agents interacting through factor and commodity markets; their behaviour is consistent with GE theory (Walrasian, neoclassical) 3

4 Characteristics (cont.) Simultaneous equation system with flexible functional forms and specification of policy instruments Simultaneous equilibrium across interdependent markets (flows and stocks; full specification of supply and demand sides in all markets; solves in relative prices) Macro-mezzo-micro levels Macro (macro/financial variables) Mezzo (sectoral structure) Micro (consumers & producers max. utility & profits subject to budget / endowment & technology constraints) Macro balances (closures) in government budget, savingsinvestment, and international trade balance 4

5 Characteristics (cont.) Model adaptation to particular analytical interest (domain of applicability) No forecasting or cyclical analysis No asset markets No money (monetary neutrality) Model dynamics : recursive-dynamic, inter-temporal updating through Savings / investments & capital accumulation Population and labour participation rate Total factor productivity / technological change 5

6 CGE model structure Figure 1: Major Payment Flows Represented in a SAM Factor Costs Producers Factor Markets Demand for Intermediate Inputs Wages & Rents Private Consumption Households Domestic Private Savings Income Taxes Transfers Government Government Consumption Government Savings Saving/Inv. Domestic Sales Product Markets Imports Indirect Taxes Demand for Final Goods Investment Demand Rest of the World Foreign Savings 6

7 replicating a social accounting matrix R E C E I Activities Commodities Factors Households Activities Commodities Factors Y value-added D domestic supply P A Y M E N T S Households Government Y HH income C private consum. G government consum. Savings Investment I investment demand Rest of the World E exports P T S Government Savings Investment Rest of the World T X indirect tax M imports T H income tax S H private savings S G government savings S F foreign savings 7

8 Calibration and validation Initial base year data (SAM) represent an equilibrium model solution Snap shot, but detailed social interaction The SAM data delivers the share parameters Model is calibrated to replicate the base year equilibrium Elasticity/behavioral parameters come from other sources and should be carefully estimated Production elasticities (factor substitution) Trade elasticities (Armington and export transformation) Income elasticities (LES, AIDS demand systems) 8

9 Dos and Don ts What CGE models are good at: Counterfactual exercises Effects in the longer term What CGE models are not meant for: Forecasting Short-term effects or transition dynamics 9

10 Policy simulations Easy cases: Policy measure directly corresponds to a change in a parameter or exogenous variable of the model (e.g. tax rates, tariffs) Challenging cases: The policy measure has to be translated into a shock to the model (e.g. TFP, mark-up rates), which requires some form of satellite exercise. 10

11 WorldScan (CPB) Multi-country, global (world) model Max. 87 GTAP* (version 6) regions Multi-sector Max. 57 GTAP (version 6) sectors Multi-period Recursive dynamic, base year 2001, calibrated to current year Factors High-skill & low-skill labour, capital, land (natural resources) One representative household per region, government, trading partners * Global Trade Analysis Project (GTAP, Purdue University) at 11

12 WorldScan (cont.) More instruments for relevant EU policy analysis (e.g. endogenous R&D) Many behavioral equations now better empirically based and partly econometrically underpinned Savings: Estimated for a OECD and non-oecd panel Imperfect capital mobility: the real interest rate is a function of Net Foreign Asset Position R&D spillovers: Relation between TFP and R&D has been estimated using historical data for different sectors in various OECD countries Sectoral TFP growth rates based on OECD data Non-trade barriers in the model (iceberg costs) 12

13 WorldScan (versions) Imperfect competition Energy break down (electricity, coal, gas, petrol, biomass, non-fossil) Endogenous firm decision on R&D spending and R&D spillovers Unemployment (under development) Human capital (under development) Expanded WorldScan database on skills and policy instruments Skills satellite model for parameter re-estimation Transfer of satellite model s skills categories into WorldScan 13

14 Example of application for APR Administrative Burden R&D expenditure MS achieve self-set targets on R&D expenditure by 2010 EU-25 average = 2.7% (up from 1.9% in 2004) Subsidy on R&D producing sector to match country-specific target Additional efforts across MS vary from 0.3% to 1.4% of GDP 14

15 R&D expenditure increase Impact of higher R&D expenditure on GDP (% changes in levels from the baseline for 2025) 4 3,5 3 2,5 2 1, Only 0,5 0 EU Czech Republic Germany United Kingdom Poland Sweden 15

16 R&D expenditure increase Direct R&D spillovers Gains through improvement of Europe s terms of trade Increase in international competitiveness: higher exports growth as compared to overall GDP growth Innovative and more efficient production processes characterised by increased labour efficiency Sectors with high export shares are particularly favoured Increase in comparative advantage will diminish if non-eu economies also increase their R&D performance 16

17 Spillovers through feedbacks Policy effects through domestic and international feedbacks Demand and production linkages through trade Terms-of-trade effect Interest rate effect: Higher TFP and employment in a MS raises demand for investment and drive up the interest rate in Euro-area. Effect on R&D expenditure and technology spillovers: Higher production and income will entail higher expenditure on R&D, allowing other countries to learn from innovative technologies 17

18 Access and application Common approach Common database (e.g. GTAP) Common programming language (e.g. GAMS) Common interface?! (e.g. GSE*) Common policy analysis, but country-specific foci Common specification of parameters, definitions and policy instruments Common generation of output and comparability of results * GAMS Simulation Environment (GSE, LEI/WUR, The Hague) at 18

19 Access and application GSE interface and MIRAGE 19

20 Access and application GSE interface and MIRAGE 20

21 Access and application GSE interface and MIRAGE 21

22 Access and application GSE interface and MIRAGE 22

23 Access and application GSE interface and MIRAGE 23

24 Access and application Database aggregation in MIRAGE 24