1 Objectives of this presentation: -Propose a conceptual framework to analyse Digital Economy -Introduce Computable General Equilibrium (CGE) class of models as an appropriate modelling platform -Provide an illustrative example of integrating a Building capacity to analyse policy impact in Digital Economy Prepared by Wojtek Szewczyk and Geomina Turlea for the IRIS meeting, IPTS, 7-8 June 2010
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1 Objectives of this presentation: -Propose a conceptual framework to analyse Digital Economy -Introduce Computable General Equilibrium (CGE) class of.
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Objectives of this presentation: -Propose a conceptual framework to analyse Digital Economy -Introduce Computable General Equilibrium (CGE) class of models
as an appropriate modelling platform -Provide an illustrative example of integrating a DE feature into a CGE model
Building capacity to analyse policy impact in Digital Economy
Prepared by Wojtek Szewczyk and Geomina Turleafor the IRIS meeting, IPTS, 7-8 June 2010
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What, How and Why ?
Increasingly Digital EconomyICT induced effects
MODELS OF ECONOMYPRE 2000
MODEL OF (INCREASINGLY) DIGITAL ECONOMY2000+
1995 2005 2010 2015
Why? – to quantitatively evaluate policies before their implementation, using accurate representation (i.e. model) of the economy
DE Characteristics
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DE Characteristics-towards a model
A theoretical framework, in order to account for the essential features of the Digital Economy, needs to embrace the following concepts:
Equation-based, behavioral, macro-balancing General - includes explicit specifications of the behaviour of
several economic actors. The actors represented can be utility maximizing households and profit maximizing firms as well as optimizing governments, trade unions, capital creators, importers and exporters
Maintains market Equilibrium between demand and supply by having an equation for each commodity’s and factor’s price, representing market clearing and ensuring that total demand does not exceed total supply
Computable - produces numerical results.
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CGE for DE – pros & cons
Pros• economy-wide structure; • considerable level of detail on sectoral composition, endowment allocation,
production, final consumption and trade to trace the technology adoption; • capacity to absorb additional theory and data, to form a model capable of
accounting various new developments;• ability to calculate consumer and producer surpluses.
Cons• assumptions of perfect competition, market clearance and income balance;
• agents’ macro-behaviour based on averaging microeconomic assumptions;
• limitations in the availability of data for the needs of a model;
• some of the phenomenon in the Digital Economy are characterised by volatility and flexibility, beyond the apparent capability of a CGE model to capture.
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Example of including a new characteristic into CGE
Process:
• DE-related characteristic identification and description• (new) Economic theory to express the characteristic• Calibration:
• Data, estimation, analysis• Integration into a CGE model
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Characteristic: DE and (ICT) productivity
ICT acts as an enabling technology with capacity to affect productivity of any business process within the economy.
Additionally, ICT technology can be a subject to a network effect (productivity of ICT resources increases sharply as they reach a critical quantity).
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Theory: DE and (ICT) productivity(a simplified illustrative example)
A
IA
TFPA add 100computers
A’
IA’
TFPA’B
IB IB’
B’TFPB’
TFPB
add 100computers
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Calibration and Data
• TFP change – EU KLEMS• TFP level – GGDC (Groningen Growth & Development Centre)
• Broadband stats – OECD• HRST – Eurostat
• TFP_Li=f(Bbpen, KICTinti, HRSTi)
exp ( )( ( , , ))_
1 exp ( )( ( , , ))i i i i i i i i
ii i i i i i i
b c g b a f BB KICT HRST aTFP L
c g b a f BB KICT HRST
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Results-Financial Interm. sector
UK
2000-07
AUT2000-07
ESP2000-07
DNK
2000-07
TFP=f(BB, K-ICT, HRST)
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Selected results, graphed
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Possible interpretation of the results
• Increase in broadband penetration by 10% in Spain will lead to 0.43% increase in productivity in Financial Intermediation sector, however
• The same increase in BB penetration would lead to increase by only 0.23% in Education sector.
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Integrate new theory into CGE
• Add new data (BB penetration, ICT capital, HRST, ...)
• Add new equations (new theory) which link, e.g. Bbpen, K-ICT and HRST with a production function.
• Add new parameters to calibrate the new add-on.
• Then we could say more about impact on production, employment, wage, trade, cross regional-effects, impact on sectors not directly affected by a policy, etc.