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 DE feature into a CGE model 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

2 What, How and Why ? Increasingly Digital Economy ICT induced effects MODELS OF ECONOMY PRE 2000 MODEL OF (INCREASINGLY) DIGITAL ECONOMY Why? – to quantitatively evaluate policies before their implementation, using accurate representation (i.e. model) of the economy DE Characteristics

3 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: Enabling technology Network effects Imperfect competition ICT sector Such a framework can serve as a platform for analysing contributions of the Digital Agenda on Europe2020 goals. The purpose of the modelling exercise is to quantify some of these contributions.

4 Proposed policy e.g. Digital Agenda -Fast Internet access -Single Digital Market -Interoperability and standards -Digital literacy, trust, security -ICT R&D -Societal challenges Economic performance measures e.g. Europe 2020 goals (employment, investment in R&D, pollution, educational attainment, poverty) Quantifying contributions of Digital Agenda onEurope2020 goals Economy model of Problem: No relevant ICT theory in the model DIGITAL ECONOMY related theory

5 From a concept to a model

6 Computable General Equilibrium (Model) 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 commoditys and factors price, representing market clearing and ensuring that total demand does not exceed total supply Computable - produces numerical results.

7 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.

8 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

9 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).

10 Theory: DE and (ICT) productivity (a simplified illustrative example) A IAIA TFP A add 100 computers A IAIA TFP A B IBIB IBIB B TFP B add 100 computers

11 Calibration and Data TFP change – EU KLEMS TFP level – GGDC (Groningen Growth & Development Centre) Broadband stats – OECD HRST – Eurostat TFP_L i =f(Bbpen, KICTint i, HRST i )

12 Results-Financial Interm. sector UK AUT ESP DNK TFP=f(BB, K-ICT, HRST)

13 Selected results, graphed

14 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.

15 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.

16 Where do we stand today ?

17 Thank you