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Building capacity to analyse policy impact in Digital Economy

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.

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Building capacity to analyse policy impact in Digital Economy

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  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 ? 1995 2005 2010 2015 Increasingly Digital Economy ICT induced effects MODELS OF ECONOMY PRE 2000 MODEL OF (INCREASINGLY) DIGITAL ECONOMY 2000+ DE Characteristics Why? – to quantitatively evaluate policies before their implementation, using accurate representation (i.e. model) of the economy

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

  5. From a concept to a model

  6. Computable GeneralEquilibrium (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 commodity’s and factor’s 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) TFPB’ B’ TFPB B TFPA’ A’ add 100 computers A TFPA add 100 computers IB’ IB IA’ IA

  11. 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)

  12. Results-Financial Interm. sector TFP=f(BB, K-ICT, HRST) UK 2000-07 DNK 2000-07 ESP 2000-07 AUT 2000-07

  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

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