ICT R&D in a CGE Model The Macro Economic Modeling of the Digital Economy 29 30 September 2010, Brussels, EU Jonathan Moyer jmoyer@du.edu The Pardee Center for International Futures Josef Korbel School of International Studies University of Denver www.ifs.du.edu 1
Organization of Presentation Introduce Participants to IFs Present Initial Modification Strategy for ICT R&D 2
International Futures (IFs) Large Scale Integrated Assessment Model Forecasts for 183 Countries from 2005 2100 Built Upon Large Historic Database (mostly from 1960), Theory and Scholarship Created by Barry B. Hughes Over 30+ Years Freely Available for Download and Use: www.ifs.du.edu 3
International Futures (IFs) 4
Patterns of Potential Human Progress (PPHP) Reducing Global Poverty 2008 Advancing Global Education 2009 Enhancing Global Health 2010* Strengthening Infrastructure 2011* Exploring Governance 2012* * forthcoming 5
Uses of IFs Help Exploration of History, Base Case and Creation of Scenarios Used by the United Nations Environment Programme, US National Intelligence Council, European Commission DG INFSO and IPTS Currently Building a Consortium in Africa: NEPAD, African Development Bank, Institute for Security Studies 6
Key Sub Modules: Population Represents 22 age sex cohorts, single year representation Calculates change in cohort specific fertility Calculates change in mortality rates Computes average life expectancy, literacy, and overall measures of human development (HDI) 7
Population Forecast 8
Key Sub Modules: Overview Agriculture: Represents production, consumption and trade of crops and meat; also land use by type Energy: Six types of energy, fossil fuel reserves, changing capital costs Environment: Carbon emissions and build up in atmosphere, water use Education: Enrollment rates by sex for primary, secondary, tertiary and science graduates; attainment of adults by type of education 9
Energy Forecast: EU27 10
Environment Forecast: PPM 11
Education Forecast: Italy 12
Key Sub Modules: Overview Health: Communicable, Non Communicable and Injuries by sub Types, DALYs Socio Political: Government Spending for 6 categories, Governance Quality, Regime Type, Corruption, State Fragility International Political: Material Power Balance, Threat of Interstate Conflict Technology: Improved productivity, efficiency, implicitly structured throughout the model 13
Health Forecast: SS Africa 14
Governance Performance: North Africa in 2020 15
Material Power: China and US 16
Key Sub Modules: Economic Six sectors: agriculture, materials, energy, industry, services, and ICT GTAP data sectors Possible to add additional sectors General equilibrium seeking model that does not force equilibrium in any given year Traditional CGE models clear markets (goods, services, labor, financial) in each time step by finding (or forcing) equilibrium IFs chases equilibrium by leaving stocks left over at each time step 17
Key Sub Modules: Economic Cobb Douglas production function Endogenously represents contributions to growth in multifactor productivity Endogenous Growth Model R&D is one of the components therein Linear Expenditure System to represents changing consumption patterns 18
Key Sub Modules: Economic Input output matrices change dynamically with development level Embedded in a social accounting matrix (SAM) 19
ICT in IFs One of Six Economic Sectors data taken from GTAP Key Stocks Forecasted Broadband, Mobile, Telephone Lines, Computers, Data Transfer Speeds, Networked People Forward Linkages to Productivity Through Physical Capital to GDP in Goods and Services Market to Energy from Physical Stocks 20
Strategy for Modification of IFs Build Tool to Forecast and Create Scenarios Using ICT R&D Understand ICT R&D as Tied to General R&D Spending Explore Relationship between Public and Private ICT R&D 21
Motivation: R&D % GDP EU Goal of 3% Source: Constructed from Various WDI measures 22
R&D in IFs Total, Public and Private Government R&D One of six government sectors: Education, Health, Military, R&D and Other (soon to add Infrastructure as a sixth sector) Driven by Government Consumption, GDP Per Capita at PPP Total R&D Driven by relationship with GDP Per Capita at PPP 23
R&D % GDP Total History and Forecast Source: Constructed from Various WDI measures 24
R&D % GDP Government History and Forecast Source: Constructed from OECD measures 25
R&D Forecast Total R&D =.0192 +.0792 GDP Per Capita ; R squared = 0.5546 Public R&D = Also Driven By GDP Per Capita and Government Consumption but Limited Coverage (27 countries) To Forecast: Separate Public and Total Private R&D is Saved Public R&D Enters Government Spending Model All Five Government Spending Sectors have Separate Algorithms Re Computed Public R&D Added Back with Private R&D for Total R&D 26
R&D for ICT Private % GDP EU Regions Source: IPTS 27
R&D for ICT % GDP Public EU Regions Source: IPTS 28
R&D in IFs: Existing and Proposed Exists within IFs Proposed to Add to IFs Total Public Private Total R&D as % GDP Total ICT R&D as % GDP Public R&D as % GDP Public ICT R&D as % GDP Private R&D as % GDP Private ICT R&D as % GDP 29
R&D Composition EU27 and USA Source: Constructed from Various measures 30
R&D Composition Source: Constructed from Various measures 31
Relationship Between Total R&D % GDP and Private R&D ICT % GDP 32
Relationship Between Total R&D % GDP and Public R&D ICT 33
ICT R&D Public and Private 34
Adding ICT R&D 35
Moving Forward Conceptualize Relationships Parameterize Relationships Find or Create Data for Rest of World Explore Results Build Policy Relevant Scenarios 36
Visit Us www.ifs.du.edu 37
ICT R&D Public and Private ICT R&D Government Productivity ICT R&D Business 38