A System Dynamics model for Planning Economic Development Brian Dangerfield Centre for OR & Applied Statistics University of Salford, UK (Email: b.c.dangerfield@salford.ac.uk)
FOUR PRINCIPAL METHODOLOGIES • Spreadsheets • Input-Output Tables • Econometrics • System Dynamics
FEATURES OF THE RESEARCH • Long gestation • Need for detail (political acceptance) • Technology Transfer • Is still a work-in- progess……
Structure Behaviour Data (Time series)
Structure Behaviour Economics & Business Research using typical methodologies Data (Time series)
Structure SD methodology Behaviour Data (Time series)
Structure SD methodology Behaviour Data (Time series)
Threshold 21 Model • System dynamics based national planning model • Used for developing & developed nations • Has been applied in some African countries + China + Italy • Is a large “off -the- shelf” model • Generic, although claimed be capable of being "customised” • Can it properly address specific issues? • Can it be easily understood given its size? • Can it handle development of States within nations?
Possible Possible future from SD Model Futures based on a definite intervention strategy: investment in capability. (Short term sacrifice for longer- term gain.) Typical “do nothing” scenario (result of an econometric projection?) Possible future from SD model based on no investment in capability. (Short-term gain but -15 Now +5 +10 +15 +20 +25 yr longer term disaster.) No modelling methodology other than system dynamics could endogenously generate projections (red & blue) given the known behaviour from -15 yrs to now.
Model purpose How and over what time-scale can the State of Sarawak best manage the transition from a production-based economy to a knowledge-based economy and thereby improve international competitiveness?
Map of Borneo
K- Indicators – Malaysia VS. United Kingdom 2001 Number of Computers* 700 60 Number of Internet Hosts * Tertiary Enrolment ^ 0 500 40 0 30 Telephone Main Lines * Infrastructure for E- commerce~ 0 20 0 1 00 0 Mobile Telephones * Availability of Venture Capital ~ Newspaper Circulation * Total Expenditure on R&D $ * per 1000 inhabitants Total R&D Personnel @ Computer Power /MIP # @ per 1000 inhabitants*100 # per 1000 inhabitants/100 UK Malaysia $ % of GDP *100 ~ index points*100 Source: The World Competitiveness Yearbook 2001 ^ % of tertiary enrolment*30
Sarawak GDP 1980-2003 (constant prices) 16,000 14,000 GDP RM Millions 12,000 10,000 8,000 6,000 4,000 2,000 0 1980 1983 1986 1989 1992 1995 1998 2001 Years
PIVOTAL ROLE OF ICT INFRASTRUCTURE Supply of Knowledge ICT Infrastructure in Sarawak Demand for Knowledge
• Development of the ICT infrastructure affects both supply and demand • Excess supply ==> migration overseas • Excess demand ==> companies/schemes close
Skills/Tech Transfer DYNAMIC HYPOTHESIS: high-level map Money Capital Equipment Human Resources Higher SUPPLY Leakage Education Overseas? Primary & (Arts) Secondary R & D Education Centres Higher (Exemplars) Education (Science) Federal Funds Vocational Education DEMAND (Sub-professional) ICT Infrastructure Primary Industry State (Agric; Forestry; Revenue Mining; M/facturing) Broadband Secondary Cabling Industry (Kms) State (Transport; Storage; Incentives Retail; Finance & Insurance) Closures? COMMS Knowledge-based Number of INFRASTRUCTURE F Industry & Services PC’s D High Value-added; I Biotech; Medicine
Sectors of the model • Population • Education & Human capital • R&D/ ICT Infrastructure/k-industries • Manufacturing; Services & GDP • Timber Production • Palm Oil: trees • Palm Oil: products • LNG & petroleum production • State Revenue & spending
The Education & Human Capital sector This is comprehensive & contains: • School & University education • Technical/vocational education • Recruits to k-industries • Recruits to Govt R&D centres • Emigration & repatriation It is difficult to see on one slide!
frac electing tech technically qualifieds educ. No. in Technical education transition to tech/vocational educ Tech educ fraction terminating <fraction terminating primary educ duration after primary educ secondary <additions to Govt after sec education> duration educ R&D centres> duration No. at No. in No. in University <av. number of scientific Primary Secondary (sciences) Education start of change frac secondary Education transition to primary enrolment personnel required> electing sciences enrolment university (sciences) <ratio of technical to scientific personnel> fraction tech recruits to frac electing <mean aging time> Tech labour terminating change frac electing R&D centres sciences after sec available to sciences <population education k-firms cohorts> slope of transition to total at university <frac electing tech change frac university (arts) <tech labour educ.> electing required per firm> sciences tech recruits to <univ educ k-firms univ educ duration graduation duration> (sciences) <new openings of No. at k-firms> Arts University initial skilled labour (arts) graduates on Conversion Graduation (arts) rate available to k-firms P/G courses into work <additions to Govt R&D centres> frac converting to P/G course ICT duration skilled conversions Scientific labour repatriation scientific recruits to Skilled ex-pats available to R&D centres k-firms emigration scientific recruits to av. number of scientific time to complete k-firms personnel required repatriation time to average time to complete recruitment rate <new av. recruitment rate emigration openings of <scientific to k-firms k-firms> labour required per firm> <scientific recruits to k-firms>
Rate of increase in science students at university is set to take total from 20% to 60% over 10 years What if we accelerate this?
Higher transition to sciences Base run "Skilled labour available to k-firms" 4,000 3,000 2,000 1,000 0 emigration 8,000 Higher % growth 6,000 rate for 4,000 2,000 transition to 0 sciences is "graduation (sciences)" better 10,000 7,500 but….higher 5,000 emigration 2,500 0 "recruits to k-firms" 4,000 3,000 2,000 1,000 0 0 10 20 Time (Year)
Shift to sciences fixed to start after 2 years. Suppose this policy shift is delayed to 4 years…
A later start of the shift to sciences makes things marginally worse new openings of k-firms 60 45 30 15 0 0 2 4 6 8 10 12 14 16 18 20 Time (Year) "new openings of k-firms" : Later start of shift to sciences firms/Year "new openings of k-firms" : Higher transition to sciences firms/Year "new openings of k-firms" : Base run firms/Year
Growth in the number of k-firms is dependent upon : • Availability of skilled human capital • Presence of an adequate ICT infrastructure
ICT resources are a necessary but not sufficient condition for growth of k-firms.
Typically three phases of growth in k-economy development Government R & D Institutes (backed by strong Higher Ed) Private sector spin-offs Foreign Multi-nationals attracted in
R&D; ICT Infrastructure & k-industries Govt R&D initial ICT infrastructure centres additions to Govt centre closures resources R&D centres ICT budgeted state infrastructure spending on R&D resources cost per R&D centres centre av. ICT start of infrastructure resources reqd ratio of technical to enhancement per firm scientific personnel potential number of new k-firms based on ICT resources enhancement of infrastructure Number of tech labour firms in required per firm new openings of k-industries closures of scientific labour k-firms k-firms required per firm potential number <Time> of new k-firms potential number of new time for new firm to k-firms based upon skilled become fully operational extra number of new labour <Scientific labour k-firms from FDI available to k-firms> F D I <Tech labour available to k-firms>
• Resource-based Industries included • Example….Palm Oil
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