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An introduction to creating a State of the Future Index. An index to forecast the trend of a country or regions future.

An introduction to creating a State of the Future Index. An index to forecast the trend of a country or regions future.

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  • This presentation is designed to explain the State of the Future Index. It includes not only a review of the Index’s development but also its application to the world as a whole and to individual countries. People who follow this material should, at the conclusion, be able to construct SOFIs for their own country or organizations. The State of the Future Index is a measure of the 10-year outlook for the future. It is constructed with key variables and forecasts that, in the aggregate, depict whether the future promises to be better or worse. The SOFI is intended to show the directions and intensity of change in the outlook and to identify the factors responsible. Some of the Millennium Project’s experiments with the index have illustrated how it might be used for policy purposes by demonstrating the effects of proposed policies on a nominal State of the Future Index. The SOFI approach provides a mechanism for studying the relationships among the items in a system—how making a single change ripples throughout a system, in other words, creating some positive and intended consequence as well unintended results.

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  • World Federation of United Nations Associations The Millennium Project October, 2007
  • http://www.weforum.org/en/media/Latest%20Press%20Releases/voiceofthepeoplesurvey
  • http://www.worldpublicopinion.org/pipa/articles/brmiddleeastnafricara/165.php?nid=&id=&pnt=165&lb=brme
    • .
    http://www.gallupworldpoll.com/content/?CI=28483
    • Is the future improving?
      • Are people getting smarter?
      • Will terrorism diminish?
      • Will people have jobs?
      • Will corruption abate?
      • Will democracy spread?
      • Will people have enough water and food?
      • Will women get fair treatment?
    • Human Development Index (UNDP)
    • Corruption Perception Index (Transparency International)
    • Environmental Sustainability Index (Center for International Earth Science Information Network (CIESIN))
    • Peace Index (The Tami Steinmetz Center for Peace Research ,Tel Aviv University)
    • Dow Jones Industrial Average (Dow Jones & Company)
    • What variables should be included?
    • How can the variables be combined?
    • How can the variables be forecast?
    • How can the variables be weighted?
    • How can double accounting be avoided?
    • What variables should be included?
      • A Delphi study asking experts for advice on important variables
    • How can the variables be combined?
      • The variables are “normalized on a scale of 1 – 100
    • How can the variables be forecast?
      • By using standard “best fit” curves
    • How can the variables be weighted?
      • Using the Delphi judgments
    • How can double accounting be avoided?
      • Careful scrutiny
    • Combining variables leads to loss of detail.
    • Judgments about what variables to include
    • Variable weights
    • Can mask variations among regions, nations, or groups.
    • Unwarranted apparent precision
    • SO…keep track of the variables
  •  
    • Please obtain the following
      • Excel spreadsheet titled “2007 National SOFI SpreadsheetB”
      • Report: A Standardized Approach to Building National SOFIs”
    • The following reports are also available:
      • Report: Millennium Project Study of State of the Future Index Variables and Their Use in Country to Country Comparisons (the Real Time Delphi)
      • Building the 2007 SOFI
    • Global
    • National Comparison
    • National Focus
    • Choosing the Variables
    • Obtaining the Historical Data
    • Extrapolating the Data
    • Non-dimensionalizing the Variables
    • Weighting the variables
    • Best and Worst Values
    • Surprise Free SOFI Computation
    • Inputs to the Trend Impact Analysis
    • Running a TIA
    • Final SOFI Calculation
  • Sheet Title General notes on this sheet Specific instructions Operational portion SHEET 1: HISTORY AND EXTRAPOLATIONS. THIS IS THE WORKSHEET THAT RECEIVES ALL NATIONAL HISTORICAL DATA AND FORECASTS OF THE VARIABLES. THE DATA SHOWN HERE IS FOR EXAMPLE ONLY; THEY APPLY TO NO COUNTRY. PLEASE SUBSTITUTE YOUR DATA FOR THAT PRESENTED HERE. Notes on the use of this spreadsheet : On this spreadsheet, you will enter the historical data for all your variables. You should obtain the equation for the best fit curve using other software It is good practice to show all "hard" data in bold print. You can use this sheet to calculate future values and (interpolate) missing data points using the best fit equations which should be entered on rows 45-60. Also please enter data sources for later reference on rows 44-45. Variable Number >>>> >>>>>>> 1 2 CO2 emissions (percent of global emissions) Energy produced from non fission, non fossil sources  (percent of total primary national energy supply) 1985 1.700 13.122 1986 1.720 13.134 1987 1.740 13.146 1988 1.750 13.158 1989 2.000 13.170
  • 1 Infant mortality (deaths per 1,000 births) 2 Food availability (Calories/capita) 3 GDP per capita (constant 2000 US) 4 Improved water source (percent of population without access) 5 Carbon dioxide emissions (Metric tons per capita) 6 Population growth rate (percent per year) 7 Percent unemployment 8 Literacy rate, (percent of people aged 15 and above) 9 Prevalence of HIV (percent of population ages 15-49) 10 Life expectancy at birth (years)
  • 11 Armed conflicts {number involving >1,000 deaths /yr) 12 Total Debt (percent of GDP: developing countries) 13 Forest Lands (% of land area) 14 People Living on Less than $1 per day) (% population) 15 People killed or injured in terrorist attacks (number) 16 Homicides (49 countries, per 100,000 population) 17 People in Free/ Partially Free Countries (% population) 18 School Enrollment, secondary (% school age) 19 Healthcare workers (per 1,000 population) 20 Countries having nuclear weapons or plans (number)
  • 21 Energy produced from non fission, non fossil sources (percent of all energy produced) 22 R&D expenditures (percent of GDP) 23 Global Surface Temperature Anomalies (degrees C) 24 People voting in free elections (% voting age pop) 25 Internet Users (users/1000 population) 26 Number of refugees, asylum seekers, and internally displaced persons (millions) 27 Energy consumption per GDP (metric tons oil equivalent/million $) 28 Seats held by women in national parliaments (%) 29 Corruption (% of world's people living in countries rated as having low levels of corruption)
    • All of the global variables except:
      • Global Surface Temperature Anomalies 
      • Nuclear Proliferation
      • Number of armed conflicts 
    • Two changes:
      • People in Countries that are Free becomes the country’s freedom rating
      • Corruption (% of world's people living in countries rated as having low levels of corruption) becomes the country’s corruption .
    • All variables are chosen specifically for the country.
    • Some examples not on the National Comparison list:
      • Size of in-country nuclear stockpile
      • Number of our soldiers killed or wounded
      • Tax rates
      • Tourism
    • Annual data for past 20 years for each variable
    • Interpolate for missing data points and extrapolate 10 years using a best fit algorithm
    • Data sources should be:
      • Continuing
      • Reliable
      • Transparent
      • Accurate
      • Primary, if possible
    • Record sources and definitions
    • Freedom House
    • Inter parliamentary Union
    • International Energy Agency
    • Transparency International
    • UN organizations such as UNDP, UNFCR, UNAIDS, UNESCO, WHO, FAO, UNICEF, ILO
    • US Census Bureau
    • US Department of Energy, Energy Information Agency
    • World Resources Institute
  • 1. The given data 2. Were fit by a quadratic equation 3. Yielding the full set of data 1991 51.81 1999 60.28 2000 62.06 2001 63.85 2002 66.59 2003 66.62 2004 65.06 Quadratic Fit: y=a+bx+cx^2 a= -48409.94 b = 47.371804 c = -0.01156779
  •  
    • The non dimensionalizing formula is:
    X = (actual value of the variable– MIN)/(MAX – MIN ) X = (actual value of the variable– MIN)/(MAX – MIN ) X = (actual value of the variable– MIN)/(MAX – MIN )
    • The Max/ Min Problem in SOFI
      • When a country wants to compute its SOFI it is not likely to have the maximum and minimum values of all other countries
      • The SOFI involves a projection of the history of the variables into the future and thus the present maximum and minimum values may not represent extremes.
    • The maximum value is the greater of the “best” estimate or the highest value over the 30 year period.
    •  
    • The minimum value is the lesser of the “worst” estimate or the lowest value over the 30 year period.
  • Year Variable V1 (Increasing is good) Variable V2 (diminishing is good) 20 years ago 30 30 10 years ago 35 35 Ten Years hence 42 10 Extreme data point in desirable direction 42 10 Extreme data point in undesirable direction 30 30 Expert Best 43 8 Expert Worst 40 20
  • Year Variable V1 (non-dimensionalized ) Variable V2 (non-dimensionalized ) 20 years ago 0.00 0.19 10 years ago 0.38 0.00 Present Year 0.77 0.74 Ten Years hence 0.92 0.93
    • Not all variables are of equal importance
    • Weights give emphasis to the more important variables
    • SOFI uses a convention that simply multiplies the non dimensionalized values by the weights.
    • Weights are taken to be constant for all values of a variable although this is only an approximation
    • See next chart for weights
    [1] The Freedom House scale runs from 1 which means completely free to 7 which is the other end of the spectrum. In the global panel, the “best” and “worst” were expressed in terms of percentage of the world population living in countries rated as free, so that the best and worst shown here represent high expectations as chosen by the staff. Similarly, in the cases of CO2 emissions, Refugees, and People killed or wounded in terrorists attacks, the “best” and “worst” targets represent the staff’s judgments, based on the global study.
  • Best 2017) Worst 2017 Weight 1 CO2 emissions (percent of global emissions) 0 25 7.82 2 Energy produced from non fission, non fossil sources (% national energy supply) 20.52 13.68 8.05 3 Food availability (Kcalories/cap/day) 3,006 2,205 7.08 4 Forest Lands (percent of national land area) 32.03 25.02 7.21 5 Freedom Level (Country Score) 1 3 7.52 6 GDP per capita (constant 2000 US$) 9,983 5,491 7.50 7 GDP per unit of energy use (constant 2000 PPP $ per kg of oil equivalent) 5.29 4.86 8.00 8 Homicides, intentional (per 100,000 population) 4.89 14.66 6.92 9 Infant mortality (deaths per 1,000 live births) 42.09 89.00 7.01 10 Internet Users (per 1,000 population) 577.36 192.45 7.90 11 Levels of Corruption (as measured by TI surveys) 4.23 3.31 8.57 12 Life expectancy at birth (years) 75.06 65.05 7.14 13 Literacy rate, adult total (% of people aged 15 and above) 90.42 78.87 7.45
  • Best 2017) Worst 2017 Weight 14 Number of refugees displaced from the country (%) 0 10 6.93 15 People killed or injured in terrorist attacks (%) 0 0.1 7.66 16 People Voting in Elections (% voting age) 70.0 50.0 7.19 17 Physicians (per 1,000 people) 2.55 1.46 7.50 18 Population growth (annual %) 1.0 1.54 7.27 19 Population lacking access to improved water sources  (%) 10.0 30.0 8.33 20 Poverty headcount ratio at $1 a day (PPP) (% pop) 12.72 26.49 7.84 21 Prevalence of HIV (percent of national population) 0.64 1.91 5.97 22 R&D Expenditures (percent of national budget) 4.0 2.0 8.63 23 School enrollment, secondary (percent gross) 79.35 59.15 8.09 24 Seats held by women in national parliament (%) 23.79 14.27 6.78 25 Total Debt Service (percent of GNI) 7.58 8.68 6.79 26 Unemployment, total (% of national labor force) 5.00 15.00 8.28
  • SOFI = sum (wt x ndv)/ SOFI ref Where SOFI is the value of the SOFI in a given year SOFI ref is the SOFI in the reference year wt is the weight assigned to a given variable ndv is the non dimensionalized value of the variable in that year
  • Development Probability by 2017 1 A nuclear accident such as Three Mile Island (causes many nuclear nations to de-nuclearize). 10 2 A very good, fast $150 laptop computer becomes available everywhere. 65 3 Advent of a “teachers without borders” movement (50,000 new teachers in the field) 30 4 A pandemic of the scale of HIV/AIDS 30 5 At least 10 countries introduce effective policies designed to increase birth rates 75 6 Automation and robotics increase productivity 25% to make “jobless" economic growth 50
  • A nuclear accident such as Three Mile Island (causes many nuclear nations to de-nuclearize). Impact 3.00 3.00       -2.00 Time 2.00 2.00       4.00 CO2 % Renew Food Forests Freedom GDP/C 2008 1.00 1 1.50 1.50 0.00 0.00 0.00 -0.50 2009 2.00 2 3.00 3.00 0.00 0.00 0.00 -1.00 2010 3.00 3 3.00 3.00 0.00 0.00 0.00 -1.50 2011 4.00 4 3.00 3.00 0.00 0.00 0.00 -2.00 2012 5.00 5 3.00 3.00 0.00 0.00 0.00 -2.00 2013 6.00 6 3.00 3.00 0.00 0.00 0.00 -2.00 2014 7.00 7 3.00 3.00 0.00 0.00 0.00 -2.00 2015 8.00 8 3.00 3.00 0.00 0.00 0.00 -2.00
  •  
  •  
  • Global SOFI National Comparison National Focus Variables Standard set Based on global; same for all countries. Newly chosen for the country Historical data Global data for last 2 decades National data for last 2 decades National data for last 2 decades Best and Worst estimates Chosen for global forecasts Use global estimates New values for the new variables and the country Weights Chosen for global forecasts Use global estimates New values for the new variables and the country TIA Developments Chosen for global forecasts Use global developments Developments important to the future of the country TIA Development Probabilities Estimated for global TIA developments Use global TIA development probabilities Global TIA values for global developments; new estimates for country specific developments TIA Development Impacts Estimated for global TIA developments and variables Use TIA development impacts as they might affect the country Use TIA development impacts as they might affect the country
    • The variable forecasts
    • Domains of interest
    • Good and bad trends
    • Dynamic presentations
    • Intellectual
      • Literacy, enrollments, R&D, Internet
    • Health
      • Life expectancy, infant mortality, physicians, HIV, food
    • Wealth
      • GDP/cap, unemployment, poverty, debt service
    • Security
      • Terrorist attacks, nuc proliferation, refugees
    • Moral
      • Corruption, freedom, voting, women in parliaments
    • Physical
      • Water, CO2, forests, temperature, renewables
  •  
  •  
    • Produce robust “enterprise level” software
    • Review and utilize the "standard" for national SOFIs
    • Construct and compare national SOFIs
    • Conduct an analysis designed to find whether country SOFIs (weighted by population) add up to the global SOFI.
    • Experiments with other applications (e.g. corporate SOFIs)
    • Consider other dimensions (e.g. a measure of national innovativeness)
    • Review and improve TIA judgments
    • Construct on line data bases of variables and events to facilitate national and other applications.
    • Presented by Zhouying JIN, Chinese Academy of Social Sciences of the Beijing Academy of Soft Technology, July, 2006
    • Example of use of National SOFI for policy studies
  • Year 2000 Long-term Strategy management and warning system    Zhouying JIN
  • Year 2020 Long-term Strategy management and warning system   Zhouying JIN
  • Year 2050 Long-term Strategy management and warning system    Zhouying JIN
  • Year 2050 If we succeed in strategic, institutional change and corporate behavior transformation …………in China optimistic Zhouying JIN
    • The process is still in development and will benefit from your suggestions and feedback, so please send observations, questions, and descriptions of approaches you have tried.