World Federation of United Nations AssociationsThe Millennium ProjectOctober, 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 weightsCan mask variations among regions,

nations, or groups. Unwarranted apparent precisionSO…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

1. Choosing the Variables2. Obtaining the Historical Data3. Extrapolating the Data4. Non-dimensionalizing the Variables5. Weighting the variables6. Best and Worst Values7. Surprise Free SOFI Computation8. Inputs to the Trend Impact Analysis9. Running a TIA10. Final SOFI Calculation

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

Sheet Title

General noteson this sheet

Specific instructions

Operational portion

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

1991 51.811999 60.282000 62.062001 63.852002 66.592003 66.622004 65.06

1. The given data

Quadratic Fit: y=a+bx+cx^2

2. Were fit by a quadratic equation

a=

-48409.94b =47.371804c =-0.01156779

3. Yielding the full set of data

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 3010 years ago 35 35Ten Years hence 42 10Extreme 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 0.1910 years ago 0.38 0.00Present Year 0.77 0.74Ten 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

2Energy 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 7.084 Forest Lands (percent of national land area) 32.03 25.02 7.215 Freedom Level (Country Score) 1 3 7.526 GDP per capita (constant 2000 US$) 9,983 5,491 7.50

7GDP 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 6.929 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 7.9011 Levels of Corruption (as measured by TI surveys) 4.23 3.31 8.5712 Life expectancy at birth (years) 75.06 65.05 7.1413 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 6.9315 People killed or injured in terrorist attacks (%) 0 0.1 7.6616 People Voting in Elections (% voting age) 70.0 50.0 7.1917 Physicians (per 1,000 people) 2.55 1.46 7.5018 Population growth (annual %) 1.0 1.54 7.2719 Population lacking access to improved water sources  (%) 10.0 30.0 8.3320 Poverty headcount ratio at $1 a day (PPP) (% pop) 12.72 26.49 7.8421 Prevalence of HIV (percent of national population) 0.64 1.91 5.9722 R&D Expenditures (percent of national budget) 4.0 2.0 8.6323 School enrollment, secondary (percent gross) 79.35 59.15 8.0924 Seats held by women in national parliament (%) 23.79 14.27 6.7825 Total Debt Service (percent of GNI) 7.58 8.68 6.7926 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 yearSOFI ref is the SOFI in the reference yearwt is the weight assigned to a given variablendv is the non dimensionalized value of the variable in that year

DevelopmentProbability

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      -2.00Time 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 -0.502009 2.00 2 3.00 3.00 0.00 0.00 0.00 -1.002010 3.00 3 3.00 3.00 0.00 0.00 0.00 -1.502011 4.00 4 3.00 3.00 0.00 0.00 0.00 -2.002012 5.00 5 3.00 3.00 0.00 0.00 0.00 -2.002013 6.00 6 3.00 3.00 0.00 0.00 0.00 -2.002014 7.00 7 3.00 3.00 0.00 0.00 0.00 -2.002015 8.00 8 3.00 3.00 0.00 0.00 0.00 -2.00

Global SOFI National Comparison National Focus

Variables Standard setBased on global; same for all countries.

Newly chosen for the country

Historical dataGlobal 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 estimatesNew values for the new variables and the country

WeightsChosen for global forecasts

Use global estimatesNew values for the new variables and the country

TIA DevelopmentsChosen for global forecasts

Use global developmentsDevelopments 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 2000Year 2000

Long-term Strategy management and warning system 　　　　

Zhouying JIN

Year 2020Year 2020

Long-term Strategy management and warning system 　　

Zhouying JIN

Year 2050Year 2050

Long-term Strategy management and warning system 　　　　

Zhouying JIN

Year 2050Year 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.