State of the Future Index
(Excerpt from the State of the Future 19.1 )
Assessing the impact and the interplay of the different potential developments affecting the future is a difficult and controversial task, but it is nevertheless valuable and necessary for coherent policymaking. Quantitative assessment of the factors of change helps us understand the system and supports the setting of priorities.
The State of the Future Index is an indication of the 10-year outlook for the future based on 20 years of historical data for a selected group of variables that in combination can depict potential systemic change. It is constructed with key indicators that are individually forecast and then aggregated to indicate the potential direction and intensity of change. It shows a potential trend; it is not a projection. Its role is solely to help understand the system and the relationships among its items—how changes to individual or several variables ripple throughout the system.
Combining many variables into a single index can lead to loss of detail, hide certain aspects by compensating losses in some areas with progress in the others, and mask variations among sectors, regions, or nations. The apparent precision of an index should not be mistaken for accuracy.
Nevertheless, the SOFI can be useful for assessing the consequences of different policies and for showing the combined potential outcomes in an easy-to-understand fashion. It has been produced by The Millennium Project since 2000. For the methodology, see “Real-Time Delphi” chapter in the Futures Research Methodology.
The variables included in the SOFI, as well as their respective weights (importance to the system) and the “best” and “worst” values in the next decade have been decided through RTD studies and updated by The Millennium Project staff. The sources of data have been carefully considered, are deemed to be reliable, and have good historical data records.
SOFI is in continuous evolution and adapted to global changes. The variables included in the computation of the 2017 SOFI are listed below.
Variables included in the computation of 2017 SOFI
- GNI per capita, PPP (constant 2011 international $) (world)
- Economic income inequality (income share held by highest 10%)
- Unemployment, total (% of world labor force)
- Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population)
- CPIA transparency, accountability, and corruption in the public sector rating (1=low; 6=high)
- Foreign direct investment, net inflows (BoP, current $, billions)
- R&D expenditures (% of GDP) (world)
- Population growth (annual %)
- Life expectancy at birth (years)
- Mortality rate, infant (per 1,000 live births)
- Prevalence of undernourishment (% of population)
- Health expenditure per capita (current $)
- Physicians (per 1,000 people)
- Improved water source (% of population with access)
- Renewable internal freshwater resources per capita (cubic meters)
- Biocapacity per capita (gha)
- Forest area (% of land area)
- CO2-equivalent mixing ratio (ppm)
- Energy efficiency (GDP per unit of energy use)
- Electricity production from renewable sources, excl. hydro (% of total)
- Literacy rate, adult total (% of people aged 15 and above)
- School enrolment, secondary (% gross)
- Share of high-skilled employment (%)
- Number of wars and armed conflicts
- Terrorism incidents
- Social unrest indicator (number of protest events/ total events) (%)
- Freedom rights (number of countries rated “free”)
- Proportion of seats held by women in national parliaments (%)
- Internet users (per 100 people)
The most important changes to the computation of the 2017 SOFI compared with earlier SOFIs include:
- New variables were added and some variables were replaced with new ones (e.g., “Social unrest indicator” has been added; “Fossil fuel and cement production emissions” has been replaced with “CO2-equivalent mixing ratio (ppm)”).
- Historical data were updated, and new series were inserted when old series were discontinued.
- New curve fit equations were derived, and new interpolations were made for missing data.
The baseline SOFI that resulted from the use of the new data sets for the variables is shown in Figure 1.
Figure 1. State of the Future Index 2017
A one-to-one comparison with the SOFIs prepared in earlier years would be misleading, since some of the variables have changed. Overall, however, the shape of this year’s SOFI is similar to earlier ones. The growth rate for the coming decade will be 1.14%, considerably slower than 3.14% for the period 1990–2017. This is mostly due to the slow recovery after the 2008 economic turmoil and because many of the hindering factors are aggravating problems. For instance, one of the variables that has a large impact on the 2017 SOFI projection is the number of terrorist attacks, which is highly unknowable. If terrorism could be contained, the world’s outlook and the rate of growth would appear to be considerably better.
SOFI can be used to test the potential impact of various policies on the entire system. As an example, the graph in Figure 2 indicates the potential impact of improving two variables by 2027: reducing by 15% GHG emissions (in CO2-equivalent) and a combined effect by adding to it a 15% reduction of income inequality.
Figure 2. State of the Future Index 2017 with sensitivity analysis
A sensitivity analysis shows that other variables with relatively significant potential impact on the overall SOFI are electricity production from renewable sources and energy efficiency (GDP per unit of energy use).
One of the advantages of computing the SOFI is the identification of the areas where we are winning, losing, or stagnating—thereby helping set priorities. Figures 3 and 4 show where humanity is making progress and where more political attention and efforts are needed.
Figure 3 Where we are winning
Figure 4 Where we are losing or there is no progress
The world seems to be making progress in more areas than it is regressing or stagnating in, but since the areas of stagnation or regress are crucially important for human and planetary survival, addressing them should be a top priority.
This can be further analyzed by assessing the individual variables and their potential trajectories.
A very nice visualization of the previous SOFI is available at: http://millennium.surge.sh/