In order to demonstrate the components and capabilities of the Inclusive Wealth Index (IWI), Fields of View is planning on using it in a game as a policy design exercise. This computer supported game will simulate different scenarios, and will enable physical interaction among the participants. The game looks at different aspects of the IWI: interconnectedness of parameters, relating qualitative and quantitative parameters, different indices, and possibilities of change for the future.
The target audience of the game are undergraduate students of economics and sustainability studies, in addition to policy-makers. It is assumed that the participants understand the mechanism of national budgets, and can perform basic mathematical operations.
This game has been designed to complement traditional teaching methods. The learning objectives of the game are as follows:
- Understanding the components that are used to calculate the IWI, and how it compares other development indices such as GDP, HDI, etc
- Learning how changes in national policies can alter different indices, and what advantages the IWI offers in understanding these changes
- Encouraging players to develop a futures orientation, and apply the same to shape real-life sustainable economic policies
In this case, the players will be asked to prepare a national budget for a given country—using their judgment based on the national indices (IWI, GDP, etc.) they’re given. Based on these standard development indicators, the players will determine a fiscal budget plan and basic monetary policy.
The game is divided into a briefing, gameplay, and debrief session. In the briefing session, participants will be given a survey to determine their decision-making preferences—which will give them some information about the socio-political context of that country. As part of the gameplay session, the players set national targets (ex. levels of employment, sustainability, poverty levels), and use preferred strategies to achieve them. The game proceeds in multiple rounds, wherein each round simulates one year of operation. The country’s economic prosperity (after each round) will then be published to the participants, and will be calculated using indicators like GDP, HDI, and IWI. Finally, the debrief session looks at the advantages and disadvantages of using different development indicators, and examines the ability of the IWI to reflect upon a country’s economic health.
The system dynamic model of the game can also be used as an interactive way of engaging players with the IWI. For example, an online interactive visualization could be developed for policymakers and students to see the effects of different policies on the future economy. The inputs and interventions will be based on data from the Inclusive Wealth Reports, and from information generated by the game.
Eventually, the IWI could become a more appropriate and comprehensive indicator than GDP or HDI to measure the sustainable development of an economy. But we have realized that this requires serious involvement of different types of audience, such as students, policymakers, politicians, educators, economists, and other such groups.
To draw audiences from different backgrounds to understand the IWI and explore the implications of planning with IWI, we are in the process of building a game called Levers of Change. All the players will be responsible for a country’s well-being, and will plan for investing in different forms of capital, such as the human, natural, and produced capital. Players should be able to balance their economic growth with sustainable development to achieve sustainable goals. The game will challenge players to plan accordingly to ensure global sustainability.
The game design process relies on the functions and indicators in the IWR 2014 report. IWI accounts the wealth of all major socio-economic and environmental parameters and is represented as an index through incorporating several complex statistical models and mathematical formulas. We are triangulating data of quantity and price of produced crops, permanent cropland and pastureland from Food and Agriculture Organization of the United Nations (FAO) to calculate wealth of agricultural land. Similarly, we triangulated statistics on forest area, and stock of timber for all listed countries from FAO. We are also validating data on production, and reserves of oil, coal, and natural gas from US Energy Information administration to calculate the wealth of fossil fuels. We apply the similar procedure for the data on production, reserve, and price of all minerals from US Geological Survey to measure the wealth of minerals.
The most interesting part of the study is to calculate wealth of natural capital. Mathematical functions to calculate the wealth of different natural resources involve multiple numbers of independent variables, such as quantities or natural stock of resources, real prices, and rental prices. The major challenges in calculating natural capital are to identify all independent variables for the model and to validate units of all variables.