Sustainability and the measurement of future paths in genuine savings: case studies

Abstract

This paper extrapolates future paths of genuine savings (GS) by using our integrated assessment model. The results with the base case (BC) indicate that both GS without population change (GS) and GS with population change (GSn) are almost positive in OECD countries in the twenty-first century (satisfying the necessary but insufficient condition for sustainability); those numbers are projected to be negative in 2100. Asia (ASIA), the Middle East and Africa (MEAF), the former Soviet Union and Eastern Europe (FSEE), and the world show upward trends for both values, showing negative signs in 2010 and positive signs after 2050 (in ASIA, MEAF, and the world) and in 2100 (in FSEE). The values in Latin America (LAMR) remain negative throughout. We examine additional following three cases: demand reduction (DR), carbon dioxide (CO₂) emissions reduction (CR), and population reduction (PR). The GSn results compared to the BC indicate that (1) GSn in DR is similar to that of BC, (2) GSn in PR is slightly higher than that of BC, and (3) GSn in CR is unexpectedly lower than that of BC. This GSn reduction in the CR case derives from the fact that the term for calculating resource depletion (especially resource rent, which equals the difference between price and cost) in GS and GSn increased, leading to a greater term being subtracted from gross savings. The resource price increases with the marginal price of natural gas, given the energy-source shift in reducing CO₂ emissions, from cheap coal to expensive natural gas.

Keywords:

• genuine savings
• wealth
• sustainable development
• sustainability
• integrated assessment model
• World Development Indicators

Notes

^1. S, resource stocks; R, resource use; X, pollutants accumulate; N, human capital; K, physical capital, GNP, gross national product; C, consumption; δK, capital depletion; n, resource rent; R, resource extraction amount; g, increased amount of capital stock; b, pollution abatement cost; e, emission of contaminant; d, natural dissipation of contaminant stock; and m, investment to human capital. The function q(m) transforms education expenditures into human capital, where q′ is the marginal cost of creating one unit of human capital.

^2. World Bank (2011) used SCC by Tol (2005).

^3. Oil, gas, coal, and uranium.

^4. Iron ore, bauxite, copper, zinc, lead, and limestone.

^5. Rice, corn, wheat, pork, chicken, mutton, and beef.

^6. Logs, wood pulp, timber/board, and paper.

^7. Global warming, local air pollution, trans-boundary acidification, ozone layer depletion, extraction and disposal mineral resources, human appropriation of potential photosynthetic net primary productivity (NPP), and the extinction risk of biodiversity caused by land-use (LU) and land-use change (LUC).

^8. North America, West Europe, Japan, Oceania, China, Southeast Asia (including India), the Middle East and North Africa, Sub-Saharan Africa, Latin America (LAMR), and the former Soviet Union and East Europe (FSEE). Results obtained are presented as OECD (North America, West Europe, Japan, and Oceania), ASIA (China, Southeast Asia), MEAF (the Middle East and North Africa, Sub-Saharan Africa), LAMR, FSEE, and the world.

^9. Numbers are taken from the marker scenarios in the Special Report on Emissions Scenarios (SRES) by the Intergovernmental Panel on Emissions Scenarios (IPCC) (hereinafter, IPCC-SRES).

^10. m = oil, gas, coal, uranium, iron, bauxite, copper, lead, zinc, and limestone.

^11. sgo = safeguarded object (human health, natural resources, potential photosynthetic net primary production (NPP), and biodiversity); sbs = greenhouse gases (GHG), ozone depletion substances (ODS), extraction and disposal of nonfuel minerals, LU, and LUC; = marginal willingness to pay, as derived from a conjoint analysis using a social survey of 1000 people in Japan in 2006;  = elasticity of benefit transfer (0.5 is assumed, from Pearce’s review (2003a)); and = the dose–response relationship from inventories released to safeguard objects, which is modified from the that LIME provides so as to make it compatible with the framework of our model. The modification methodology is described Kosugi et al. (2009): = inventories treated in the model, such as CO₂, SO_x, and NO_x from fuel combustion; CO₂ released via deforestation; five types of non-CO₂ GHG (NCGHG); 14 types of ODS; the extraction and disposal of nonfuel minerals; and LU and LUC. NCGHG and ODS are exogenous, while all other inventories are endogenous.

^12. See note 8 for the geographical allocations, as well as the related abbreviations.

^13. Please refer to note 8 for a full abbreviation listing for the regions studied.