Development of weighting factors for G20 countries. Part 2: estimation of willingness to pay and annual global damage cost

Purpose: This paper is the second part of a series of articles presenting the results of research on monetary weighting factors (MWFs) for the G20 countries, which together account for approximately 90% of the global GDP. We developed their MWFs with regard to Life Cycle Impact Assessment (LCIA) and evaluated them via a large-scale questionnaire survey. We estimated the economic value of one unit of damage caused by human activities. Methods: To ensure that the MWFs covered all areas of protection as defined by the LCIA method based on Endpoint Modeling (human health, social assets, biodiversity, and primary production), we conducted a choice experiment in all G20 countries. We conducted face-to-face interviews to minimize survey bias and ensure that the questions were understood by the emerging G20 countries’ respondents. Internet surveys were adopted to collect samples from the developed G20 countries’ respondents, where Internet diffusion rates are generally high. We obtained response data from 200 to 250 and 500 to 600 households of all the emerging and all the developed G20 countries, respectively. We gathered 6400 responses in all. We estimated preference intensities using the random parameter logit model. We calculated MWFs based on each respondent’s willingness to pay. Results and discussion: We devised MWFs providing the costs of damage to four safeguard subjects. All the estimated values are statistically significant at the 1% level, with the exception of monetary attributes from Mexico. The MWFs for the G20 are 23,000 USD for human health (per year), 2.5 USD for social assets (per USD of resources), 11 billion USD for biodiversity (per species), and 5.6 billion USD for primary production (per 100 million tons). The differences between the developed and emerging G20 countries are considerable, with the values generally being smaller for the latter in purchasing power parity (USD) terms. The estimated global total economic annual impact was approximately 5.1 trillion USD (6.7% of the world’s total GDP). Conclusions: We obtained reasonable and conservative global-scale MWFs compared with previous studies. Moreover, the cross-country heterogeneity in this study potentially helps extrapolate future/global value developments from current/local estimates. The variations in human health and social asset MWFs are small enough within developed countries to allow international transfers among them, while significant variations in biodiversity and primary production MWFs are a caveat to up-front international transfers even within developed countries.