Modelling linked to the better representation of the socio-economic mechanisms of climate policy
Related topicsClimate change modelling Climate mitigation
■ In a recently published article in Nature Climate Change, researchers at PBL Netherlands Environmental Assessment Agency and Utrecht University present a single transparent metamodel of climate change action which estimates the costs of reducing GHG emissions, the impact of the emissions on climate change and the socio-economic developments associated with the costs and emissions. The main finding of the study is that the cost of limiting global temperature increase to below 2°C – or even below 1.5°C – would be between 2% and 4% of global aggregate income for the period 2015-2100. However, these estimates come with a large margin of uncertainty – the costs of keeping global temperature increase under 1.5°C could be three times higher or lower than estimated. This uncertainty is largely a product of uncertainty in physical factors (e.g. relationship between GHG and temperature increases) and socio-economic developments (e.g. population growth, economic growth, human behaviour). The uncertainty of achieving the more ambitious temperature targets are mainly socio-economic uncertainties, which shows that climate change costs and impacts should be taken into account in all policy areas, not just climate policy. The findings also show that more research is needed to develop data and models that improve the estimates of socio-economic factors and decrease the margin of uncertainty. The data and model code used in the article are publicly available online.
■ Research from the University of Waterloo in Canada reflects on the use of the cross-impact balances (CIB) technique to explore uncertainties in climate change research. CIB uses scenarios rather than relying only on expert predictions, and the article applies the technique in two areas: 1) socio-technical uncertainties not represented in IAMs, and 2) sampling the space of possible futures to model. The key finding is that CIB can reveal system behaviours that are not obvious when social variables (e.g. quality of governance) are not explicitly modelled in IAMs. Moreover, CIB can algorithmically rank the possible future scenarios to model based on how self-consistent they are. The CIB technique can improve the choice of what possible futures to model. These choices are usually based on expert intuitions and what looks “obvious” – which often leads to analysis of only a sub-set of policy options. The article is available online.
■ A new discussion paper from researchers at the Inter-American Development Bank estimates the labour impacts of decarbonisation in Chile. The study explores the labour impact of four scenarios of electricity generation in Chile, including three coal power phase-down scenarios. These scenarios were developed by the government of Chile to inform the debate on the appropriate timing of coal phase out in Chile. The authors find that the four scenarios would result in the creation of between 32 and 40 thousand direct and indirect jobs and between US$1.7 and US$1.8 billion in value added in 2030, compared to present-day situation. These net numbers, however, mask the sectoral and regional distribution of new jobs and value added created. The most significant negative impact would be the gradual disappearance of 4 thousand jobs in coal power plants by 2030 or 2050 depending on the scenario. These impacts are not significant when compared to the size of Chile’s labour markets and GDP. Chile’s economy routinely creates more than 40 thousand jobs per trimester, and US$1.7 billion is just 0.8% of GDP, while GDP is expected to grow at least 2.5% per year between today and 2030. At the national level, the results suggest that a careful planning and implementation of coal phase-out could be able to mitigate its negative impacts, given that they will be small relative to the size of Chile’s economy. Whether the jobs created nationally will match the skills available in the geographical location of current coal power plants is likely to play a key role. A separate forthcoming technical note studies affected communities in more details and will provide lessons learned from the historic management of the labour impacts of policy reforms.