Conference Agenda

It is widely acknowledged that wealth-based indicators and their rate of change - saving-based indicators - face problems regarding the equivalence of their theoretical terms and theoretical limitations, and show significant discrepancies in empirical estimates. Hence, the indicators are considered by many to be unsuitable to serve as accurate and practical guides for economic and policy decisions regarding sustainable development. The current study contributes to the economics literature by addressing the shortcomings of the indicators. Instead of the commonly used observed market prices for shadow prices and past datasets for quantities, we employ our climate–welfare economy integrated assessment model that generates quantities and their shadow prices up to 2150. Our model endogenously generates utility flow determined by per capita consumption over 10-year time intervals, enabling us to compute the growth rate of the discounted sum of utility (i.e., social welfare) and per capita consumption. We compared these growth rates with those of the indicators. The growth rates of comprehensive wealth including health capital based on Arrow et al. 2012 and adjusted net savings-based (ANS-based) wealth are the closest to those of social welfare and per capita consumption, respectively.

The green energy transition is necessary within the next few decades to mitigate climate change. In the paper, I explore the effectiveness of carbon pricing and the role of technological spillovers in achieving decarbonization, with a particular focus on the challenges faced by developing countries. I develop a two-region integrated assessment model that incorporates fossil fuel and renewable energy sources to investigate the quantitative impact of spillovers on decarbonization in developing

countries. The findings indicate that technological spillovers in developing countries contribute to the replacement of fossil fuels with renewable energy inputs. The study suggests that implementing carbon taxation in both advanced and developing regions, along with technological spillovers, yields the most favorable outcomes for the climate. However, the absence of carbon tax in developing countries with spillovers still delivers slightly better environmental results compared to taxing both regions without spillovers. The results emphasize the importance of considering spillovers and carbon taxation when designing effective policies to achieve environmental goals.

Despite the urgency of a low-carbon transition, the path to clean technologies remains erratic, marked by path dependence, technological lock-in, and coordination failures. This paper explores the pivotal role of beliefs in shaping this transition, emphasising the reciprocal relationship between innovation pace and beliefs. A tractable continuous-time two-sector general equilibrium model incorporating Bayesian learning about sustainable research productivity reveals that belief heterogeneity leads to research misallocation, but these beliefs can also significantly influence the transition trajectory and equilibrium selection. Particularly, with enough optimism about clean technologies, the economy can transition away from otherwise locked-in polluting technologies. However, the convergence of beliefs to the true productivity of clean technologies due to learning mitigates the effect of optimism and pessimism, especially if the clean sector is too small or unproductive.

Current climate change mitigation policies exhibit a mismatch between weak short-term efforts and ambitious long-term goals. Integrated Assessment Models (IAMs) have been utilized to evaluate the CO2 emission pathways associated with these "Delayed Transition" scenarios. However, these tools used to inform climate policy-making fall short in capturing crucial aspects of decision-making. Specifically, they often assume that economic agents have perfect information and trust regarding future climate policies. This paper contributes to the literature by providing a comprehensive framework to integrate imperfect foresight and climate policy uncertainty in climate policy assessment. We explore situations of imperfect foresight about future climate policies and plausible behavioral response of economic agents in the IAM IMACLIM-R. We demonstrate that imperfect foresight puts the achievement of climate change mitigation targets at risks, with an increase in cumulative CO2 emissions of 33% in the scenario that combines delayed implementation and deep uncertainty about future climate policies, compared to an early transition with perfect foresight and credible policies.