Global Warming, Uncertainty and Endogenous Technical Change

Abstract

What impact does ecological uncertainty have on agents' decisions concerning domestic emissions abatement, physical investments, and R&D expenditures? How sensitive are the answers to these questions when we move from exogenous to endogenous technical change? To investigate these issues we modify the ETC-RICE model described in by embedding in it a hazard rate function as in Bosello and Moretto (1999). With this model at hand we run numerical optimisations focusing our attention on the control variables of the representative agents, i.e., domestic abatement rate, investments in physical capital, and R&D spending, as well as on the endogenous patterns of GDP level and CO 2 emissions. Our results show that uncertainty strongly influences agents behaviour; in particular, agents slow down their emissions in order to maintain a more sustainable growth path. In addition, R&D expenditures trigger the "engine of growth" exclusively when environmental technical change is formalized in an endogenous fashion. However, even if environmental uncertainty may stimulate technical change, long-run growth it turns out to be negatively affected by the former, as also predicted by Clarke and Reed (1994) Tsur andZemel (1996) and Bosello and Moretto (1999).

Assessments of ‘Greenhouse Insurance’: A Methodological Review

“…Similar approaches applying a hazard function are seen in the studies by Bosello and Moretto (1999); Castelnuovo et al (2003); Nakajima et al (2006), and Kosugi (2007). More complicated analyses of this kind were performed by Naevdal (2006) and Naevdal and Oppenheimer (2006), who used hazard functions to solve dynamic optimization problems with multiple thresholds located in n-dimensional space taking into consideration the uncertain thresholds of the breakdown of the West Antarctic Ice Sheet and the slowdown of the thermohaline circulation.…”

Uncertainty and economic analysis of climate change: A survey of approaches and findings

“…Even though there are exceptions where uncertainties do not markedly affect optimal abatement levels [42] or even lead to lower abatement [43], most modeling results show (as can be expected) that there is optimally more emission abatement if uncertainties in parameters or the possibility of catastrophic events are considered [12,17,32,44,45,46]. Pizer [34] for example finds that while the optimal rate of CO 2 reduction accounting for uncertainty is only slightly higher than the rate obtained when ignoring uncertainty and taking best guess values in the beginning, it grows over time.…”

On the Value of Conducting and Communicating Counterfactual Exercise: Lessons from Epidemiology and Climate Science

“…Identifying the relevant decision-makers measurable priorities is critical, though, because it is their net benefit valuation protocols that produce the VOI metrics with which these calculations can be conducted. The Academy study emphasized that the application of decision theory could provide explicit descriptions of how rigorously to evaluate the appropriate value of perfect and imperfect information, much as done 30 years ago in [45][46][47].…”