The Long-Term Economics of Climate Change: Beyond a Doubling of Greenhouse Gas Concentrations: Volume 3

One of the principal tools in analyzing climate change control policies is integrated assessment modeling. While indispensable for asking logical “what if” questions, such as the cost-effectiveness of alternative policies or the economic efficiency of carbon taxes versus R&D subsidies, integrated assessment models (IAMs) can only produce “answers” that are as good as their underlying assumptions and structural fidelity to a very complex multi-component system. However, due to the complexity of the models, the assumptions underlying the models are often obscured. It is especially important to identify how IAMs treat uncertainty and the value-laden assumptions underlying the analysis.In particular, IAMs have difficulty adequately addressing the issue of uncertainty inherent to the study of climate change, its impacts, and appropriate policy responses. In this chapter, we discuss how uncertainty about climate damages influences the conclusions from IAMs and the policy implications. Specifically, estimating climate damages using information from extreme events, contemporary spatial climate analogs and subjective probability assessments, transients, “imaginable” surprises, adaptation, market distortions and technological change are given as examples of problematic areas that IA modelers need to explicitly address and make transparent of IAMs are to enlighten more than they conceal.

This chapter contributes to efforts to improve the accuracy of estimating damages resulting from climate change. It examines potential hydrological impacts on California, and how the state might adapt. For a doubled-CO2 scenario, general circulation models coupled with California hydrological data predict increased winter precipitation and dryer summers, elevated snowlines with correspondingly reduced snowpack, shifts in seasonal peak runoff patterns, increased numbers and intensity of extreme weather events, increased evapotranspiration, and declining soil moisture. Adaptations by water managers could include de-emphasizing the role multi-purpose reservoirs play in flood control in order to enhance their water-storage capabilities, making firm long-term commitments to provide water to wetlands and other ecologically-sensitive areas, and increasing the management flexibility available to local water agencies through intraregional contracting and mergers. In its conclusion, the chapter notes that while the water sector is accustomed to adapting to climatic variation, adaptations may not be consistent with an integrated assessment model's least-cost path. A region's gain or loss of overall water supplies should be evaluated in the context of its ongoing reallocation of water among competing uses. And in order to capture an appropriate level of detail, the scale of impact studies needs to be reduced to the national or sub-national level.

Crop yield variability is a defining characteristic of agriculture. Variations in yield and production are strongly influenced by fluctuations in weather. Concern has been expressed about the consequences of the buildup of greenhouse gases (GHGs) in the atmosphere on long-term climate patterns, including the frequency of extreme events, and the subsequent effect on crop yields and yield variability. In this chapter we present background on the variability issue, including a review of the physical and human dimensions of climate change as related to agricultural production. We also present the results of two recent studies; the first focuses on the effects of climatic variability on yields and the second on the effects of increases in extreme weather events on agriculture. The first study shows that temperature and precipitation changes affect both the mean and variances of crop yields, usually in opposite ways, e.g. under increasing temperatures, corn yields decrease and yield variance increases, while increases in precipitation increase corn yields and reduce variability. In the second study, increases in the frequency and strength of one type of extreme event, the El Niño-Southern Oscillation or ENSO, results in economica damages to agriculture. These damages can be averted by using forecasts of such events in agricultural planting decisions.

As CO2 equivalent gases increase beyond a doubling, there will likely be unavoidable damage to U.S. agriculture. In equatorial regions of the world, damage from global warming will occur earlier than in the U.S. Biogeophysical lags, including deep-ocean mixing with warmer surface waters, can delay the warming caused by CO2 emissions. In this chapter, comparative dynamics trace the path of damage to U.S. agriculture from climate change, after considering adaptation to climate change, technological change that will occur both with and without climate change, and ocean thermal lag.

Algorithmic models specifying the kinds of computations carried out by economic organizations have the potential to account for the serious discrepancies between the real-world behavior of firms and the predictions of conventional maximization models. The algorithmic approach uncovers a surprising degree of complexity in organizational structure and performance. The fact that firms are composed of networks of individual agents drastically raises the complexity of the firm's optimization problem. Even in very simple network models, a large number of organizational characteristics, including some for which no polynomial time computational algorithm is known, appear to influence economic performance. We explore these effects using regression analysis, and through application of standard search heuristics. The calculations show that discovering optimal network structures can be extraordinarily difficult, even when a single clear organizational objective exists and the agents belonging to the firms are homogeneous. One implication is that firms are likely to operate at local rather than global optima. In addition, if organizational fitness is a function of the ability to solve multiple problems, the structure that evolves may not solve any of the individual problems optimally. These results raise the possibility that externally-driven objectives, such as energy efficiency or pollution control, may shift the firm to a new structural compromise that advances other objectives of the firm also, rather than necessarily imposing economic losses.

This report describes an analysis of possible technology-based scenarios for the U.S. energy system that would result in both carbon savings and net economic benefits. We use a modified version of the Energy Information Administration's National Energy Modeling System (LBNL-NEMS) to assess the potential energy, carbon, and bill savings from a portfolio of carbon saving options. This analysis is based on technology resource potentials estimated in previous bottom-up studies, but it uses the integrated LBNL-NEMS framework to assess interactions and synergies among these options. The High-Efficiency Low Carbon scenario analyzed in this study would result in significant annual net savings to the U.S. economy, even after accounting for all relevant investment costs and program implementation costs. This strategy would result in roughly half of the carbon reductions needed to meet the Kyoto target being achieved from domestic U.S. investments, and net savings of more than $50B per year for the U.S. in 2010.

The conventional economic perspective on long run resource limitations is that short run scarcity will lead to price increases, which will induce innovation, which will in turn, overcome scarcity. In the global warming case, if we are convinced that cost-effective low carbon technologies will in fact emerge as carbon prices rise, why wait? Given that the investment dollars will be spent regardless, would it not be more efficient to invest in the new technologies today? In that way, we might avoid several decades of carbon emissions and consequent environmental damage. Moreover, such an approach is attractive for its likely impacts on both the size and composition of national R&D spending, as well as for its insurance function. On the other hand, informational constraints may argue against a technology policy strategy. This chapter explores these issues. In an application to the wind industry, I conclude that if wind power continues down its experience curve at its historical pace, early investment in wind would be socially efficient.

This chapter examines the validity of standard technology assumptions used in climate economy models, and explores the policy consequences of changing them to reflect actual as opposed to postulated trends. In this analysis, global oil production is determined by an augmented Hotelling model in which demand functions incorporate growth in world income and population. The equilibrium production trajectory rises in the near term, peaks, and then declines as the resource approaches depletion. Contrary to most other work, oil is replaced by an even more carbon intensive but proven energy form, such as coal or shale based synthetic fuel, for an ap[reciable length of time. At the same time, our econometric model projects energy intensity of the global economy stabilizing around the current level. This alternative arises from an analysis of historical data from the early 1970s to the present. While the scenarios explored here might be interpreted as pessimistic, we consider them highly plausible. The significant policy conclusion that emerges is the need for earlier and more aggressive climate policies than typically found in other work: the optimal control rate for carbon emissions is significantly higher. With existing and known alternative technologies significant reductions in carbon emissions are very expensive, as evidenced by the very high tax rates needed to achieve these reductions. We believe these results underli e the desirability for policies with increased emphasis on research on low cost, efficient substitutes for current technologies.

The Clean Development Mechanism (CDM) has been proposed as a means of reducing the costs of abating greenhouse gasses, and for assisting developing countries. Although the CDM offers apparent environmental benefits, in addition to benefiting both investors and developing country hosts, it has generated considerable controversy. We review and evaluate the arguments surrounding the CDM and we provide new empirical evidence concerning its potential benefits.

This chapter demonstrates that results from climate change models using the OLG approach can depend significantly on various economic and social conditions. Thereby, policy recommendations derived from OLG models can prove rather different from those resulting from conventional ILA models. This chapter presents the integrated assessment OLG model for the analysis of global warming ALICE 1.2, which allows for modeling a flexible interest rate and for incorporating various assumptions on demographic change and public institutions designed for the protection of the environment. Thus, ALICE 1.2 is particularly appropriate for providing policy makers with quantitative figures about the desirable and feasible reduction levels of carbon dioxide emissions.

Conservationists claim that future generations are morally entitled to enjoy the benefits of stable climatic conditions. Libertarians argue that polluters are entitled to emit greenhouse gases in the absence of undue regulation. This chapter explores the implications of these competing value judgements in a numerically calibrated overlapping generations model. Although short-term welfare is significantly higher under a laissez faire scenario in which greenhouse gas emissions remain unregulated, the stabilization of current climatic conditions confers substantial benefits on future generations that augment long-run economic growth. The finetuning of greenhouse gas emissions to achieve Pareto efficiency generates net gains that are small in comparison with the welfare differences between the laissez faire and climate stabilization paths.