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Technical change is generally considered the key to the solution of environmental problems, in particular global phenomena like climate change. Scientists differ in their views on the thaumaturgic virtues of technical change. There are those who are confident that pollution-free technologies will materialize at some time in the future and will prevent humans from suffering the catastrophic consequences of climate change. Others believe that there are inexpensive technologies already available and argue the case for no-regret adoption policies (e.g. subsidies). Others again believe that the process of technological change responds to economic stimuli. These economic incentives to technological innovation are provided not only by forces that are endogenous to the economic system, but also by suitably designed environmental and innovation policies. In this paper, we consider and translate into analytical counterparts these different views of technical change. We then study alternative formulations of technical change and, with the help of a computerized climate-economy model, carry out a number of optimization runs in order to assess what type of technical change plays a role (assuming it does) in the evaluation of the impact of climate change and of the policies designed to cope with it.
Climate-economy models aiming at quantifying the costs and effects of climate change impacts and policies have become important tools for climate policy decision-making. Although there are several important dimensions along which models differ, this paper focuses on a key component of climate change economics and policy, namely technical change. This paper tackles the issues of whether technical change is biased towards the energy sectors, the importance of the elasticity of substitution between factors in determining this bias and how mitigation policy is likely to affect it. The analysis is performed using the World Induced Technical Change model, WITCH. Three different versions of the model are proposed. The starting set-up includes endogenous technical change only in the energy sector. A second version introduces endogenous technical change in both the energy and non-energy sectors. A third version of the model embodies different sources of technical change, namely R&D and human capital. Although different formulations of endogenous technical change have only a minor influence on climate policy costs, the macroeconomic effects on knowledge and human capital formation can vary greatly.
This insightful book explores the issue of sustainable development in its more operative and applied sense. Although a great deal of research has addressed potential interpretations and definitions of sustainable development, much of this work is too abstract to offer policy-makers and researchers the feasible and effective guidelines they require. This book redresses the balance. The authors highlight how various indicators and aggregate measures can be included in models that are used for decision-making support and sustainability assessment. They also demonstrate the importance of identifying practical means to assess whether policy proposals, specific decisions or targeted scenarios are sustainable. With discussions of basic concepts relevant to understanding applied sustainability analysis, such as definitions of costs and revenue recycling, this book provides policy-makers, researchers and graduate students with feasible and effective principles for measuring sustainable development.
This work develops a framework for the analysis at the macro-level of the relationship between adaptation and mitigation policies. The FEEM-RICE growth model with stock pollution, endogenous Ramp;D investment and emission abatement is enriched with a planned-adaptation module where a defensive capital stock is built through adaptation investment. Within this framework the optimal path of planned adaptation, the optimal inter and intra temporal mix between adaptation, mitigation and investment in Ramp;D, and the sensitivity of a strategy to each other is identified. The major conclusions of this research show that adaptation, mitigation and Ramp;D are strategic complements as all concur together to the solution of the climate change problem; nonetheless the possibility to adapt reduces the need to mitigate and partly crowds out other forms of investment like those in Ramp;D. The optimal intertemporal distribution of strategies is also described: it requires to anticipate mitigation effort that should start already when climate damages are low and postpone adaptation intervention until they are substantial. Thus the possibility to adapt is not a justification to delay abatement activities. A sensitivity analysis demonstrates the robustness of these results to different parameterizations, in particular to changes in expected climate-change damages and in the discount rates.
This thesis consists of four papers studying endogenous technical change (TC) in climate policy analysis. The first paper provides a conceptual framework of analyzing the mechanism through which TC can be induced by climate mitigation policies. The second paper develops a computable general equilibrium (CGE) numerical model to quantitatively analyze the effect of endogenous TC on the timing and cost of carbon abatements. The third paper develops a multi-region modelling framework to examine the mechanism of international technology diffusion and its effect on domestic carbon savings. The fourth paper analyzes the mechanism of international technology coordination resulting from reciprocal cross-nation knowledge spillovers and its effect on global climate governance. The first paper, "Revisiting the mechanism of endogenous technical change for climate policy analysis", aims to reconcile the diverging specifications of endogenous TC in existing climate policy modeling literature. Drawing on the theory of R&D-induced TC, I provide a generalized framework to analyze the mechanism through which TC can be induced by climate mitigation policies. The second paper, "Can technological innovation help China take on its climate responsibility? A computable general equilibrium analysis", examines the effectiveness of China's indigenous R&D and technological innovation to cut its carbon emissions. The mechanism of endogenous TC is incorporated into a CGE numerical model. R&D investment and knowledge creation is modeled as the endogenous behavior of profit-seeking private producers. The accumulated stocks of productive knowledge are applied in a production process to induce the rate and bias of production TC. The third paper, "Can China harness globalization to reap domestic carbon savings? Modelling international technology diffusion in a multi-region framework", aims to examine the effect of globalization, particularly international technology diffusion, on reducing China's domestic carbon emissions. The single-country CGE model is extended into a multi-region framework, where both indigenous R&D and foreign technology diffusion are explicitly considered as two sources of endogenous TC for domestic carbon savings. The model systematically describes foreign technology diffusion through three diffusion channels of trade, foreign direct investment (FDI) and disembodied knowledge spillovers, with an elaborate treatment of local knowledge absorptive capacity. The fourth paper, "International knowledge spillover and technology externality: Why multilateral R&D coordination matter for global climate governance", investigates the mechanism of international technology cooperation and its effect on lowering global climate mitigation cost, with an aim of exploring the potentials of complementing international emission-based agreements with technology cooperation in the post-2012 climate regime. For that purpose, this paper firstly presents an analytical framework that describes how the mechanism of international R&D coordination can work for climate change mitigation. This mechanism is then quantitatively examined in a multi-region global numerical model that explicitly considers multilateral knowledge spillovers and resulting technology externality for global climate governance.
The research supported by this award pursued three lines of inquiry: (1) The construction of dynamic general equilibrium models to simulate the accumulation and substitution of knowledge, which has resulted in the preparation and submission of several papers: (a) A submitted pedagogic paper which clarifies the structure and operation of computable general equilibrium (CGE) models (C.2), and a review article in press which develops a taxonomy for understanding the representation of technical change in economic and engineering models for climate policy analysis (B.3). (b) A paper which models knowledge directly as a homogeneous factor, and demonstrates that inter-sectoral reallocation of knowledge is the key margin of adjustment which enables induced technical change to lower the costs of climate policy (C.1). (c) An empirical paper which estimates the contribution of embodied knowledge to aggregate energy intensity in the U.S. (C.3), followed by a companion article which embeds these results within a CGE model to understand the degree to which autonomous energy efficiency improvement (AEEI) is attributable to technical change as opposed to sub-sectoral shifts in industrial composition (C.4) (d) Finally, ongoing theoretical work to characterize the precursors and implications of the response of innovation to emission limits (E.2). (2) Data development and simulation modeling to understand how the characteristics of discrete energy supply technologies determine their succession in response to emission limits when they are embedded within a general equilibrium framework. This work has produced two peer-reviewed articles which are currently in press (B.1 and B.2). (3) Empirical investigation of trade as an avenue for the transmission of technological change to developing countries, and its implications for leakage, which has resulted in an econometric study which is being revised for submission to a journal (E.1). As work commenced on this topic, the U.S. withdrawal from Kyoto and the administration's announcement of a voluntary target based on emission intensity made it apparent that the degree of emission leakage to developing countries would depend on (i) the form of the emission limit set by developed countries and (ii) the incentives faced by developing nations to accede to an international climate regime. This realization led to synergistic research on the properties of intensity targets under uncertainty, which resulted in two theoretical studies, one which has been published (A.1) and the other which is currently in review (C.5).
Despite growing empirical evidence of the link between environmental policy and innovation, most economic models of environmental policy treat technology as exogenous. For long-term problems such as climate change, this omission can be significant. In this paper, I modify the DICE model of climate change (Nordhaus 1994, Nordhaus and Boyer 2000) to allow for induced innovation in the energy sector. Ignoring induced technological change overstates the welfare costs of an optimal carbon tax policy by 8.3 percent. However, cost-savings, rather than increased environmental benefits, appear to drive the welfare gains, as the effect of induced innovation on emissions and mean global temperature is small. Sensitivity analysis shows that potential crowding out of other R&D and market failures in the R&D sector are the most important limiting factors to the potential of induced innovation. Differences in these key assumptions explain much of the variation in the findings of other similar models
This study argues that because of the incomplete understanding of the mechanics of international technological change, the multiplicity of policy options and ultimately the presence of climate and technological change deep uncertainty, climate financing institutions such as the GCF, require new analytical methods for designing long-term robust investment plans. Motivated by these challenges, this dissertation shows that the application of new analytical methods, such as Robust Decision Making (RDM) and Exploratory Modeling (Lempert, Popper and Bankes, 2003) to the study of international technological change and climate policy provides useful insights that can be used for designing a robust architecture of international technological cooperation for climate change mitigation.