Modeling The Economics Of Climate Change

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Translating changes in future climate into economic impacts measured in monetary terms is a challenging task for a number of reasons. First, in order to understand how climate will affect the global and regional economies, a solid understanding of how the economically relevant dimensions of climate are going to vary at these spatial scales is required. Global climate models (GCMs) provide predictions of the main variables of interest, rainfall and temperature, at increasingly finer temporal and spatial resolution. However, there is much uncertainty remaining over the predicted spatial and temporal distribution of climate across GCMs and emission scenarios. In economic impact evaluation, this uncertainty is amplified by the uncertainty about how individuals, firms, and governments respond to the changing climate directly, and are affected by it indirectly through its impacts on ecosystems.

The economy is a complex system, whose response to a changing climate must be studied using models because, unlike physical scientists, economists lack the opportunity to conduct controlled experiments on this system. Agents in this complex system will sometimes respond in offsetting directions to climate changes. Individuals, for example, respond to incrementally hotter summers and milder winters by cooling more during the hot months and heating less during the cold months, resulting in increased energy consumption in the summers and decreased energy consumption in the winters. Further, responses to the changing climate may be gradual and small or abrupt and sizable. For example, farmers may respond to slightly drier and hotter growing seasons by planting and harvesting earlier in the season. If, however, summers become significantly drier and hotter, farmers may switch crops and/or install irrigation equipment. More households may purchase air conditioners or run existing ones not only during the day, but also during the night. Such adaptions make it extremely difficult to predict impacts on humans and the economy as a whole, because individuals respond to exogenous changes in often-unpredictable ways.

One aspect that is especially difficult to predict is the investment in successful research and devel opment of new technologies. The energy intensity of most industrialized economies has dropped significantly since World War II. This is partially due to improved energy efficiency of capital, but also due to a structural shift of these economies away from manufacturing toward the production of services. Much of manufacturing, which is thought to be more carbon intensive, has shifted to the developing world. Predicting the future path of energy efficiency and structural composition of the worlds' larger economies is a difficult task. This is especially true for technological innovation, which often progresses in discrete leaps that are virtually impossible to predict.

The timespan used to assess the economic impacts of climate change is much longer than that for many other environmental problems, due to the long atmospheric lifespan of many greenhouse gases. While there is evidence of climate change impacts at the beginning of 21st century, many of the potentially larger effects are expected to occur after mid-century. In order to evaluate the potential costs of climate change, economists discount its future costs and benefits. Discounting essentially recognizes that a dollar today is worth more than a future dollar, because investments are productive and, therefore, resources today are more valuable than resources tomorrow. This implies that if there are two equally damaging outcomes 10 years apart, the second bad outcome would be judged to have lower current dollar damages. There is a much debate over the practice of discounting and the choice of discount rate. Some advocate a discount rate of zero. The choice of discounting method and discount rate has a significant impact on the calculated damages valued in present-day currency.

There are several classes of models used to simulate the economic damages from climate change. Statistical/econometric models are used to estimate the benefits/damages from climate change on, for example, agricultural yields and net profits at the farm or county level using historical data. The estimated relationship between yields or net profits and climate based on observed data is then coupled with GCM output to provide estimates of future yields and farm profits. The advantage of the econometric approach is that it uses actual observed data, which reflects individuals' responses to already-observed changes in climate. The disadvantage of this approach is that these studies deal with specific sectors at the country or a lower level of spatial aggregation. Therefore, many studies are required to obtain global estimates of impacts. Finally, these models are sensitive to estimation technique and the choice of variables used to explain variation in yields/ net profits. Several econometric studies have been conducted to estimate the impact of climate change on agriculture, mortality, energy demand, water demand, ecosystem damage, and stream flows.

One alternative to modeling the potential damages from climate change is the use of large-scale simulation models. This computer-based modeling approach represents the different sectors of the global or national economy individually, and assumes specific climate sensitivities for the relevant sectors. As in reality, the economic sectors are interlinked; thus, climate-change induced damages, for example, in the agricultural sector may affect labor markets, which may affect wages in the agricultural (and potentially, other) sectors. Some of these simulation models have built in the fact that economic growth is directly linked to the amount of greenhouse gases emitted into the atmosphere.

Through this feedback loop, climate change impacts in the model depend on emissions, which are dependent on the state of the economy. The advantage of these simulation models is their ability to represent spillover effects across sectors and the feedback between the economy and the climate system. The disadvantage of these complicated computer models is the need to make a assumptions concerning how individual sectors of the economy are linked, as well as how they respond to changes in climate. Results from econometric studies are often used to inform these simulation models, yet the necessary number of parameters needed in these simulation models is much greater than what our current knowledge from econometric models. The simulation models do have the crucial advantage of simulating the impacts of different policy tools on emissions, as well as on the economy as a whole.

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