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close this bookThe Costs of Climate Protection: A Guide for the Perplexed (WRI, 1997, 60 pages)
View the document(introduction...)
View the documentACKNOWLEDGMENTS
View the documentFOREWORD
View the documentINTRODUCTION
Open this folder and view contents3. MORE DETAIL ON THE KEY ASSUMPTIONS
Open this folder and view contents4. TRADE AND EQUITY ISSUES
View the documentREFERENCES
View the documentANNEX
View the documentABOUT THE AUTHORS
View the documentBOARD OF DIRECTORS


An economic model is no more than a coherent set of assumptions about the structure and functioning of the economy. A model is used to predict the consequences of some change, often a policy change like the imposition of a carbon tax. Naturally, the prediction depends entirely on the assumptions imbedded in the model - how could it be otherwise? Many of the assumptions of an economic model are simplifications, adopted to make the model easier to analyze or to compute. Modelers hope that in making these simplifying assumptions the baby is not disappearing along with the bathwater, but, alas, that is not always so. Many are based on empirical studies, often quite sophisticated, of particular relationships in the economy, and the modeler hopes not only that the relationship has been described accurately but also that it will continue in the future as it was in the past.

Many people are critical of the assumptions economists make but none more so than economists themselves. Typically, economic modeling of important issues is subjected to widespread and intense scrutiny within the economics profession, and unrealistic assumptions tend to be identified, improved, or discarded. Just as climate scientists and modelers over the past decade have criticized and improved the atmospheric models linking greenhouse gas emissions to changes in climate, so have economists improved the modeling of the economic impacts of a carbon tax. There has been prolonged economic debate and significant intellectual progress in making the models used for economic simulation more realistic. This report reflects some of that intellectual history.

Two kinds of assumptions in the models are critical: those that largely determine the predicted economic costs of abating carbon emissions and those relating to the economic benefits from forestalling environmental impacts from fossil fuel emissions. With respect to the costs of limiting carbon emissions, the key assumptions are

1. the extent to which substitution among energy sources, energy technologies, products, and production methods is possible;

2. the extent to which market and policy distortions create opportunities for low-cost (or no-cost) improvements in energy efficiency;

3. the likely rate of technological innovation and the responsiveness of such change to price signals;

4. the availability and likely future cost of non-fossil, backstop energy sources;

5. the potential for international 'joint implementation' of emissions reductions; and

6. the possibility that carbon tax revenues would be recycled through the reduction of economically burdensome tax rates.

Just as climate scientists and modelers over the past decade have criticized and improved the atmospheric models linking greenhouse gas emissions to changes in climate, so have economists improved the modeling of the economic impacts of a carbon tax.


Predictions of the economic impacts of climate protection policies have been made on the basis of two main kinds of economic analyses, commonly referred to as 'top-down' and 'bottom-up' models. Top-down models are aggregate models of the whole economy that represent the sale of goods and services by producers to households and the reciprocal flow of labor and investment funds from households to industries. Models used for policy simulations also describe the role of government in imposing taxes, transferring income, and purchasing goods and services. Computable general equilibrium (CGE) models depict the formation of market-clearing prices in the process of matching the demand for goods and services from users to their supply by producers. Demand and supply conditions in such models are based on assumptions that consumers and producers allocate their resources to maximize their welfare or profits, respectively. However, demand and supply conditions are typically based on statistically estimated relationships observed in the past. Optimizing models derive their predictions by explicitly maximizing some assumed mathematical formula representing household welfare as a function of present and future consumption. Such general equilibrium models assume that households and industries will eventually respond efficiently to any policy change, though some models describe irreversible investment decisions and imperfect foresight regarding future prices that serve to delay the adjustment process.

In contrast, macroeconomic models predict economic behavior from statistically estimated relationships among economic variables in the past. Although such relationships are developed from accepted economic theory, macro models do not derive the predicted response to a policy shift from an explicit assumption that firms and households respond efficiently or with accurate foresight. Because they are estimated from actual macroeconomic behavior, they can reflect the short-term adjustment costs in response to an unexpected economic policy change, including business cycles, inflation, and unemployment. Macro and CGE models can be complementary in predicting short-run and long-run responses to a policy change. Moreover, modelers have learned to combine features of both (Hourcade and Robinson, 1996; Shackleton et al., 1992).

Top-down models used to analyze climate policies emphasize interactions between the energy sector and the rest of the economy. A tax-induced change in the price of carbon fuels directly affects demand and supply for energy, and indirectly affects other markets for commodities, labor, and capital. Therefore, consumer prices, incomes, savings, and labor supply are also affected, resulting in new levels of GDP, investment, and future growth. These can all be compared to baseline projections. More detailed analyses offer insights into distributional incidence on particular industries and income groups. When key assumptions are standardized among models, the range of their predictions narrows (Gaskins and Weyant, 1993).

Bottom-up analyses examine the technological options for energy savings and fuel-switching that are available in individual sectors of the economy, such as housing, transportation, and industry. Information on the costs of these options in individual sectors is then aggregated to calculate the overall cost of achieving a reduction in CO2 emissions. In contrast to top-down models, in which the scope for technological substitution is extrapolated from past experience, bottom-up analyses estimate possibilities by considering explicitly the actual technologies that firms could profitably adopt at various energy price levels. Bottom-up analyses tend to be more optimistic about the scope for cost-effective energy savings.

To some extent, this optimism comes from overlooking important barriers to implementation, such as management and retraining time, risk-aversion toward unproven technologies, capital constraints, household preferences, or lack of information (Boero et al., 1991). Top-down models based on past rates of substitution and technological change implicitly incorporate such effects. Moreover, bottom-up analyses do not deal as adequately with overall macroeconomic constraints on capital availability or market demand as top-down models do. Despite these limitations, bottom-up analyses have highlighted energy inefficiencies and technological opportunities. Some top-down climate models have adopted features of bottom-up analyses by incorporating detailed descriptions of technological options for energy supply, conversion, and use.

Assumptions about the use of revenues generated from carbon taxes or from auctioning off carbon permits are crucial.

Top-down models that assume limited substitution, slow technological change that does not respond to price signals, limited, expensive, or no availability of non-fossil energy sources, and the absence of international cooperation in achieving emissions reductions at least cost unfailingly predict that the economic costs of achieving any given carbon abatement target will be high. At the other extreme, bottom-up analyses that embody optimistic assumptions about the potential availability and rapidity of cost-effective, energy-saving technological improvements, and that neglect capital and other resource constraints can be counted on to predict low abatement costs.

In addition, assumptions about the use of revenues generated from carbon taxes or from auctioning off carbon permits are crucial. These revenues can be used to offset reductions in revenues if rates are cut on other taxes that are economically burdensome, without raising fiscal deficits. Many existing taxes on incomes, profits, and payrolls discourage savings, work, or investment by lowering after-tax returns to those activities. Economic studies suggest that lowering marginal tax rates for such existing forms of taxation and making up the revenue through a carbon tax would lessen the economic impacts of achieving a carbon abatement target. However, many early economic modeling simulations assumed that revenues from a carbon tax would not be used in this way but somehow returned in arbitrary "lump-sum" distributions to households, with no effect on incentives to work, save, or invest.

The final set of key assumptions concerns the environmental damages a carbon tax would avoid. Though averting these potential damages is the rationale for a carbon tax, most economic models are not constructed in ways that can take these damages into account. However, some models have factored in two types of savings:

1. avoiding the economic damages from climate change (the 'climate benefits'); and

2. reducing other air pollution damages associated with the burning of coal and other fossil fuels (the 'non-climate benefits').

The impact of climate change on the U.S. economy is a matter of great uncertainty, with predictions ranging from potential disasters - floods, hurricanes, droughts, and pestilence - to potentially mild or even benign effects. Attempts at comprehensive assessment have projected that, on balance, climate change will impose net economic costs over the next century, rising with the extent and rapidity of the change in climate (IPCC, 1996b; Nordhaus, 1993; Cline, 1992). Some assessments have assumed a degree of risk-aversion that gives more emphasis to low-probability but severely damaging outcomes.

Though averting potential environmental damages is the rationale for a carbon tax, most economic models are not constructed in ways that can take these damages into account.

Few models have dealt with the potential environmental side-benefits of a carbon tax that would make coal and petroleum fuels more expensive and discourage their consumption. Since baseline projections predict that without a carbon tax coal burning in power plants and gasoline consumption in motor vehicles will increase in coming decades, air quality might deteriorate, harming human health and necessitating higher medical expenditures. A carbon tax would reduce these risks. Whether or not models take such environmental side-benefits into account substantially affects the economic impacts they predict.

As the next section will demonstrate, the divergent assumptions built into economic models in these key areas largely explain why their predictions regarding the economic costs of reducing emissions differ so widely. Under a reasonable standardized set of assumptions, most economic models would predict that the macroeconomic impacts of a carbon tax designed to stabilize carbon emissions would be small and potentially favorable.

Aside from the macroeconomic impacts, other considerations enter the debate over climate protection policies: notably, their distributional impacts and their effects on our international competitive position. As discussed in the final section of this report, the disproportionate impact of a carbon tax on low-income households now appears to be less than first thought and could be easily offset by other tax reductions or cost-of-living adjustments in social security and other transfer programs. By contrast, the disproportionate impacts on certain industries, particularly the coal mining industry and coal-carrying railway lines, would undoubtedly be substantial. To put this in context, the baseline projections against which these effects are evaluated predict substantial expansion in coal mining in the western United States. The effects of a carbon tax designed to stabilize emissions at something like current levels would be largely to reduce the industry's rate of growth.

Under a reasonable standardized set of assumptions, most economic models would predict that the macroeconomic impacts of a carbon tax designed to stabilize carbon emissions would be small and potentially favorable.

Concerns regarding the effects of carbon abatement policies on the international position of the U.S. economy have also weakened in force because of recent developments. The key issues, closely interrelated, are

1. whether reduced energy demand in the United States would help hold down world oil prices, improving our terms of trade;

2. whether higher domestic energy prices would stimulate energy-intensive industries in other countries to expand more rapidly; and

3. whether other countries would also adopt similar policies to restrict greenhouse gases, following the U.S. lead.

The United States is a sufficiently large importer of petroleum products that its demand affects world prices. Baseline projections imply that in the absence of a carbon tax petroleum consumption would continue to outgrow production capacity in non-OPEC regions, so that OPEC would supply an increasing share of the world oil market. By 2015, OPECs share would exceed its peak two-thirds share in 1974, when it was able to raise energy prices sharply (U.S. EIA, 1996). A U.S. carbon tax that reduced U.S. energy demand could forestall increases in these prices and shift some of the economic impact on to foreign oil producers.

If, however, the United States alone imposed a significant carbon tax, international trade and investment in some energy-intensive industries might shift sufficiently to expand carbon emissions elsewhere and reduce U.S. production of those products. This now seems unlikely. Differential environmental policies appear to have a weak impact on trade and investment flows, if any (Repetto, 1995). Moreover, many non-OECD countries, including India, China, Mexico, and the republics of the former Soviet Union, have already raised energy prices unilaterally for purely economic reasons. Major OECD countries are likely to follow suit in instituting climate protection policies if the United States takes the lead. A few European countries have already enacted modest carbon taxes; others are seriously considering replacing some labor taxes with environmental taxes (OECD, 1997; Carraro and Siniscalco, 1996). The greater likelihood of coordinated international action means that adverse trade effects can be avoided.