Characterizing regional economic impacts and responses to climate change

Characterizing regional economic impacts and responses to climate change

Global and Planetary Change 25 Ž2000. 67–81 www.elsevier.comrlocatergloplacha Characterizing regional economic impacts and responses to climate chang...

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Global and Planetary Change 25 Ž2000. 67–81 www.elsevier.comrlocatergloplacha

Characterizing regional economic impacts and responses to climate change David Abler a,) , James Shortle b,1, Adam Rose c,2 , Gbadebo Oladosu c,2 a

Agricultural Economics, PennsylÕania State UniÕersity, 207 Armsby Building, UniÕersity Park, PA 16802, USA Agricultural Economics, PennsylÕania State UniÕersity, 112 Armsby Building, UniÕersity Park, PA 16802, USA Energy, EnÕironmental, and Mineral Economics, PennsylÕania State UniÕersity, 221 Walker Building, UniÕersity Park, PA 16802, USA b

c

Received 20 September 1998; accepted 1 May 1999

Abstract While much progress has been made in recent years in modeling the impacts of greenhouse gases on global climate and impacts of global climate change on regional climates, much less progress has been made in modeling economic impacts and responses to climate change, particularly at a regional level. This lack of progress is due, in large part, to the fact that there is no generally accepted framework for characterizing the regional economic impacts of, and responses to, climate change. The objective of this paper is to make a start at such a framework. We divide economic impacts at a regional level into four broad categories: direct impacts on production of market goods and services; direct impacts on production of nonmarket goods and services; indirect impacts on other economic sectors within the region; and indirect impacts operating through other regions and countries. We go on to consider two modeling frameworks for responses to climate change: static, in which regional capital stocks, technologies, and public and private institutions are exogenous; and dynamic, in which these variables are endogenous. Dynamic responses in capital stocks, technologies, and institutions are likely to be the most important adaptations to climate change and its effects on ecosystems, but also the least well understood at the present time. q 2000 Elsevier Science B.V. All rights reserved. Keywords: adaptation; climate; economics; global warming; regional; response

1. Introduction Much progress has been made in recent years in modeling the impacts of greenhouse gases on global

) Corresponding author. Tel.: q1-814-863-8630; fax: q1-814865-3746. E-mail addresses: [email protected] ŽD. Abler., [email protected] ŽJ. Shortle., [email protected] ŽA. Rose., [email protected] ŽG. Oladosu.. 1 Fax: q1-814-865-3746. 2 Fax: q1-814-863-7433.

climate and impacts of global climate change on regional climates ŽCrane and Hewitson, 1998; Jenkins and Barron, 1997; Easterling, 1997.. Much less progress has been made in modeling economic impacts and responses to climate change, particularly at a regional level. There is some evidence and much speculation on ways that climate change may affect climate-sensitive sectors of an economy. For instance, much is now known about the impacts of changes in temperature, precipitation, atmospheric carbon dioxide, and other variables on crop yields in many regions of the world ŽIPCC, 1996a.. However,

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we generally lack information on potential responses of economic actors Žcompanies, institutions, households, and individuals. to these changes. We also lack information on how economic actors in one region might respond to climate-induced economic changes in another region. In addition, little is known about how economic actors in one economic sector might respond to climate-induced economic changes in another sector. This lack of information on the types and extent of potential responses makes it very difficult to model regional adaptation to climate change or to assess vulnerabilities. There is some evidence at the regional level on the kinds of adaptation that are possible, but much less on the specific adaptation strategies that are actually likely to be adopted at a regional level ŽIPCC, 1996a,b.. This absence of information is not simply due to the fact, that the necessary empirical work has yet to be done. It is also due to the fact, that there is, at present, no generally accepted framework for characterizing the regional economic impacts of, and responses to, climate change. The objective of this paper is to make a start at such a framework. Our focus is not on the biological or physical effects of climate change Že.g., vector-borne diseases or extreme weather events.. We instead take these effects as starting points in thinking about how to characterize regional economic impacts and responses. Many of the issues involved are at the frontier of economic modeling. This paper does not undertake any empirical modeling work itself, but instead suggests issues that should be considered when designing and implementing an empirical model of regional economic impacts and responses. The focus of this paper is on medium- to long-run economic impacts and responses rather than short-run impacts and responses to extreme weather events. For example, a flood can have immediate and severe economic impacts, including forced evacuations and dislocations, business closings, and temporary unavailability of many goods and services. Responses on the part of individuals, businesses, and emergency authorities during and immediately after a flood can be critical in minimizing these impacts or, if inappropriate, can potentially make matters worse. While these impacts and responses are important, they present much different analytical issues and challenges

than the longer-term actions that individuals, businesses, and governments take to reduce Žor increase. their vulnerability to climate change and to respond to the longer-term economic impacts of climate change. Regional modeling of the economic impacts of climate change is important for many reasons ŽEasterling, 1997.. Many public decisions about adaptation policies will be made not at the national or international level but at the regional or local level. By the same token, decisions by private economic actors such as companies, households, and individuals about if, how, and when to respond to climate change will be made at a regional or local level. Information on the potential economic impacts of climate change at a regional level, not just a national or global level, is essential for guiding their responses, especially in areas that influence long-term vulnerability. Even regional analyses may be too geographically aggregated for some purposes, but they are a step in the right direction. Regional economic modeling is also needed because the efficacy of adaptation strategies and in turn vulnerabilities to climate change are likely to vary substantially from one region to another. Some regions will have the knowledge, skills, and resources to adapt well to negative impacts and take advantage of positive impacts, while others will not.

2. Regional analyses vs. more aggregate analyses Several recent studies have been directed at the potential economic consequences of climate change at a national or international level ŽTol and Fankhauser, 1998; Tol et al., 1998.. However, studies at the regional level are rare. Regional level studies include the MINK study ŽRosenberg, 1993; Easterling et al., 1993. and a study of the U.S. Susquehanna River Basin by Abler et al. Ž1998.. A regional analysis of the economic consequences of climate change is at once both more complicated and less complicated than an analysis at geographically more aggregate levels. On the one hand, unlike more aggregate analyses, a regional level analysis must account in a detailed manner for economic and ecological interactions with other regions in the same country. Ecological interactions would include

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changes in habitat for migratory wildlife or disease vectors. Economic interactions would include exports and imports of goods and services, labor migration, and capital flows. In particular, a regional level analysis must account for inflows of capital from other regions and outflows of capital to other regions in response to attractive investment opportunities, insurance payments, and government assistance. Most aggregate analyses overlook these interactions, with the economy implicitly treated as a single, homogenous unit. Another complicating factor is that important economic data Že.g., the capital stock. are often missing or only roughly estimated at a regional level. In addition, many economic processes and interrelationships are less stable over time and consequently less predictable at a regional level. This is because large shifts in the production of many goods and services can occur from one region to another within a country based on regional differentials in labor costs, government fiscal and regulatory policies, or other factors. These shifts can lead to significant changes in income, employment, and economic structure at the regional level even while these variables are relatively stable for the country as a whole. On the other hand, regional economic models can be interfaced in a more realistic manner with downscaling, hydrologic, ecosystem, and other biophysical models than national or global economic models. A national economic model can only describe what might occur on average in a country as a whole. It cannot describe what might occur in a particular river basin or ecosystem of that country. Regional economies also tend to be simpler and more transparent than national economies or the international economy ŽIsard, 1975.. Furthermore, regional economies tend to be small in economic ‘‘size’’ Žas measured by their shares of income, employment, the capital stock, and population. relative to the global economy and many national economies. For this reason, many economic variables can be modeled as exogenous at the regional level that must otherwise be modeled as endogenous, including prices for most goods and services, wage rates paid to workers, interest rates paid on loans and received on investments, and available technologies. Forces at more aggregate levels usually determine these variables. For example, prices of

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agricultural commodities are determined on world agricultural markets; interest rates on loans and investments are determined on national or global capital markets. As a result, a regional economic model does not need to derive solutions for these variables. Instead, values for these variables can be obtained from other sources and used as inputs into the regional economic model. A ‘‘region’’, as we are using the term, could in some cases be applied to an entire country. Many countries, including most developing countries, are small in economic size. Fig. 1 illustrates linkages between the global climate, a regional economy, and the economy of the rest of the world Žwhich encompasses other regions of the same country and other countries.. Climate can potentially have strong impacts on both the regional economy and the rest-of-world economy. Activities in the rest-of-world economy can also have strong feedback effects on climate, but activities in the regional economy are less likely to have significant feedback effects because most regions, when defined at the scale of a river basin or other similar scale, are small in economic terms. However, it might still be possible for a region to be small in economic terms but important as a source or sink of greenhouse gases or other climate-altering activities. For reasons noted above, the rest-of-world economy can exert a strong influence on the regional economy. Again, however, any one regional economy is unlikely to affect the rest-of-world economy because it is small in economic terms. Of course, the sum total of regions comprises the global economy, and regional analysis is valuable as a bottom–up determination of aggregates.

Fig. 1. Climate–regional economic interactions.

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3. Characterizing economic impacts at a regional level Broadly speaking, climate change can have four types of economic impacts at a regional level. First, it can affect the production of market goods and services within the region. Market goods and services are those sold by an economic actor Ža company, institution, household, or individual. to another economic actor, with payment being in cash, in kind Žbarter transactions., or both. Second, climate change can affect the supply of nonmarket goods and services within the region. Nonmarket goods are those that are not traded, and in which property rights are not well defined. Unlike a market good, the value of a nonmarket good Žwhat people would be willing to pay for it if it were bought and sold. is unaccounted for by the market. Third, climate change can have indirect effects on economic sectors within the region that are not directly affected by climate change. Fourth, climate change can have indirect effects on the region through effects on other regions of the same country or other countries. Table 1, which is reproduced from the 1995 IPCC report ŽIPCC, 1996b., provides an overview of several potential market and nonmarket impacts of climate change, as well as the state of the literature on estimating these impacts at the time the report was written. The table is helpful in providing some examples of market and nonmarket goods. For instance, agricultural products, forest products, water, and energy are all market goods, since they are all bought and sold, at least in most countries. On the other hand, ecosystems, species, human health, and human life are all nonmarket goods because there are no markets where these goods are bought and sold. All these goods are valuable yet there are no markets to assign prices to them. Excluded from the nonmarket category in Table 1 are more traditional public goods such as education, national defense, police protection, and information services. Although these goods are very important and could potentially be affected by climate change, we will confine our discussion here to human health and environmental services. The distinction between market and nonmarket goods is critical in analyzing the impacts of climate change. Those who have property rights in market goods stand to reap the rewards or suffer the conse-

quences of direct and indirect effects that climate change may have on the value of their assets. This gives them incentives to anticipate climate change and respond to its impacts. In contrast, while nonmarket goods are essential to human welfare and of great economic importance Žsee, e.g., Costanza et al., 1997., markets do not provide meaningful incentives or mechanisms to reduce risks or exploit opportunities. Referring to Fig. 1, effects on market and nonmarket goods and services within the region are represented by the arrow running directly from global climate to the regional economy. Effects operating indirectly through other regions are represented by the two arrows running first from global climate to the rest-of-world economy and then from the restof-world economy to the regional economy. 3.1. Production of market goods and serÕices Climate change could have positive or negative impacts on production of market goods and services within a region through a variety of channels and in a variety of economic sectors. In general, these impacts can be divided into three categories: health impacts; property or asset losses; and impacts on productivity in primary goods and services sectors Ži.e., agriculture, forestry, and fisheries. apart from health impacts and assets losses. Although health impacts are put into the nonmarket portion of Table 1, since that is where they first occur, they can have repercussions on production of market goods and services. Premature deaths among those of working age or workdays lost to illness reduce the amount of labor available for market production. Work time that is not completely lost but is less productive because of illness or disease also has repercussions for production of market goods and services. Climate change could have positive or negative health impacts. Sudden losses of property due to extreme events such as floods and hurricanes represent a loss of physical capital for production of market goods and services. Chronic damage to capital goods because of unfavorable weather conditions essentially causes capital to depreciate more quickly, and as such also has negative impacts on production. Any capital good that is exposed to the elements may be subject

State of literature

Market impacts Primary economic sectors

Other economic sectors

Fully estimated, based on willingness to pay

Agriculture

Fully estimated, using approximations

Forestry

Water supply

Partially estimated

Fisheries

Energy demand leisure activity

Not yet estimated

Nonmarket impacts Property loss

Damage from extreme events

Dryland loss Coastal protection

Insurance Construction Transport Energy supply

Urban infrastructure

Ecosystem damage

Human impacts

Damage from extreme events

Wetland loss

Hurricane damage

Forest loss

Hurricane damage

Damage from droughts

Species loss

Human life Air pollution Water pollution Migration

Nontropical storms River floods HotrCold spells Other catastrophes

Other ecosystem loss

Morbidity Physical comfort Political stability Human hardship

Nontropical storms River floods Hotrcold spells Other catastrophes

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Table 1 A taxonomy of market and nonmarket impacts of climate change Source: IPCC Ž1996b., Chap. 6.

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to this type of chronic damage, but those in agriculture, forestry, fisheries, construction, transport, electric power generation, and water supply would be especially vulnerable. Commercial, residential and government buildings might also be vulnerable. Depending on changes in extreme events and long-term weather patterns, climate change could have positive or negative impacts on property losses. In addition to health impacts and property losses, there are those primary economic sectors Žagriculture, forestry, and fisheries. where climate is an essential input into the production of market goods, at least using conventional production systems. Changes in extreme events and changes in long-term weather conditions in these sectors could have significant positive or negative impacts on production. Discussions of potential climate change impacts sometimes focus on primary sector impacts and give little attention to health impacts or property losses from extreme weather events, but this may be a mistake. Simulations for the U.S. Susquehanna River Basin by Abler et al. Ž1998. suggest that property losses and especially health impacts may be the most important types of impacts, at least within a static framework. Simulations by Dalton Ž1997. also suggest a focus on climatic variability and not just mean climatic conditions. An additional issue in characterizing regional economic impacts and responses is whether compensation is received by companies or by households through insurance or government aid. In the U.S. and other developed countries, compensation is sometimes received for extreme events, depending on a company’s or a household’s insurance policies and on government programs. Compensation is hardly ever received for more chronic, persistent events. Insurance and government payment programs are important because, if these programs are sufficiently generous, aggregate income in a region can actually increase in spite of a disaster ŽAbler et al., 1998; Rose et al., 1997.. As a caveat, even if incomes within a region increase, they do so at the expense of people outside the region who must cover the costs of insurance settlements and government aid. Furthermore, an increase in income in this context is not the same as well being or utility. Extreme weather events have obvious negative impacts on utility apart from any effects they have on income. In addition, as

discussed in Section 5 below, improperly structured insurance and government payment programs can so diminish market incentives for adaptation as to cause maladaptation ŽLewandrowski and Brazee, 1993.. 3.2. Production of nonmarket goods and serÕices Environmental goods belong to the class of nonmarket goods because their value is partially or completely unaccounted for by the market. A nonmarket good may be a separate good in and of itself or a quality characteristic of another market or nonmarket good. Many climate-related goods such as air and water quality can be seen as quality characteristics. On the other hand, recreational resources for hunting, fishing, sightseeing, etc., are tangible, independent goods. Unlike market goods, nonmarket goods are not traded between one economic actor and another. For example, while it possible to purchase many market goods and services that can contribute to good health, no one can buy good health directly. It is instead produced within a household using market goods and the time of household members, and then consumed by that same household. Nonmarket goods provide benefits that are often grouped into use and non-use values. Use values refer to benefits resulting to economic actors from utilization of the good, while non-use values are those not related to actual consumption Že.g., deriving satisfaction from simply knowing that a species has not been made extinct.. Non-use values may be further broken down into various subgroups including bequest values and existence values ŽFreeman, 1993.. Given that nonmarket goods cannot be assigned prices like market goods, the derivation of economic values for these goods has relied on several valuation approaches. A review of these approaches is beyond our scope here, but they are discussed by Freeman Ž1993. and Smith Ž1997.. Climate itself is a multi-dimensional nonmarket good. In a sense, the direct and indirect impacts of climate change are direct and indirect impacts of the change in a nonmarket good. There are a variety of ways to characterize the nonmarket impacts induced by climate change. Following Freeman Ž1993., one would be by the type of nonmarket good Že.g., air,

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water, and outdoor recreation.. This would be analogous to classifying economic impacts by economic sector. Another would be by the type of impacts, such as direct impacts of humans Že.g., health or esthetics., bioeconomic systems, and nonliving systems. Although each alternative has merit, for symmetry, we maintain the distinctions we introduced above between health impacts, property impacts, and productivity impacts. As in Table 1, health impacts from changes in heat stress, changes in disease risks associated with weather events or ecosystem change, and weather-related accidents are nonmarket impacts. They lead to market impacts as a consequence of changes in the supply of labor and the demand for market goods, such air conditioners or health services. They can have similar impacts on the demand and supply of nonmarket goods like hunting, fishing, and other forms of recreation. Similarly, beaches, wetlands, forests and others forms of property, which we can view as environmental assets, as well as other forms of property such as boats, docks, trails, and lodges, are inputs to the supply and quality of outdoor recreation services, water, and other nonmarket goods. Thus, changes in damages to environmental assets will have nonmarket impacts. Finally, nonmarket goods such as hunting, fishing, boating, and sightseeing are counterparts to agricultural, forestry, and fishery goods in the sense that, in all cases, climate is an integral input into production using conventional production systems. In all cases, changes in average climatic conditions or in climate variability could have significant positive or negative impacts on production. In characterizing impacts on household production of nonmarket goods, interactions between the production of one nonmarket good and another should be recognized. For example, an individual’s recreational choices depend on several factors, prominent among which are the state of health and the quality and supply of outdoor recreation services. Similarly, interactions between market and household production should also be recognized, as in the case of health discussed above. In addition, market and household production represent competing uses for time, with time spent working in the market being unavailable for household production of nonmarket goods, and vice versa.

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3.3. Indirect impacts on other economic sectors within the region Direct climate impacts on production of market and nonmarket goods within the region are only part of the picture. An economic sector might be totally insulated from climate change in terms of its own production processes and yet affected indirectly by other, climate-sensitive economic sectors within the region. For example, prices of capital, labor, materials, or other production inputs facing producers in one economic sector might change as a result of climate change impacts on other sectors within the region. Similarly, output prices received by producers in one sector might change as a result of climate change impacts on other sectors. For both outputs and inputs, price changes stimulate substitution away from higher-priced goods and toward lower-priced goods. These phenomena acting through markets and prices are commonly referred to as general equilibrium effects. In addition, changes in prices of inputs can lead to changes in personal income, because ultimately, individuals are the owners and suppliers of inputs such as labor, capital, and many natural resources. Impacts such as these are not limited to first-round effects because the first-round effects can generate a chain reaction of additional, although increasingly smaller, rounds of indirect effects. The total impact, taking into account all rounds of effects on all economic sectors, is some multiple of the direct impacts, and hence, the often-used term ‘‘multiplier’’ effects. Taking into account the indirect impacts of climate change on sectors that are not directly climatesensitive can represent a significant additional research burden, since the sectors that are not directly climate-sensitive tend to be more numerous and larger in economic terms in most regions than the climatesensitive sectors. Some economic models have been developed for individual countries, groups of countries, or the entire world that include these indirect impacts ŽTol and Fankhauser, 1998.. However, there are comparatively few economic models of regions defined at the scale of a river basin or some similar scale that take these impacts into account. Examples at this scale include the MINK model ŽRosenberg, 1993; Easterling et al., 1993. and a computable

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general equilibrium ŽCGE. model of the U.S. Susquehanna River Basin ŽAbler et al., 1998.. Rose Ž1996. outlines the CGE modeling approach and its advantages relative to other economic modeling approaches.

3.4. Indirect impacts through other regions and countries In addition to impacts on production of market and nonmarket goods and services within a region, it is imperative to consider impacts relative to other regions of the same country and other countries. Although national economies are not closed systems, and are rarely well approximated as closed systems, this is particularly true at the regional level. Regional economies tend to be highly open as measured by exports, imports, inflows and outflows of capital, and in-migration and out-migration of labor. Climate change in other regions or other countries could potentially have significant impacts on national and global markets for goods, services, and factors of production Že.g., capital, labor. facing the region under investigation. For this reason, even a region in which there were no direct impacts on production of market or nonmarket goods could be significantly affected by climate change. Moreover, even in a region with significant direct impacts, impacts operating through national and global markets could still potentially be more important. Taking into account impacts not only within the focus region but also in other regions and countries Žor at least those regions and countries that compete as suppliers of goods, services, or factor supplies. is a potentially significant additional research burden. Thus far in the literature on climate change, no study has come close to addressing these impacts adequately. In fact, most studies focus only on the single region or country in question and ignore the others. This is tantamount to assuming that there are no direct or indirect climate impacts elsewhere. CGE modeling offers one approach to dealing with these impacts in a systematic manner ŽKamat et al., 1998; Rose, 1996.. Differences in climate impacts between regions affect the economic competitiveness of one region

relative to another. For example, relatively greater heat and dryness in one region translates into lower crop yields relative to other regions, and a disadvantage relative to other regions in national and international agricultural markets. Likewise, climate change may damage local recreation sites and cause local residents to venture elsewhere to satisfy their demands for this service. Even slight differentials can have major repercussions on regional and international trading patterns. However, transportation and travel costs act as a type of buffer because they discourage trade between regions and countries. In other words, goods and services with relatively high transportation and travel costs will, to some extent, be nontradable and therefore isolated from changes outside the region. To date, nearly all major climate impact studies have ignored the issue of indirect impacts through other regions and countries. The ideal approach would be to have a fully integrated model of all world regions from both economic and environmental standpoints, but this is a daunting task. Some models have attempted to integrate regions of a major country Žsee, e.g., Polenske, 1990., but these efforts have been met with limited success due to data limitations and, moreover, they have not ventured into the environmental area at all. An alternative approach would be to adapt information from separate analyses of other regions into the study of the focus region. For example, Kamat et al. Ž1998. utilized the results of Jorgenson and Wilcoxen Ž1993. on carbon tax impacts as the basis for their ‘‘rest of the U.S.’’ price changes in an analysis of the impacts of a worldwide carbon tax on the Susquehanna River Basin.

4. Characterizing responses and adaptation possibilities Studies of the economic impacts of climate change differ substantially in the assumptions they make about the ability of economic actors to respond and adapt to a changing climate ŽTol and Fankhauser, 1998; Tol et al., 1998.. Tol et al. Ž1998. distinguish between four approaches to characterizing adaptation in the economic literature: no adaptation; arbitrarily

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imposed types or levels of adaptation Žarbitrary adaptation.; adaptation based on observed responses by economic actors to different climatic conditions in other regions or at previous points in time Žobserved adaptation.; and adaptation based on simulation models of the behavior of economic actors Žmodeled adaptation.. Economic simulation models typically presume that economic actors make choices so as to maximize their own respective objective functions, subject to limits on the physical and financial resources at their disposal and to constraints imposed by the economic, political, and natural environment. The extreme characterization of no adaptation is sometimes referred to as ‘‘business as usual’’ or, more pejoratively, the ‘‘dumb farmer’’ hypothesis. For market goods and services, no adaptation is an implausible assumption. In so far as changes in climate lead to changes in prices of market goods and services, or prices of inputs into production, producers and consumers will have direct and obvious economic incentives to respond to climate change. Simulations in Yohe and Schlesinger Ž1998. suggest that adaptation can significantly reduce the economic costs of sea level rise along the U.S. coastline. Studies of agricultural impacts also indicate that adaptation by farmers can significantly reduce economic costs or increase economic gains Žsee Tol et al., 1998.. On the other hand, the situation could be much different for nonmarket goods and services, since there are no direct price signals to guide producers and consumers. Of the three remaining approaches to characterizing adaptation, modeled adaptation may be most appropriate for assessing responses to climate change. Modeled adaptation can be impeded by computational considerations, which often require the aggregation of goods, services, inputs into production, and economic actors into a relatively small number of categories, and which often necessitate strong simplifying assumptions about the behavior of economic actors. Nonetheless, unlike arbitrary adaptation, which is typically confined to a few alternative adaptation possibilities, modeled adaptation can permit a wide range of types and levels of responses. These responses may be ones that a modeler attempting to construct a list of ‘‘plausible’’ alternatives for an arbitrary adaptation exercise would have never foreseen. Unlike observed adaptation, modeled adap-

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tation can, in principle, examine responses under scenarios regarding future climates, technologies, and economic and political institutions that have no contemporary or historic analogues. In addition, modeled adaptation in a wellcalibrated simulation model will be based, in part, on observed responses to different climates in other regions and at other points in time ŽSchimmelpfennig, 1996., so that modeled adaptation in this sense encompasses observed adaptation. Observed responses depend, in part, on information, technologies, and other resources available to economic actors in the regions and times being examined. In modeled adaptation, care must be exercised to avoid overly optimistic assumptions Že.g., perfect knowledge of current climate or perfect foresight about climate change. and overly pessimistic assumptions Že.g., present-day technologies if there are good reasons to believe that significant technological progress will occur that reduces climate vulnerabilities.. Within the category of modeled adaptation, two modeling frameworks may be distinguished: static and dynamic. By ‘‘static,’’ we mean that production technologies for market and nonmarket goods used within the region, the region’s stock of human capital Ždenoted by K h ., its stock of physical capital Ždenoted by K m ., its stock of natural capital Ždenoted by K n ., and its economic and political institutions are all assumed to be exogenous. Stocks of physical, human, and natural capital may change as a direct consequence of climate change Že.g., losses in physical capital due to hurricanes., but they do not change in response to decisions made by economic actors within or outside of the region. Within a dynamic framework, technologies, capital stocks, andror institutions are endogenous and, as such, can change in response to decisions by economic actors. Human capital refers to the knowledge, information, skills, and abilities possessed by people. Physical capital refers to machines, transportation and communications infrastructure, water resource management structures, buildings, and other tangible investment goods. Physical capital is usually just known as ‘‘capital,’’ but referring to it as physical capital helps distinguish it from other forms of capital. Natural capital encompasses all renewable and nonrenewable natural resources, and all market and nonmarket natural resources. It includes not only

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conventional commodity resources, such as fossil fuels, metals, fisheries, and forests, but other elements of nature that directly or indirectly affect human welfare Že.g., genetic material, the ozone layer, and hydrologic and carbon cycles.. As discussed in Section 5 below, a static framework avoids a number of thorny and unresolved economic modeling issues that a dynamic framework must confront. However, it does so at the cost of imposing significant restrictions on the types of responses and adaptations to climate change that are considered. Essentially, economic actors are limited to reallocating existing human, physical, and natural resources among various uses, within the confines of existing technologies and existing economic and political institutions. For example, changes in capital markets can lead to the movement of physical capital out of one economic sector and into another within the region. However, within a static framework, there is no growth or decline in the region’s total stock of physical capital as a result of decisions by economic actors, no development or adoption of any new technologies that might affect the productivity of capital Žor other inputs into production., and no changes in the institutional environment within which investors, borrowers, and financial intermediaries make decisions. The simulation models to date of economic impacts and responses generally rely on a static framework rather than a dynamic framework. The DICE model of Nordhaus Ž1994. and its successors, such as the RICE model ŽNordhaus and Yang, 1996., are partial exceptions because total stocks of physical capital adjust endogenously over time. Even in these models, however, technologies, stocks of human capital, stocks of natural capital, and economic and political institutions are implicitly held fixed or are at least exogenous.

5. Characterizing responses and adaptation within a dynamic framework Climate change, and indeed, expectations of climate change, may lead to significant changes in capital stocks, technologies, and institutions. These dynamic responses are likely to be the most important adaptations to climate change and its effects on

ecosystems, but also among the most difficult to predict and model. 5.1. Substitution among types of capital At least two overlapping incentives exist for climate-induced changes in capital stocks. First, existing investments in human capital and physical capital have been made in the context of present-day and previous climatic conditions. Climate change that affects the productivity of different types of human and physical capital should lead to adjustments in capital stocks, either to reduce vulnerabilities or exploit opportunities ŽIPCC, 1996b; Toman, 1998.. Secondly, and perhaps more importantly, K h and K m may be substituted for climate in production. Climate can be viewed from an economic perspective as a component of the earth’s stock of natural capital. In this context, climate change is a change in K n . The overall change in K n in a region will reflect the change in regional climate variables, such as temperature and precipitation, and also the climateinduced changes in other forms of natural capital, such as sea level, forests, water resources, and the range of disease vectors and pests. Economic growth from the beginning of civilization, and especially since the industrial revolution, has involved substitution of K h and K m for K n , greatly reducing the degree to which human conditions are affected by and dependent on the natural environment ŽSolow, 1992; Ruttan, 1992.. Most people live and work in structures that protect them from the elements, and many in structures with sophisticated climate control systems. Unlike preindustrial times, even in many developing countries, only a small proportion of the population is directly engaged in producing food and fuel. Substitution of K h and K m for K n Žthrough, e.g., mechanization, specialization of production, irrigation systems, pest management systems, transportation systems to move food and inputs. has tremendously increased the productivity of agricultural systems in developed countries and many developing countries ŽHayami and Ruttan, 1985.. In very broad terms, and barring cataclysmic climate change, the economic impacts of climate in a region will depend, in large part, on how important K n is to the region, how the region’s K n is affected by climate change, and the substitutability

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of K h and K m for K n . From prior research on the substitution of human and physical capital for natural capital, we know that there is some degree of substitutability, but that it is less than perfect ŽPearce and Atkinson, 1995; Toman et al., 1995; Ruttan, 1992.. Beyond this, these are open and very difficult questions.

5.2. Technological responses The historical substitution of K h and K m for K n was made possible by technological and institutional innovations. Technological change has dramatically increased the range and quality of inputs into production and of consumer goods and services. It has also substantially reduced the costs of these inputs, goods, and services, and it has made enormous strides in improving transportation, communication, and the availability and use of information. It is reasonable to presume that technologies will adjust in response to threats and opportunities created by climate change ŽToman, 1998.. Technical change can dramatically broaden the options available to economic actors for climate change adaptation and mitigation ŽIPCC, 1996b; Chakravorty et al., 1997.. Unfortunately, economists’ understanding of the forces driving the development and adoption of new technologies remains limited. As Ruttan Ž1997. describes, there are three different approaches to technical change in the economic literature that have yet to be reconciled with each other. The first, induced innovation, views technologies as developed and adopted in response to changes in the economic environment; in particular, technologies are developed and adopted to conserve on increasingly expensive inputs into production. The second approach, evolutionary theory, views technologies as developed by producers through a process of search, experimentation, and imitation. Less successful technologies and producers are weeded out by competition in the marketplace, while more successful ones are rewarded. The third approach, path dependence, argues that past technological choices can profoundly influence current directions in research and development, even to the point where producers may be ‘‘locked in’’ to technologies that are clearly no longer optimal

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in light of current economic conditions. The need for a more general theory combining all three of these approaches seems clear ŽRuttan, 1997.. At the regional level, available technologies are largely exogenous because most technologies are developed for national or global markets, and most regions are too small economically to significantly affect national and global rates of technical change. This does not mean that technologies will fail to respond but rather that responses are likely to depend on what happens at the national and global level as opposed to the level of a particular region. However, the fact that a technology is available does not mean that it must or will be used. Individual economic actors within each region will make these choices. Given assumptions about available technologies, there is a large economic literature on technological adoption and diffusion that can be brought to bear on the analysis of technology choice within a particular region ŽKarshenas and Stoneman, 1995; Metcalfe, 1997..

5.3. Institutional responses Institutions can be defined as the rules that guide behavior by individuals within economic units such as households, companies, organizations, and governments, as well as the rules that guide behavior between one economic unit and another Že.g., rules governing contracts.. Institutional change in developed countries — in particular, evolving property rights, rules governing the operation of markets, the development of markets for new types of goods and services, and collective institutions for the provision of public goods such as environmental protection — has fostered research and development, education, investment in infrastructure, interregional trade, economic growth and specialization, and mechanisms for reducing the social costs of risk ŽNorth, 1990; Hayami and Ruttan, 1985.. In the private sector, dynamic adjustments in institutional arrangements will occur more or less autonomously as households and businesses react to experiences with climate change and evolving expectations. For example, to reduce the costs of climate variability in climate-sensitive sectors, new products

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for risk management may be developed. These could include improved private forecasting services and products Že.g., insurance, futures, and options. with which to trade climate-related risks. Changes in the availability, rates, deductibles, liability limits, and other terms of existing insurance products are also likely responses to changes in climate variability ŽBerz, 1998.. However, the development of insurance products for very long-term climate-related risks is unlikely because of the time horizons and significant uncertainty involved ŽTol, 1998.. Characterizing and modeling institutional responses in the public sector are much more formidable tasks than in the private sector. Models of conventional economic markets are well developed and have been successfully used to explain behavior in a wide variety of markets in many countries. Our understanding of public institutions and of other nonmarket mechanisms of resource allocation is crude by comparison. As in the case of technical change, there are a number of competing theories of institutional behavior in the public sector that have yet to be reconciled into a single, unified theory. Some of the more prominent theories postulate that public institutions are largely benevolent and supply important public goods; that public institutions seek to maximize their own budgets or their own control over society’s resources; that each public institution tends to be ‘‘captured’’ by a single or small number political pressure groups; and that a variety of political pressure groups compete for control of the agendas and activities of public institutions, which sometimes leads these institutions to balance the interests of diverse groups and at other times leads to capture by narrow special interests ŽMoe, 1997; Stigler, 1988.. Bearing in mind that knowledge of public institution behavior is still quite limited, it is possible to speculate on ways that public agencies may respond to changes in perceived risks and opportunities caused by climate change. In the short run, responses will be limited by budgetary and legal considerations. In the long run, budgets and mandates may adjust to climate-induced changes in demand for public services. For example, constituents expecting increased risks from infectious disease may demand public health measures to better protect water and food supplies, and control disease vectors. Constituents expecting

increased flooding may demand structural and nonstructural measures to reduce risks. Constituents facing increased water scarcity may demand investments in water development or changes in water law and management governing the allocation of water. The degree to which public institutions evolve in response to changes in constituent demand depends on many factors, including the type of government and the susceptibility of public agencies to demands by political pressure groups whose interests conflict with those of society at large ŽNorth, 1990; Olson, 1982.. Public institutions in developed, democratic countries have proven capable of significant innovation, but the same cannot be said for public institutions in many developing countries. Even in developed countries, imperfections in political and market processes may lead to maladaptation on the part of the private sector instead of adaptation. In agriculture, e.g., government policies such as product price supports, input subsidies, agricultural trade barriers, and payments for crop failures can hinder adaptation to climate change if they encourage the production of climate-sensitive crops, the use of cropping systems ill-suited to the changed climate, or limit incentives for relocation or innovation ŽLewandrowski and Brazee, 1993.. Government disaster assistance policies that encourage people to live in climate-sensitive areas such as flood plains or coastal regions subject to hurricanes, or to rebuild in such areas following natural disasters, can also hinder adaptation. Identification of likely problems in private and collective responses can facilitate policy development to minimize such problems. At a regional level, national and international institutions are largely exogenous because most regions are too small Žin economic and in other terms. to influence the structure or overall policies of institutions at a national or international level. However, institutions at the local and regional level have significant responsibilities in many countries, and their responses to climate change will have a critical effect on economic and ecological impacts. For example, local governments in the U.S. exert substantial influence on land use through zoning, tax, and other policies, while local and state governments have significant control over water allocation, public health programs, and investments in infrastructure within their jurisdictions.

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6. Baseline economic scenarios By definition, economic impact analysis involves comparing ‘‘with’’ and ‘‘without’’ states of the economy. In climate impact research, climate scenarios are typically generating using a range of assumptions about growth in emissions of greenhouse gases and other driving forces behind climate change. Economic impacts are then analyzed based on the climate scenarios. This approach ignores dynamic feedbacks between economic activity and climate, where the economy affects climate and vice versa. At the global or large-scale regional level, climate and the economy are necessarily inseparable and dynamic. For a region defined at the scale of a river basin or other similar scale, however, economic activity within the region is likely to have much smaller effects on climate, and thus, separable climate and economic scenarios are somewhat more plausible. Because climate change is a long-term phenomenon, generating baseline economic scenarios requires consideration of potential economic conditions far into the future. Global, national, and regional economies have changed radically over the last century, and there is no reason to expect that the rapid pace of economic change will slow down. Regional economies will undoubtedly be substantially different in the future than they are today in terms of their sensitivity to climate change and their potential for response and adaptation. Inserting future climate scenarios into a model of a present-day economy could yield very misleading conclusions about economic impacts and responses. Nevertheless, putting future climate scenarios into a model of a present-day economy can have some value as a ‘‘bounding’’ exercise on potential future climate impacts. Specifically, if the impacts of future climate change on a present-day economy are small, and if the economy is expected to become less vulnerable to climate change in the future, then, barring catastrophic change, it can be concluded that future economic impacts are also likely to be small. Conversely, if the impacts of future climate change on a present-day economy are large, and if the economy is expected to become more vulnerable to climate change in the future, then it can be concluded that future economic impacts are also likely to be large. In the other two cases — present-day

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impacts are large but the economy is expected to become less vulnerable or present-day impacts are small but the economy is expected to become more vulnerable — no bounds can be set by present-day impacts. In these two cases, we come back to the necessity of thinking about future baseline economic conditions. In economics, forecasting accuracy diminishes with forecast length, and it would be sheer folly to derive only point estimates of economic activity even just 25 years into the future. An alternative is to provide a range of baseline scenarios, each embodying a different set of assumptions about underlying determinants of the types, levels, characteristics, and geographic locations of economic activities in the absence of climate change. The key input assumptions associated with baseline economic scenarios for a region include economic conditions outside the region Žin other regions and countries. and the alternative technologies and institutional arrangements that are available to economic actors within the region. Clearly, the uncertainty associated with these factors can be overwhelming. One common approach in the literature to dealing with uncertainty is to specify a small number of alternative scenarios. These scenarios are often constructed by placing one extreme set of assumptions together as a ‘‘pessimistic’’ scenario and another as an ‘‘optimistic’’ scenario, with various demarcations in between. While this approach has the advantage of simplicity, it limits the scenarios under consideration to those lying on a ‘‘pessimistic–optimistic’’ continuum. It may be important to consider scenarios that are ‘‘pessimistic’’ in some respects but ‘‘optimistic’’ in others. For example, a scenario may be optimistic for some industry but pessimistic for environmental externalities from production in that industry, or vice versa. A major effort to evaluate alternative economic scenarios was undertaken by the Stanford Energy Modeling Forum in relation to the IPCC Second and Third Assessments. This involved meetings of modelers to agree on a common set of assumptions in the hope that this would narrow the range of outcomes. Such attempts have proven moderately successful for baselines, but have been less successful in narrowing the range of projections associated with public policies to limit greenhouse gas emissions Žsee, e.g.,

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Gaskins and Weyant, 1993; Stanford Energy Modeling Forum, 1997..

7. Conclusions The objective of this paper was to make a start at a framework for characterizing the regional economic impacts of, and responses to, climate change. The principal stumbling block to the development of such a framework is an inadequate understanding of dynamic responses in capital stocks, technologies, and institutions. These responses are likely to be the most important adaptations to climate change and its effects on ecosystems, but are also the least understood economic processes at the present time. Three important issues not covered here are the tremendous uncertainty surrounding the potential magnitudes of climate change impacts, whether or not these impacts may be irreversible, and how to properly and yet tractably model these uncertainties. Discussions of these issues and possible modeling strategies can be found in Kolstad Ž1996., Lempert et al. Ž1996., Schimmelpfennig Ž1996., Ulph and Ulph Ž1997., and Woodward and Bishop Ž1997.. Within the sphere of modeled adaptation, another important issue is the type of simulation model to be used. A number of alternatives exist, including econometric, input–output ŽI–O., and CGE models. A review of these alternatives and a discussion of their relative merits can be found in Rose Ž1996..

Acknowledgements This research is sponsored by U.S. National Science Foundation grant no. SBR-9521952, Methods of Integrated Regional Assessment of Global Climate Change; by U.S. Environmental Protection Agency Cooperative Agreement no. CR 824369-01, GCC Impacts on Water Resources and Ecosystems; and by U.S. Environmental Protection Agency Cooperative Agreement no. CR 826554-01-0, Mid-Atlantic Regional Assessment. The authors are very grateful to Rajnish Kamat for his research assistance.

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