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Home / Publications / Research / Economic Brief / 2021

Economic Brief
January 2021, No. 21-02

Delving into Climate Change Economics
Article by: Molly Harnish

By quantifying climate change's e ects and assessing potential mitigation and
adaptation techniques, economists contribute valuable perspectives to political,
ecological and social conversations about the planet's future. This Economic Brief
summarizes presentations from the Richmond Fed's recent conference on the
economics of climate change.
Climate change presents a myriad of economic questions: What innovations might be
coming in the energy sector? To what extent will natural disasters and rising sea levels
a ect local and regional economies? And what are the costs and bene ts of carbon taxes
and other mitigation and adaptation policies? In November, the Federal Reserve Bank of
Richmond hosted a virtual conference on the economics of climate change to discuss these
and other topics. Presenters addressed the implications of climate change for
infrastructure planning and local economies. They also reviewed ways to measure the
social discount rate and the social cost of carbon dioxide emissions, two components of the
present and future costs of climate change. Finally, presenters examined adaptation and
mitigation policies, including carbon taxes and nancial adaptation to climate default risk.

Climate Defaults and Financial Adaptation
Increasing the probability of sovereign debt crises is a signi cant potential e ect of natural
disasters, especially in less nancially developed countries. Unfortunately, many of those
countries are also the most vulnerable to climate change.1 Toan Phan and Felipe
Schwartzman of the Richmond Fed presented a theoretical and quantitative framework that
analyzes a country's "climate default" risk — which captures the relationship between its
risk of facing climate-related natural disasters and its risk of facing sovereign default — and
potential tools for nancial adaptation.

In their model — calibrated with data from strong cyclones — a natural disaster delivers a
shock to the nancial system that causes investment to decrease and default risk to
increase. This result further decreases investment, creating a vicious cycle. Also, the default
risk increases with the frequency of, and damage caused by, the disasters. Thus, to the
extent that climate change intensi es and increases the frequency of natural disasters, it
raises the probability of sovereign default in developing economies with high climate
change vulnerability.
In light of this prognosis, Phan and Schwartzman examined two instruments of nancial
adaptation: CAT bonds, also known as act-of-God or catastrophe bonds, and disaster
insurance. CAT bonds pay bondholders unless a catastrophe occurs, in which case the
bonds' issuers are no longer obligated to repay the principal or to pay interest; disaster
insurance allows countries to account for disaster risk, even if they default on their debt.
Each instrument individually produces a relatively small welfare gain, but the welfare gain
from the combination of CAT bonds and disaster insurance is almost 30 percent of the loss
that results from an increase in natural disasters. While disaster insurance eases the
recovery process, CAT bonds reduce default risk, allowing vulnerable economies to borrow
more in the aftermath of a disaster. Phan and Schwartzman's research produces not only a
method for analyzing climate default risk and the e ects of nancial adaptation measures,
but also a framework for combining the two analyses.

In Harm's Way? Infrastructure Investments and the Persistence of Coastal Cities
Coastal countries are particularly vulnerable to rising sea levels, yet infrastructure
investment in coastal regions shows no sign of abating. In her presentation, Clare Balboni
of the Massachusetts Institute of Technology focused on Vietnam — one of the ve
countries most likely to be a ected by climate change — and examined the optimal
allocation of infrastructure investments in the country given the prospect of rising sea
levels.
Using geographic, economic, transportation and demographic data spanning 2000–10 in
more than 500 districts of Vietnam, Balboni developed a dynamic, multiregion spatial
equilibrium model to estimate the welfare e ects of coastal infrastructure investments
under various scenarios of rising sea levels. Her model accounts for roadbuilding's
generally positive e ects on growth; locational di erences in amenities, productivity and
trade links; imperfect mobility of goods and workers; and roads' durability. Road
investments and rising sea levels have opposite welfare e ects: Roadbuilding increases
market access, reduces prices and increases wages, while rising sea levels reduce land
supply.
Balboni compared the welfare e ects of status quo infrastructure investments, which tend
to be concentrated in coastal regions, to other potential infrastructure allocations and rising
sea level scenarios. She examined four counterfactual road networks: one connecting

major administrative centers, another maximizing market potential regardless of the
location of coastal zones, a third maximizing market potential outside the ve-meter coastal
zone (coastal areas with elevations within ve meters of sea level) and a fourth maximizing
market potential outside the one-meter coastal zone. She also included two sea level
scenarios: a one-meter rise over the next century, consistent with the Intergovernmental
Panel on Climate Change's Fifth Assessment Report, and no sea level rise.2 She found that
the road network that avoided the one-meter coastal zone and maximized market potential
(the network that addressed rising sea levels and connected densely populated regions)
had the highest aggregate welfare gain. Even in the absence of rising sea levels, however,
she concluded that there are gains to be made from reallocating infrastructure investments
away from the coast. Adding rising sea levels to the analysis only strengthens this
conclusion.

The Local Economic Impact of Natural Disasters
Turning to impacts on the United States, Brigitte Roth Tran of the Board of Governors of the
Federal Reserve System presented work with Daniel J. Wilson of the Federal Reserve Bank
of San Francisco on the local economic impact of natural disasters. The prevalence and cost
of natural disasters have increased in recent decades, and climate change likely will
perpetuate this trend, but the economic impact of disasters is unclear. Some evidence
indicates that no economic recovery occurs after a natural disaster or that regions simply
recover to trend, while other evidence points to a "creative destruction" e ect — a
signi cantly higher level of per-capita income following the disaster. Between these two
scenarios is a "build-back-better" pathway that exceeds the preexisting economic trend but
does not rise to the level of creative destruction. Tran and Wilson's research supports this
build-back-better hypothesis and highlights evidence of di erences in outcomes between
counties and disaster types.
Tran and Wilson's panel dataset spans 1980–2017 and includes county-level data on
damages, per-capita income, employment, average weekly wages, house prices,
government aid and U.S. population. Using a panel version of the local projections method,
which regresses future outcomes on present variables,3 to estimate natural disasters'
e ects on economic outcomes, they found that personal income per capita tended to
increase after natural disasters, as predicted by the build-back-better hypothesis.4 This
increase was driven by an increase in employment in the short run and by higher average
wages in the long run. Tran also explained that it could be a result of the rebuilding process:
If local capital stock improved during post-disaster rebuilding, productivity and per-capita
income would increase.
However, not all disasters and counties are the same. Tran and Wilson accounted for this
heterogeneity by separating outcomes based on disaster severity and type and by each
county's predisaster income and historical experience with disasters. They also estimated

spatial spillover e ects to determine if economic recovery in one county came at the
expense of neighboring counties. In fact, they did nd di erences when disasters and
counties were separated by these criteria. More severe disasters had larger positive e ects
on personal income but also trended toward di erent equilibria due to declines in
population and home prices in the long run. Moreover, the build-back-better outcome did
not follow for all disaster types or county pro les: Income per capita did not increase after
oods, severe storms and extreme winter weather, nor did it increase in counties that were
inexperienced with disasters. This heterogeneity in economic outcomes emphasizes the
need to use caution when extrapolating results.

The Rising Cost of Climate Change: Evidence from the Bond Market
Researchers also are attempting to measure the cost of climate change. Calculating the
social cost of CO2 emissions requires a comparison of present bene ts and future costs.
The social discount rate (SDR), a measurement of the present value of future damages,
captures this comparison. SDRs can either be prescriptive (based on normative judgments
of what is morally acceptable)5 or descriptive (based on real returns from nancial
markets).6 Since descriptive SDRs tend to be higher than prescriptive ones, estimates of the
social costs of carbon emissions that use descriptive SDRs tend to be lower than those that
use prescriptive SDRs. Glenn D. Rudebusch of the Federal Reserve Bank of San Francisco,
presenting a joint paper with Michael D. Bauer of the Universität Hamburg, assessed
various SDRs using evidence from the bond market. Their work demonstrates that taking
the recent secular decline in the steady-state interest rate into account lowers descriptive
SDRs closer to prescriptive levels.
The steady-state interest rate has been declining for decades as a result of changes in
population, productivity and savings patterns, among other factors. Bauer and Rudebusch
showed that this steady-state interest rate anchors the term structure, also known as the
yield curve, of discount rates. They focused on risk-free discount rates, which are used for
payo s that are certain or certainty-equivalent, in their analysis. Using a time-series model
and data on in ation-adjusted Treasury bond yields, they estimated that the steady-state
interest rate fell by between one and two percentage points from 1990 to 2019 for all bond
maturities. Because the term structure of SDRs is anchored to the steady-state interest rate,
the downward shift in the interest rate implies that the term structure of risk-free SDRs has
shifted downward.
This nding has dramatic implications for the social cost of carbon, boosting it by at least 96
percent. Although Bauer and Rudebusch use a 1994 integrated assessment model (IAM) to
calculate the social cost of carbon, their ndings are robust to other, more recent damage
functions. Their results highlight both the importance of macro nance for climate policy
and the possibility of aligning descriptive and prescriptive SDRs.

Estimating a Social Cost of Carbon for Global Energy Consumption
Another approach to measuring the cost of climate change focuses on the negative
externalities of carbon dioxide emissions. In other words, CO2 emissions are costly to
"external" groups, people who don't bene t from the economic activity that emits the
carbon. According to economist Arthur Pigou, internalizing such externalities requires
imposing a tax that lifts the private cost of carbon to match the social cost. However,
imposing this tax at the correct level requires policymakers to determine the social cost of
carbon. Solomon Hsiang of the University of California at Berkeley and his colleagues at the
Climate Impact Lab have taken a step in that direction. Using global data from the
International Energy Agency spanning the years 1971–2012 for 146 countries, they have
quanti ed part of the social cost of CO2 emissions in what Hsiang presented as "the rst
estimate of the global impact of climate change on total end-use energy consumption."
Since energy consumption varies with income as well as with temperature, accounting for
economic development is one of the model's key features. In fact, at the national level,
income matters more than temperature for electricity consumption. Building on this
relationship and on earlier versions of IAMs, Hsiang and his fellow researchers analyzed
25,000 regions to project the energy impacts of climate change. As one might expect, they
found that when temperatures increased, warmer areas used more energy. However, the
increase in total electricity consumption varied across regions and energy sources. For
example, they projected that total electricity consumption would increase by 2 percent in
the United States but 113 percent in India as global temperatures increased. They also
predicted that global consumption would decrease for fuels used for purposes other than
generating electricity or providing transportation. Again, the results were unequally
distributed across countries: They predicted that consumption would fall by 7 percent in
the United States and 42 percent in India.
Once they modeled changes in energy consumption as a result of warming, the researchers
were able to estimate an empirical damage function for the energy sector that accounted
for uncertainty and price growth. They concluded that the partial energy consumption-only
social cost of carbon (SCC) — that is, the social cost for the energy sector, not for society as
a whole — is negative $1 per ton of carbon dioxide. The negative sign indicates a social
bene t of carbon (in terms of energy consumption only) rather than a social cost: In other
words, temperature increases result in one dollar of energy savings per ton of carbon
dioxide emissions. The nonlinear relationship between income and energy consumption
accounts for this outcome: When global temperatures increase, emerging (and warming)
countries consume more electricity, but wealthy, cooler countries save even more on other
uses of fuel, counteracting the increase in electricity consumption.

Climate Change, Directed Innovation and Energy Transition: The Long-Run
Consequences of the Shale Gas Revolution

Since the late 2000s, U.S. natural gas production has skyrocketed, a phenomenon known as
the "shale revolution." Since natural gas burns cleaner than coal, the increase in natural gas
production has coincided with a decline in carbon dioxide emissions from U.S. electricity
generation. However, it also has coincided with a decrease in technological innovation in
clean energy production. Lint Barrage of the University of California at Santa Barbara
presented on work with Daron Acemoglu of the Massachusetts Institute of Technology,
Philippe Aghion of the Collège de France and London School of Economics and David
Hémous of the University of Zurich to analyze this decline in clean energy innovation and
quantify the shale boom's long-term impact on innovation and the U.S. economy.
These economists developed a model in which production of coal, natural gas and green
energy depends on energy inputs, such as power plants and resource extraction. After
calibrating the model using parameters from the literature and data on the costs and
outputs of U.S. electricity generators, they found that carbon dioxide emissions decreased
after the shale boom in the short run. In the long run, however, the model predicts an
increase in emissions as a result of the boom's negative e ect on clean energy innovation.
This is because more technologically advanced sectors tend to attract more scientists,
increasing those sectors' pro ts and advancing their technology still further. Ultimately, this
tendency creates a positive feedback cycle in which better technology drives more
innovation. Thus, when a one-time increase in natural gas extraction technology — such as
the shale revolution — boosts technological advancement in natural gas extraction relative
to clean energy, the resulting boom reduces long-run innovation in clean energy
technologies.
The degree to which the boom reduces innovation depends on the initial level of clean
energy generation technology and the growth rate of the productivity of fossil fuel
extraction. A higher initial level of clean energy technology and a lack of growth in fossil fuel
extraction technology make an eventual transition to clean energy more likely. Even in this
best-case scenario, however, the shale boom still delays the transition. In light of this
nding, Barrage and her fellow researchers called for a two-pronged policy approach: a
carbon tax to internalize the social cost of carbon dioxide emissions and a subsidy to
encourage innovation in clean energy.

The Macroeconomic Impact of Europe's Carbon Taxes
Many other economists also have advocated carbon taxes, but economic theory suggests
that carbon taxes will result in a parallel shift downward in GDP with no long-run e ect on
employment. To test that theory, presenter James H. Stock of Harvard University and
Gilbert E. Metcalf of Tufts University examined the macroeconomic impact of European
carbon taxes. Their dataset consisted of GDP, population, employment, fuel prices, fuel

taxes and emissions from 1985–2018 for the 31 European nations in the Emissions Trading
System, in addition to carbon prices for the 15 nations within that group that had adopted
carbon taxes at varying levels and in di erent years.
Using two di erent econometric approaches — local projections and panel vector
autoregression — Stock and Metcalf estimated the cumulative dynamic causal e ect of a
change in the carbon tax on GDP, employment and emissions. They found that a $40
increase in the carbon tax had neither a long-run nor a short-run e ect on GDP, a nding
that was robust in both approaches. They also tested whether this nding was a result of
revenue recycling (returning revenue from carbon taxes to taxpayers). However, even when
they separated revenue-recycling and nonrevenue-recycling countries, they found no
statistically signi cant e ect for this practice. While carbon taxes did not have statistically
signi cant e ects on GDP or employment in the short or long run, they did reduce
emissions by 4 percent to 6 percent in the sectors covered by the tax.

Suboptimal Climate Policy
Formulating optimal climate policy is di cult, but the tools of economics not only allow
economists to estimate social discount rates and the social cost of carbon, but also provide
opportunities to compare markets under di erent taxation and regulatory frameworks. In
this vein of research, Per Krusell of Stockholm University and his colleagues — John Hassler
of Stockholm University, Conny Olovsson of Sveriges Riksbank and Michael Reiter of the
Institute for Advanced Studies in Vienna and New York University-Abu Dhabi — compared
the costs and bene ts of suboptimal climate policy. Instead of trying to determine the right
policy, they focused on the consequences of obviously imperfect policies, namely setting
carbon taxes much too high or much too low, imposing regional rather than global carbon
taxes and doling out green energy subsidies instead of levying carbon taxes. The
researchers analyzed these policies using an IAM that di erentiates between oil-producing
and oil-consuming regions. They calibrated the model with data on energy use and
production, total factor productivity and initial capital stock in those regions.
First, they examined the suboptimal policy of enacting carbon taxes that are too high or too
low. The results showed that the cost of too-low taxes surpassed the cost of too-high taxes
in terms of consumption loss. Next, they compared global and regional taxes, revealing that
regional taxation that exempts developing areas results in overall welfare loss. Finally, they
showed that subsidies of green energy initiatives are less e ective than taxes at combating
climate change. Analyzing suboptimal policies in this way sheds light on both the potential
contributions of IAMs and the ways that economic tools can inform policy analysis.

Conclusion

As climate change threatens to change individual and national ways of life, it is important
for policymakers and researchers to understand its costs and consequences. By quantifying
climate change's e ects and assessing potential mitigation and adaptation techniques,
economists contribute valuable perspectives to the larger political, ecological and social
conversations about the planet's future.
Molly Harnish is a senior economics major at George Mason University and a former intern
in the Research Department at the Federal Reserve Bank of Richmond.

1

See Kartik Athreya, "The Risks and Inequities of Climate Change," Opening remarks to the

Federal Reserve Bank of Richmond Conference on Climate Change Economics, Nov. 19, 2020.
2

Intergovernmental Panel on Climate Change, "Fifth Assessment Report," 2013.

3

Òscar Jordà, "Estimation and Inference of Impulse Responses by Local Projections," American

Economic Review, March 2005, vol. 95, no. 1, pp. 161–182.
4

The researchers note that this nding is not a result of population loss. In other words, it is not

due to a shrinking denominator in the per-capita income calculation.
5

For an example of the logic behind prescriptive SDRs, see Nicholas Stern, The Economics of

Climate Change: The Stern Review, Cambridge, UK: Cambridge University Press, 2007.
6

William Nordhaus, who won the Nobel Memorial Prize in Economic Sciences in 2018 "for
integrating climate change into long-run macroeconomic analysis," favors this approach.

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and the Federal Reserve Bank of Richmond and include the italicized statement below.
Views expressed in this article are those of the author and not necessarily those of the Federal
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