The Stern Report has generated world wide headlines. A leading economist argues that climate change will be quite costly perhaps costing us 5% of world GNP each year in the future. In this interesting report on the Stern Review, Bill Nordhaus argues that many of the Stern Report's findings are driven by its implicit assumption of a 0% interest rate in calculating the present discounted value of flows of benefits and costs associated with climate change.

While I give you the Nordhaus piece, I apologize for the strange way the footnotes get embedded in the text.

This issue of discounting returns to the "old" Robert Solow question on sustainability concerning whether physical capital and human capital substitutes for natural capital. If innovation (new ideas) and physical capital (better New Orleans Levees) can protect natural capital then it is important from a sustainability perspective to think about the next best alternative (i.e opportunity cost) for resources we spend on fighting climate change today.





http://www.econ.yale.edu/~nordhaus/homepage/SternReviewD2.pdf

The Stern Review on the Economics of Climate Change1

William Nordhaus
November 17, 2006

Opposite ends of the globe

It appears that no two global warming policies on earth are farther
apart than the White House and 10 Downing Street. In 2001, President G.W.
Bush announced his opposition to binding constraints on greenhouse gas
(GHG) emissions. In his letter of opposition, he stated, “I oppose the Kyoto
Protocol because it exempts 80 percent of the world, including major
population centers such as China and India, from compliance, and would
cause serious harm to the U.S. economy.” This policy, much like the war in
Iraq, was undertaken with no discernible economic analysis.2
In stark contrast, the British government in November 2006 presented a
comprehensive new study, the Stern Review on the Economics of Climate Change
1 The author is grateful for helpful comments by Scott Barrett, William Brainard,
Partha Dasgupta, Robert Stavins, Nicholas Stern, and John Weyant.
2
Text of a Letter from the President to Senators Hagel, Helms, Craig, and Roberts, March
13, 2001, http://www.whitehouse.gov/news/releases/2001/03/20010314.html
(downloaded November 13, 2006). There is no record of a fact sheet or other
economic analysis accompanying the letter. The Bush Administration’s economic
analysis was contained in the 2002 Economic Report of the President and the Council of
Economic Advisers, published almost a year after President Bush’s letter to the
Senators. The Economic Report’s analysis suggests that the Kyoto Protocol is costly,
but its analysis does not show that binding action is economically unwarranted.
2
(hereafter the Review).3 Prime Minister Tony Blair painted a dark picture for
the globe at its unveiling, “It is not in doubt that if the science is right, the
consequences for our planet are literally disastrous…. [W]ithout radical
international measures to reduce carbon emissions within the next 10 to 15
years, there is compelling evidence to suggest we might lose the chance to
control temperature rises.”4
The summary in the Review was equally stark: “[T]he Review estimates
that if we don’t act, the overall costs and risks of climate change will be
equivalent to losing at least 5% of global GDP each year, now and forever. If a
wider range of risks and impacts is taken into account, the estimates of
damage could rise to 20% of GDP or more.… Our actions now and over the
coming decades could create risks … on a scale similar to those associated
with the great wars and the economic depression of the first half of the 20th
century.”5
These results are dramatically different from earlier economic models
that use the same basic data and analytical structure. One of the major
findings in the economics of climate change has been that efficient or
“optimal” economic policies to slow climate change involve modest rates of
emissions reductions in the near term, followed by sharp reductions in the
3 All citations in this note were from the online version at http://www.hmtreasury.
gov.uk/independent_reviews/stern_review_economics_climate_change/
sternreview_index.cfm (downloaded various dates, November 2006).
4 PM's comments at launch of Stern Review, http://www.number-
10.gov.uk/output/Page10300.asp (downloaded November 13, 2006).
5 Review, Summary of Conclusions.
3
medium and long term. We might call this the climate-policy ramp, in which
policies to slow global warming increasingly tighten or ramp up over time.6
While seemingly counterintuitive, the findings about the climate-policy
ramp have survived the tests of multiple alternative modeling strategies,
different climate goals, alternative specifications of the scientific modules, and
more than a decade of revisions in integrated assessment models. The logic of
the climate-policy ramp is straightforward. In a world where capital is
productive, the highest-return investments are primarily in tangible,
technological, and human capital, including research and development in
low-carbon-emissions technologies. As societies become richer in the coming
decades, it becomes efficient to shift investments toward policies that intensify
the pace of emissions reductions and otherwise slow GHG emissions. The
exact mix and timing of emissions reductions depends upon details of costs,
damages, and the extent to which climate change and damages are
irreversible.
While scientists have sounded many somber warnings about the longterm
peril of unchecked climate change,7 the Review attempts to justify strong
6 This strategy was one of the major conclusions in a review of integrated-assessment
models: “Perhaps the most surprising result is the consensus that given calibrated
interest rates and low future economic growth, modest controls are generally
optimal.” David L. Kelly and Charles D. Kolstad, Integrated Assessment Models For
Climate Change Control,” Henk Folmer and Tom Tietenberg (eds.), International
Yearbook of Environmental and Resource Economics 1999/2000: A Survey of Current Issues,
Cheltenham, UK, Edward Elgar, 1999.
7
For a recent warning, see James Hansen, Makiko Sato, Reto Ruedy, Ken Lo, David
W. Lea, and Martin Medina-Elizade Global temperature change, Proceedings of the
National Academy of Sciences (US), 103, 2006, pp. 14288-14293.
4
current action in a cost-benefit economic framework.8 Because it has
conclusions that are so different from most economic studies, the present note
examines the reasons for this major difference. Is this radical revision of
global-warming economics warranted?
Overview of the Review
I will not summarize the basic findings of the Review – a clear summary
is found on its website. Instead, I begin with five summary reactions. First, the
Review is an impressive document, buttressed by more than a dozen
background studies. There is little new science or economics here, but it
provides many new syntheses of the extensive and rapidly growing literature.
While not as balanced and ponderously reviewed as the reports of the
Intergovernmental Panel on Climate Change (IPCC), it is much more current
than the latest IPCC report, published in 2001.9 For those seriously interested
in global warming, it is worth a few days’ study.
Second, while I question some of the Review’s modeling and economic
assumptions, its results are fundamentally correct in sign if not in size. The
approach taken in the Review – selecting climate-change policies with an eye
to balancing economic needs with environmental dangers – is solidly
grounded in mainstream economic analysis. By linking climate-change
policies to both economic and environmental objectives, the Review has
8 The early precursor of this Review is the study by William R. Cline, The Economics
of Global Warming, Washington, Institute for International Economics, 1992.
9 Contribution of Working Group I to the Third Assessment Report of the
Intergovernmental Panel on Climate Change, Climate Change 2001: The Scientific Basis,
J. T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P. J. van der Linden, and D. Xiaosu,
eds., Cambridge, Cambridge University Press, 2001.
5
corrected one of the fundamental flaws of the Kyoto Protocol, which had no
such linkage. By contrast, the parallel analysis of the Bush Administration,
cited in footnote 2 above, provided no support for the Bush Administration’s
rejection of binding emissions constraints on GHG emissions.
Third, the Review should be viewed as a political document. Its chief
author is Sir Nicholas Stern, who has had a distinguished career in academic
and government positions. Until 1993, he was a public-finance economist in
British universities specializing in taxation and economic development; today,
he is Head of the Government Economics Service and Adviser to the
Government. The disciplinary background of a public-finance economist is the
leitmotiv running through the chapters. However, it is not an academic study.
Like most government reports, the Review was published without an appraisal
of methods and assumptions by independent outside experts. But even the
analysis of HM Government needs peer review.
The fourth comment concerns the Review’s emphasis on the need for
increasing the price of carbon emissions. The Review summarizes its
discussion here as follows, “Creating a transparent and comparable carbon
price signal around the world is an urgent challenge for international
collective action.” In plain English, the Review argues that it is critical to have a
harmonized carbon tax or similar regulatory device both to provide incentives
to individual firms and households and to stimulate research and
development in low-carbon technologies. Carbon prices must be raised to
transmit the social costs of GHG emissions to the everyday decisions of
billions of firms and people. This simple yet inconvenient economic insight is
virtually absent from most political discussions of climate change policy
(including the marathon slide show by Al Gore in An Inconvenient Truth).
6
But these points are not the nub of the matter. Rather, and this is the
final comment, the Review’s radical revision arises because of an extreme
assumption about discounting. Discounting is a factor in climate-change
policy – indeed in all investment decisions – which involves the relative
weight of future and present payoffs. At first blush, this area would appear a
technicality that should properly be left to abstruse treatises and graduate
courses in economics. Unfortunately, it cannot be buried in a footnote, for
discounting is the central to the radical revision. The Review proposes using a
social discount rate that is essentially zero. Combined with other assumptions,
this magnifies enormously impacts in the distant future and rationalizes deep
cuts in emissions, and indeed in all consumption, today. If we were to
substitute more conventional discount rates used in other global-warming
analyses, by governments, by consumers, or by businesses, the Review’s
dramatic results would disappear, and we would come back to the climatepolicy
ramp described above. The balance of this discussion focuses on this
central issue.
The social discount rate: concepts and assumptions
Discounting involves a concept called the pure rate of social time
preference – I will call this “the social discount rate” for short. The social
discount rate is a parameter that measures the importance of the welfare of
future generations relative to the present. It is calculated in percent per year,
like an interest rate, but refers to the discount in future “utility” or welfare,
not future goods or dollars. A zero social discount rate means that future
generations into the indefinite future are treated equally with present
generations; a positive social discount rate means that the welfares of future
7
generations are reduced or “discounted” compared to nearer generations.
Philosophers and economists have conducted vigorous debates about how to
apply social discount rates in areas as diverse as economic growth, climate
change, energy policy, nuclear waste, major infrastructure programs such as
levees, and reparations for slavery.10
Discussions about discount rates need to respect the distinction
between the social discount rate and the discount rate on goods. The former
refers to the relative weights on different people or generations and is the
major source of concern in this note. The latter refers to discounts on bundles
of goods and is measured as a “real interest rate.” I discuss the connection
between these two concepts below.
The sections that follow examine the philosophical arguments about
intergenerational equity, how discounting affects the measurement of
damages, the role of discounting in economic modeling of climate change,
saving behavior, and behavior under uncertainty.
10 Many of the issues involved is discounting, particularly relating to climate change,
are discussed in the different studies in Paul Portney and John Weyant, Discounting
and Intergenerational Equity, Resources for the Future, Washington, D.C., 1999. Note
that the pure rate of social time preference differs from the real interest rate or the
discount rate on goods and services, which is in principle observed in the market
place. A useful summary is contained in K. J. Arrow, W. Cline, K.G. Maler, M.
Munasinghe, R. Squitieri, and J. Stiglitz, “Intertemporal equity, discounting and
economic efficiency,” in Climate Change 1995—Economic and Social Dimensions of
Climate Change, edited by J. Bruce, H. Lee, and E. Haites, 1996, Cambridge:
Cambridge University Press, pp. 125–44.
8
Philosophical questions about the social discount rate
At the outset, we should recall the warning that Tjalling Koopmans
gave in his pathbreaking analysis of discounting in growth theory. He wrote,
“[T]he problem of optimal growth is too complicated, or at least too
unfamiliar, for one to feel comfortable in making an entirely a priori choice of
[a social discount rate] before one knows the implications of alternative
choices.”11 This conclusion applies with even greater force in global warming
models, which have much greater complexity than the simple, deterministic,
stationary, two-input models that Koopmans analyzed.
The Review argues that it is indefensible to make long-term decisions
with a positive social discount rate. The conclusion of the approach is the
following, “The argument … and that of many other economists and
philosophers who have examined these long-run, ethical issues, is that [a
positive social discount rate] is relevant only to account for the exogenous
possibility of extinction.” (Annex to Chapter 2, p. 52) The argument is that a
high social discount rate would lead societies to ignore large costs that occur
in the distant future. The actual social discount rate used in the Review is 0.1
percent per year, which is only vaguely justified by extinction estimates; for
our purposes, it can be treated as near-zero.
11 Tjalling C. Koopmans, “On the Concept of Optimal Economic Growth,” in
Pontificiae Academiae Scientiarum Scripta Varia 28, 1, Semaine D'Etude sur Le Role de
L'analyse Econometrique dans la Formulation de Plans de Developpement, 1965, pp. 1-75
(available for download at http://cowles.econ.yale.edu/P/au/p_koopmans.htm.)
Zero discounting leads to deep mathematical problems such as non-convergence of
the objective function and incompleteness of the functional. For the analytical
background, see also Frank Ramsey, “A Mathematical Theory of Saving,” Economic
Journal, 1928, 38, pp. 543–559; David Cass, “Optimum Growth in an Aggregative
Model of Capital Accumulation,” Review of Economic Studies, 1965, 32, pp. 233–240.
9
The logic behind the Review’s social welfare function is not as conclusive
as it claims. The Review argues that fundamental ethics require
intergenerational neutrality using an additive separable logarithmic utility
function. Quite another ethical stance would be to hold that each generation
should leave at least as much total societal capital (tangible, natural, human,
and technological) as it inherited. This would admit a wide array of social
discount rates. A third alternative would be a Rawlsian perspective that
societies should maximize the economic well-being of the poorest generation.
Under this policy, current consumption would increase sharply to reflect likely
future improvements in productivity. Yet a fourth perspective would be a
precautionary (minimax) principle in which societies maximize the minimum
consumption along the riskiest path; this might involve stockpiling vaccines,
grain, oil, and water in contemplation of possible plagues and famines.
Without choosing among these positions, it should be clear that alternative
ethical perspectives are possible. Moreover, as I suggest below, alternative
perspectives provide vastly different prescriptions about desirable climatechange
policies.
Even if a low social discount is chosen, a second issue arises in the
calibration of the social discount rate to actual macroeconomic. Behind the
Review’s modeling is the assumption that the world economy is in long-run
equilibrium of a Ramsey optimal growth model. In a Ramsey equilibrium
with stable population, there are two observables – the rate of return on
capital and the rate of growth of consumption; and there are two normative
parameters – the social discount rate and the curvature of the utility function
(more precisely, the elasticity of the marginal utility of consumption). A
realistic analysis would also need to account for distortions in the tax system,
10
for uncertainties and risk premiums, and for the equity-premium puzzle, but
these complications can be ignored in the present context.
The Review assumes a relatively low curvature parameter (the
logarithmic utility function) along with the near-zero social discount rate.
However, in calibrating a growth model, the social discount rate and the
curvature parameter cannot be chosen independently if the model is designed
to match observable variables. A low curvature (such as in the logarithmic
utility function) implies a relatively high social discount rate. A high
curvature (represented by a high degree of risk aversion or a high aversion to
intergenerational inequality) implies a low or even negative social discount
rate. It turns out that the calibration of the utility function makes an enormous
difference to the results in global-warming models, as I show in the modeling
section below.
Measuring impacts with near-zero discounting
With these analytical points behind us, I next discuss the Review’s
estimates of the aggregate economic impacts. The Review concludes, “Putting
these three factors together would probably increase the cost of climate
change to the equivalent of a 20% cut in per-capita consumption, now and
forever.” This frightening statement suggests that the globe is perilously close
to driving off a climatic cliff in the very near future. However, this is an
unusual definition of consumption losses, and when the Review says that there
are substantial losses “now,” this does not mean “today.” The measure of
consumption used is the “balanced growth equivalents” of consumption.
Roughly speaking, with low discounting, this is the certainty equivalent of the
average annual consumption loss over the indefinite future. The measure is
11
akin to an annuity. In fact, the Review’s estimate of the output loss now, as in
“today,” appears to be zero.
If we look inside the impact boxes, we find some strange things. The
damage estimates are much higher than the standard estimates in the impact
literature. This probably occurs because of assumptions that tilt up the
damage curve: rapid economic growth forever, high economic damage
estimates, high climatic impacts of GHG accumulation, catastrophic risks,
adverse health impacts, yet higher sensitivity of the climate system, and an
adjustment for inequality across countries. Additionally, the Review drew
selectively from studies, emphasizing those with high damage estimates,
some of which are highly speculative. For example, the Review used estimates
from the study of Nordhaus and Boyer (see footnote 12 below) that projected
damages way beyond 2100; however, those authors noted that projections
beyond 2100 were particularly unreliable.
However, the major point is that these impacts are far into the future,
and the calculations depend critically upon the assumption of low
discounting. Take as an example the high-climate scenario with catastrophic
and non-market impacts. For this case, the mean losses are less than 1 percent
of world output in 2050, 2.9 percent in 2100, and 13.8 percent in 2200 (see
Figure 6.5d). Yet this somehow turns into a mean annual impact of 14.4
percent shown in Table 6.1, and after a few other gloomy ingredients are
stirred in, it becomes the “20% cut in per-capita consumption, now and
forever.”
How do damages, which average around 5 percent of output over the
next two centuries turn into a 14.4 percent reduction in consumption now and
12
forever? The answer lies in the way that near-zero discounting magnifies
distant impacts. With near-zero discounting, the low damages in the next two
centuries get overwhelmed by the long-term average over many centuries. We
can illustrate using the Review’s model discussed in Box 6.3. Suppose that
scientists discover that that a wrinkle in the climatic system will cause
damages equal to 0.01 percent of output starting in 2200 and continuing at
that rate thereafter.
How large a one-time investment would be justified today to remove the
wrinkle starting after two centuries? The answer is that a payment of 15 percent
of world consumption today (approximately $7 trillion) would pass the
Review’s cost-benefit test. This seems completely absurd. The bizarre result
arises because the value of the future consumption stream is so high with
near-zero discounting that we would trade off a large fraction of today’s
income to increase a far-future income stream by a very tiny fraction. This
bizarre implication reminds us of Koopmans’s warning quoted above to
proceed cautiously to accept theoretical assumptions about discounting before
examining their full consequences.
Hence, the damage puzzle is resolved. The large damages from global
warming reflect large and speculative damages in the far-distant future; the
impacts now, as in today, are small; and, as I will suggest below, the 20
percent cut in consumption from global-warming might be reduced by an
order of magnitude if alternative assumptions about discounting are used.
13
Economic modeling with low discount rates
I next apply these points in an empirical model of the economics of
global warming. To foreshadow the result, these calculations show that the
assumption of a near-zero social discount rate drives most of the economic
results in the Review.
It is virtually impossible for mortals outside the group that did the
modeling to understand the detailed results of the Review. It would involve
studying the economics and geophysics in several chapters, taking apart a
complex analysis (the PAGE model), and examining the derivation and
implications of each of the economic and scientific judgments.
The alternative approach followed here is to use a small and welldocumented
model of the economics of climate change to estimate the optimal
policy, and then to make parameter adjustments to parallel assumptions made
in the Review. For this purpose, I use the “DICE model,” which is an acronym
for a Dynamic Integrated model of Climate and the Economy. This model,
developed in the early 1990s, uses a simple dynamic representation of the
scientific and economic links among population, technological change, GHG
emissions, concentrations, climate change, and damages. The analytical
structure of the DICE model is identical to that in the Review. DICE calculates
the paths of capital investment and GHG reductions that maximize a social
welfare function, where the social welfare function is the discounted sum of
population-weighted utilities of per capita consumption. The DICE model
assumes a pure rate of social time preference starting at 3 percent per year and
declining slowly to about 1 percent per year in 300 years. The social discount
14
rate was chosen to be consistent with a logarithmic utility function, market
interest rates, and rates of private and public saving and investment. 12
For this analysis, I have updated the DICE model to 2005 data,
economics, science, and 2006 prices.13 I then make three runs, which are
explained as we proceed:
Run 1. Optimal climate change policy in the DICE-2006 model
Run 2. Optimal climate change using the Stern Review zero discount rate
Run 3. Optimal climate change using a recalibrated zero discount rate
Run 1. Run 1 is the Optimal climate change policy in DICE-2006. This run
takes the DICE-2006 model and calculates the optimal trajectory of climate
change policies as described above. This calculation leads to an optimal
carbon price in 2005 of $17.12 per ton C, rising over time to $84 in 2050 and
$270 in 2100. (The “optimal carbon price,” or carbon tax, sometimes called the
“social cost of carbon,” is the calculated price of carbon emissions that will
balance the incremental costs of reducing carbon emissions with the
12 Results and documentation of the DICE model are provided in William Nordhaus,
“An Optimal Transition Path for Controlling Greenhouse Gases,” Science, vol. 258,
November 20, 1992, pp. 1315-1319; William Nordhaus, Managing the Global Commons:
The Economics of Climate Change, MIT Press, Cambridge, Mass., 1994; William
Nordhaus and Zili Yang “A Regional Dynamic General-Equilibrium Model of
Alternative Climate-Change Strategies,”, American Economic Review, vol. 86, No. 4,
September 1996, pp. 741-765; William Nordhaus and Joseph Boyer, Warming the
World: Economic Modeling of Global Warming, MIT Press, Cambridge, Mass, 2000;
William Nordhaus, “Global Warming Economics,” Science, November 9, 2001, vol.
294, no. 5545, pp. 1283-1284.
13 Documentation of the changes in the DICE-2006 model and the GAMS computer
program for the DICE-2006 model are provided in William D. Nordhaus,
“Documentation for DICE-2006, November 2006 round,” November 17, 2006,
available at www.nordhaus.econ.yale.edu , under “Recent Stuff.”
15
incremental benefits of reducing climate damages.) The optimal rate of
emissions reduction is 6 percent in 2005, 14 percent in 2050, and 25 percent in
2100.14 This optimized path leads to a projected global temperature increase
from 2000 to 2100 of around 1.8 degrees C. While the findings of such
mainstream economic assessments may not satisfy the most ardent
environmentalists, if followed they would go far beyond current global
emissions reductions and would be a good first step on a journey of many
miles.
Run 2. The results of the standard DICE model just discussed are
completely different from those in the Review. The Review recommends a
social cost of carbon of $311 per ton C. This number is almost 20 times the
DICE model result. Based on calculations made in earlier publications (see
footnote 12), it seems likely that the major reason for the Review’s sharp
emissions reductions and high carbon price is the low social discount rate. I
therefore calculated run 2, Optimal climate change using the Stern Review zero
discount rate. The assumptions are the same as Run 1 except that the social
discount rate is changed to 0.1 percent per year. This dramatically changes the
trajectory of climate-change policy. The 2005 optimal carbon price in the DICE
model rises from $17.12 in Run 1 to $159 per ton C in Run 2.15 Efficient
emissions reductions in Run 2 are much larger – with emissions reductions of
14 The future numbers are the solutions to the model based on current information
and provide estimates of optimal future policies under current estimates of
parameters. They are not decisions that are taken today. They should be revised over
time as new scientific and economic information becomes available.
15 The social cost of carbon estimated in the Review is approximately two times
higher than the number calculated in Run 2. Because different models are used, it is
not possible to identify reasons for the discrepancy. Modeling results are extremely
sensitive to parameter changes when the discount rate is near-zero.
16
50 percent in 2015 – because future damages are in effect treated as occurring
today. The climate-policy ramp flattens out.
Run 3.An earlier section noted that alternative calibrations of the social
welfare function are consistent with observable variables. So the final run is
one in which assumes a low social discount rate but where the curvature
parameter is calibrated so that the economic growth path conforms to
observable variables. Some history might be helpful here. When the DICE
model was constructed fifteen years ago, I assumed logarithmic utility for
computational reasons – alternative utility functions would not converge
numerically. This calibration led to a social discount rate of 3 percent per year,
which was calibrated to match the growth of consumption, savings rates, and
market rates of return on capital. Because of improvements in computers and
software, we can now easily calibrate alterative utility functions. Experiments
with the DICE-2006 model indicate that a social discount rate of 0.1 percent
per year is consistent with a utility curvature parameter of 2.25. However, the
Review’s social discount rate of 0.1 percent per year is inconsistent with its
utility curvature assumption of 1.16 The Review’s calibration gives too low a
rate of return and too high a savings rate compared to macroeconomic data,
16 The discussion in the text assumes zero population growth. More generally, the
Ramsey-Cass-Koopmans steady-state optimal growth equilibrium equation is
r = ρ + αg + n, where r = the marginal product of capital, ρ = social discount rate,
α = elasticity of the marginal utility of consumption, g = growth of per capita
consumption, and n = rate of growth of population. Conceptually, the marginal
product of capital has the same units as the real interest rate, but entirely different
units from the social discount rate. To apply this equilibrium condition, assume that
the observable variables (in rates per year) are r = 0.05, n = 0.00, and g = 0.02. For this
simplest equation, if we assume that the social discount rate is ρ = 0 per year, then α
= 2.5. If we take the log-linear utility function of the Review together with the
observable variables in this footnote, then this implies that ρ = 0.03 per year. The
calibrations in DICE-2006 are slightly different from these equilibrium calculations
because of positive population growth and non-constant consumption growth, but
these equilibrium calculations given the flavor of the results.
17
but the alternative calibration proposed here fits the macroeconomic data
underlying the DICE model.
We can now rerun the DICE-2006 model with the near-zero social
discount rate and the associated calibrated curvature parameter derived in the
last paragraph. This is Run 3, Optimal climate change with recalibrated zero
discount rate. Run 3 looks very similar to Run 1, the standard DICE-2006 model
optimal policy. The first-period social cost of carbon in Run 3 is $19.55 per ton
C, slightly above Run 1. The recalibrated run looks nothing like Run 2, which
is the run that reflects the Review’s assumption. How can it be that Run 3, with
a near-zero social discount rate, looks so much like Run 1? The reason is that
the recalibrated social discount rate in Run 3 maintains the assumption of
productive capital, with a relatively high real interest rate in the near term.
This high return means that the logic of the climate-policy ramp continues to
hold even though the social choice function has been recalibrated to a zero
social discount rate. This calibration removes the cost-benefit dilemmas just
discussed as well as the savings and uncertainty problems discussed in the
next two sections.
Implications for saving and investment
I return for the balance of this note to the Review’s assumptions on both
social discount rate and utility curvature (the assumptions that underlie Run
2). One surprising implication of the Review’s social discount rate is the effect
on consumption and saving. If the Review’s philosophy were adopted as a
general policy, it would produce much higher overall saving as compared
with today. In Run 2 (Optimization with Stern discount parameter), the global net
savings rate almost doubles compared to the historical numbers or Run 1. This
18
implies that global consumption would be reduced by about 14 percent,
requiring a reduction of $6 trillion per year in current consumption.
Where would the consumption cuts come from? From India and Africa?
That hardly seems equitable. The higher investment would be more than five
times total overseas development aid of all countries today. Perhaps the
consumption should come from the wasteful Americans? This would be fourfifths
of current levels of consumption and many times the decline in the
Great Depression.
Aside from the question of who pays, we might wonder whether such a
large decline in current consumption today is desirable in a world where
average consumption is growing rapidly. The Review projects that per capita
consumption will grow at 1.3 percent per year over the next two centuries (p.
162). In 2006 dollars, this means that today’s per capita consumption of $7,600
would grow to $94,000 in 2200. Here perhaps is a shard of hope for the globe.
However, this growth also means that future climatic damages will
come out of a much higher level of income. For example, the high-damage
case is associated with a 13.8 percent decline in consumption in 2200 as
discussed above. This means that per capita consumption would grow from
$7,800 today to only $81,000 in 2200. Hence, the Review advocates reducing
current consumption to prevent the decline in consumption of future
generations that it projects to be much richer than today. While this might be
worth contemplating, it hardly seems ethically compelling.
Faced with these implications of the discounting assumption, advocates
of the Review policy might propose a “dual-discounting” approach – limiting
19
the scope of the low social discount rate to climate policy. In other words,
perhaps countries should choose global-warming policies assuming the nearzero
social discount rate, but leave the rest of the economy to operate with the
present high social discount rate. While this seems an attractive possibility, it
is in fact a roundabout way to slow climate change sharply. In effect, we are
using a low social discount rate to “prevent dangerous interference with the
climate system” (in the language of the Framework Convention on Climate
Change). If that is the reason, why not impose the limit directly? Instead of
using the near-zero social discount rate as an analytic subterfuge to slow
climate change, why not simply adopt policies that will directly keep climate
change below the dangerous threshold? Limiting climate change directly is
more efficient as well as more transparent.
Hair triggers and uncertainty
A further unattractive feature of the Review’s near-zero social discount
rate is that it puts present decisions on a hair-trigger in response to far-future
contingencies. Under conventional discounting, contingencies many centuries
ahead have a tiny weight in today’s decisions. Decisions focus on the near
future. With the Review’s discounting procedure, by contrast, present
decisions become extremely sensitive to uncertain events in the distant future.
We saw above how an infinitesimal impact on the post-2200 income
stream could justify a large consumption sacrifice today. We can use the same
example to illustrate how far-future uncertainties are magnified by low
discount rates. Suppose that we suddenly learn that there is a 10 percent
probability of the wrinkle in the climatic system that reduces the post-2200
income stream by 0.01 percent. What insurance premium would be justified
20
today to reduce that probability to zero? With conventional discount rates, we
would probably ignore any tiny wrinkle two or three centuries ahead. If we
did a careful calculation using conventional discount rates, we would
calculate a breakeven 0.0002 percent insurance premium to remove the year-
2200 contingency, and a 0.0000003 percent premium for the year-2400
contingency. Moreover, these dollar premiums are small whether the
probability is large or small.
With the Review’s near-zero discount rate, offsetting the low-probability
wrinkle would be worth an insurance premium today of almost 2 percent of
current income, or $1 trillion. We would pay almost the same amount if that
threshold were to be crossed in 2400 rather than in 2200. Because the future is
so greatly magnified by a near-zero social discount rate, policies would be
virtually identical for different threshold dates. Moreover, a small refinement
in the probability estimate would trigger a large change in the dollar premium
we would pay. We are in effect forced to make current decisions about highly
uncertain events in the distant future even though these estimates are highly
speculative and are almost sure to be refined over the coming decades.
While this feature of low discounting might appear benign in climatechange
policy, we could imagine other areas where the implications could
themselves be dangerous. Imagine the preventive war strategies that might be
devised with low social discount rates. Countries might start wars today
because of the possibility of nuclear proliferation a century ahead; or because
of a potential adverse shift in the balance of power two centuries ahead; or
because of speculative futuristic technologies three centuries ahead. It is not
clear how long the globe could long survive the calculations and machinations
21
of zero-discount-rate military powers. This is yet a final example of a
surprising implication of a low discount rate.
Summary verdict
How much and how fast should the globe reduce greenhouse-gas
emissions? How should nations balance the costs of the reductions against the
damages and dangers of climate change? The Stern Review answers these
questions clearly and unambiguously: we need urgent, sharp, and immediate
reductions in greenhouse-gas emissions.
I am reminded here of President Harry Truman’s complaint that his
economists would always say, on the one hand this and on the other hand
that. He wanted a one-handed economist. The Stern Review is a Prime
Minister’s dream come true. It provides decisive and compelling answers
instead of the dreaded conjectures, contingencies, and qualifications.
However, a closer look reveals that there is indeed another hand to
these answers. The radical revision of the economics of climate change
proposed by the Review does not arise from any new economics, science, or
modeling. Rather, it depends decisively on the assumption of a near-zero
social discount rate. The Review’s unambiguous conclusions about the need for
extreme immediate action will not survive the substitution of discounting
assumptions that are consistent with today’s market place. So the central
questions about global-warming policy – how much, how fast, and how costly
– remain open. The Review informs but does not answer these fundamental
questions.
  1. Dear Readers, In recent months, I have posted my public writing to my free Substack. I have such fond memories of Google Blogspot, thus it deeply surprises me that Google's search engine does a terrible job in helping those who search to find past blog posts. This deeply surprises me. As I age, I'm trying to post more dignified material to my Substack. I am sticking to what I know based on my ongoing research in microeconomics. Thanks very much for reading my posts. Best Regards, Matthew E. Kahn
  2. I have moved my blog over to Substack (and I've lost many readers). Please join me there. Here is a recent column. The Wall Street Journal has published an important piece about how the high heat is reducing economic activity in Houston. The piece has a pessimistic tone that the heat melts the city’s infrastructure and shaves off economic activity as people don’t want to go outside. When microeconomists study consumer expenditure dynamics as people buy cars, go out to dinner and buy groceries. During hot spells, people are less likely to go out for dinner or to play multiple rounds of golf. A microeconomist would say that this evidence indicates that people have “state dependent preferences”. In English, this means that how much we enjoy a steak dinner at an outdoor restaurant depends on whether it is 75 degrees outside or 95 degrees outside (this is the “state of the world”). I certainly believe that hot and humid Houston is in a type of “macroeconomic Siesta” right now and this reduces economic activity. But, permit me to make some counter-points. #1 The money people in Houston do not spend on the hot July 28th 2023 is still in their bank account and they can spend it on a cooler November 5th 2023 day. Note this intertemporal substitution. The media focuses on the direct effect of the heat (that high heat is reducing economic activity today) but my counter-hypothesis is that it displaces expenditure to the future when it will be cooler later this year in Houston. So, will the New York Times write a piece saying that high summer heat causes a fall boom in Houston? I don’t think so. This type of cross-elasticity is ignored by the “climate crisis” focused media. #2 The WSJ interviewed a few people who want to leave Houston. As always, they are free to choose. As more workers can engage in WFH, those who hate the high heat will leave the city in summer. If they own a home, they can AirBNB it. WFH is a climate adaptation strategy as it makes people more geographically footloose. I discuss this in my 2022 book. #3 We have to live somewhere. Is Houston becoming more miserable to live in summer than other cities? If the answer is “yes”, then its home prices will fall. Here are some data from Zillow.
    Even with higher interest rates, I don’t see a collapse here in the Zillow index. Are you going to sell short Houston homes as your strategy to get rich? Incumbent home owners form a strong interest group to invest in adaptation strategies to protect their asset’s value. WHAT are possible adaptation strategies? #1 Road construction materials can be re-evaluated to reduce the urban heat island effect. Read this report. The City has strong incentives to embrace the cost-effective strategies discussed here. #2 Golf courses can open up part of the area and charge people to enter on hot days to use them as private parks. #3 Here are personal cooling strategies. On a personal level, of course the city needs access to strong air conditioning. Firms that make them and repair them will enjoy a boom. The Electricity GRID must remain reliable. The Climatopolis logic is that Houston competes with other cities to attract successful people and firms. The system of cities and the fear of brain drain gives Houston’s leaders and land owners strong incentives to be pro-active in adapting to climate change. Such efforts will be messy as there will be fights over who pays for such local public goods but the end result will be a more resilient Houston where the high heat causes less economic damage in the short term and medium term. This is the climate change adaptation hypothesis.
  3. The New Economic Geography of WFH Matthew E. Kahn Over the last three years, companies from all over the world have learned valuable information about how their firm’s productivity and worker satisfaction is affected when workers can engage in Work from Home (WFH) on at least a part-time basis. Each firm faces fundamental tradeoffs in not requiring workers to return full time to the office. On the one hand, WFH accommodates worker lifestyles and responsibilities at home. WFH workers gain from commuting less often and some may choose to live further from their place of work because they commute in on fewer days. Firms with happier workers are less likely to face retention challenges and will pay less retraining workers. Given that WFH is a non-taxed perk, firms that offer this job amenity can be less generous in giving workers pay raises. Firms located in expensive areas can economize on expensive commercial real estate. If a firm requires that workers be in the office just half the week, then a firm can reduce its space requirements by 50%! On the other hand, firms benefit from face to face communication. Younger workers gain more from such mentoring. Building up the firm’s culture and monitoring worker effort is easier to do if workers are on site. Each company has a strong incentive to experiment with different workplace practices to learn what works best for their organization. The pursuit of profit actually accelerates this learning process. Economists are always looking for new ways to study firm dynamics. The rise of the WFH economy opens up many questions related to what types of firms will encourage their workers to engage in WFH. Famous executives such as Elon Musk at Tesla and Jamie Dimon at JP Morgan have been encouraging workers to return to the office. Why? Up until now, a lack of data has hindered the systematic analysis of what types of firms prioritize allowing workers to engage in WFH on at least a part-time basis. The newly released Flex Index provides a unique opportunity for researchers. As an urban economist, I am especially interested in the geographic determinants of why different firms engage in hybrid-WFH. The Flex Index provides data on each firm’s headquarters’ location. I focus on those that are based in the United States. I use data for 2528 of them. For this set of firms, I merged in three geographic variables. The first variable is the Zillow Median Home Price Index. Zillow uses a repeat home price index methodology to create a standardized “apples to apples” measure of home prices that can be compared across cities at a point in time or within a given city over time. In the analysis I present below I use Zillow data from December 2022. The second variable I merge in to the Flex Index is the percent of voters in the Headquarters State that voted for Joe Biden in the 2020 Presidential Election. The third variable I merge in from the Zillow data base is the city’s size. So, New York City is the first ranked city in the nation because it is the largest city. I use these data to test two hypotheses; Hypothesis #1: All else equal, firms are more likely to engage in WFH work if home prices are higher in the HQ City. Hypothesis #2: All else equal, firms are more likely to engage in WFH in more Progressive states. To test these hypotheses, I use a linear multivariate regression framework. To standardize the firms, I include industry fixed effects (this variable is in the Flex Index database). The dependent variable is a dummy variable that equals one if the firm’s workers all work on site. In the database, 39% of the firms report having the workers work fully on site. Table One reports four regressions with each column reporting a separate regression. I use the regression output to test the hypotheses presented above. Main Results All else equal, firms are more likely to engage WFH work if home prices are higher in the Headquarter (HQ) City. Based on the results in columns (1) and (3), I find that for the full set of industries and for the Healthcare and Biotechnology industry that workers are more likely to be engaging in WFH if home prices are higher in the HQ’s city. Based on the results in column (2), a doubling of home prices is associated with a log(2)*-.088 = -.06 or a six percentage point reduction in workers working solely on site. This effect is even larger for the Health Care industry. For this subset of firms, a doubling of local home prices is associated with a 12.7 percentage point increase in WFH. For the other two industries, I fail to reject the hypothesis that firms are not more likely to allow workers to engage in WFH as a function of local home prices. All else equal, firms are more likely to engage in WFH in more Progressive states. The test of this hypothesis is based on the coefficient on the 2020 Joe Biden vote share. Across all four specifications presented in Table One, I find consistent evidence that firms are more likely to allow their workers to engage in WFH when the HQ is located in a more liberal state. A ten percentage point increase in Joe Biden’s vote share is associated with a 3 percentage point increase in the probability that a firm allows its workers to engage in WFH on at least a part-time basis. Conclusion The Flex Index is a terrific new data source that allows empirical researchers to study how different firms are incorporating WFH into their work routines. In my 2022 Going Remote book, I hypothesized that the rise of WFH would benefit workers in high home price areas. The evidence presented here supports this hypothesis. Here, I also find a Red State/Blue State divide such that firms located in Blue States are more likely to allow their workers to engage in WFH. Future research should explain why we observe this fact. Are such firms in progressive states more concerned about work/life balance and gender equality issues? There are many open questions that improved data access will allow for us to provide credible answers.
  4. A majority of American adults live in owner occupied housing. As an economist, I celebrate the logic of revealed preference. While many poor people are renters, many non-poor people reveal that the benefits of ownership exceed the costs. In this entry, I would like to delve into the details here. Up front, let me say that I don’t want to discuss the tax code and the nitty gritty of mortgage interest deductions, the GSEs, etc. Instead, I want to talk about why people gain life satisfaction from ownership and what are some of the hidden costs of ownership under our current “rules of the game”. As an urban economist, I want to contrast the private benefits to an adult of owning a home and the local social benefits conveyed to a community when it consists of home owners. Portfolio Risk from Home Ownership Let’s start with a personal example. Back in 2000, We purchased a home in Belmont, MA (a Boston suburb), we paid 1/2 in cash and got a loan for the rest. The cash we invested in the home had a next best alternative. We could have invested in a diversified portfolio of assets rather than making a place based bet. By buying this home, we were raising our migration costs for moving away from Boston and thus were losing some option value if the local economy performed worse than the rest of the nation. A strange feature of the housing market is that owners hold an undiversified portfolio. Imagine an alternative world where I could own 36% of my Belmont home and own 2% of 32 other homes scattered around the United States. This would be a more diversified portfolio. Of course there would be contracting issues in designing this contract. My friend and co-author Joe Tracy co-authored a MIT Press book on implementing these contracts. The Past Rate of Return on Housing for African-Americans In 2021, I released an NBER Working Paper where I use several data sets to make a simple point. Here is my paper’ abstract: “The racial and ethnic composition of home buyers varies across geographic locations. For example, Asians and Hispanics are much more likely to buy homes in California than Blacks and Blacks are more likely to buy homes in Georgia than other demographic groups. Home prices grow at different rates across geographic units such as counties or zip codes. Hedonic bundling inhibits buyers from purchasing shares of different homes and forming a spatially diversified housing portfolio. Spatial variation in purchases suggests that the average rate of return to housing varies across racial and ethnic groups. To test this claim, I construct a geographic shift-share index by combining Zillow geographic specific home price index data with HMDA micro data. The shift share calculations yield the average rate of return to home ownership by purchase year, and sale year for different demographic groups. Over the years 2007 to 2020, Blacks earned a lower rate of return on home purchases than Asians and Hispanics and the sample average. Within geographic areas, average loan differences across racial and ethnic groups are very small.” Let’s unpack this. Over the last 25 years, cities such as San Francisco, Boston, Portland, Seattle, San Jose, Malibu, and Santa Monica have boomed. None of these cities is known to be an African-American city. African-Americans tend to buy in other cities such as Baltimore, Cleveland and Detroit. What is going on here? (and of course I am telling an Average story —- LeBron James lives close to me in Los Angeles’s Brentwood). African-Americans on average have lower wealth than Whites and are less likely to be able to afford the down payment to buy housing in Superstar Cities. African-Americans are less likely to work in Tech than Whites and Asians and this reduces the likelihood that they are living in the major tech hubs. In the areas where African-Americans have ties, house prices have not appreciated much and this means that the AVERAGE African-American homeowner has earned a lower rate of return on housing over the last 25 years. Going forward (from 2023 to 2040) will Baltimore’s housing market outperform San Jose’s? This is possible. In my recent WFH Going Remote book, I present microeconomic arguments for why this is possible if Baltimore improves its quality of life. In closing this section, I want my readers thinking about opportunity cost. If an African-American family owns housing in Baltimore then that money is not invested in the SP500 stock market index. Opportunity cost for asset investments always exist. What About the Consumption Value of Home Ownership? When we teach Econ 101, we introduce our students to the utility function. This is the economist’s “thermometer” measuring how much pleasure we gain from different consumption bundles such as consuming beer or pizza. The consumer knows herself and knows her budget constraint and makes the right (affordable) consumption choice. Assuming people are consistent over time, we learn about their priorities from the choices they make as market prices and their income changes. With this preamble, why does home ownership raise one’s utility? One hypothesis is “pride of ownership”. But what do these words mean? Economists have struggled with modeling the demand for “status”. Economists have taken Veblen seriously and have sought tests of which subgroups of people seek to own and display luxury goods to signal that they are special. Here is a paper about cars and jewelry ownership. Of course, I understand the desire for status. I continue to submit papers to Top 5 journals and to track my Twitter Follower count! But, the point of this 1/2 joke is that there is an ever increasing number of strategies for producing “status”. As I age, I gain pride by reaching my Google Fit target of 10,000 steps a day. During my life time, I have lived in fancy rental housing in Manhattan, Singapore, and Baltimore. Given the changing demographics of our population, real estate suppliers will offer rental properties if there is demand. Don’t Renters Face Displacement Risk and Gentrification Risk? Yes, but if this is a serious concern then renters can sign longer term contracts up front. Scottie Pippen signed a 10 year contract with the Chicago Bulls at the start of his career because of his fear of injury. In a renter economy, there would be less support for local NIMBYism and real estate developers would build more housing and this would reduce rent rise risk. The ongoing conversion of commercial urban real estate into residential housing also reduces the likelihood of medium term rent spikes. I claim that it is time to visit this important paper by Todd and Nick. Sinai, Todd, and Nicholas S. Souleles. "Owner-occupied housing as a hedge against rent risk." The Quarterly Journal of Economics 120, no. 2 (2005): 763-789. Neighborhood Social Capital Boosts Due to Home Ownership? Ed Glaeser and Denise DiPasquale have posited a positive spillover that when real estate is owner occupied that the owner has the right incentives to maintain the property (to maintain the resale value) and to not free-ride in terms of neighborhood attributes such as safety and neighborhood greenness. Their empirical strategy in their applied research was to use panel data at the individual level and observe how the same person behaves before and after she becomes a home owner. A field experiment researcher would want to go a step further and randomly assign similar people at the baseline to renting versus owning and then observe how their home is treated and how their neighborhood’s quality of life changes over time. I greatly admire their work here but I want to be provocative and argue that their work is out of date due to technological change. I want to return to a paper by Baker, George P., and Thomas N. Hubbard. "Contractibility and asset ownership: On-board computers and governance in US trucking." The Quarterly Journal of Economics 119, no. 4 (2004): 1443-1479. These authors tell the following story. Back in the 1970s, truck drivers bringing stuff from California to Baltimore markets had private information about their routes and effort. The food company gave the truck driver a share of the profits to incentivize them to not shirk with respect to effort. The advent of cheap GPS computers meant that the food company could easily monitor the trucker and could now pay him a fixed wage. The same idea holds in 2023 for rental housing. The big data monitor era allows the property manager to have a very good sense of how the tenant is using the property and what is going on in the local neighborhood. If crime rises, the property manager can hire private guards. If litter increases, a crew can be hired to pick up the trash. Markets substitute for social capital and volunteering! Conclusion The modern Economy’s Big Data revolution and climate change risk both create incentives for more of us to be renters. Going forward if more of us are renters in the year 2040; then we gain the following adaptation benefits; #1; Our assets are less exposed to place based shocks (i.e Hurricane Ian), #2 we hold a real option to move away from areas that turn out to be at greater risk from shocks, #3 There is less lobbying for place based subsidies using national subsidies because “victims” have fewer place based assets at risk (i.e we are each holding a more diversified portfolio). If government steps back from insurance markets, the private sector will step up its game and insurance innovation will further spur the pace of climate change adaptation. If these ideas interest you, read my 2021 Yale Press book Adapting to Climate Change.
  5. Climate change adaptation refers to our individual and collective ability to cope with Mother Nature’s more intense weather punches in terms of extreme heat, drought, fire, flood and many other place based risks. My microeconomics research, as sketched out in my 2010 Climatopolis book and my 2021 Adapting to Climate Change books, argues that capitalism accelerates our ability to adapt as market price signals encourage substitution and innovation. Whether government policy complements the private sector muffles the private sector’s efforts continues to be a major research topic. In my 2010 Climatopolis book, I asked; “If Milton Friedman ran the U.S FEMA (and thus committed to no generous ex-post bailouts to shocked places) how much faster would adaptation occur?” In my ongoing empirical work, I continue to study how extreme weather affects our economy. I see evidence of adaptation progress as the “climate damage function” flattens and this means that the same punches thrown by Mother Nature cause less damage over time. My students are studying this hypothesis in the developing world and investigating what frictions (such as government policy) inhibit adaptation from taking place. An example would be government price supports for agriculture that create a moral hazard effect. See this 2015 paper set in the United States. My Thoughts About the Work by Two Talented New York Times Journalists The New York Times continues to be the paper of record. Two of the leading authors for the Times are Christopher Flavelle and David Wallace-Wells. I link to their work so you can read it on your own. David recently published a huge New York Times Magazine piece that you can read here. I want to keep this entry short but I plan to expand upon the themes I present below. I must acknowledge upfront that I have not interviewed either of them about their climate change adaptation pessimism. My points I present here are based on my reading of their work. How Does a “Climate “Crisis” Emerge? Global greenhouse gas emissions will continue to rise. Read our 2022 NBER paper. We do not know how much global average temperatures will rise due to rising emissions and we do not know what “crazy” weather will emerge because of what we have collectively unleashed. In a series of case studies, Flavelle argues that we have built up billions of dollars of place based capital in increasingly risky areas such as Florida that face more severe disaster risk. He emphasizes the moral hazard effect that the expectation that there will be Federal Bailouts of struck areas encourages more rebuilding in these areas. So, he is telling a story that we do not learn from our mistakes. He does not explain who is the “adult in the room”? Why don’t city urban planners, the mortgage lending industry, the real estate development industry, the insurance industry adopt new “rules of the game” so that new real estate development is nudged to “higher ground” or if we build in risky places that private actors are incentivized to invest in pre-cautions that reduce the damage caused by the next storm. Starting with my Climatopolis book, I have argued that if people make place based bets (such as investing in Miami real estate), then they should flip two sided coins. They get to keep the upside appreciation if local prices rise but they also must “eat” the downside loss if local prices decline because of rising risk and better opportunities in other real estate markets such as Boston or Houston or Buffalo. I do respect his point that the public sector activism in insurance markets is causing an important free market distortion. As the social cost of this distortion rises, economic theory predicts that political reform will take place. Why should tax payers on “higher ground” bail out risk takers over and over again? Why reward “bad behavior”? As we saw with the economy’s reorganization during the COVID crisis of 2020, markets adapt and change when new news occurs if government does not distort price signals. The rise of the Zoom WFH experiment was an amazing example of adaptation. David Wallace-Wells argues that adaptation is costly and will exacerbate existing inequality. A quote “Talk enough about adaptation, and you drift into technical-seeming matters: Can new dikes be built, or the most vulnerable communities resettled? Can crop lands be moved, and new drought-resistant seeds developed? Can cooling infrastructure offset the risks of new heat extremes, and early warning systems protect human life from natural disaster? How much help can innovation be expected to provide in dealing with environmental challenges never seen before in human history? But perhaps the more profound questions are about distribution: Who gets those seeds? Who manages to build those dikes? Who is exposed when they fail or go unbuilt? And what is the fate of those most frontally assaulted by warming? The political discourse orbiting these issues is known loosely as “climate justice”: To what extent will climate change harden and deepen already unconscionable levels of global inequality, and to what degree can the countries of the global south engineer and exit from the already oppressive condition that the scholar Farhana Sultana has called “climate coloniality”?” These are great questions but note that these are economics questions. What is the quality adjusted price of the goods we need to continue to be safe, comfortable and healthy? David Wallace-Wells owns a computer and a cell phone. These products didn’t exist in 1940. Every day they grow cheaper and become of higher quality. This is what market competition does. More poor people in the developing world can afford these products as quality adjusted prices decline. Note that Wallace-Wells is rightly concerned with poverty and the challenges that poor people will face going forward. An economist would reply to his pessimism; “okay, you are not worried about Elon Musk’s ability to adapt to new risks. Let’s rank all of the world’s population with respect to their income. Who are the people who currently do not have the capacity to adapt to the serious challenges that wacky weather is posing? What income growth would give them the opportunity to adapt? Why isn’t this income growth occurring? “ Note that David Wallace-Wells is saying that economic growth in the developing world is the key to adapting to climate change. We need poverty alleviation to help everyone to be able to adapt. Here we agree. Economic growth is the key tool for adapting to climate change. Such economic growth reduces poverty. Here is a study of global poverty alleviation by a leading macro-economist. I recognize that I am positing that national economic growth reduces poverty. Is this a controversial claim?
  6. This has been a very hot summer.  For every person on the planet, what is her willingness to pay to avoid this hot summer?  So, on a day when it s 93 degrees on average --- how much is Sally in Seattle willing to pay for this day to have been 78 degrees instead?

    In a "make versus buy" economy, one can either pay God to not face the 93 degree day in Seattle or one can use a suite of adaptation strategies to cope with the high heat.  Basic economic logic teaches us that one's willingness to pay to avoid the heat is bounded by what it would cost you to adapt to the heat.   This blog post focuses on the microeconomic determinants of adapting to the heat.

    I will argue that at any point in time, this adaptation strategy set is almost infinite dimensional and that the dimensions of the adaptation strategy set grow over time so that it gets ever easier for us to adapt to the high heat.  This means that our willingness to pay to avoid facing the extreme heat actually declines over time because it is getting cheaper for us to adapt on our own to the heat.   In my 2021 Adapting to Climate Change book, I expand on this point that the Social Cost of Carbon can actually decline over time for many people as their adaptation choice set grows.

    Let's start with the marginal cost curve that is familiar to anyone who has taken Econ 101.

    Case #1:   A firm produces pizza using a linear production function such that pizza=10*Labor and the price of Labor = 2 each.

    Given the linear production function, the firm can always make one more pizza if it hires .1 workers. It costs $2 per worker so the marginal cost to the firm of producing an extra pizza =2*.1 = 20 cents and this is a constant function.

    Case #2:   A firm produces pizza using a concave production function such that pizza=10*square root of Labor and the price of labor is .4 each.

    In this case the amount of labor needed to make a pizza can be expressed as =  Pizza*Pizza/100  and the $ expenditure to purchase this labor equals Pizza*Pizza/25  .   This mechanical marginal cost function is convex.

    Given this definition of marginal cost, now let's turn to the marginal cost of avoiding heat.  Consider a person in Spain today confronted with high heat where she currently lives and works.  Here is her strategy set for adapting;

    #1   Move to a cooler place (either outdoors or inside such as below ground).  Such migration can be permanent or temporary in an economy featuring cross-city transportation services and AirBNB short term housing.  

    #2   seek out a shady place with a breeze 

    #3  turn on air conditioning or go to a public place with air conditioning,   A theme in my 2010 Climatopolis book was that if an area is known to face rising summer heat then people will change their durables and their home and work place architecture to be better prepared for the heat. We are not passive victims!!

    #4 wear lighter clothing

    #5  use a damp towel

    #6  drink water

    #7  take a Siesta and stop working during the hottest hours

    #8   Eat lightly

    Each of these adaptation strategies has a financial cost and a time cost.  As Gary Becker taught us the full price equals the financial cost + your wage*time cost.   For example, migrating will require more time and for high value of time people, this will mean incurring a larger cost.  

    I will stop here but note the following.  Taking permutations of these various options yields an almost infinite dimensional adaptation choice set.  Modern climate economics assumes that this choice set is stationary. In truth, it expands on a daily basis as we make progress building higher quality durables such as housing and air conditioning units and as we retire older capital and install newer capital.  Modern economics is weak on capital updating problem.  John Rust wrote a famous bus engine replacement paper but climate economists haven't incorporated this logic into the updating of the spatial capital stock.  My paper with Devin Bunten is one attempt to address this issue.

    Once we acknowledge that we have an ever growing set of adaptation strategies that are becoming cheaper and cheaper to use then one becomes more optimistic about the ability of the rich and the poor to adapt to the new serious challenges we face.

    One example of the rising permutations.  More and more educated people now have the opportunity to engage in Work from Home.  These individuals can now more easily take a Siesta on a hot day.  This is an example of the permutations of the strategy set listed above.  

    My critique of modern climate economics is that so many researchers are content to estimate reduced form empirical regressions of the form;

    Person i's suffering on day j in location q =  constant +  b*Extreme heat on day j in location q +   U

    and take "b" as a physics constant.   Assume that "suffering" is measured by lost income and that this can be measured by the statistician.  

    "b" is an interesting reduced form parameter. It represents a slope that measures at a point in time how much suffering extreme heat has caused to the average person who lives at location q at day j.

    My Point  is that "b" is determined by all of the factors I discussed above.   As society's innovation and urban planning continues;  "b" converges to zero over time and this pace of "b" shrinking from a positive number towards zero over time is a measure of our adaptation progress.

    I want to see more climate economists exploring the microeconomic determinants of when does "b" change over time and when does it remain constant.   Government policies that distort adaptation decisions such as subsidies will likely turn out to be a major determinant of slowing down adaptation.

    As the marginal costs of climate adaptation decline, simple economics predicts that more individuals and firms will engage in adaptation (as they compare the benefits to the costs of adaptation) and as they engage in such self protection, the empirical reduced form researcher will estimate climate damage functions showing an ever declining amount of damage caused by climate change.

    The Climate Change adaptation literature needs to take basic microeconomic logic about rational choice more seriously and then we will make more progress understanding the pace of adaptation and the frictions that slow down adaptation.











  7. Is face to face interaction over-rated?   I am not talking about participating in the service economy (i.e getting a haircut), romance, friends and family interaction. I am talking about workplace face to face interactions and the vaunted "Water Cooler" (WC).  

    The cliche WC story has focused on serendipity and spontaneity that occurs when people casually chat about this and that.   This is not "directed search".  

    POINT #1;   Pessimists claim that the rise of WFH-HYBRID work will tax the Water Cooler such that organizations will become less productive.

    Counter-Point:    The pessimists forget what they learned about self-selection.  Workers know themselves, they know when they want to be social and when they want to be left alone.  Such workers also respond to incentives.  If the boss says; "hey , let's get our creative juices flowing".  Workers will respond and be charming and engage on those days.

    I claim that there is quantity and quality of F2F interactions.  The lazy urban economics productivity literature implicitly assumed that F2F interactions are homogeneous and are just a question of their count. So, if you meet with me 1000 times; the probability we have a breakthrough is 10 times higher than if we only meet 100 times face to face. I reject this.  Anyone who has met me knows that sharp diminishing returns kick in -- -in speaking with me!

    POINT #2;   The Water Cooler is a pre-AI, pre-UBER entity.   I am interested in directed search.  UBER matches drivers and riders to achieve efficiency criteria.  Why can't successful firms introduce a type of UBER AI matching to bring different workers together?  Why can't a boss make some recommendations about such matching?

    Point #3  Given successful within firm AI matching of Water Cooler Workers, why do they have to meet at work? Is the firm afraid of romance?   That would be a funny reason for the persistence of the office!

    Point #4;  Pessimists claim that we will get into a bad Nash Equilibrium such that social workers will go to the office and discover nobody to chat with as everyone else will be engaging in WFH on that day. In this age of AI Matching, can this misallocation really persist?


    So, to summarize this blog post;  The Quality versus Quantity tradeoff always exists.    Organizations have strong incentives to experiment here to see how to maintain their productivity under different organizational rules.  How firms adapt to the new opportunity created by WFH is fascinating.

    FINAL POINT:  Note that I set up this blog post such that the spontaneous face to face interactions occur by workers who work at the same firm. In this case, there is a residual claimant who has an incentive to get the rules of engagement right.

    What happens when workers work at different firms but work in the same city?  I doubt that spontaneous F2F is that important for these folks.  There isn't that much time in the day.   You might say that a Harvard economist and a MIT economist can have coffee and make research magic happen if they both go to work. I accept this example but this is a special example. Do Elon Musk's Tesla engineers hang out at the local bar looking to chat with engineers from other firms?   

    Since urban and labor economists do not have a real understanding of the production function of knowledge firms , we don't understand how the time allocation equilibrium induced by WFH will evolve over time.

    Of course, I do think that small firms will want to agglomerate close to each other for Labor pooling reasons but this is distinct from the gains from F2F interaction.  







  8. Millions of American workers engaged in Work from Home (WFH) during the pandemic.   WFH helped us to adapt to the risk of disease contagion.  Going forward, WFH will also helps us to adapt to the rising climate risks we now face.   Given that global greenhouse gas emissions are likely to continue to rise as the world’s population and per-capita income grows faster than the decarbonization of the world economy (declining GHG emissions per dollar of GNP), the climate change challenge will grow more severe over time. 

    New climate risk modelling firms such as First Street Foundation and Jupiter are mapping the risks of flooding and fire risk that every land parcel may face over the next decades. Of course, these science based models cannot offer certainty about emerging risks but they do play a “Paul Revere” role in educating both firms and workers about new place based climate risks.  You can type in any residential address here and First Street Foundation reports the property's expected fire risk and flood risk for free! Going forward, more and more property buyers will "do their climate risk homework" before making a large $ investment in a property.

    Before 2020, only the super rich and senior citizens were “footloose” and able to move to an area solely based on its amenities (or on its absence of risk).   The rise of WFH allows more and more American workers to live where they want to live as their daily commute to work is no longer looming over where they choose to live.  In our recent past,  the expectation that one would commute to work 5 days a week for 48 weeks a year pinned down a worker and her family to specific locations near the corporate headquarters. 

    Perceptions and concerns about emerging climate risks will influence where workers choose to live. Those who are risk lovers will actually be attracted to risky areas because property prices will be lower there! For those WFH eligible workers who are risk averse, their menu of locational choices will expand as they can live further from where they work. 
    While no two WFH workers are identical,  climate change will influence their locational choices.  For those WFH workers who are especially sensitive to air pollution, they will anticipate that elevated fire risk in the American West will create PM2.5 spikes during summer months.  They will figure out how to avoid these areas at those times.   For those WFH workers who are especially risk averse, they will be willing to pay more for housing in places where climate risk modelers predict that they face less risk.   Those WFH workers with niche preferences for leisure and exercise will have increased opportunity to live where they can engage in their hobby and meet like minded people. 

    As different workers choose their own best “climate niche”, this will improve their mental and physical health and raise their workplace productivity.  Surveys of young people have documented extreme ecological anxiety.  The ability to choose one’s own favorite location that will be likely to attract like minded people will help them to better cope in the face of the new risks we face. 

    If WFH workers choose to cluster in relatively safer parts of the U.S that feature less extreme heat, less drought risk, less flood and fire risk then firms will have an incentive to locate their future HQ2s and HQ3s closer to these areas.  Firms will benefit from lower turnover from less burnout and greater worker satisfaction.  Firms that expect that workers will stay with the firm longer have a greater incentive to mentor and invest in such workers.    Firms will use their corporate data on the location of their workforce and can use this information to decide where to open up HQ2s and HQ3s.    An old idea in urban economics focuses on the “chicken and egg” issue of whether people go where the jobs are or whether jobs move to where the people are.   In our emerging economy where more WFH are footloose, they will increasingly take into account the emerging climate risks and move to relatively higher quality of life areas.  As firms see these spatial clusters, the leadership can open up HQ2s closer to these worker hubs to increase face to face interaction and to buildup the company’s corporate culture. 
    Some worry that the rise of WFH is elitist.   As new WFH clusters form in climate resilient places, there will be an increased local service sector demand. This creates a local multiplier effect.  Well paid WFH workers will need local teachers living nearby, dentists, repair people, and there will be jobs in construction.  This increased local labor demand in a relatively high quality of life area featuring lower rents than in the Superstar Cities offers new opportunities for non-WFH eligible workers.
    Today, more educated people are more likely to work in industries and occupations that are WFH “friendly”.   If WFH facilitates adapting to climate change and facing less climate risk, then this creates an extra imperative for improving American education so that more young people can have the option to engage in WFH when they are older. 
    Before 2020, America’s most productive places were located in areas that face emerging risks.  There are worries about flooding in New York City and wildfire risk affecting the American West.  WFH accommodates our diversity.   Millions of workers will have the personal freedom to live where they want to live and this will reduce their stress during a time of rising risk. 

    Matthew E. Kahn is the Provost Professor of Economics at USC and the author of the New Book Going Remote.  This piece presents some ideas from his new book.  

    A Postscript:  Back in 2016, a prominent University of Chicago economist (who does not have a PHD from Chicago!) told me that snowstorms disrupt Chicago's productivity. I countered that I bet that he is even more productive on those days because he didn't go to work and nobody bugged him on such a day.  He just looked at me.  Flash forward to 2022 and I am even more confident about my 2016 comment.  The WFH option is now available to more and more highly educated people and they can "reoptimize" when a day turns out to be nasty to still be able to "seize the day" and get work done.   Of course a snowstorm can disrupt a dentist appointment but for more and more of the key tasks in the modern economy, these can be done "anywhere" and a footloose population will each make decentralized decisions for how to make the best of that day before the weather goes back to normal.   The reduced form empirical researcher then observes that the same Chicago snowstorm causes less economic damage and this is the empirical benchmark test that adaptation is taking place!  Mother Nature's punches cause less damage over time in an economy enjoying adaptation progress.   



  9.  I joined the USC Economics faculty in 2015 and Romain Ranciere also joined that year.  Permit me to list the impressive scholars who have subsequently joined our faculty.

    Marianne Andries 

    Tim Armstrong

    Vittorio Bassi

    Augustin Bergeron

    Fanny Camara 

    Thomas Chaney

    Pablo Kurlat

    Jonathan Libgober

    Robert Metcalfe

    Monica Morlacco

    Afshin Nikzad 

    Paulina Oliva

    Simon Quah 

    Jeffrey Weaver 

    David Zeke

    In July 2022, a star theorist will join our department as our newest hire.

    USC fascinates many people.  This list highlights that the hype about us is earned.  Note that we continue to build up strength in micro theory, macro, econometrics and applied micro.  A balanced, optimistic department.  

    The next piece of the jigsaw puzzle is to build up a PHD program that trains and places students to achieve their career goals.   

  10. The Los Angeles Times rejected my piece that I present below.  Of course, I'm trying to sell my new 2022 Going Remote book!!

     

    The New New Geography of Jobs


    LeBron James joined the Los Angeles Lakers in 2018.  He wanted to live and work in Los Angeles.   How many of us have compromised as we live in a place because our work is nearby? 

    Going forward, a silver lining of the pandemic is that more and more of us will have the option to live where we want to live as we engage in WFH on either a part-time or full time basis.  How will this new freedom affect our quality of life?

    More educated workers are more likely to be working in occupations and industries that are WFH “friendly”.  While a surgeon cannot work from home, a book author can.  More and more people have learned due to our experience we gained from the COVID lockdown that we can be quite productive while working at home.

    WFH workers reduce their weekly commute time.  The rise of WFH allows for staggered work hours removing many peak commuters off the roads.  The typical WFH worker saves perhaps 5 hours a week in commute time.   Will traffic speeds increase for everyone else?  This depends on whether more drivers take non-work related trips when road speeds increase. 

    WFH workers will have increased freedom in their lives to exercise more, to spend more time with children, to participate in family chores and to co-ordinate their leisure time with their nearby neighbors and friends.   This opens up the possibility of new civic engagement.   On days when a child is sick or bad weather days, the WFH worker can be productive and caring while at home.  This opportunity reduces one’s stress and improves one’s mental health.

    In 2021 and 2022, economists have used U.S Postal Service change of address data to study migration patterns.  We are already spreading out.  People have been moving to the exurbs and bidding up home prices there.   People will move to areas where they want to be now that they are “untethered” and can live where they want to live.  People who love to ski will move to such areas.  Those with an aging mother may move closer to her without facing the same labor market penalty as before the rise of WFH.  The ability to seek out cheaper housing will allow families to achieve their goals.  One economic study argued that when people live in larger housing that this causes them to have more children!

    During this time of deep concern about inequality,  will WFH be elitist such that those who are not WFH eligible will be left behind and housing will become unaffordable in areas far from the cities?   While these are open questions, economic logic offers several insights.  First, with the rise of new WFH communities, there will be a local demand for the service economy as construction workers, teachers and restaurants will be in demand. For those non-WFH workers with a taste for the area’s lifestyle, new opportunities will emerge.  Second, home prices do not have to soar in the medium term if real estate developers are allowed to build new housing in these places that have plenty of land. American’s NIMBYism could be a key constraint on how the rise of WFH affects our nations’ geography.

    Consider California.  Our state is suffering from drought right now and features extremely high home prices.  Farmers consume over 75% of the state’s water.  If some farmland could be rezoned as suburban housing, then water consumption would decrease and the supply of affordable housing would increase as that land is converted into housing.  The rise of WFH helps our state to adapt to climate change and to increase the supply of affordable housing!

    Third, our cities feature many durable buildings. If many WFH workers “head for the hills”, this opens up new possibilities for those who want to live in a San Francisco or a Boston to find housing there. This possibility only grows if commercial real estate in these areas is converted into residential buildings.

    In the medium term, the rise of WFH opens new opportunities for parents of young children. In the past, many women opted out of the workforce to raise children.  WFH opens up the possibility of working part-time for one’s firm while the kids are young.  A firm that anticipates this dynamic will continue to mentor such young female workers and this will close the gender earnings gap.  In the past, women disproportionately entered fields such as being a pharmacist because of the job’s flexibility. WFH opens up the possibility of more flexibility and thus accommodates our diversity.  

    In the past, African Americans were under-represented in the Tech Sector.  Relatively few African-Americans live in tech cities such as San Francisco and Seattle.  Few tech companies have headquarters in Baltimore or Detroit.  The rise of WFH raises the possibility of the “best of both worlds”.  One can live in Baltimore and work and physically appear from time to time at Amazon HQ2 or a future HQ3.  Such tech firms will be able to attract a more diverse workforce and depressed cities such as Baltimore will attract role models who boost the local tax base. 

    A “New” New Geography of Jobs is now emerging.  Those firms that recognize this point will build a stronger, more diverse and more loyal workforce. Those places that compete to attract such workers will enjoy growth and an influx of new blood.’. A stronger America emerges as people can live where they want to live and change their schedules to meet their goals and responsibilities. 

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