For those who wonder if a Department Chairman can get some work done, here is the introduction of my new paper that I will present at the Hoover Institution on 11/8/2017.
Urban Climate Change Adaptation and Local Real Estate Markets
Matthew E. Kahn
University of Southern California and NBER
Introduction
The major productivity hubs in the United
States are located in coastal areas such as San Francisco, Seattle , New York
City and Boston (Hsieh and Moretti 2017). In each of these areas, a set
of high technology firms and high human capital workers have co-agglomerated
creating highly productive clusters. These cities both attract
talent and the close physical proximity between these workers and firms causes
better matching between workers and firms such that cross-firm learning takes
place (Combes et. al 2012, Glaeser 1998,
Rosenthal and Strange 2004).
Such coastal productivity centers raises concerns
that natural disaster risk and climate change will impose enormous costs for
the U.S because it could disrupt economic activity. In early
September 2017, Hurricane Harvey shocked
the Houston economy and Hurricane Irma significantly damaged Florida. These
events highlight how natural disasters can impact real estate capital. While the science of climate change features
many open questions, we have an increased understanding that different
geographic regions will face more extreme temperature and rainfall events and
that tail risk of severe natural disasters could worsen (see https://www.ipcc.ch/report/ar5/wg1/).
The economic consequences of these geographic
shocks hinges on how and where we build our cities. Over decades, we have made durable investments
in capital and infrastructure that place millions of people and billions of
dollars of capital in areas that could be at increased risk of sea level rise
and other challenges posed by climate change (Changnon et. al. 2000, Pielke et.
al. 1998, 1999).
Zillow’s researchers have made scary
predictions about the aggregate capital losses (perhaps $400 billion in Florida
alone) that might occur in the year 2100.[1] This prospective research overlays maps of
current coastal assets with different scenarios of future sea level rise. An
emerging climate economics literature studies the historical relationship
between geographic places (such as nations or counties) and examines how their
economic growth and population growth co-varies with climate conditions (Hsiang
2016). This research has documented a negative correlation between average
temperatures (i.e summer heat) and economic growth (Deryugina and Hsiang 2014).
The Lucas Critique teaches us that past
historical relationships may not yield good forecasting rules if economic
decision makers reoptimize “as the rules of the game change” (Lucas 1976). While Lucas originally focused on how
individuals respond to changes in government policy, this same logic applies in
thinking through how individuals respond to changes in climate patterns.
Starting with the early work on rational
expectations, economists have emphasized that investment patterns are a
function of future expectations (Lucas and Prescott 1971). If investors “know that they do not know” the
likelihood of fat tail risks, they will be less likely to make irreversible
large sunk investments. Such rational
agents will instead seek a series of less costly investments that offer the
option to wait and see how the threat a specific area faces (Bunten and Kahn
2016).
Expectations of changing climate conditions
drives investment patterns and these investments facilitate the creation of
real estate structures, neighborhoods and cities that are more robust to the
major challenges that climate change will pose.
For example, areas in Florida that flood during hurricanes will be more
likely to face this same risk in the future.
Such geographic predictability creates the possibility for forward
looking people and firms to invest in several strategies to cope with
risks. These include; where we live, the
structures we live in and our investments in resilient infrastructure and
disaster preparation.
This logic challenges the recent climate
economics literature that implicitly assumes that economic agents do not form
rational expectations and thus do not plan ahead based on anticipated
trends. There is a certain irony that the “new climate
economics” implicitly embraces the 1950s model of cobweb expectations formation
as economic decision makers base their future expectations solely using the past
historical record.
This paper melds ideas based on the efficient
markets hypothesis from finance and the rational expectations model from
macroeconomics to generate a series of empirical hypotheses for testing whether
our urban economy and real estate assets are increasingly resilient in the face
of emerging climate risk.
While this paper is prospective, I present a
set of testable claims for judging the role of free markets for facilitating
adaptation at ever lower cost. A central
premise of this paper is that cities compete for jobs and the high skilled. If a city such as San Francisco becomes
riskier and less livable, then it could certainly experience a brain drain but
urban people will substitute to their next best alternative. If no alternative city is a close substitute
for San Francisco, then those who greatly demand San Francisco’s amenities do
lose the most. Such loss in consumer
surplus is a cost of climate change. In
his 2002 AEA Presidential Address, Sherwin Rosen (2002) wrote: “Markets
accommodate diversity by establishing prices that tend to make different things
relatively close substitutes at the margin.”
Some cities and neighborhoods may face extreme
climate induced challenges, other geographic areas may have a comparative
advantage in coping. If extreme heat is the challenge, then coastal cities at
northern latitudes may have an edge.
China has demonstrated that multi-million person cities can quickly be
built. The U.S is blessed with ample land.
If just ½ of Montana was built up to Hong Kong population density, 1.5
billion people could live there. This
example highlights how we might build our future cities if local land use
regulation does not inhibit such construction (Kahn 2011, Kerkoff, Prescott,
Ohanian 2017).
For geographic areas such as Phoenix that are
predicted to face increased extreme heat due to climate change, financial
economics makes strong predictions about how assets tied to Phoenix will be
affected. The theory of compensating
differentials and the efficient markets hypothesis predicts that asset prices
(i.e home prices) reflect all available information about the current and
future expected dividends. In the case
of real estate markets, the dividend is the flow value of productivity and
amenities enjoyed by living in a given location. If an area’s productivity and amenity value
is expected to decline in the near future because of climate change, then home
prices today will be lower to reflect this future reduction in the dividend.[2] If incumbent home owners are the residual
claimants on “bad climate news”, then they become an interest group lobbying
local officials to make investments that boost the city’s resilience (i.e
infrastructure that is more flood resistant, electricity systems that can
withstand heat and storms). Such individuals will demand adaptive products such
as improved housing and better air conditioning.
The demand for adaptation friendly products
creates a market for entrepreneurs who can supply them (Acemoglu and Linn 2004,
Kahn and Zhao 2017). I will discuss the
technological and entrepreneurial opportunities created by extreme climate conditions. Whether the best of these products can offset
much of the new risks that Mother Nature will expose us to remains an open
question. The ongoing decline in deaths
from extreme heat observed in both the United States and in the developing
world suggests grounds for optimism here (Baccera et. al. 2016, Burgess et. al.
2016). When we anticipate a trend, we
have the resources and the incentive to take actions to reduce our risk
exposure. The death count from natural disasters
declines with economic development and the diffusion of information technology
such as cell phones (Kahn 2005).
While this paper embraces an optimistic view of
our collective ability to adapt, some subgroups of the population face adjustment
costs that could limit their set of feasible adaptation strategies. Consider migration costs. The elderly and the less educated are less
likely to migrate. I explore the causes of such migration costs such as demographics
and built up place based social networks. For many people, their identity is tied to a
specific place (Akerlof and Kranton 2000).
I discuss emerging technologies that are likely to attenuate these
issues. A final subgroup of the
population who may face adaptation challenges are those with a propensity to
under-estimate emerging risks. This
group will neither support mitigation strategies such as a carbon tax nor will
they take pro-active costly steps to protect themselves.
Local, state and federal laws set the rules of
the game that affect the spatial equilibrium.
Building on past research on the
unintended consequences of government policy, this paper will highlight several
cases in which government rules impinge on adaptation. Free market adaptation economics offers new
insights about the costs of government activism (Kahn 2010).
[1] https://www.zillow.com/research/climate-change-underwater-homes-12890/
[2] For example of climate economics
that quantify how places are affected by natural disasters see https://www.nytimes.com/2017/09/29/opinion/puerto-rico-hurricane-maria.html?utm_source=NewsClips+Subscribers&utm_campaign=6afeaca480-EMAIL_CAMPAIGN_2017_08_22&utm_medium=email&utm_term=0_6ac49021ff-6afeaca480-154294709&_r=1. This literature abstracts away
from quantifying the cross-elasticity of where labor and capital flow to as the
origin area is shocked.