At USC Economics, I (in my role as department Chair) have a busy schedule. We are hiring new faculty, creating new curriculum and engaging in fundraising. Each day brings new challenges and new opportunities. On Tuesday, I will be interacting with our talented majors outside of the classroom in two different events;
Noon: Lunch with Undergraduates
6pm The Economics of Bitcoins
A department chair is a type of cheerleader. I try to convey an optimism and enthusiasm for what we are trying to achieve. I try to discourage free riding and I try to celebrate effort and public goods provision.
I keep thinking back to my undergraduate education and I ask myself; what events would I have learned from if I had had these opportunities 30 years ago? Based on my memories of my past, I keep trying to schedule meaningful (and fun) events.
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This new NBER paper looks quite interesting. Suppose that I am an inventor and I create a blood test that correctly detects your probability of having cancer .5 years from now. For my test to accurately predict your future risk probability, a trained nurse must administer the blood sampling. As I debut my product, I will make sure that the qualified nurse does the test. The Scaling up problem is that if my test starts to sell by the millions, its accuracy will decline because there aren't enough qualified nurses to administer my test.
So, this isn't a case of constant returns to scale. As my production rises, the quality of my product declines and the RCT economists would say that my pilot study's average treatment effect over-states the average treatment effect as I scale up the size of my market.
But is this true? In a rational expectations model, If I can pre-commit that my product will be "big" (both in scale and with regards to its benefits if administered by a well trained nurse), then young nurses will train to be experts in my technology and will obtain the human capital necessary to operate my product. In this case, diminishing returns to my product may not kick in. I cannot credible signal my future success then a co-ordination failure will occur and the empirical researcher will observe that the average treatment effect declines with my scale of production (because I can't find qualified nurses to administer it).
Alternatively, suppose that I only roll out my product in California. High quality nurses may start to move to California because they can work with my technology and deliver results. In this case, my product's average treatment effect will not decline with the scale of my sales.
So, when there is a complementarity between a treatment (such as my blood test) and human skills --- the key issue for scale up is "rational expectations and market size" or "migration and general equilibrium".
Scarce inputs will not remain scarce for long if we receive a "heads up" of rising demand (i.e high nurse earnings for skilled nurses) or high demand in given spatial location (i.e nurse salaries for high skilled nurses in California). As usual, the shape of the supply curve in the long run versus the short run plays the key role here. RCT results can be scaled up if the complementary input is elastically supplied. If it isn't then you must ask, why isn't it? What is the barrier to entry?
Note that this is a blog post. I am ignoring "essential heterogeneity" of those at risk to be treated. Instead, I am focusing on the endogenous determination of the treatment's quality (not the demander's response to this treatment). #supplymatters -
Sherwin Rosen was one of the greatest University of Chicago economists. While he did not win a Nobel Prize (he died at age 62 during the year when he was the President of the American Economic Association), his student Richard Thaler won the Nobel Prize and his student Kevin Murphy has won multiple major economics honors. I was not his best student but he continues to teach me new lessons about economics. I just read his 1997 paper on Austrian Economics. I now see that my Climatopolis work is a type of Austrian Economics.
My 2010 book (see the short version here) argues that the combination of rising urbanization, human capital and innovation together will allow us to adapt to climate change. Cities compete for the skilled and those cities that successfully adapt to the challenge of climate change will gain in human capital. Home prices (and thus income effects) will fall in areas that fail to adapt. This competition and the potential for migration creates a more overall resilient economy. While I cannot tell you today which cities will win this competition, I am very confident in this "Austrian" vision.
At the same time that I continue this work, there are plenty of NBER environmental economics researchers estimating reduced form single equation models of the general form:
economic outcome = a + b*climate conditions + U
for example, the outcome variable might be mortality, or worker productivity and the key explanatory variable might be annual days of the year that the temperature is over 100 degrees.
Researchers seek out "credible research" designs to estimate "b". This slope represents the current marginal effect of climate on an economic outcome. This research ignores cross-elasticities. If the climate is bad in Kansas but great in Oklahoma and expected to remain so, the negative shock to Kansas will actually create a boom in Oklahoma. This is a migration (zero sum game) effect.
Yes, a migration cost must be paid but this is a 2nd order effect.
Given my read of Sherwin Rosen's paper, I now see that Austrian Economics focuses on the evolution of the economic system. Entrepreneurs intuit that there is emerging demand for this product (think of Uber) and begin the experimentation to develop it. Some succeed and some fail. The system evolves to economize on scarce resources (signaled by prices) that may becoming increasingly scarce.
What can NBER's empiricists actually do here to satisfy an Austrian economist's vision? One empirical agenda is to study emerging venture capital fund investments. Another would be to study patenting behavior in key sectors affected by climate change. Investment under Knightian uncertainty is an under-researched topic. In this case, firms know that they do not know the future for certain but they foresee certain emerging trends such as increased drought conditions in the American West. Rather than being passive victims, some firms see this as an opportunity and this starts the endogenous R&D progress.
Note that the empirical researcher who assumes she is studying a stationary process will begin to observe that the "b" coefficient defined above converges to zero over time (perhaps not in a linear fashion) as lumpy new innovations are developed and brought to market. This point is one of our key points in this 2017 paper.
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Here are two photos I took of our new neighbor.
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The NY Times challenges the Coase Theorem today without ever mentioning Coase. Several examples are given of "neighbors going to war against each other" over low stakes stuff. To an economist, the puzzle here is why isn't there more "peace and love"? The fight didn't have to occur. Instead, they should have traded with each other. Let me set up an example and let's think this through.
You and I are neighbors and I use a leaf blower on Saturdays that makes you nuts. You suffer $80 of pain each time I use it when you are home. I would suffer $50 a week in "pain" if my lawn is filled with leaves. Given that we are neighbors and can easily communicate and you know that I have the right to use my leaf blower and you know that I"m the cause of the noise, we can solve this issue by trading. Suppose you give me $30 each week and in return I make sure to only use my leaf blower when you aren't home. Both of us are made better off by this "trade".
Of course, you would prefer not to pay me but nothing is free. Why don't these offers occur more often?
Another example is the famous fight between Bono and Billy Squier. Note that my solution involves no lawyers, no broken ribs and no laws. Yes, there is a mutual agreement on who has the "property rights" . When you enter a Starbucks, the buyer of a cup of coffee knows that he does not have a right to a cup of coffee. What is the difference between local noise pollution and a cup of coffee?
As Coase knew, much of the modern economy is actually a fight over who actually has the initial property rights. If we could all commit to a common agreement over who owns what and never renege on this deal, our society would be much richer.
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This report card suggests that I need to invest more time in the quality of my Ph.D. students.
You can also obtain rankings of top institutions and economists in the regions of your affiliated institution(s):
- United States (you rank 203 of 10448, top 2%)
- California (United States) (you rank 36 of 1080, top 4%)
- Pacific States (United States) (you rank 37 of 1280, top 3%)
*: fewer than 5 scores available for this institution.
Institution h-index is defined differently from author h-index.Similarly ranked authors
These peers are ranked around you and are listed in random order:
- Giovanni Peri
- Martín Uribe
- Laurence Ball
- Athanasios Orphanides
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- Andrew Abel
- Roger B. Myerson
- Richard H. Clarida
- Harvey Rosen
- Edward E. Leamer
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- Viral V. Acharya
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- Norman V. Loayza
- Narayana Kocherlakota
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- Jong-Wha Lee
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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 MarketsMatthew E. KahnUniversity of Southern California and NBERIntroductionThe 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. -
Michael Greenstone has written an excellent piece about how climate change is likely to affect marathon races and the runners. While the headline hints at "doom and gloom", the real meat of the article is highly optimistic about our ability to adapt to this outdoor stress. The piece has a cliched paragraph listing the litany of challenges we will face but the historical record highlights that the death rate from disasters is declining quickly over time and that induced innovation will step up to address several of the challenges that climate change will pose.
Let's be clear, this is the Julian Simon vs. Paul Ehlich debate all over again. Economists, are you with Simon or not? My 2010 Climatopolis book anticipated these themes. In late 2016, I sketched my evolving thinking in this PERC piece.
Back, to Dr. Greenstone;
Here is a direct optimistic quote:
Marathons will be no exception. The organizers of the New York race will probably not want their event to be one where it is difficult, or perhaps even impossible, for people to set their personal best or to lower the world record. So they may want to adapt by moving the marathon to later in the year.At the same time, runners may switch from the New York City Marathon to others held in cooler climates to find the perfect temperature at just the right time of year. Could a Montreal Marathon be among the world’s most prestigious by 2050?Athletic equipment companies will surely develop new technologies to aid adaptation as well. For runners, the breathable mesh and cooling towels of today could easily be traded in for shirts with built-in air-conditioners. Seem far-fetched? They already exist. Indeed, I was one of the authors of a recent study of just how powerful a role technology can play in helping people adapt to warmer temperatures. For example, the rise of air-conditioning has reduced the mortality consequences of extremely hot days in the United States by more than 70 percent since 1960.Marathons and marathon runners appear likely to be able to adapt to climate change with relative ease through changes in when, where and how.
