This blog post builds on my last post on a related topic.      My critics say to me;  "Matt, our centers of productivity are located in coastal places and these places face ever increasing climate risks.  In a Paul Krugman  style "History versus Expectations" economy, we have built our productive hubs in places that are now under siege and our economy could be wiped out by future punches."  Note that these persistence pessimists downplay the role of Expectations.  Lucas lives on.  Capital is finite lived and there is always a new generation of young people.  They don't need to follow the herd and sink as the seas rise.  

My counter-points takes several forms;

First, I can point to my 2017 JUE paper on Chinese Industrial Parks.  These recent phenomena highlight how new centers of local economic productivity can quickly be built. Yes, China's government has certain unique powers that U.S governments don't have but are you so pessimistic about the ability of private firms to co-ordinate activity and move to higher ground as they anticipate threats to where they currently locate?

Second, as I discuss in my 2022 Work from Home (WFH) book, the rise of WFH  will only increase our resilience to climate shocks for those who are eligible to work in such jobs.   WFH eligible workers have strong incentive to move to "higher ground" and service worker will follow them (the Moretti local multiplier effect revisited!).  

Third, forward looking firms have strong incentives to anticipate the new risks they will face and to invest in the fixed costs to continue to be productive.  See my 2016 paper with Josh Graff-Zivin.

Fourth, I can point to the Davis and Weinstein key work on city resilience in the face of enormous shocks.  The death toll from natural disasters declines with economic development (see my 2005 RETAT paper).   Was Nietzsche right?  What doesn't kill us makes us stronger?

Fifth,  U.S cities compete against each other to attract productive firms. If a firm such as Amazon is not productive in a specific location, it will look around the nation for alternative locations as a HQ2. This competition fuels resilience.  Competition is a key idea that is missing in the recent climate economics literature.  IO economists study the benefits of competition but environmental economists do not.  The latter are implicitly assuming that all firms and people are stuck in place.  Is persistence really that persistent? 

My work on climate change adaptation focuses on both people and places.  As I discuss in my 2021 Yale Press book, we need to hold more real options and not lock in to any one place. My book fleshes out all of the points I make in this blog post.  The ability to reoptimize as we learn about the spatial distribution of risks is crucial for adapting to the very serious challenge that we face.

When one drops the macro approach to measuring climate change damage (see Nordhaus and Weitzman) and introduces geography, the adaptation margins actually increase to almost infinity given the number of locations, building types, construction materials and permutations with club goods that can be used in the face of every location specific climate threat.   Such adaptation is costly but how costly in an economy featuring learning by doing and global supply chains?    This is the exciting research agenda that merits new work.   

The point of this blog post is to explore how to use the Rosen/Roback spatial compensating differentials model to evaluate the challenge of climate change adaptation.  In the original Rosen/Roback model, tied local public goods were exogenously determined, common knowledge, and not changing over time.  In English, San Francisco has great summer weather and Detroit does not and everyone knows this.  The final assumption in the model is that people face zero migration costs.  Given these assumptions, people arbitrage as they move across locations.  In equilibrium, nobody moves because they are indifferent between paying more for great amenities through lower earnings and higher rents in the places with great quality of life.  

Climate change shakes up the rankings of locations as Mother Nature punches some areas harder than other areas but the equilibrium pricing gradients adjust and the local land owners in the places that suffer more from the punches bear the incidence of these shocks.  This logic suggests that such land owners have strong incentives to seek out solutions both through private markets and through local government policy to offset Mother Nature's harder local punches.

This was the core logic of my 2010 Climatopolis book and forms my core argument for why I continue to be optimistic about our potential to adapt to climate change's very real challenges.  Here is my 2010 book and here is the two page summary.   Competition between cities in supply climate resilience (a increasingly valued local public good) helps to protect urbanites.  Many environmental scholars ignore the benefits of competition. If Miami fails to cope with sea level rise, other cities such as Atlanta gain population and jobs. This cross-elasticity is ignored in the simple "climate damage" regressions.  

We can relax many assumptions in the core model.  Suppose that people do not know each of the dynamic attributes of each location (the differentiated products).   If they know that they do not know these attributes, they will seek out new trusted information.  Entities such as First Street Foundation pop up to supply such information.

Suppose there is durable capital that turns out to be in the wrong place so that it now faces sea level rise.  Durable capital does not last forever and maintenance investment can be shrunk to zero to allow for faster depreciation. I explore that point in my 2017 paper with Devin Bunten.  In this sense, the spatial capital stock is reversible.  

 Suppose that poor people face higher migration costs and live in increasingly risk cities due to place based natural disasters.  We explore this in our new 2020 NBER working paper.      It is true that minority cities have been more likely to be hit with storms over the last 40 years.  If this triggers out migration, then given that the housing stock is durable --- rents decline in such areas.  This hurts minority home owners but helps minority renters if their gains from paying lower rents exceeds their losses from rising exposure to disaster risk. These nuances are missing in the popular media discussions.

There are certainly some people who deny the importance of the climate change challenge.  The climate economics literature has not fully explored the general equilibrium consequences of such individuals populating the economy. In our 2018 paper we explore how the market rate of adaptation innovation and the hedonic rental gradient across safe and increasingly risky cities is affected by the presence of climate skeptics.

The COVID-19 shock hit all spatial markets at the same time. In contrast, the climate change shocks feature some degree of spatial independence across the U.S and they are serially correlated over time (in English, the same places get hit again and again).  These facts mean that insurance markets can be used to offset the risks of the climate punches and that aggregate output is less affected by place based shocks. These points become even more accurate in a Work from Home economy.  Think. What climate shock could slow down Jeff Bezos and Amazon?    In our 2016 paper, we argue that larger firms with higher quality managers have a comparative advantage in coping with such shocks.  

Note how microeconomic ideas are at the core here.  Climate change shakes up the hedonic assignment problem of people across space.   People are finite lived. In an Over Lapping Generations model, there is always a new generation of young people choosing their own place to live their lives. They take into account the circumstances they encounter and anticipate where and how they will live their lives.  This leads  to migration to higher ground if land use zoning codes permit this.

Some reduced form researchers would say; "Okay , let's use the baseline hedonic gradients and a climate change model to see which areas lose from climate change.  I did these calculations in this 2009 paper.    The weakness of such an approach is that it forgets that the reduced form coefficients depend on the existing technological menu. If the set of air conditioners improves over time then the housing discount one receives for living in a very hot place will shrink over time.  This is Walter Oi's old point. Read his paper.  

If this discussion interests you, I encourage you to buy my 2021 Yale Press book titled "Adapting to Climate Change:  that expands on these themes.

 I have been to India once.  In this note, I would like to sketch out a research agenda on the microeconomics of urban slum dweller adaptation to emerging climate risk.  My points will only zero in on India's specifics a couple of times.  There are many slums throughout the developing world.  I will only focus on the challenge of extreme heat exposure.

My starting point is Robert Townsend's 1994 Econometrica paper.      His empirics focus on rural India as he tests for whether arrangements take place between farmers to smooth their idiosyncratic income shocks.  Risk averse poor people have an incentive to figure out ways to pool their incomes and then each take an average slice of the pie.   Of course, there are incentives issues that such a contract scheme could introduce moral hazard effects of devoting less costly effort.  

The risk pooling literature is an example of how markets are used to adapt to risk and such implicit markets become even more important if the variance of shocks increase and if people face subsistence utility levels (i.e risk of starving).

The relevant lesson that I take from Rob's great paper is that when people face risk they seek out adaptation strategies to reduce the risk's impact on their families. People are not PASSIVE VICTIMS.  So much of the climate change damage literature implicitly assumes that people are naive, passive victims. My 2021 Yale Press Book rejects this logic.  While my book mainly focuses on the United States, I argue that every day we build up more of a capacity to adapt to the punches that Mother Nature throws. In this sense, there is a "great race" taking place. Mother Nature is throwing harder climate punches but we are growing more resilient in handling those punches.   Our increased resilience arises due to human capital, markets and experimentation.

In the case of India's slums, here is a microeconomic perspective. My discussion slightly dovetails with past Google Scholar papers on the topic. 

1. Are urban slum dwellers aware of the weather patterns that their families face over the course of the day and by season?  Are they aware that the heat is growing worse?  If the answer is "no", then NGOs can play a key role here with nudging and informing households.

2.  What are the current strategies that slum dwellers have to protect themselves? Using sensors, we need new measurement of how hot it gets in different slum units over the course of the day. Who is home at those times? When is the high heat?   Do people take a Siesta then?

3.  How affordable are market products for slum dwellers?  How much disposable income do these families have to purchase such durables that Amazon sells?

4. Building on #3, are any Indian entrepreneurs designing cheaper adaptation friendly products?  The answer is "yes".  Induced innovation will deliver an improved menu here.     There is an interesting asymmetry in modern environmental economics.  NBER economists are happy to talk about induced innovation the carbon mitigation case but tend to ignore it in the climate change adaptation case.   The symmetry exists.  See my 2019 paper.

5.  If a representative set of Indian slum dwellers would be willing to wear a health sensor , their blood pressure and other biomarkers could be measured over the course of the day.  Alan Krueger's work convinces me of the importance of collecting real time indicators of happiness and well being. Patrick Baylis' work on tweets could be mimicked to further study real time well being dynamics in the hot places.   Of course, health diaries and medication consumption could also be tracked.

6.   In my Climatopolis book, I argued that the American System of Cities protects urbanites.   If one place is suffering, people can move away from it to a more resilient place. In the case of the India' s slums, do such Tiebout ideas hold? Do any slums have a geographic comparative advantage?  Are there any different architecture designs that reduce slum resident risk?  In the slums that are more climate resilient, can more housing be built there? What is the elasticity of the slum housing supply curve in more resilient places? Are there limits to resilient slum growth?

7.  Do children in slums face long run damage from extreme weather? Where are their schools?  Is their learning impeded by the heat? How do the elderly in slums handle the heat?

8.  Rents are cheap in the slums. This raises a slum dweller's disposable income.  What do these slum dwellers consume? Does a better diet or better medicines that they can better afford because of their low rents help them to offset the damage caused by extreme heat?

9.  Building on America's Move to Opportunity, will an ambitious JPAL team offer randomized rental vouchers to India's slum residents and encourage them to move to less climate impacted areas?  Over the medium term, will children in the treatment group be more likely to achieve their full potential?  

10. Does extreme heat lower slum dweller earnings?  Are they working outside?  Has the boss who hires them figured out how to "beat the heat"?  Given that extreme heat can be predicted, do workers work different shifts of hours to avoid the heat? 

NOTE that I haven't mentioned government once in this post.  The private sector really drives adaptation. Another way to accelerate adaptation here is if there is a pro-poor politician who wants to make her name boosting resilience. What could she do to "climate proof" a slum? What public goods would enhance resilience and how would she pay for it and who would pay that bill?

How does poverty impeded climate change adaptation and why?  For the non-poor who live in slums, how much better are they at adapting to new risks?

I have only explored extreme heat here. The same questions can be raised about extreme rainfall or other "fat tail" events.   If we anticipate that the we face fat tail risk, is the damage "fat tail"?  My simple answer is "no".  

UPDATE:  I haven't discussed rural to urban migration and such migration increases the population of the slums and climate change (through impacting rural profitability) can accelerate rural to urban migration. I discuss this issue at length in this handbook chapter.

I also think that it is interesting to collect matched slum dweller/slum unit data --- so to track people and the housing over time. In the year 2015, who lives in a particular slum unit? In the year 2021, who now lives in the same slum unit?   This approach would  mimic the strategy that Stuart Rosenthal follows in his AER filtering paper.

I would love to also see better data at the household level on the inventory of durables in the slum home. How many fans does the household operate?  Is there a fridge? Do the residents have cell phones? What is the temperature inside the unit on extremely hot days? What is the indoor PM2.5 level on outdoor polluted days? Are the prices of adaptation friendly products declining in India?  Who is the poorest slum dweller who can afford these products and how much risk do these products offset?

How able are urban poor people in 2021 to adapt to rising risk?  Is their life expectancy at risk? Or does India's urban growth help to boost their income and they are increasingly able to protect themselves because their incomes are rising and the real price index of adaptation durables are declining?  So, the Boskin Report on CPI bias is relevant for thinking about the Urban slum dweller's adaptation challenge. 

 With the upcoming publication of my 2021 Yale Press book Adapting to Climate Change,  I am making plans to follow the advice of Esther Duflo and Al Roth and try to be both a plumber and a market maker.  

I have created the new firm Climate Economics  to set up a vehicle to help me work with specific firms and entities that face their own unique adaptation challenges.