1. 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.
  2. 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?
  3. 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.











  4. 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.  







  5. 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.   



  6.  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.   

  7. 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. 

  8. Tomorrow, the University of California Press will publish my Going Remote book.  In February 2021, Johns Hopkins Press published my Co-authored "Unlocking the Potential of Post-Industrial Cities" and in March 2021, Yale University Press published my book; "Adapting to Climate Change".

    Why did I write these 600 total pages of stuff?

    The Ongoing Challenge faced by Baltimore, Cleveland and Detroit

    I spent two years working at Johns Hopkins University and I lived in downtown Baltimore for a year before the pandemic hit.  I wrote the Unlocking book because I recognized that I was living in a city that was stuck in a poverty trap. Very few people were actively thinking about the basic building blocks of economic growth namely attracting productive firms, encouraging private capital investment in firms, and upgrading old durable real estate capital. Young people were not investing in their skills because there were few local private sector jobs.  The basics of building a high quality of life city focused on improving school quality and safe streets and clean air and clean water were not being fully addressed as Baltimore's officials showed little interest in experimentation and formal evaluation of different program's effectiveness.  

    Adapting to Climate Change

    My book is an optimistic study as I synthesize what I have learned over my 15 years of researching and reading the climate change economics adaptation literature.   

    Name any climate change challenge you can think of ranging from sea level rise, to extreme heat, to increased fire risk and I discuss how capitalism helps us to adapt to the challenge.  For capitalism to help us to adapt, prices must be allowed to signal scarcity. If drought occurs, water prices must rise. If real estate in a specific location faces new risk, then the price will decline and the new buyer will be a person with an edge in adapting to the risk.  Such an edge can be built up through developing skill or if there is sufficient demand to protect properties that can flood then it becomes profitable for firms to enter the "flood protection" business to protect such home owners.  As we learned from the development of the COVID vaccine, our economy features amazing adaptation potential.

    Climate adaptation optimism is still viewed as politically incorrect stuff.  Why?  Through rising incomes, access to markets and rising educational attainment, our ability to adapt to new shocks increases every day.  

    Going Remote

    This is a book about the urban and environmental implications of the persistence of WFH in a post-COVID economy. I argue that the "experience good" effect that we enjoyed during COVID will offer huge medium term gains for our quality of life going forward.

    Cities such as Baltimore will experience an influx of WFH workers as people who want to live in that city because they desire its affordable housing and culture and lifestyle can now live and have a good job as they work for a Amazon HQ2 or HQ3 of Google in a 2 hour drive in some direction.   The unbundling of where we live from where we work will help cities that have failed to attract modern companies to make a comeback if they offer good services and good quality of life.  If a Baltimore attracts more talent to live there, then this will stabilize the taxbase and increase the demand for the local Consumer City. This will create a service sector multiplier effect and increase opportunities for those workers who are not WFH eligible.   As young people foresee that they can be WFH workers if they have the skills, they will invest more in themselves and their parents will seek better schools for them. This will put pressure on the local public sector unions to teach!

    So, there is a clear link between my Unlocking book and the Going Remote book.

    The link to climate change adaptation is that a WFH eligible workforce can spread out. For those who seek to work for a Seattle firm but fear how climate change will impact Seattle, they are free to choose and "head for the hills".  The permutations become huge when you can work for one firm and live elsewhere.  Milton Friedman's "Free to Choose" becomes a more accurate description of our economy and this increases our wellbeing.

    In 2019, the great jobs were in congested, expensive Superstar cities that faced increased climate risks.  WFH unbundles where we live from where we work and opens up many, many possibilities for how we configure our lives.  This represents a significant real pay raise!

    I am not a modest man. I view my three books as creating a series of empirical predictions for how the urban system of cities will unfold over the next decades.  I would hope that my teacher Sherwin Rosen would respect how I have taken his hedonic equilibrium ideas and built on his edifice.  




  9.  The New York Times has published a good opinion piece by a Professor of English on the unintended consequences of federal subsidies and regulations for living in flood plains.

    In this brief piece, I am not talking about surviving a flood.  Instead, I will discuss how flood risk (ex-ante) and flooding affects the real estate market and the distribution of income.   In an increasingly risky economy, who should own the risky assets?

    When one owns an asset, there is uncertainty about how the price of the asset will change over time.  A share of Tesla can either rise or fall over time.  A home's value can go up or down over time.  The asset's owner is not guaranteed that "nothing bad" will ever happen to the home.   Under the logic of the efficient markets hypothesis,  expected future risks to a specific property will be reflected in the value of the asset today.

    For example, if crime is expected to rise in the year 2024 in a Los Angeles neighborhood because the police have announced that they will no longer patrol there --- economics predicts that home prices for such homes in April 2022 in these areas will decline now to compensate buyers for the emerging risks as crime rises. Those who buy the homes today are "adults" and know what risks they are taking on.  Economics predicts that self-selection will arise. Those with an edge at defending themselves (so think of Clint Eastwood or Bruce Lee or the Terminator) will be more likely to buy these homes due to comparative advantage in self-defense.  A home buyer can buy one of these discount homes and install security cameras and use a private car to drive one around to avoid contact with potential robbers.

    This same logic applies in flood zones.   Professor Rush gives some quotes of home owners who are frustrated that the value of their home has declined because of increased flooding.  Are they victims who the rest of society should subsidize?  These individuals chose to own when the opportunity cost is that they could have rented and held a more diversified portfolio.  Most poor people are not home owners.  This means that middle class and richer people own these at risk to flood homes are they really the "vulnerable" people who deserve federal handouts for choices they voluntarily made?

    I think the answer is no for several reasons.  First, none of us flip "one sided coins". If their homes had tripled in value, they would not have given 50% of their equity gain back to us.  These home buyers want to keep their capital gains and nationalize any losses.  This subsidy of risk taking creates moral hazard effects.  

    These home owners could have sold their homes previously and rented in the same area to reduce their risk exposure and to keep their social network and commute.  These home owners can sell housing equity in their home to outside investors to diversify their portfolio.   If home owners do not engage in any of these risk diversification strategies, are they victims?

    Note that up until now I have focused on the incumbent property owners who are increasingly aware of the flood risk they face both from their past experience and because of new entities such as First Street Foundation's Flood Score.

    As I argue in my 2021 Yale University Press book Adapting to Climate Change, we will be better able to adapt to flood risk if society agrees on evolving flood risk maps such as First Street's that show property by property the expected risk.  Banks and insurers should be allowed to risk price based on these such that riskier properties face higher interest rates, lower loan to value ratios and higher insurance premiums.    Home buyers who are quoted these interest rates and insurance premiums will quickly figure out that the property is risky and these Bayesians will update their beliefs and bid less for the home.  The owner of the home will receive a lower sales price for the "common knowledge" that the home is riskier due to climate change.  

    The Banks and Insurers will act as the "adults in the room" nudging real estate buyers to reduce their demand in risky places and increase their demand for housing and real estate in safer places.  If we change our zoning codes to up zone in safer places featuring less fire risk, flood risk and extreme heat then a more elastic housing supply curve emerges there and prices of real estate will reflect demand and increased supply. Worries about climate gentrification on higher ground will be muted.

    Will flood zones be emptied out?  No, I predict that in beautiful and productive locations that happen to be flood zones, single family homes that are adjacent to each other will be purchased and knocked down. They will be replaced with wetlands and tall buildings that have empty lower floors to reduce building damage.  Civil Engineers will figure out how to have productive real estate assets that are acclimated to the risks.

    The key to this smooth adaptation dynamic is for government to retreat.  Government is taxing people on higher ground to subsidize people taking risks.  Why is that fair?  Mancur Olsen  asymmetric interest group logic can explain this political equilibrium but I believe that reforms will occur as tax payers realize the size of the subsidies we are paying to the risk takers.

    The next steps in the climate change adaptation research agenda is to focus on induced innovation. As more home owners face flood risk, this creates a demand for solutions and this creates profit opportunities for innovations that offset this damage.  Do you doubt that capitalism will deliver here?

    Finally, note that at no time in this piece did I discuss major engineering projects.  Such projects can protect an area from flood risk but I argue in my 2021 book that they should be funded locally. Such projects protect local land and home owners own those and thus should pay for their own defenses. The central government can provide the expertise and human capital but local public goods should be funded locally.

    One More Point!   Those who cry that climate change is lowering the value of homes in areas that now face flood risk ignore that there are other homes on "higher ground" whose values rise because they are relatively safer. It is an exaggeration to call this a "zero sum game" but even good economists ignore this cross-elasticity point.  General equilibrium effects always exist.  












  10. This will be a "big think" blog post that shares my thinking about this March 2022 Nature Human Behavior paper titled "The data revolution in social science needs qualitative research".

    Permit me to focus on one example.  Consider a sample of 5,000 equally talented and ambitious 18 year olds.  Each has graduated from High School and each is considering applying to the University of California.  The students differ that some are Asian and some are Hispanic.  To simplify, let's assume everyone is a member of one of these two groups.  

    The researcher observes that 72% of Asians 18 year olds in the sample apply to the University of California while only 32% of Hispanic 18 year olds in the sample do.

    A qualitative researcher would take the next step of interviewing a random subset of the Asians and the Hispanics in this sample to ask them various questions about their beliefs, life goals, family circumstances and several other nuances that cannot be captured by a standard demographic survey.

    A field experiment researcher would proceed with a different strategy.  She would take a new sample of 5,000 equally talented and ambitious 18 year old Hispanic and Asian students in the next year and randomly assign a subset of each group to a specific treatment such as a 20 minute information course on understanding the application process to the University of California and the gains to attending an elite 4 year college.  The control group would not receive any of this information

    The field experiment researcher would observe the following pieces of information;

    X1 =  percentage of Asians who apply to the University of California given random assignment to the treatment group.

    X2 =  percentage of Asians who apply to the University of California given random assignment to the control group.

    X3 =  percentage of Hispanics who apply to the University of California given random assignment to the treatment group.

    X4 =  percentage of Hispanics who apply to the University of California given random assignment to the control group.

    Suppose for this new sample of young people that the researcher observes the following facts;

    X1 =  74%

    X2 =  72%

    X3 = 70%

    X4 =  32%

    These data immediately indicate that the intervention had a much larger impact on the Hispanic teens than on the Asian teens.  The intervention closed the gap.

    What is My Point?

    I am interested in asymmetries in social science.  Economists assume that people know themselves and have a life plan and a "conception of the good life" and they strategically make their choices such as who they marry, where they live and how much education to attain with their plan's goals in mind.  The observer knows that she does not know what is each person's life goal. Social scientists learn about people based on the choices we observe them make.

    In the example sketched out above, a field experiment researcher seeks to explain the "education gap" and to test for what might be cost-effective strategies for closing this gap.  How did the field experiment researcher choose the specific intervention that turned out to be effective?

    One answer is introspection. Another answer is the researcher has read journalistic accounts explaining why some talented teens do not apply to great schools.  Another answer is that the field experiment researcher has engaged in her own qualitative research to list out the menu of possible explanations for the education gap.  

    The question here pertains to how quickly will the Big Data researcher zero in on the right treatment to pilot?   If the Big Data field experiment researcher is baffled concerning what treatment to pilot, then qualitative research is crucial for narrowing down the set of strategies.  

    Given the publication incentives of academic researchers and given their finite research budgets, they have strong incentives to pursue treatment effect designs that are effective. Researchers cannot publish papers that say; "I tried this crazed treatment and it turned out to have no effect.".   The self doubt of the field experiment researcher leads her to pursue qualitative strategies (at least on a small sample) to reduce her risk exposure of investing her time and $ in a project that doesn't yield credible statistically significant results.


    "Dynamic" Facts in the Social Science

    Note that the effective intervention means that the "Old fact" (that eligible Asians are much more likely to apply to the great colleges than eligible Hispanics) is no longer a fact going forward as the effective intervention brings about convergence.   In Physics, this does not occur.   


    Final Point and a New Thought

    When the field experiment researcher knows that she does not know the causes of behavior (so in this case why Hispanics are not often applying to the UCs), she has an incentive to invest in qualitative research to help hone the actual treatment.  

    In the example I have sketched above for both Hispanic and Asian teens in the treatment group (so they received the information session) who both choose to apply to the UC and not apply , I would find it interesting to interview a subset of them.  There is a jump from the "intention to treat" to "treatment status" and I don't think we understand what types of personalities and under what circumstances are people eager to play along and try something new.  








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