Dear Readers, In recent months, I have posted my public writing to my free Substack. I have such fond memories of Google Blogspot, thus it deeply surprises me that Google's search engine does a terrible job in helping those who search to find past blog posts. This deeply surprises me. As I age, I'm trying to post more dignified material to my Substack. I am sticking to what I know based on my ongoing research in microeconomics. Thanks very much for reading my posts. Best Regards, Matthew E. Kahn

I have moved my blog over to Substack (and I've lost many readers). Please join me there. Here is a recent column. The Wall Street Journal has published an important piece about how the high heat is reducing economic activity in Houston. The piece has a pessimistic tone that the heat melts the city’s infrastructure and shaves off economic activity as people don’t want to go outside. When microeconomists study consumer expenditure dynamics as people buy cars, go out to dinner and buy groceries. During hot spells, people are less likely to go out for dinner or to play multiple rounds of golf. A microeconomist would say that this evidence indicates that people have “state dependent preferences”. In English, this means that how much we enjoy a steak dinner at an outdoor restaurant depends on whether it is 75 degrees outside or 95 degrees outside (this is the “state of the world”). I certainly believe that hot and humid Houston is in a type of “macroeconomic Siesta” right now and this reduces economic activity. But, permit me to make some counter-points. #1 The money people in Houston do not spend on the hot July 28th 2023 is still in their bank account and they can spend it on a cooler November 5th 2023 day. Note this intertemporal substitution. The media focuses on the direct effect of the heat (that high heat is reducing economic activity today) but my counter-hypothesis is that it displaces expenditure to the future when it will be cooler later this year in Houston. So, will the New York Times write a piece saying that high summer heat causes a fall boom in Houston? I don’t think so. This type of cross-elasticity is ignored by the “climate crisis” focused media. #2 The WSJ interviewed a few people who want to leave Houston. As always, they are free to choose. As more workers can engage in WFH, those who hate the high heat will leave the city in summer. If they own a home, they can AirBNB it. WFH is a climate adaptation strategy as it makes people more geographically footloose. I discuss this in my 2022 book. #3 We have to live somewhere. Is Houston becoming more miserable to live in summer than other cities? If the answer is “yes”, then its home prices will fall. Here are some data from Zillow. Even with higher interest rates, I don’t see a collapse here in the Zillow index. Are you going to sell short Houston homes as your strategy to get rich? Incumbent home owners form a strong interest group to invest in adaptation strategies to protect their asset’s value. WHAT are possible adaptation strategies? #1 Road construction materials can be re-evaluated to reduce the urban heat island effect. Read this report. The City has strong incentives to embrace the cost-effective strategies discussed here. #2 Golf courses can open up part of the area and charge people to enter on hot days to use them as private parks. #3 Here are personal cooling strategies. On a personal level, of course the city needs access to strong air conditioning. Firms that make them and repair them will enjoy a boom. The Electricity GRID must remain reliable. The Climatopolis logic is that Houston competes with other cities to attract successful people and firms. The system of cities and the fear of brain drain gives Houston’s leaders and land owners strong incentives to be pro-active in adapting to climate change. Such efforts will be messy as there will be fights over who pays for such local public goods but the end result will be a more resilient Houston where the high heat causes less economic damage in the short term and medium term. This is the climate change adaptation hypothesis.

The New Economic Geography of WFH Matthew E. Kahn Over the last three years, companies from all over the world have learned valuable information about how their firm’s productivity and worker satisfaction is affected when workers can engage in Work from Home (WFH) on at least a part-time basis. Each firm faces fundamental tradeoffs in not requiring workers to return full time to the office. On the one hand, WFH accommodates worker lifestyles and responsibilities at home. WFH workers gain from commuting less often and some may choose to live further from their place of work because they commute in on fewer days. Firms with happier workers are less likely to face retention challenges and will pay less retraining workers. Given that WFH is a non-taxed perk, firms that offer this job amenity can be less generous in giving workers pay raises. Firms located in expensive areas can economize on expensive commercial real estate. If a firm requires that workers be in the office just half the week, then a firm can reduce its space requirements by 50%! On the other hand, firms benefit from face to face communication. Younger workers gain more from such mentoring. Building up the firm’s culture and monitoring worker effort is easier to do if workers are on site. Each company has a strong incentive to experiment with different workplace practices to learn what works best for their organization. The pursuit of profit actually accelerates this learning process. Economists are always looking for new ways to study firm dynamics. The rise of the WFH economy opens up many questions related to what types of firms will encourage their workers to engage in WFH. Famous executives such as Elon Musk at Tesla and Jamie Dimon at JP Morgan have been encouraging workers to return to the office. Why? Up until now, a lack of data has hindered the systematic analysis of what types of firms prioritize allowing workers to engage in WFH on at least a part-time basis. The newly released Flex Index provides a unique opportunity for researchers. As an urban economist, I am especially interested in the geographic determinants of why different firms engage in hybrid-WFH. The Flex Index provides data on each firm’s headquarters’ location. I focus on those that are based in the United States. I use data for 2528 of them. For this set of firms, I merged in three geographic variables. The first variable is the Zillow Median Home Price Index. Zillow uses a repeat home price index methodology to create a standardized “apples to apples” measure of home prices that can be compared across cities at a point in time or within a given city over time. In the analysis I present below I use Zillow data from December 2022. The second variable I merge in to the Flex Index is the percent of voters in the Headquarters State that voted for Joe Biden in the 2020 Presidential Election. The third variable I merge in from the Zillow data base is the city’s size. So, New York City is the first ranked city in the nation because it is the largest city. I use these data to test two hypotheses; Hypothesis #1: All else equal, firms are more likely to engage in WFH work if home prices are higher in the HQ City. Hypothesis #2: All else equal, firms are more likely to engage in WFH in more Progressive states. To test these hypotheses, I use a linear multivariate regression framework. To standardize the firms, I include industry fixed effects (this variable is in the Flex Index database). The dependent variable is a dummy variable that equals one if the firm’s workers all work on site. In the database, 39% of the firms report having the workers work fully on site. Table One reports four regressions with each column reporting a separate regression. I use the regression output to test the hypotheses presented above. Main Results All else equal, firms are more likely to engage WFH work if home prices are higher in the Headquarter (HQ) City. Based on the results in columns (1) and (3), I find that for the full set of industries and for the Healthcare and Biotechnology industry that workers are more likely to be engaging in WFH if home prices are higher in the HQ’s city. Based on the results in column (2), a doubling of home prices is associated with a log(2)*-.088 = -.06 or a six percentage point reduction in workers working solely on site. This effect is even larger for the Health Care industry. For this subset of firms, a doubling of local home prices is associated with a 12.7 percentage point increase in WFH. For the other two industries, I fail to reject the hypothesis that firms are not more likely to allow workers to engage in WFH as a function of local home prices. All else equal, firms are more likely to engage in WFH in more Progressive states. The test of this hypothesis is based on the coefficient on the 2020 Joe Biden vote share. Across all four specifications presented in Table One, I find consistent evidence that firms are more likely to allow their workers to engage in WFH when the HQ is located in a more liberal state. A ten percentage point increase in Joe Biden’s vote share is associated with a 3 percentage point increase in the probability that a firm allows its workers to engage in WFH on at least a part-time basis. Conclusion The Flex Index is a terrific new data source that allows empirical researchers to study how different firms are incorporating WFH into their work routines. In my 2022 Going Remote book, I hypothesized that the rise of WFH would benefit workers in high home price areas. The evidence presented here supports this hypothesis. Here, I also find a Red State/Blue State divide such that firms located in Blue States are more likely to allow their workers to engage in WFH. Future research should explain why we observe this fact. Are such firms in progressive states more concerned about work/life balance and gender equality issues? There are many open questions that improved data access will allow for us to provide credible answers.

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.

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?

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.

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).  

 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.   

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.