1.  Applied economists are "detectives". We know that we do not know your preferences. If we could learn about your willingness to pay for market goods such as cell phones or for non-market goods such as clean air and safe streets, then both businesses and governments will demand our services. Economists look for clues and design experiments to learn about people. For example, if a person buys a $5 Starbucks drink then we immediately learn that a lower bound on how much she is willing to pay for such a drink is $5. If a week later, when the price is now $7 if she no longer buys it then, we now have learned that we can bound her willingness to pay for this product between $5 and $7 dollars. This book applies this revealed preference logic to dozens of problems to teach you how economists learn about people by watching what they choose under different circumstances.

    If the following revealed preference problem interests you, you can buy my Amazon book;  "An Introduction to Empirical Microeconomics" for $1 on Amazon.


    In the typical intermediate microeconomics class, the teacher tells you the consumer's utility function and the consumer's budget constraint and tells you to solve for the consumer's optimal behavior.

    My entire book studies the inverse of this problem. I tell you what the consumer chose and what her budget constraint was.  As the budget constraint shifts (because of changes in the economy), I ask you to solve for what you have learned about the consumer's utility function.

    This is an important exercise because in this age of Big Data, this is what applied economists actually do for a living.

    Here is one example from my book.  When I revise this example, I will include a utility function and ask the reader to put bounds on the consumer's marginal rate of substitution at various points of the domain of the function in pizza, cell phone minutes consumption space.


    New Problem

     

    Maurice gains utility from eating pizza and talking on his cell phone (measured in minutes talking).  He has an income of $300.  The market price of pizza is $1.   Maurice does not own a cell phone.  The cell phone company offers him three different annual plans.  The cell phone company knows that people have different preferences over pizza and talking but doesn’t know “who is who”.

     

    Plan B:  Maurice pays $50 for the phone and he must pay 20 cents per minute of talking.

     

    Plan C:   Maurice  pays $120 for the phone and he must pay 0 cents per minute of talking.

     

    Make a graph with pizza consumption on the vertical axis and minutes talking on the horizontal axis.   Graph the two plans in the same graph and label each.

     

    Answer

     

     



     

     

    Take a careful look at the figure above, do you see that plan B dominates plan C for people who want talk less than 180 minutes on the phone while plan C (the free talking plan) dominates plan B for those who want to talk more than 180 minutes.

     

    How do I see that?  Consumers gain utility from eating pizza and talking on the phone.  Consider a person who wants to talk 500 minutes on the phone. If she chooses plan C, she will have 180 pieces of pizza while if she chooses plan B, she will have 250 - .2*500 = 150 slices of pizza so this person will pick plan C.

     

    The two different plans create a separating equilibrium as those who “love to talk” will choose plan C, while those quiet people will self select to choose plan B.

     

    Note that the two plans cross each other at the point pizza = 180 and minutes = 350.  So, anyone who is willing to pay more than .2 slices of pizza to speak for a 181st minute should pick plan C over plan B.  Why?  The price of a marginal minute under plan B is .2 slices of pizza while the price of a minute under plan C is 0.  If you choose plan C over plan B, you reveal you value an extra minute of talk more than the marginal cost (measured in pizza) of purchasing that minute.

     

     

     

     

     

    New Problem

     

    Building on the previous problem, now suppose the cell phone company offers a modified Plan B such that the price is set at 10 cents per minute.  Under what set of circumstances will this new pricing policy be profitable for the firm?

     

    Answer

     

    First, let’s graph the original plans and the new pricing plan.

     


     


     

    Under the new modified plan B, the budget line is less steep because cell phone talkers only now have to sacrifice .1 slices of pizza per minute they talk versus under plan B when they had to sacrifice .2 slices.

     

    Notice several points based on the graph.   All of those people who picked plan B will now prefer Modified plan B because it offers a lower price per minute.  Note that the green line (modified plan B) lies above plan B so it offers more pizza and cell phone minutes. 

     

    Point #2 is that some Plan C people will now substitute to modified plan B.  These are the people who seek to talk for less than 700 minutes (where the green line and red line cross).  Those people who love to talk will choose plan C.

     

    Could it be profitable for the cell phone company to offer Modified plan B rather than Plan B?  Note that by lowering the price of a cell minute, people who move from plan B to modified Plan B will talk more minutes.   Also note that people who substitute from plan C to modified plan B will now pay per minute. It is true that the company would not earn the $120 per plan C enrollment. The rational company would trade this off.

     

    My goal here is to teach you how a company uses a non-linear pricing strategy to allow it to learn about its heterogeneous customer’s preferences. By offering these different plans, the diverse population reveals “their type”.

     

    The cell phone company would observe the percentage of all customers who choose each plan.  Since the cell phone company knows your zip code (because they mail you a bill), it can also calculate the percentage of all customers who choose Plan B, Modified Plan B and Plan C by zip code.  Such simple data could indicate patterns for example zip codes with more teenagers may feature a larger percentage of households choosing plan C.  Such information is useful for future marketing campaigns.

     


  2.  General Motors has announced that it will only produce electric vehicles starting in the year 2035.  Suppose that there no more new fossil fuel vehicles purchased by U.S consumers in the year 2035 and going forward.  There are 270 million vehicles in the United States right now and most of them are used.  This webpage says that 13 million new vehicles are purchased each year in the U.S.

    In the year 2040 as the gasoline vehicle fleet ages,  the count of gasoline stations will decline (especially in EV areas such as West Los Angeles).  As the count of accessible gaso stations declines, the Gary Becker full price of refueling (including the time it takes to get to a gas station) will increase.  This will be a tax on poorer people who own the used gasoline vehicles.

    Given the complementarity between gas stations and driving gas vehicles, interesting issues will arise concerning local market power and price gouging. Individual gas stations will charge more for gas (as predicted by the Hotelling retail model) and this will further nudge some drivers to substitute to EV vehicles.  

    An interesting question is what will be the value of used gasoline vehicles in the year 2040?  If their prices sink (because of carbon pricing and the dearth of gasoline stations), then a future entrepreneur will purchase millions of these vehicles and prepare to ship them to the developing world.  This entrepreneur's path to wealth will be accelerated by the demise of the local gas station.  

    The economic incidence of the rise of new EV market merits new research.  



  3.  The New York Times has published an important piece on free speech on American University campuses.  I'd like to share some thoughts from the perspective of urban economics.

    Back in 1986, I was living in London because I was a Visiting Student at the London School of Economics. On some weekends, I would go to Hyde Park or Regents Park and there would be a small crowd listening to a charismatic speaker standing on a box and he would be talking about Karl Marx or Ms. Thatcher.

    Standing on his "soap box", the park solved a co-ordination issue.  Some people showed up to hear him speak because they thought it would be interesting. He showed up to speak because he anticipated that there would be a crowd.  His platform was local and fleeting (in the space and time dimension). Nobody recorded the event and nobody who wasn't standing there heard it.   Think of the Beatles Song Eleanor Rigby! 

    By giving his talk in a big city (i.e London), this created an incentive for the speaker to prepare his remarks and invest some time to give a good talk.  Similar to a restaurant competing for business, this public speaker was competing for attention.  This was a local market because people from Scotland or France were not going to travel to London to compete with him.

    Flashforward to 2021 and the Economics of Superstars now plays out.  In an era with Zoom, YouTube, blogs and Twitter, this public speaker from 1987 would now face much more competition for attention but there are billions of people who might use Google to "find him".

    Note that Google directs traffic to his platform if their algorithm identifies him to be a star.

    This introduction is relevant for the New York Times piece.  University students at Columbia and NYU are concerned that their famous universities are offering a platform to speakers who they disagree with. If these students knew that nobody would listen to a speech, then I doubt that they would bother devoting effort to expressing their concerns.

    When a famous University allows its "platform" to be used to host a zoom talk, then this has several effects.  Moderates who do not have a prior opinion on an issue are more willing to take the content at face value because the famous University has implicitly endorsed it.  So, my claim is that the same message has a larger treatment effect on a person's worldview when a "Harvard" is the host for the same talk.   Has this been tested using a statistical research design?

    With a Zoom talk, it is recorded for posterity and can be played over and over again and can take on a life of its own.  Given that social scientists have not made much progress in understanding "social interactions" , would we have a more stable society if there are no permanent recordings of charismatic speakers?   Do we want less persistent shocks to occur to our society?    

    If Sarah gives a speech in Hyde Park London in 1987 that is not recorded, this is a less persistent shock then the same talk at LSE in 2021 on Zoom.

    Returning to the University Zoom meetings, what is the University trying to maximize here?  Dialogue?  Mutual respect and understanding?  Debate?  Donations to the school?  

    Each university has a reputation and a platform.  While a cure for cancer is not controversial (except perhaps the ethics of who are the guinea pigs for being the first to take the experimental drugs), how does a university use its platform for controversial topics?  Would there be a greater willingness to explore free speech if the records created at the event were not permanent and at zero cost able to be shipped by email anywhere in the world?

    Returning to urban economics, has the reduction in the marginal cost of shipping ideas to zero actually diminished free debate as people fear showing their true line of thinking?    

    Did the high cost of "shipping ideas'" reduce political correctness back in the 1980s?

    Or is this logic backwards?  Since idea "shipping costs" are now zero, there are new entrants who want to give extreme Zoom talks in order to be a partisan superstar?  Could both stories be right as some people "exit" the platform domain and others will "enter" because of the permanence and low cost of distributing zoom content?






  4. While every Mayor of a Big U.S city would love to receive an unconditional cash transfer from President Biden, this blog post will not explore this idea.

    As Mac and I discuss in our 2021 Johns Hopkins University Press book, Unlocking the Potential of Post Industrial Cities,     cities such as Baltimore, Cleveland and Detroit face several common challenges related to the local economy, the local housing stock, local infrastructure, local quality of life, and local investment in health and human capital.  

    The Biden Administration through the proper use of incentives can nudge each of these cities to "raise their game" and this will improve local quality of life for the rich, middle class and poor in these cities.

    Baltimore's murder count each year has been higher than what would be predicted given the city's population.   A simple statistical approach would regress a city's annual murder count on its population.

    Murder count for city j in year t =   constant_t +   b_t*population of city j in year t  +  error term for city j,t

    The slope "b at time t" would be positive.   Given that Baltimore has 600,000 people, the statistical analyst would predict that Baltimore's murder count should equal =  constant + b_t*600000  but the analyst would see that Baltimore's murder count is way higher than this prediction.

    The Biden Administration should work with the City of Baltimore to adopt murder prevention strategies that comply with the law and protecting citizen's basic rights.

    The Biden Administration could convene a national group of experts to create a Murder Taskforce to bring various social scientists together to identify different crime reduction strategies that have been rigorously tested in terms of "causal effects" and ranked relative to their price tags.  For example, if method A is a "stop and frisk" approach for finding illegal guns and method B is a "night basketball for teenagers" approach; what are murder reduction benefits from each of these and would be the total cost to scale these up to have an impact at the city level?  

    Once the Taskforce has ranked proposals and considered their intended and unintended consequences, the Biden Administration could offer a 80% subsidy to cities that adopt these programs.  The Biden Administration could require that each participating city collect baseline data on people and places within the city that are high crime areas and devise a scientific data collection effort to analyze whether the same intervention (phased in in different high crime cities) actually achieves the expected crime reductions.

    This is the scientific approach for how the Federal government uses its unique powers to improve city quality of life.   In future blog posts, I will discuss other strategies to boost the post-industrial cities' quality of life.

    A subtle reader will note the "recipe" here.

    The Federal Government solves the co-ordination problem of bring the best minds together to sketch out the possible strategies for mitigating wicked "urban problems".

    The Federal Government brings in the City Mayor's team to be briefed on the right strategies to proceed.

    The City Mayor receives a take it or leave it offer to implement the advice.  A deep subsidy is offered but there are strings attached. The City must collect real data to track whether the intervention is effective.  This creates accountability as cities are benchmarked relative to each other.

    The national news can play a muckraker role here reporting on progress (or the lack of progress).  Real estate investors and parents (perhaps considering whether to send their kids to school at Johns Hopkins) will pay close attention to whether urban challenges are improving.

    The Federal Government has unique powers to standardize data collection, to incentivize policy change and to share information about "what works".  For too long, Mayors of cities have had too much discretion in setting policy.  My proposal does not strip them of this power. Instead, I want to incentivize them to "raise their game" using a scientific approach to improve local quality of life.  While every city has its own unique history, there are many commonalities across cities that create the possibility of cross-city learning.  I do not believe that this "cross-city" learning is happening at  a fast enough rate right now and young people living in high poverty areas in these cities are suffering because of this.

     
















     


  5.  In this blog post, I want to market my new co-authored book "Unlocking the Potential of Post Industrial Cities" .  I will do this by talking about past research on the Economics of the Rust Belt.   Here is chapter one of my book and here is a recent video where I talk about the book.

    The most prominent "Rust Belt" economics paper is the 2005 Glaeser and Gyourko paper on Urban Decline and Durable Housing.   On a slightly deep level, this paper is about gross flows and sunk capital.  In the 1950s, cities such as Detroit and Pittsburgh were doing quite well as their main manufacturing industries and the major firms in those industries were booming.   Local workers were well paid (and African-Americans were an important part of this workforce).  New homes were being built in the 1950s.

    We all know that over the last few decades these cities have deindustrialized.  As the manufacturing jobs left, there was also a service sector multiplier effect.  Detroit has less demand for good local restaurants that cater to middle class people if most of the middle class purchasing power (tied to the manufacturing base) vanishes.  This ugly dynamic leads to fewer people moving to these cities and more of the incumbents moving out.  As net population shrinks (Baltimore's population has shrunk from 900,000 to 600,000 today), there is a surplus of housing in these cities. The durable housing is depreciates but still stands.  The equilibrium market rents fall and these cities become poverty magnets.   If home owners could costlessly (like a turtle) take their home to where they move, then much of this poverty effect would vanish as these cities would have just shrunk in population size.

    Another Interesting Rust Belt paper is this Brookings paper.


    As older cities such as Chicago,  Pittsburgh, St. Louis, Baltimore and Detroit have deindustrialized, their environmental quality has improved. I explored this point in my 1999 paper and my 2006 Green Cities book.   Siqi and I have explored this same theme in our urban China work.

    An important point is that the industrial transition that mitigates an ugly pollution externality has key distributional effects that increase inequality.  Educated people who do not work in the polluting industries (think of Carnegie Mellon professors in Pittsburgh) gain an improvement in air quality as steel jobs vanish.  These college professors do not face higher unemployment risk as middle class people in Pittsburgh lose their steel jobs.

    All of this is a setup for our new 2021 book.  For six key cities, we explore these themes and preview how these cities can make a comeback.  Post-COVID and in an emerging Work from Home economy, there will be a demand for livable, affordable cities and there are ways that Baltimore, Cleveland, Detroit, Philly, Pittsburgh and St. Louis can "raise their game" to better compete for the footloose jobs and educated people.

    The system of cities provides a powerful framework for studying the competition that plays out for attracting "market share".  If a city such as Baltimore could attract more skilled people to live in the city, this would boost the tax base and it would increase local service demand and it would mean that more role models live in the city.    Our book studies the urban poverty trap and focuses on both the James Heckman approach for reducing poverty and some urban economics pathways for increasing opportunity and building better cities.

    Our 2021 book.










  6.  I have spent my career publishing in environmental and urban economics.  You can look up my Google Scholar page to see that many of my papers are well cited.

    Over the years, I have written out a distinctive undergraduate environmental economics textbook that I use in my classes. You can buy the Amazon e-book here for $8.  

    To encourage Professors to adopt parts of this book in their courses, I provide you with my 350 of my lecture slides for free and many practice exam problems.

    Please email me if you have any comments for how to improve these materials.  I was impressed with Tim Taylor's efforts to provide open source economics content and this is my effort to match his effort

    I make my Amazon E-book available for free twice each year for a week.   How much consumer surplus does this generate? I don't think that any of the other environmental economics books are good substitutes for my book.  



  7. Suppose that masks are invisible,  would more people wear them?  Would more supporters of President Trump wear them?  How much of the opposition to playing it safe and putting on a mask is due to the economics of identity?    To repeat my question, if you could put on a mask but everyone else wouldn't know that you were wearing one, would this increase your probability of putting it on?

    Let's review the economics of risk taking.

    Case #1:  Decision makers who do not have social preferences.

    In the 1970s, my friend Glenn Blomquist wrote a nice paper on the economics of putting on a seatbelt.  In his 1979 JPE paper,  Glenn studies a tradeoff. When one puts on a seatbelt before driving, this takes you time and effort (a cost) and it offers you a benefit (a lower probability of suffering in an accident).   Glenn collects some data and uses statistical methods to infer how much people are willing to pay for a small reduction in risk.  If we could estimate this willingness to pay for risk reduction for each person, we could identify the subset of people who do not value putting on a seat belt. This group's behavior would be affected by a government seatbelt mandate and enforcement of this law. This group would be likely to complain about this benevolent paternalism of the state.

    I raise this case because mask wearing can be thought of as similar to a seat belt mandate.  Yes,  I understand that putting on a mask protects both the person and those people who the person comes into close physical contact with.

    Case #2   The Decision Maker has social preferences

    What do I mean by "social preferences"? In the Akerlof and Kranton framework on the economics of identity, this person gains utility from "fitting in" with her peers.  In my  past work, I have argued that a person who lives in Berkeley gains direct utility from driving a Prius or Tesla because this is a green car and she gains additional utility by signaling that she is a good environmentalist. We drive in public and what we drive signals our "type".  This latter effect is what I mean by social preferences.  You can also read my 2001 Boston Globe editorial.

    So, in my old green products work --- I argued that social preferences accelerates the diffusion of green products such as solar panels and clean cars.   I'm worried that the same logic explains the distinctive refusal of many to wear masks at this key time.  Invisible masks would solve this issue.

    In the case of masks and the Pandemic, are social preferences to fit in with one's group slowing down our progress in fighting the contagion? If the masks were invisible, we could unbundle fighting the virus from fitting in with one's libertarian brothers.   How many of this group would exercise this option? How much would R0 decline by?

    To keep this blog post simple, I have introduced population variation in risk aversion of beliefs about the effectiveness of masks, or discomfort in wearing a mask.  What we wear in public sends signals about who we are. Veblen was thinking about such conspicuous consumption a long time ago.

    If an "invisible mask" exists and if there is no government mandate to wear a mask, this product would be purchased by people who fear the disease and have social preferences such that they want to fit in with President Trump's supporters.  Whether this is a big group or not, the existence of this set of people means that they will wear the mask if the product exists and they won't wear the mask if the product does not exist.  The size of this group determines how much the aggregate contagion parameter shrinks by when the product is introduced.










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