Solved Problem: Why Is Starbucks Closing Stores in New York City?

Supports:  Econ Chapter 12, Section 12.4, “Deciding Whether to Produce or Shut Down in the Short Run,” and Section 12.5, “‘If Everyone Can Do It, You Can’t Make Money at It’: The Entry and Exit of Firms in the Long Run”; and Essentials: Chapter 9, Section 9.4 and Section 9.5.

Photo from the Associated Press.

Solved Problem: Why Is Starbucks Closing Stores in New York City?

   In May 2021, many businesses in the United States began fully reopening as local governments eased restrictions on capacity imposed to contain the spread of Covid-19. An article on crainsnewyork.com discussed the decisions Starbucks was making with respect to its stores in New York City. Starbucks intended to keep some stores open, some stores would be permanently closed, and “about 20 others that are currently in business will shutter when their leases end in the next year.” Analyze the relationship between cost and revenue for each of these three categories of Starbucks stores: 1) the stores that will remain permanently open; 2) the stores that will not reopen; and 3) the stores that will remain open only until their leases expire. In particularly, be sure to explain why Starbucks didn’t close the stores in category 3) immediately rather than waiting until the their leases expire.

Source: Cara Eisenpress, “Starbucks Closing Some City Locations as It Moves to a Smaller, Pickup Model,” crainsnewyork.com, May 19, 2021.

Solving the Problem

Step 1:   Review the chapter material. This problem is about the break-even price for a firm in the short run and in the long run, so you may want to review Chapter 12, Section 12.4, “Deciding Whether to Produce or to Shut Down in the Short Run,” and Section 12.5, “‘If Everyone Can Do It, You Can’t Make Money at It’: The Entry and Exit of Firms in the Long Run.”

Step 2:   Explain why stores in category 1) will remain permanently open. We know that firms will continue to operate a store if the revenue from the store is greater than or equal to all of the store’s costs—both its fixed costs and its variable costs.  So, Starbucks must expect this relationship between revenue and cost to hold for the stores that it will keep permanently open.

Step 3: Explain why Starbucks will not reopen stores in category 2). Firms will close a store in the short run if the loss from operating the store is greater than the store’s fixed costs. Put another way, the firm won’t be willing to lose more than the store’s fixed costs. We can conclude that Starbucks believes that if it reopens stores in category 2) its loss from operating those stores will be greater than the stores’ fixed costs.

Step 4: Explain why Starbucks will operate some stores only until their leases expire and then will shut them down. If a firm’s revenue from operating a store is greater than the store’s variable costs, the firm will operate the store even though it is incurring an economic loss. If it closed the store, it would still have to pay the fixed costs of the store, the most important of which in this case is the rent it has to pay the owner of the building the store is in. By operating the store, Starbucks will incur a smaller loss than by immediately closing the store. But recall that there are no fixed costs in the long run. The stores’ leases will eventually expire, eliminating that fixed cost. So, in the long run, a firm will close a store that is incurring a loss. Because Starbucks doesn’t believe that in the long run it can cover all the costs of operating stores in category 3, it intends to operate them until their leases expire and then shut them down.

Guest Post from Eva Dziadula of Notre Dame on Using Behavioral Economics to Improve Test Scores

Eva is an Associate Teaching Professor at the University of Notre Dame, where she is also a fellow of the Kellogg Institute for International Studies, the Liu Institute for Asia and Asian Studies, and the Pulte Institute for Global Development.  She received her PhD from the University of Illinois, Chicago in 2014.

Last June, we interviewed Eva on our podcast. That podcast can be found HERE.

Can a Behavioral Nudge with Small Commitment Lead to Better Exam Scores?

So Covid brought challenges…. we can’t really even count them. In the world of education, it meant switching to online delivery and while that may be hard on us professors, it also requires a lot more from students. Learning from home requires more discipline, there is a degree of freedom (statistics pun intended). There is also a lack of accountability that typically comes with attending an in-person class where the professor can call you out for not being prepared. This is what non-traditional students who have a job, a family, go through on a regular basis even without Covid. The often opt for online classes in the first place. It can also be a tougher adjustment for students who come from traditionally underrepresented groups in higher education, as they may not grow up watching their parents make lists, prioritize, and manage time that would promote college success. Is there something that could help alter students’ behavior and overcome this inequality?

In all of our introductory economic models, we assume that agents are rational. If that assumption is violated, we cannot really predict how they will respond to incentives and our models would lose their predictive power. The 2017 Nobel Prize in Economics was awarded to Richard Thaler for his contributions to behavioral economics. The art and science of “irrationality”. Well, about time as we seem to violate rationality a lot! We know we should study, we know we should not procrastinate, yes we know but… These choices can have serious long-term consequences, so it is important to study our behaviors and why we make decisions that perhaps do not appear rational. And it is important to study how we could alter certain behaviors. Research has shown that simply nudging students with a text message doesn’t really lead to improvements in academic performance. A 2019 NBER working paper summarized it pretty well: “The Remarkable Unresponsiveness of College Students to Nudging and What We Can Learn from It.” [The paper can be found HERE.] 

In our paper “Microcommitments: The Effect of Small Commitments on Academic Performance,” we set out to test whether a text message nudge accompanied by a small commitment can “push” students in the right direction. In economics, the gold standard of answering questions like this is a randomized controlled trial. If assignment is not random and students are selected into treatment and control groups, then we would not be able to identify the role of the intervention, as these groups may be responding differently in the first place. For example, imagine we tested the nudge with commitment on a group of women and men served as the “placebo” control group. If we find higher exam scores for women, then it may be because of the nudge with commitment but it is also entirely possible that women could have scored higher regardless, this is referred to as a selection bias. We overcome this by randomly assigning almost 1,000 students from the University of Notre Dame, Florida Atlantic University, and University of Illinois into two groups, which after close examination of observable characteristics look very similar. This is called a balance test. After randomization, the two groups have a similar proportion of women, similar average SAT, GPA, age, family structure, their procrastination tendencies, self-efficacy, study habits, etc. Some of the students are enrolled in regular in-person classes, and some are enrolled in a hybrid/online classes. 

After the first exam of the semester, which will serve as a baseline comparison, the experiment begins! Both groups receive text messages in the morning with content related to material covered in class. Students know they are not required to submit their answers and it is not mandatory, these messages are just extra practice on how to think as an economist. The control group received the content as a simple text message. The treatment group’s text message also had “I commit” to click. Then at 4pm, they also got a follow up text with “I did it” click. This is the commitment device we are testing and it is the only difference between the treatment and control groups, everything else is identical. The research question is: Does a small commitment (really to yourself, as it is not required) compel you to complete the task and does this engagement then improve your future exam score? The regression estimation allows us to hold everything else constant, so we are adhering to our ceteris paribus condition.

It turns out that the small commitment does make a difference! In fact, the positive results on the exam which followed the experiment is driven by students in hybrid and online classes who scored 3.5 percentage points higher than students in the control group which received the same message content but did not receive the commitment! We find no effect on the academic performance among students in regular in-person classes. It appears that this simple intervention partially substitutes for the lack of instructor contact for students in hybrid and online classes. We also find that students who tend to procrastinate and those with lower GPA benefit from the commitment device more, which then acts as an equalizing force in terms of academic performance and could have positive implications for social mobility and economic equity. Who would have thought that making a small promise to yourself could actually make a difference!!!

References: Felkey, Amanda J, Eva Dziadula, Eric P Chiang, and Jose Vazquez. 2021. “Microcommitments: The Effect of Small Commitments on Academic Performance.” AEA Papers and Proceedings 111: 1–6. [The paper can be found HERE.]

Oreopoulos, Philip, and Uros Petronijevic. 2019. “The Remarkable Unresponsiveness of College Students to Nudging and What We Can Learn from It.” [The paper can be found HERE.]

The Wild Ride of GameStop’s Stock Price

Supports:  Hubbard/O’Brien, Chapter 8, Firms, the Stock Market, and Corporate Governance; Macroeconomics Chapter 6; Essentials of Economics Chapter 6; Money, Banking, and the Financial System, Chapter 6.

We’ve seen that a firm’s stock price should represent the best estimates of investors as to how profitable the firm will be in the future. How, then, can we explain the following graph of the price of shares of GameStop, the retail chain that primarily sells video game cartridges and video game systems? The graph shows the price of the stock from December 1, 2020 through February 9, 2021. If the main reason the price of a stock changes is that investors have become more or less optimistic about the profitability of the firm, is it plausible that opinions on GameStop’s profitability changed so much in such a short period of time?.

  Sometimes investors do abruptly change their minds about the profitability of a firm but typically this happens when the firm’s profitability is heavily dependent on the success of a single product. For instance, the price of the stock a biotech firm might soar as investors believe that a new drug therapy the firm is developing will succeed and then the price of the stock might crash when the drug is unable to gain regulatory approval.  But it wasn’t news about its business that was driving the price of GameStop’s stock from $15 per share during December 2020 to a high of $347 per share on January 27, 2021 and then down to $49 per share on February 9.

            To understand these prices swings, first we need to take into account that not all people buying stock do so because they are making long-term investments to accumulate funds to purchase a house, pay for their children’s educations, or for their retirement. Some people who buy stock are speculators who hope to profit by buying and selling stock during a short period—perhaps as short as a few minutes or less. The availability of online stock trading apps, such as Robinhood, that don’t charge commissions for buying and selling stock, and online stock discussion groups on sites like Reddit, have made it easier for some individual investors to become day traders, frequently buying and selling stocks in the hopes of making a short-term profit.

Many day traders engage in momentum investing, which means they buy stocks that have increasing prices and sell stocks that have falling prices, ignoring other aspects of the firm’s situation, including the firm’s likely future profitability. Momentum investing is an example of what economists call noise trading, or buying and selling stocks on the basis of factors not directly related to a firm’s profitability. Noise trading can result in a bubble in a firm’s stock, which means that the price rises above the fundamental value of the stock as indicated by the firm’s profitability. Once a bubble begins, a speculator may buy a stock to resell it quickly for a profit, even if the speculator knows that the price is greater than the stock’s fundamental value. Some economists explain a bubble in the price of a stock by the greater fool theory: An investor is not a fool to buy an overvalued stock as long as there’s a greater fool willing to buy it later for a still higher price. 

Although the factors mentioned played a role in explaining the volatility in GameStop’s stock price, there was another important factor that involved hedge funds and short selling. Hedge funds are similar to mutual funds in that they use money from savers to make investments. But unlike mutual funds, by federal regulation only wealthy individuals or institutional investors such as pension funds or university endowment funds are allowed to invest in hedge funds. Hedge funds frequently engage in short selling, which means that when they identify a firm whose stock they consider to be overvalued, they borrow shares of the firm’s stock from a broker or dealer and sell them in the stock market, planning to make a profit by buying the shares back after their prices have fallen.

In early 2021, several large hedge funds were shorting GameStop’s stock believing that the market for video game cassettes would continue to decline as more gamers switched to downloading games. Some people in online forums—notably the WallStreetBets forum on Reddit—dedicated to discussing investing strategies argued that if enough day traders bought GameStop’s stock they could make money through a short squeeze. A short squeeze happens when a heavily shorted stock increases in price. The speculators who shorted the stock may then have to buy back the stock to avoid large losses or having to pay very high fees to dealers who had loaned them the shares they were shorting. As the short sellers buy stock, the price of the stock is bid up further, earning a profit for day traders who had bought the stock in anticipation of the short squeeze. One MIT graduate student made a profit of more than $200,000 on a $500 investment in GameStop stock. Some hedge funds that had been shorting GameStop lost billions of dollars.

Some of the day traders involved saw this episode as one of David defeating Goliath because the people executing the short squeeze were primarily young with moderate incomes whereas the people running the hedge funds taking substantial losses in the short squeeze were older with high incomes. The reality was more complex because as the price of GameStop stock declined from $347 on to $54 on February 4, some day traders who bought the stock after its price had already substantially risen lost money. And all the winners from the short squeeze weren’t day traders; some were hedge funds. For instance, by early February, the hedge fund Senvest Management had earned $700 million from its trading in GameStop’s stock.  

Economists had differing opinions about whether the GameStop episode had a wider significance for understanding how the stock market works or for how it was likely to work in the future. Some economists and investment professionals argued that what happened with GameStop’s stock price was not very different from previous episodes in which speculators buying and selling a stock will for a time cause increased volatility in the stock’s price. In the long run, they believe that stock prices return to their fundamental values. Other economists and investors thought that the increased number of day traders combined with the availability of no-commission stock buying and selling meant that stock prices might be entering a new period of increased volatility. They noted that similar, if less spectacular, price swings had happened at the same time in other stocks such as AMC, the movie theater chain, and Express, the clothing store chain. An article on bloomberg.com quoted one analyst as saying, “We’ve made gambling on the stock market cheaper than gambling on sports and gambling in Vegas.” 

            Federal regulators, including Treasury Secretary Janet Yellen, were evaluating what had happened and whether they needed to revise existing government regulations of financial markets.  

Sources: Misyrlena Egkolfopoulou and Sarah Ponczek, “Robinhood Crisis Reveals Hidden Costs in Zero-Fee Trading Model,” bloomberg.com, February 3, 2021; Gunjan Banerji,  Juliet Chung, and Caitlin McCabe, “GameStop Mania Reveals Power Shift on Wall Street—and the Pros Are Reeling,” Wall Street Journal, January 27, 2021; Gregory Zuckerman, “For One GameStop Trader, the Wild Ride Was Almost as Good as the Enormous Payoff,” Wall Street Journal, February 3, 2021; Juliet Chung, “Wall Street Hedge Funds Stung by Market Turmoil,” Wall Street Journal, January 28, 2021; and Juliet Chung, “This Hedge Fund Made $700 Million on GameStop,” Wall Street Journal, February 3, 2021. 

           

Questions 

  1. During the same week that the price of GameStop’s stock was soaring to a record high, an article in the Wall Street Journal noted the following: “Analysts expect GameStop to post its fourth consecutive annual decline in revenue in its latest fiscal year amid declines in its core operations [of selling video game cartridges and video game consoles in retail stores].” Don’t stock prices reflect the expected profitability of the firms that issue the stock? If so, why in January 2021 was the price of GameStop’s stock greatly increasing when it seemed unlikely that the firm would become more profitable in the future?

Source: Sarah E. Needleman, “GameStop and AMC’s Stocks Are on a Tear, but Their Businesses Aren’t,” Wall Street Journal, January 31, 2021

2. In early 2021, as the stock price of GameStop was soaring, a columnist in the New York Times advised that: “A better option [than buying stock in GameStop] would be salting away money in dull, well-diversified stock and bond portfolios, these days preferably in low-cost index funds.”

a. What does the columnist mean by “salting money away”?

b. are index funds and why might they be considered dull when compared to investing in an individual stock like GameStop?

c. Why would the columnist consider investing in an index mutual fund to be a better option than investing money in an individual stock like GameStop? 

Source: Jeff Sommer, “How to Keep Your Cool in the GameStop Market,” New York Times, January 29, 2021.

Instructors can access the answers to these questions by emailing Pearson at christopher.dejohn@pearson.com and stating your name, affiliation, school email address, course number.

Guest Post from Jadrian Wooten of Penn State on Using Pop Culture to Teach Economics

Jadrain Wooten is an associate teaching professor of economics at Penn State. Jadrian created the Economics Media Library. Clips to the site are included in Jadrian’s essay below.

Last September, we interviewed Jadrian on our podcast. That podcast episode can be found HERE.

What follows is an essay from Jadrian on ideas for teaching economics using examples from pop culture.

Using Pop Culture to Teach Economics

My favorite courses as an undergraduate student weren’t always economics courses. Don’t get me wrong, I loved my intermediate microeconomics so much that I immediately dropped my summer internship so I could add economics as a second major (thanks Ed!). The principles courses, however, weren’t that interesting. We drew graphs, talked about efficiency, and then left for the day. The first class I remember that heavily used media as a teaching tool was Mark Frank’s Business and Government class.

Instead of a traditional textbook, we read The Art of Strategy, When Genius Failed, and The Regulators. Instead of straight lecture, Mark ran experiments and showed a particular episode from ABC Primetime that I still show my students today, over 14 years later. It was the last semester of my undergraduate degree, but his course confirmed that I wanted to get a PhD in economics, and that I wanted to teach my courses like he had taught that course.

I had other amazing professors who used media in the classroom (thanks Darren!), and I landed in a graduate program that trusted me to teach my how I saw fit. For me, that meant a heavy dose of television and movie clips in order to avoid the Ferris Bueller treatment of economics. One of the best parts of teaching today compared to a decade ago is just how much media is available online (shameless plug for Economics Media Library). Thanks in part to cheap hosting services, economics educators have created entire websites specific to economic content found in television shows (Breaking Bad, Modern Family, Parks and Recreation, Seinfeld, Shark Tank, and Superstore), Broadway musicals, and country music.

Many of these educators have also arranged lesson plans and projects associated with various topics as specific as marginal revenue product and the Coase Theorem. Lesson plans (1, 2, 3, 4) have been prepared that take scenes from different shows and detail how they can be integrated into a lesson. Many of the show-specific websites linked earlier also have a section detailing ways to integrate their clips. Most of this focus is at the principles level, but there are also some resources designed for upper-level courses.

Pop culture isn’t just limited to television and film clips! One of the teaching methods I adopted from my undergraduate experience was assigning trade books. Student in my Principles of Microeconomics course read Think Like a Freak and The Why Axis. My Labor Economics students go through “New Geography of Jobs” and We Wanted Workers, while Economics of Crime students read Narconomics, and my Natural Resource Economics students read Endangered Economies. For almost every course out there, there is likely a trade book that presents current research in a digestible manner. Assessing students on readings can be as varied as creating random assignments for each student or using Monte Carlo Quizzes. Using trade books, in addition to the textbook, gives students another avenue for applying the concepts and theories.

Bridging the gap between books and television shows is the use of podcasts. Rebecca Moryl has put together a series of papers (1, 2, 3) as well as a website that categorizes podcasts that can be used to teach (my favorite is Planet Money). Similar to how I use trade books, my students are assigned podcasts along with readings and are assessed with a Monte Carlo Quiz or on their midterm exams. Short podcasts can be played during class to spark a discussion on upcoming topics or as a review of previous material. I love Planet Money’s “A Mall With Two Minimum Wages” for the labor markets chapter.

The number of available resources will only grow as educators continue to develop creative ways to use media in the classroom. What’s my general advice to instructors interested in using media in the classroom? Start small. Play some music before class starts, but link that song to the lesson. Play Brad Paisley’s “American Saturday Night” before you start your lesson on trade and see how your students respond. We teach our students about marginal analysis, so take the same approach to using media!

If the pre-class music video goes well, consider adding a short clip to introduce a topic. Before teaching about liquidity, show this scene from Modern Family where Luke confuses the meaning of “frozen assets.” Need an example for comparative advantage? Try this scene from King of the Hill where Hank and his neighbor debate the best products from the United States and Canada. Just play the clip and then transition straight to your lesson. Let your students know you’ll cover those concepts in class that day, then refer back to the scene when you get to the relevant section.

Ready to go a bit further and really integrate media into your lessons? Play this interview from The Colbert Report and ask students to draw the market for cashmere, including the externality. Have students calculate consumer and producer surplus after watching this scene from Just Go With It. See if students can identify the type of unemployment from this scene in Brooklyn 99. Check out Economics Media Library to see if there’s a clip that you can use in your next lesson. If all of that goes well, check out all of the great resources educators have put together to see what would work in your classroom for the next semester. Maybe one day you’ll teach an entire course on economics through film or one themed entirely on Parks and Recreation.

Solved Problem: Why Will No One Buy This Farm?

Supports:  Economics: Chapter 12 – Firms in Perfectly Competitive Markets (Section 12.5); Microeconomics: Chapter 12, Section 12.5; and Essentials: Chapter 9, Section 9.5

Solved Problem: Explaining Entry and Exit

An article in the Pittsburgh Post-Gazette had the headline: “The Last Harvest: Beaver County Organic Farm Closes after Failure to Find Successor.” The article discusses the decision by a 71-year old famer to close down his organic vegetable farm after failing to find a buyer for it despite a 10-year search. Several people, including his four adult children, considered purchasing the farm but in end none did so. His only requirement in selling the farm was that the buyer use the land to grow organic crops. The famer was puzzled by his inability to find a buyer because “There’s money in organics.” The article notes that: “In a U.S. Department of Agriculture study, organic food products generally commanded a [price] premium exceeding 20% over conventionally grown vegetables.”

a. Does the fact that organically grown vegetables sell for prices that are 20 percent higher than the prices of conventionally grown vegetables mean that growing organic vegetables will earn a farmer a larger economic profit than growing vegetables using conventional methods? Briefly explain.

b. Is it likely that the requirement that a buyer had to agree to use the land only to grow organic vegetables affected the inability of the farmer to find a buyer? Briefly explain.

c. What is the likeliest explanation for the farmer being unable to find a buyer for his farm?

Source: Khris B. Mamula, “The Last Harvest: Beaver County Organic Farm Closes after Failure to Find Successor,” Pittsburgh Post-Gazette, January 3, 2021.

Solving the Problem

Step 1:   Review the chapter material. This problem is about the reason that firms exit an industry, so you may want to review Chapter 12, Section 28.2 “If Everyone Can Do It, You Can’t Make Money at It.”

Step 2:   Answer part a. by discussing whether the fact that organic vegetables sell for higher prices than conventionally grown vegetables means that growing organic vegetables will earn a farmer a larger economic profit than growing vegetables using conventional methods. Profit depend on costs as well as prices. We’ve seen in this chapter that organic growing methods typically have higher costs than conventional growing methods. Therefore, the fact that organic vegetables sell for higher prices than conventionally grown vegetables doesn’t guarantee that farmers selling organic vegetables are earning an economic profit. In fact, in the long run we would expect that entry and exit will ensure that the price farmers sell vegetablesfor will just equal the average cost of growing them, whether the vegetables are grown organically or conentionally. In other words, in the long run the higher price of organic vegetables will just offset the higher cost of growthing them and farmers will earn a zero economic profit whichever method they use to grow vegetables.

Step 3:   Answer part b. by explaining whether the farme’s requirement that the farm be used only to grow organic vegetables affected his difficulty in finding a buyer. Generally when a firm exits a market, as this farmer is exiting the market for organic vegetables, the firm’s resources will be sold and used for other purposes. For example, when the market for renting videos collapsed, the buildings video rental stores had been in were used for other purposes. (A former Blockbuster video store near where one of the authors lives was converted into a tire store.) Or a resaurant serving Italian food may close and the tables, chairs, and ovens may be used by a restaurant serving Thai food that opens in the same building. By insisting that his farm only be used for growing organic vegetables, the farmer limited the number of buyers who would be interested in buying it. Anyone who wanted to use the land to grow vegetables using conventional methods or wanted to use it for a nonagricultural purpose would not buy the farm.

Step 4: Answer part c. by discussing the likeliest reason that the farmer was unable to find a buyer for his farm. We would expect that someone wanting to sell a firm that is earning an economic profit would have no trouble finding a buyer if the price being asked would allow a buyer to also earn an economic profit on the buyer’s investment. That the farmer in this article couldn’t find a buyer after 10 years of searching is an indication that a buyer of the farm at the price he was asking would at best break even. As noted in the answer to part b., that the farmer wouldn’t allow a buyer to use the land for any purpose other than organic farming reduced the number of potential buyers.

Guest Post from Bill Goffe of Penn State on Ways to Improve Your Teaching with Ideas Outside of Economics

Bill Goffe is a teaching professor at Penn State. Many instructors know Bill from his “Resources of Economists on the Internet,” which appears on the website of the American Economic Association and can be accessed HERE. Bill is also an associate editor of the Journal Economic Education. The journal’s website can be accessed HERE.

Last May, we interviewed Bill on our podcast. That podcast episode can be found HERE.

What follows is an essay from Bill on ideas on teaching from instructors in other disciplines that economics instructors might find useful.

Improve Your Teaching with Ideas from Outside Economics

According to “The Superiority of Economists” economists tend not to cite other social science disciplines. This is eminently sensible if the topic is monetary policy, welfare theory, or market structures. But, what about teaching? Might other disciplines have useful things to say on this topic that economists might use in their classrooms? As I think the reader will see from the following links to both websites and papers, I think that the clear answer is “yes.” Underlying this answer lie two reasons. First, some other disciplines have devoted substantially more resources to improving teaching than economists have. Second, their approaches are often based on findings from cognitive science.

Perhaps my favorite site for teaching ideas is the Carl Wieman Science Education Initiative at the University of British Columbia. One can think of Wieman as a peer of George Akerlof, Michael Spence, or Joseph Stiglitz as he too was awarded a Nobel Prize in 2001. In Wieman’s case, it was in physics. Before this prize he did some work in physics education research and after the prize all his research time has been devoted to this subject. As he describes in “Why Not Try a Scientific Approach to Science Education,” Wieman was in part puzzled why his “brilliantly clear explanations” led to very little learning by his students. To understand why, he started to read what cognitive science has to say about how humans learn, and he went on to apply these ideas to his teaching; all this is outlined in this paper.

Wieman is one of the most influential STEM education researchers; it is telling that of his ten most cited papers, two are in physics education research. He is still very active with 9 papers published in 2019 and 2020. While now at Stanford, his previous appointment was at the University of British Columbia and a website devoted to his and his group’s work is still actively maintained at the “Carl Wieman Science Education Initiative.” Under the “Resources” tab one will find guides for instructors, which range from classroom videos that illustrate “evidence-based teaching methods” to numerous easily digestible two-page guides. These range from how to write effective homeworks to motivating students to a description of how students think differently than faculty. It is the single most useful site for college teaching that I know of as its many suggestions are based on what is known about how humans learn.

Wieman’s most cited teaching paper is “Improved Learning in a Large Enrollment Physics Class.” Here, learning in two classes over one week is compared. One was taught by an experienced instructor with high student ratings and the other was taught by a novice instructor using evidence-based teaching methods. Students of the latter showed more than two standard deviations learning than students of the former. A particular form of active learning, “deliberate practice” was used by the novice instructor. The cognitive scientist Anders Ericsson coined deliberate practice when studying how novices were transformed into experts (an early collaborator of Ericsson was Herbert Simon).

Another resource from physics education researchers is PhysPort. Besides marveling at the 100+ assessments that STEM education researchers have developed for college classrooms, there are “expert recommendations” on selling active learning to students, on how one might create a community in a classroom, and on creating effective small groups.

While physics education researchers have developed an impressive body of work that economists can use in their classrooms, biology education researchers have also amassed a considerable literature. One of the leading biology education research groups is at the University of Washington. As one can see, their motto is “Ask, Don’t Tell.” That is, teach by asking carefully designed questions that students take seriously. Their “Teaching Resources” succinctly outline the classroom implications of their research. For instance, their video “Effective use of Clickers” demonstrates their use in a large class with frequent references to the relevant literature. The most recent publication of this group is “Active Learning Narrows Achievement Gaps for Underrepresented Students in Undergraduate Science, Technology, Engineering, and Math.” This metaanalysis included data from some 40,000 students.

Another favorite paper of mine by biology education researchers is “The Role of the Lecturer as Tutor: Doing What Effective Tutors Do in a Large Lecture Class.” It follows the theme of “Ask, Don’t Tell” by first reviewing the literature on how expert tutors work with students. The best tutors teach by largely asking questions and these authors extend this idea to teaching large classes. It might be worth pointing out that Wood is a leading lab biologist as he was elected to the National Academy of Sciences at the age of 34. Like Carl Wieman, he feels it is important to devote some of his research time to improving undergraduate education.

Finally, cognitive scientists have written works that economists might directly use. Most anyone who has taught has heard from a student that they studied for an exam, yet the student performed poorly and the student thought that they did better. A very thorough analysis of effective study methods is described in “Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology.” It is a rather foreboding paper to read given its level of detail, but a very readable summary is “Strengthening the Student Toolbox: Study Strategies to Boost Learning.” With the study methods describe here, an economist can give evidence-based suggestions to their students on how to study better for the next exam.

More Than You Probably Want to Know about the Debate Over Whether Giving Presents Causes a Deadweight Loss

If your sister gives you a sweater that you don’t like, the subjective value you place on the sweater will probably be less than the price your sister paid for it. As we saw in Chapter 4, Sections 4.1 and 4.2, consumer surplus is the difference between the highest price a consumer is willing to pay for a good (which equals the consumer’s marginal benefit from the good) and the actual price the consumer pays. We expect that you will only buy things that have a marginal benefit to you greater than (or, at worst, equal to) the price you paid. Therefore, everything you buy provides you with positive (or, again at worst, zero) consumer surplus. But if the price is greater than the marginal benefit—as is the case with the sweater your sister gave you—consumer surplus is negative and there is a deadweight loss.

In the early 1990s, Joel Waldfogel, currently at the University of Minnesota, published an article in the American Economic Review in which he reported surveying his undergraduate students, asking them to: (1) list every gift they had received for Christmas, (2) estimate the retail price of each gift, and (3) state how much they would have been willing to pay for each gift. Waldfogel’s students estimated that their families and friends had paid $438 on average on the students’ gifts. The students themselves, however, would have been willing to pay only $313 for the goods they received as gifts—so, on average, each student’s gifts caused a deadweight loss of $313 – $438 = –$125. If the deadweight losses experienced by Waldfogel’s students were extrapolated to the whole population, the total deadweight loss of Christmas gift giving could be as much as $23 billion (adjusting the value in Waldfogel’s article to 2020 prices).

If the gifts had been cash, the people receiving the gifts would not have been constrained by the gift givers’ choices, and there would have been no deadweight loss. If your sister had given you cash instead of that sweater you didn’t like, you could have bought whatever you wanted and received positive consumer surplus.

Waldfogel’s article attracted much more attention than is received by the typical academic journal article, being covered in newspaper articles and on television. It also set off a lively debate among economists over whether his approach was valid. Waldfogel later published a short book, Scroogenomics, in which he argued that, in fact, his journal article had underestimated the deadweight loss of gift giving because it compared the value of the gift to the person receiving it to the value of receiving cash instead. He noted that a more accurate comparison would be not to cash but to the value of the good the person receiving the gift would have bought with the cash. Because that purchase would provide positive consumer surplus to the buyer, the buyer’s loss from receiving a gift rather than cash is significantly greater than he had originally calculated.

Waldfogel again surveyed his undergraduate students asking them to make this revised comparison and found (p. 35): “Dollars on gifts for you produce 18 percent less satisfaction, per dollar, than dollars you spend on yourself.” Waldfogel also noted that a gift giver has to spend time shopping for a gift, which—unless the giver enjoys spending time shopping—should be added to the cost of gift giving.

As a number of critics of Waldfogel’s analysis have noted, if giving gifts rather than cash makes the recipient worse off and the giver no better off (or worse off if we take into account the cost of the time spent shopping) why has the tradition of giving gifts on holidays and birthdays persisted? Waldfogel argues that for a large fraction of the U.S. population, giving gifts at Christmas is a strong social custom that people are reluctant to break. He believes there is also a social custom against close friends and relatives—parents, siblings, girlfriends, boyfriends, and spouses—giving cash. (Although he believes that it’s socially acceptable for relatives—such as grandparents, aunts, and uncles—who see the gift recipient infrequently to give cash or gift cards).

Some economists have questioned Waldfogel’s results because he surveyed only college students, who are not a representative sample of the population because they are on average younger and come from higher-income families. Because Waldfogel’s students were all enrolled in an economics course, their views may have been affected by what they learned in class. Sarah Solnick, of the University of Vermont, and David Hemenway, of the Harvard University School of Public Health, argue that because most economics students know the economic result that receiving cash as a gift is likely to be preferable to receiving a good, they may have felt social pressure to value their gifts at less than the price paid for them.

To see whether Waldfogel’s including only college students in his survey mattered for his results, Solnick and Hemenway surveyed graduate students and staff at the Harvard School of Public Health as well as people randomly approached at train stations and airports in Boston and Philadelphia. On average the people Solnick and Hemenway surveyed gave their Christmas gifts a value 114 percent higher than the price they estimated the gift giver had paid. In other words, contrary to Waldfogel’s result, gift giving generated a large positive consumer surplus or a welfare gain rather than a welfare loss. The authors speculate that the positive consumer surplus in gift giving may result because the recipient “respects the tastes of the giver, or the item is something the recipient never remembers to get.” Or, perhaps, “The individual wants the item but would feel bad purchasing it for herself. She is grateful to receive it as a gift.”

Solnick and Hemenway’s analysis has also been criticized. Bradley Ruffle and Orit Tykocinski of Ben Gurion University in Israel point out that the order in which questions are asked in a survey can influence the responses. Both Waldfogel and Solnick and Hemenway asked people being surveyed to first estimate what the giver had paid for the gift before asking the value the recipient assigned to the gift. Ruffle and Tykocinski also noted that Solnick and Hemenway changed one question being asked from “the amount of cash such that you are indifferent” between receiving the gift and receiving cash (which is how Waldfogel phrased the question) to the “amount of money that would make you equally happy.” Ruffle and Tykocinski believe this change in wording may also help account for why Solnick and Hemenway’s results differed from Waldfogel’s.

Ruffle and Tykocinski carried out a survey using undergraduate psychology and economics students, varying the wording and the order of the questions. Their results indicated that the wording of the questions mattered, although the order the questions had only a slight effect, and that the psychology students and the economics students did not have significant differences in how much they valued gifts, although psychology students tended to estimate that gift givers had paid a higher price for the gifts. The authors concluded: “Is gift-giving a source of deadweight loss? Our results indicate that it depends critically on how you ask the question and, to a lesser degree, on whom you ask.”

Solnick and Hemenway responded that Ruffle and Tykocinski’s analysis was flawed because, like Waldfogel, they surveyed only undergraduate students: “Ours remains the only study to use adults, living independently, as subjects.” They note that “Ruffle and Tykocinski’s subjects performed poorly in estimating costs,” which may indicate that they lack the experience in buying a large range of goods and so have trouble comparing the value they place on a gift to the cost the giver paid.

John List, of the University of Chicago, and Jason Shogren, of the University of Wyoming, raised the issue of whether the hypothetical nature of the values the gift recipients placed on their gifts mattered. That is, whatever subjective value the recipient gave to a gift, he or she would not actually have the opportunity to sell the gift at a price equal to that value. To test the possibility the recipient’s valuation of a gift would change if the recipient had the opportunity to sell the gift, List and Shogren asked a group of undergraduates to estimate the costs of the gifts they had received for Christmas and to indicate the value they placed on the gifts (just as Waldfogel and the other economists discussed earlier had done). But List and Shogren then added another step by carrying out a so-called random nth price auction of the gifts: “For example, suppose G = 500 gifts overall and #6 was chosen as the random nth price, then only the five lowest-valuation gifts overall would be purchased at the sixth lowest offer.” This somewhat complicated auction design was intended to make it more likely that the students being surveyed would reveal the true value they placed on the gifts.

The results were similar to those found by Solnick and Hemenway in that the recipients put a higher value on the gifts than their estimates of the price the givers paid—so there was positive consumer surplus from gift giving. Their estimate of the welfare gain was significantly smaller than Solnick and Hemenway’s estimate—21 percent to 35 percent versus 114 percent.

Solnick and Hemenway were not entirely convinced by List and Shogren’s findings. They note that because the auction design made it unlikely that the students would actually have to sell their most expensive gifts, the students may have placed a subjective value on these gifts that was too low. In addition, they note that List and Shogren, like Waldfogel, included only college students in their survey.

Joel Waldfogel also replied to List and Shogren, making several of the points he was later to elaborate on in his Scroogenomics book, as discussed above: Basic economic analysis assumes that consumers choose the goods and services they buy to maximize their utility (see Chapter 10 in our textbook), therefore: “If givers, through their choice of gifts, can achieve higher recipient utility than can the recipients themselves, then a fundamental economic assumption is called into question.” List and Shogren compare the value students place on their gifts to the value of receiving cash rather than to the consumer surplus the students would receive from the goods and services they could buy with the cash. Finally, Waldfogel notes that List and Shogren’s results may be affected by what behavioral economists call the endowment effect: The tendency of people to be unwilling to sell a good they already own even if they are offered a price that is greater than the price they would be willing to pay to buy the good if they didn’t already own it. (See the discussion in Chapter 10, Section 10.4 of our textbook.) Because people will require a higher price to sell a good they already own than the price they would pay to buy it, “deadweight loss estimates based on selling prices are much smaller than deadweight loss estimates based on buying prices.”

Even though economists have carried on the debate over the deadweight loss of gift giving in technical terms involving how consumer surplus is best measured, how surveys should be designed, and how best to solicit accurate answers from survey takers, journalists have been intrigued enough by the debate to write it about for general audiences. Josh Barro, who writes for New York magazine and is the son of Harvard economist Robert Barro, wrote a column for the New York Times, “An Economist Goes Christmas Shopping,” in which he observes that the debate among economists over gift giving “makes ordinary people think economists are kind of crazy.” He writes that his father had given him a box of chocolates for Christmas and notes that because he’s on a diet, the gift was “an example of what Mr. Waldfogel warned us about: gift mismatch leading to deadweight loss.” But that he actually ate half the box of chocolates indicated that his father had “identified an item I would not have bought for myself but apparently wanted.” But “now feel I should not have eaten the chocolates, or at least not so many of them in two days.” He concludes that, “The real drag on the economy then isn’t gifts; it’s bad gifts.”

A recent article by Andrew Silver on the Wired website in the United Kingdom notes that a study by academics in India found “an average deadweight loss of about 15 per cent for non-monetary gifts” given during the Hindu festival Diwali. Silver notes that the deadweight loss to gift giving is difficult to avoid because the social custom of gift giving during holidays is very strong in many countries. He concludes, “Sometimes you’ve just got to buckle down and buy something you suspect the recipient won’t value as much as you paid for it.”

Finally, do most economists agree with Waldfogel that there is a significant deadweight loss to gift giving or do they agree with his critics who argue that holiday gift giving actually increases welfare? Although the question has never been asked in a large survey of economists, it was included in a survey of leading economists conducted by the Booth School of Business at the University of Chicago as part of its Initiative on Global Markets (IGM). The IGM regularly surveys a panel of economists on important (although in this case, maybe not so important) economic issues.

A few years ago, they asked their panel whether they agreed with this statement: “Giving specific presents as holiday gifts is inefficient, because recipients could satisfy their preferences much better with cash.” Of the 42 economists who responded to the question, 25 disagreed with the statement, 7 agreed, and 10 were uncertain. Of those who commented, several mentioned a point that Waldfogel had intentionally excluded from his analysis: the sentimental or emotional value that some people attach to giving and receiving presents. For instance, Janet Currie of Princeton noted that: “Gifts serve many functions such as signaling regard and demonstrating social ties with the recipient. Cash transfers don’t do this as well.” Or as Barry Eichengreen of the University of California, Berkeley put it: “Implications of a specific gift (signal it sends, behavioral impact) may give additional utility to either the giver or receiver.” Eric Maskin of Harvard may have stated his reason for disagreeing with the statement most succinctly: “Only an economist could think like this.”

Sources: Joel Waldfogel, “The Deadweight Loss of Christmas,” American Economic Review, Vol. 83, No. 4, December 1993, pp. 328–336; Joel Waldfogel, Scroogenomics: Why You Shouldn’t Buy Presents for the Holidays, Princeton, NJ: Princeton University Press, 2009; Sara J. Solnick and David Hemenway, “The Deadweight Loss of Christmas: Comment,” American Economic Review, Vol. 86, No. 5, December 1996, pp. 1299-1305; Bradley J. Ruffle and Orit Tykocinski, ““The Deadweight Loss of Christmas: Comment,” American Economic Review, Vol. 90, No. 1, March 2000, pp. 319-324; Sara J. Solnick and David Hemenway, “The Deadweight Loss of Christmas: Reply,” American Economic Review, Vol. 90, No. 1, March 2000, pp. 325-326; John A. List and Jason F. Shogren, “The Deadweight Loss of Christmas: Comment,” American Economic Review, Vol. 88, No. 5, December 1998, pp. 1350-1355; Sara J. Solnick and David Hemenway, “The Deadweight Loss of Christmas: Reply,” American Economic Review, Vol. 88, No. 5, December 1998, pp. 1356-1357; Joel Waldfogel, “The Deadweight Loss of Christmas: Reply,” American Economic Review, Vol. 88, No. 5, December 1998, pp. 1358-1360; Tim Hyde, “Did Holiday Gift Giving Just Create a Multi-Billion-Dollar Loss for the Economy?” aeaweb.org, December 28, 2015; Josh Barro, “An Economist Goes Christmas Shopping,” New York Times, December 19, 2014; Andrew Silver, “Economists Want You to Have the Most Boring Christmas Possible,” wired.co.uk, December 17, 2020; and Chicago Booth School of Business, The Initiative on Markets, “Bah, Humbug,” December 17, 2013.

How Do firms Evaluate New Hires? The Curious Case of NFL Quarterbacks

As we discuss in Chapter 16, the demand for labor depends on the marginal product of labor. In our basic model of a competitive labor market we assume that all workers have the same ability, skills, and training. Firms can hire as many workers as they would like at the market equilibrium wage. Because, by assumption, all workers have the same abilities, firms don’t have to worry about whether one person might be less able or willing to perform the assigned work than another person.

In reality, we know that most firms face more complicated hiring decisions. Even for a job, such as being a cashier in supermarket, that most people can be quickly trained to do, workers differ in how well they carry out their tasks and whether they can be relied on to regularly show up for work and to treat customers politely.

When hiring workers, firms face a problem of asymmetric information: Workers know more about whether they intend to work hard than firms know. Even for applicants who have a work history, a firm may have difficulty discovering how well or how poorly the applicant performed his or her duties in earlier jobs. In responding to inquiries from other firms about a job applicant, firms are rarely willing to do more than confirm that a person has worked at the firm because they are afraid that reporting anything negative about the person—even if true—might expose the firm to a law suit. In Section 16.5, we discuss the field of personnel economics, which includes the study of how firms design compensation policies that attempt to ensure that workers have an incentive to work hard.

When hiring someone entering the labor market, such as a new college graduate, firms have a particular problem in gauging the likely performance of a worker who may have no job history. In this case, there may not be a problem of asymmetric information because the worker may also be uncertain as to how well he or she will be able to perform the job, particularly if the worker has not previously held a full-time job in that field. When hiring new college graduates, firms may rely on an applicant’s college grades, the reputation of the applicant’s college, and the applicant’s scores on standardized test. Some firms have also developed their own tests to measure an applicant’s cognitive skills, knowledge relevant to the position applied for, and even psychological temperament. Some technology firms and investment banks ask applicants to complete demanding problems that may be unrelated to either technology or banking but can provide insight into whether the applicant has the cognitive ability and temperament to quickly complete complicated tasks.

Teams in the National Football League (NFL) face an interesting problem when hiring new players, particularly those playing the position of quarterback. College football players hoping to play professional football enter the NFL draft in which each of the 32 teams select players in eight rounds, with the selections being in reverse order of the teams’ records during the previous football season. There is often a substantial gap between an athlete’s ability to be successful playing college football and his ability to be successful in the NFL. As a result, many players who are stars in college are unable to succeed as professionals.

The position of quarterback is usually thought to be the most difficult to succeed at. Many highly-regarded college quarterbacks fail to do well in the NFL. Teams typically settle on one player as their starting quarterback who will play most of the time. But teams also have one or two backups. Sometimes the backups are older, former starters on other teams, but often they are players chosen in the draft of college players. It’s very difficult to judge how well a quarterback is likely to perform except by seeing him play in a game. Players who perform well in practice often don’t play well in games. As a result, a backup quarterback may be drafted and, if the starting quarterback on his team remains healthy and is effective, earn a nice salary from year to year without actually playing in many games. If a team’s starting quarterback is injured or is ineffective, the backup quarterback may play in several games during a season.

If the backup shows himself to be an effective player, the team may decide to retain him as the starter—with a substantial increase in salary. But given the difficulty of playing the position of quarterback, a more likely outcome is that the backup plays poorly and the team decides to draft another backup quarterback the following year.

The result is an odd situation: The more that a backup quarterback plays in games, often the less likely he is to keep his job. And the less that a backup quarterback plays, the more likely he is to keep his job. Or as one NFL head coach put it: “Backups who don’t play a lot tend to have long NFL careers, while those who are exposed [by actually] playing … have shorter careers.”

This outcome is an extreme example of the difficulty firms sometimes have in measuring how well new hires are likely to perform in their jobs.

Source for quote: Sportswriter David Lombardi on Twitter, quoting San Francisco 49ers’ head coach Kyle Shanahan, December 14, 2020.

How the Effects of the Covid-19 Recession Differed Across Business Sectors and Income Groups

The recession that resulted from the Covid-19 pandemic affected most sectors of the U.S. economy, but some sectors of the economy fared better than others. As a broad generalization, we can say that online retailers, such as Amazon; delivery firms, such as FedEx and DoorDash; many manufacturers, including GM, Tesla, and other automobile firms; and firms, such as Zoom, that facilitate online meetings and lessons, have done well. Again, generalizing broadly, firms that supply a service, particularly if doing so requires in-person contact, have done poorly. Examples are restaurants, movie theaters, hotels, hair salons, and gyms.

The following figure uses data from the Federal Reserve Economic Data (FRED) website (fred.stlouisfed.org) on employment in several business sectors—note that the sectors shown in the figure do not account for all employment in the U.S. economy. For ease of comparison, total employment in each sector in February 2020 has been set equal to 100.

Employment in each sector dropped sharply between February and April as the pandemic began to spread throughout the United States, leading governors and mayors to order many businesses and schools closed. Even in areas where most businesses remained open, many people became reluctant to shop in stores, eat in restaurants, or exercise in gyms. From April to November, there were substantial employment gains in each sector, with employment in all goods-producing industries and employment in manufacturing (a subcategory of goods-producing industries) in November being just 5 percent less than in February. Employment in professional and business services (firms in this sector include legal, accounting, engineering, legal, consulting, and business software firms), rose to about the same level, but employment in all service industries was still 7 percent below its February level and employment in restaurants and bars was 17 percent below its February level.

Raj Chetty of Harvard University and colleagues have created the Opportunity Insights website that brings together data on a number of economic indicators that reflect employment, income, spending, and production in geographic areas down to the county or, for some cities, the ZIP code level. The Opportunity Insights website can be found HERE.

In a paper using these data, Chetty and colleagues find that during the pandemic “spending fell primarily because high-income households started spending much less.… Spending reductions were concentrated in services that require in-person physical interaction, such as hotels and restaurants …. These findings suggest that high-income households reduced spending primarily because of health concerns rather than a reduction in income or wealth, perhaps because they were able to self-isolate more easily than lower-income individuals (e.g., by substituting to remote work).”

As a result, “Small business revenues in the highest-income and highest-rent ZIP codes (e.g., the Upper East Side of Manhattan) fell by more than 65% between March and mid-April, compared with 30% in the least affluent ZIP codes. These reductions in revenue resulted in a much higher rate of small business closure in affluent areas within a given county than in less affluent areas.” As the revenues of small businesses declined, the businesses laid off workers and sometimes reduced the wages of workers they continued to employ. The employees of these small businesses, were typically lower- wage workers. The authors conclude from the data that: “Employment for high- wage workers also rebounded much more quickly: employment levels for workers in the top wage quartile [the top 20 percent of wages] were almost back to pre-COVID levels by the end of May, but remained 20% below baseline for low-wage workers even as of October 2020.”

The paper, which goes into much greater detail than the brief summary just given, can be found HERE.

Census Bureau Releases Results from the American Community Survey

Each year the U.S. Census Bureau conducts the American Community Survey (ACS) by surveying 3.5 million households on a wide range of questions including their income, their employment, their ethnicity, their marital status, how large their house or apartment is, and how many cars they own. The ACS is the most reliable source of data on these issues and is widely used by economists, business managers, and government policy makers. The data for 2019 and for the five-year period 2015-2019 were released on December 10. You can learn more about the survey and explore the data on the ACS website.

The ACS provides data on increases in income over time by different ethnic groups. This news article discusses the result that between 2005 and 2019, the incomes of Asian American grew the fastest, followed by the incomes of Hispanics, the incomes of non-Hispanic whites, and the incomes of African Americans.