Glenn Hubbard and Tony O’Brien continue their podcast series hosting guest – Professor Mike Ryan of Western Michigan University. During the conversation, we learn about Mike’s experiences working with faculty from Western Michigan School of Business taking their courses online. He also offers his thoughts on the current trade situation as well as personal insights from a January visit to Japan.
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Glenn Hubbard and Tony O’Brien continue their podcast series hosting guest – Jonathan Meer, Professor of Economics from Texas A&M University as well as the Director of the Private Enterprise Research Center at Texas A&M. During the conversation, we learn about Jonathan’s teaching over 3,500 students annually in a large online Principles of Microeconomics lecture course. He discusses how his usual online teaching absolutely helped his transition when Texas A&M closed for the semester. He also talks about the state of Higher Education, non-profit giving, as well as some challenges nonprofits face in these uncertain times.
Some notes from this Podcast if you’d like more information:
1. Link to Jonathan Meer’s Youtube video on setting up an online course:
2. Link to Jonathan’s website page providing links to his research papers on altruism and charitable giving: http://people.tamu.edu/~jmeer/research.html
3. Nontechnical summary of Jonathan’s research with Harvey Rosen on charitable giving: https://www.nber.org/reporter/2018number1/rosen.html
4. Please refer to the Apply the Concept feature from Chapter 2 of Hubbard and O’Brien Economics, 7/E, on the use of market mechanisms to allocate food at the Feeding America charity (for your convenience, we hope to post this shortly so check back).
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Glenn Hubbard and Tony O’Brien continue their podcast series with a first – hosing a guest – Penn State Economics Professor, James Tierney. We learn about the transition James had from an early return from spring break to now teaching hundreds of students exclusively online in response to the pandemic. Glenn and Tony also discuss with James the struggles of the housing market in a small college town like State College, PA. We also learn the reasons behind James becoming the founder of an adult Improv company in the State College-area and the impact it had on his teaching. Please listen and share!
Glenn Hubbard and Tony O’Brien continue their podcast series by spending just under 15 minutes discussing why it was so difficult for economists to see this pandemic and the associated economic downturn coming. Just as scientists lacked the indicators to see the pandemic coming, economists also didn’t have the tools available to see where the economy was headed even though some early signs were present. Please listen and SHARE with your students.
Glenn Hubbard and Tony O’Brien continued their podcast series by spending about 15 minutes discussing the impact of the Pandemic on the Mom and Pop Businesses across the country. Much of the stimulus package has been developed to save small business but might it be too late or just not enough? Please listen and SHARE with your students.
Supports: Econ (Chapter 19) & Micro (Chapter 9): Unemployment and Inflation; Essentials: Chapter 13.
Apply the Concept: The Double-Edged Sword of Unemployment Insurance
Here’s the key point: Unemployment insurance payments during the pandemic cushioned worker income losses but made layoffs more likely and made some workers reluctant to return to work.
When workers lose their jobs, they are usually eligible for unemployment insurance payments. State governments are responsible for funding the payments, although the federal government provides guidelines states must meet and contributes funds to pay for administering the program. As the following figure shows, the U.S. experienced an extraordinary surge in weekly unemployment insurance claims during April 2020. The increase in claims was much greater than occurred at any point during the Great Recession of 2007-2009, which was the most severe recession the U.S. economy had experienced since the Great Depression of the 1930s.
The spike in people losing their jobs and applying for unemployment insurance was primarily due to many mayors and governors ordering the closure of nonessential businesses to fight the spread of the Covid-19 disease caused by the coronavirus. Unemployment insurance payments vary across states but typically last for 26 weeks and are intended to replace about 50 percent of a worker’s wage, subject to a cap. In 2020, Congress and President Donald Trump enacted the Coronavirus Aid, Relief, and Economic Security (CARES) Act to provide funds to support firms and businesses suffering from the effects of the coronavirus pandemic. Included in the act was a provision to increase the normal state unemployment insurance payment by $600 per week for up to four months.
Congress and President Franklin Roosevelt created the U.S. unemployment insurance system during the Great Depression as part of the Social Security Act of 1935. The first payments were made in 1939. Congress has had two main goals in establishing and maintaining a system of unemployment insurance: (1) To provide the means for workers who have lost their jobs to continue to buy food, clothing, and other necessities; and (2) to help support the level of total spending in the economy to avoid making recessions worse. From the beginning, some members of Congress and some state legislators were concerned that payments to the unemployed would reduce the recipients’ incentive to quickly find a new job. In establishing the program in the 1930s, policymakers were influenced by the experience in England where high rates of unemployment throughout most of the 1920s had resulted in many people receiving government payments—being “on the dole”—for years. In reaction, most states established 26 weeks as the length of time the unemployed could receive payments and kept the amount of money at roughly half a worker’s previous wage.
Economists believe that any type of insurance results in moral hazard, which refers to the actions people take after they have entered into a transaction. In particular, insurance makes the event being insured against more likely. For instance, once a firm has purchased a fire insurance policy on a warehouse, it may choose not to install an expensive sprinkler system thereby increasing the chance that the warehouse will burn down. People with health insurance may visit a doctor for treatment of a cold or other minor illness, which they would not do if they lacked insurance. Similarly, moral hazard resulting from the unemployment insurance system may result in workers not accepting jobs that they would have taken in the absence of unemployment insurance.
Economists debate the extent to which the moral hazard involved in unemployment insurance has a significant effect on U.S. labor markets. Most studies indicate that unemployment does increase the length of time that workers are unemployed—the duration of spells of unemployment—thereby reducing the efficiency of the economy by decreasing the size of the labor force and the quantity of goods and services produced. But because unemployment insurance reduces the opportunity cost of searching for a job—since workers give up less income during the time they are searching—it may also result in a better fit between workers and jobs, thereby increasing worker productivity and economic efficiency. Most economists conclude that, on balance, unemployment insurance that lasts for only 26 weeks and replaces only 50 percent of previous income probably does not significantly reduce economic efficiency in the United States.
After passage of the CARES, some policymakers and economists again raised the issue of whether the unemployment insurance system provides disincentives for people to work. The additional $600 that an unemployed worker received under the CARES act increased the average unemployment insurance benefit from $378 per week to $978 per week. That income was equivalent to a wage of $24.45 per hour for a 40-hour week and was greater than the wage rate received by more than half of workers in the United States in early 2020, before the coronavirus pandemic began. As a result, some workers were reluctant to return to their previous jobs as some firms began to reopen during May.
A restaurant owner in Oregon noted that one of his cooks was receiving $376 more per week in unemployment insurance than he had earned working: “Why on earth would he want to come back to work?” The restaurant was having difficulty attracting enough workers to provide takeout and delivery services while the restaurant’s dining room was closed. As the head of the National Restaurant Association put it: “It’s not that these workers are lazy, they’re just making the best economic decision for their families.”
Some firms that were unsure whether to continue to employ workers during the period the firms were ordered closed. Retaining workers would make it easier to restart once mayors and governors had lifted restrictions on operating. But the availability of higher unemployment insurance payments made some of these firms decide to lay off workers instead. For example, according to an article in the Wall Street Journal, Macy’s chief executive stated that “the new benefits in the federal stimulus program played a role in the company’s decision to furlough 125,000 workers this past week.”
The supplementary unemployment insurance payments included in the CARES act succeeded in cushioning the income losses workers suffered from the layoffs during the pandemic, but they had also made it more likely that firms would lay off workers and made some workers more reluctant to return to work. Given that the additional $600 payments were scheduled to end after four months, it remained unclear whether the payments would have a lasting effect on the U.S. labor market.
Sources: Kurt Huffman, “Our Restaurants Can’t Reopen Until August,” Wall Street Journal, April 12, 20202; Eric Morath, “Coronavirus Relief Often Pays Workers More Than Work,” Wall Street Journal, April 28, 2020; Patrick Thomas and Chip Cutter, “Companies Cite New Government Benefits in Cutting Workers,” Wall Street Journal, April 7, 2020; Henry S. Farber and Robert G. Valletta, “Do Extended Unemployment Benefits Lengthen Unemployment Spells? Evidence from Recent Cycles in the U.S. Labor Market,” Journal of Human Resources, Vol. 50, No. 4, Fall 2015, pp. 873-909; Congressional Budget Office, “Understanding and Responding to Persistently High Unemployment,” February 2012; Daniel N. Price, “Unemployment Insurance, Then and Now, 1935-85,” Social Security Bulletin, Vol. 48, No. 10, October 1985, pp. 22-32; and Federal Reserve Bank of St. Louis.
Question: An article published in the New York Times during April 2020, quoted a policy analyst as stating that: “I would never two months ago have ever thought of advocating for 100 percent income replacement.”
Source: Ella Koeze, “The $600 Unemployment Booster Shot, State by State,” New York Times, April 23, 2020.
For Economics Instructors that would like the approved answers to the above questions, please email Christopher DeJohn from Pearson at christopher.dejohn@pearson.com and list your Institution and Course Number.
Supports: Econ (Chapter 20) & Macro (Chapter 10): Economics Growth, the Financial System, and Business Cycles; Essentials: Chapter 14.
Why Do Economists Have Trouble Predicting Recessions?
During the 2008 financial crisis,Queen Elizabeth of England visited the London School of Economics and famously asked the economists present, “Why did nobody notice it?” The queen is not alone in wondering why economists seem unable to predict when an economic crisis or financial crisis will hit.
There are three main reasons recessions are difficult for economists to predict:
Many economists believed that the doubling of housing prices between 2000 and 2006 was unsustainable. But few economists or policymakers realized that falling housing prices would lead many homeowners to default on their mortgages, particularly so-called subprime borrowers who had poor credit histories. Economists also didn’t realize these defaults would lead to falling prices of mortgage-backed and severe problems for financial firms that owned these securities. In a speech given in 2007, a few months before the Great Recession began, Federal Reserve Chair Ben Bernanke stated that: “We believe the effect of the troubles in the subprime sector on the broader housing market will likely be limited, and we do not expect significant spillovers from the subprime market to the rest of economy or to the financial system.” Bernanke’s opinion was shared by many other economists inside and outside the Fed. Because they didn’t fully understand that, given changes in the financial system over the previous 20 years, falling housing prices would lead to a financial crisis, most economists failed to predict the financial crisis that led to the Great Recession.
Similarly, most economists and policymakers underestimated the effects of Covid-19 when the disease first appeared in China at the end of 2019. In the past 20 years, the world has seen four similar viruses:
For various reasons, none of these viruses reached the levels in the United States that required widespread quarantines or the closing of schools and other social distancing measures, although more than 12,000 people may have died of swine flu in the United States.
This experience led many economists, policymakers, firms, and investors to believe that the United States was unlikely to experience a significant economic disruption as a result of the coronavirus. From mid-December 2019 to mid-January 2020, none of the most widely followed forecasts of U.S. real GDP growth for the year 2020 indicated that a recession was likely. The real GDP forecasts from the Congressional Budget Office, the Federal Reserve’s Federal Open Market Committee, the Goldman Sachs investment bank, and 60 economists surveyed by the Wall Street Journal were all between 1.9 percent and 2.3 percent—comparable to the 2.3 percent increase in real GDP that the U.S. had experienced during 2019. The S&P 500 stock index reached a record high on February 19, 2020, despite China already having more than 50,000 cases of infection from the virus.
By mid-March, as cases of Covid-19 became common in the United States and most cities and states were announcing social distancing policies that included closing many non-essential businesses, the S&P 500 had declined by more than 30 percent and economists and policymakers all realized that the U.S. economy would be experiencing a substantial recession
That economists failed to predict the recessions of 2007-2009 and 2020 should probably not have been surprising. Economists Zidong An, João Tovar Jalles, and Prakash Loungani of the International Monetary Fund (IMF) studied how accurate economists were in forecasting recessions in 63 countries over the period from 1990 to 2014. They found that both economists in the private sector as well as the IMF’s own economists rarely succeeded in forecasting a recession before it had begun. On average during this period, real GDP declined by 2.8 percent during the first year of a recession. But in April of the year prior to the start of a recession, the average forecast from private sector economists and economists at the IMF was for an increase in real GDP of 3 percent. By October of the year prior to a recession, private economists had reduced their forecasts of real GDP for the following year on average to an increase of 2 percent and economists at the IMF had reduced their forecast to 2.5 percent but these forecasts were still well above the actual decline in real GDP of 2.8 percent.
In recent years, economists have devoted resources to forecasting how real GDP will change during the current quarter. This nowcasting, if accurate, can provide policymakers and economists information on how a recession is progressing while it is occurring. Nowcasting generally relies on identifying relationships between economic variables that have data available monthly or weekly and real GDP, which in the United States is calculated by the BEA quarterly. Because economists disagree on which data provide the most accurate forecasts of real GDP during the current quarter, their nowcasts can be strikingly different.
The following table shows seven nowcasts issued during mid-April 2020 of real GDP during the second quarter of 2020, during the recession caused by the coronavirus pandemic. The data are given as changes expressed at an annual rate, which means they should be interpreted as indicating what the change in real GDP would be if the rate at which GDP changed in that quarter were sustained for a year. (Note that the Weekly Economic Index (WEI) and the uncertainty based forecast were originally presented as the percentage change from the same quarter in the previous year and have been converted to an annual rate.) Six of the forecasts agree in predicting that real GDP would decline during the quarter at a very high rate of more than 25 percent. As a standard of comparison, before the second quarter of 2020, the largest two quarterly declines in real GDP since 1947 were the decline of 10.0 percent in the first quarter of 1958 and the decline of 8.4 percent in the fourth quarter of 2008. Even the more moderate decline predicted by the New York Fed’s Nowcast would be among the largest in the past 75 years.
Ultimately, the difficulty that macroeconomists encounter in forecasting changes in real GDP indicates the complexity of the macroeconomy. Economists have not yet succeeded in reducing this complexity to a statistical model that can reliably forecast changes in real GDP—particularly whether a recession is likely to occur.
Sources: Scott Baker, Nicholas Bloom, Steven Davis, and Stephen Terry, “Covid-Induced Economic Uncertainty,” National Bureau of Economic Research Working Paper 26983, April 2020; Zidong An, João Tovar Jalles, and Prakash Loungani, “How Well Do Economists Forecast Recessions?” IMF Working Paper, March 2018; Board of Governors of the Federal Reserve System, “Economic Projections of Federal Reserve Board Members and Federal Reserve Bank Presidents, under Their Individual Assumptions of Projected Appropriate Monetary Policy,” federalreserve.gov, December 11, 2019; Goldman Sachs, “What’s the Outlook for the U.S. Stock Market in 2020?” January 6, 2020; “Economic Forecasting Survey,” wsj.com; Lisa Beilfuss, “Why a 50% Drop in U.S. GDP Isn’t as Bad as It Seems, barrons.com, April 14, 2020; Andrew Pierce, “The Queen Asks Why No One Saw the Credit Crunch Coming,” telegraph.com.uk, November 5, 2008; Brian Domitrovic, “The Stock Market Has Predicted Nine of the Past Five Recessions,” forbes.com, November 22, 2018; and Federal Reserve Bank of St. Louis.
Question: During the coronavirus pandemic, some people wondered why biologists seemed unable to answer many questions about the virus, including why children appeared rarely to become ill, why men were more likely than women to die from the virus, and why there was great uncertainty about whether some existing pharmaceuticals would be effective in treating the disease. Briefly discuss similarities and differences between the problem biologists faced in understanding the coronavirus and the problem economists face in predicting recessions.
For Economics Instructors that would like the approved answers to the above questions, please email Christopher DeJohn from Pearson at christopher.dejohn@pearson.com and list your Institution and Course Number.
Supports: Econ & Micro: Chapter 11, Technology, Production, and Costs (Section 11.6); Chapter 13, Monopolistic Competition; Chapter 14, Oligopoly (Section 14.1); Essentials: Chapter 9, Technology, Production, and Costs; Chapter 11, Monopolistic Competition and Oligopoly
Can Mom and Pop Businesses Survive the Coronavirus Pandemic?
By early April 2020, because of the coronavirus pandemic, all 50 state governments had issued declarations of emergency and had closed schools and some or all businesses considered to be non-essential. A survey by Alexander Bartik of the University of Illinois and colleagues indicated that about 43 percent of small businesses in the Unites States had closed, causing most of their revenue to disappear. As a result, those businesses had laid off about 40 percent of their employees.
In March 2020, Congress and President Donald Trump enacted the Coronavirus Aid, Relief, and Economic Security (CARES) Act. The act included the Paycheck Protection Program (PPP), which provided loans to businesses with 500 or fewer employees to pay for up to eight weeks of payroll expenses and certain other costs. The government would forgive the loans if business owners used 75 percent of the funds for payroll expenses.
The PPP was administered by the federal Small Business Administration with the loans being made primarily by local banks. Many small businesses have trouble borrowing from banks, particularly if they lack collateral, such as owning the building they operate in, or if they don’t have a long-term relationship with a bank by having borrowed from them in the past or having maintained a business checking account with them. In a survey by the Federal Reserve conducted in 2019, before the coronavirus pandemic, 64 percent of small businesses had faced financial challenges, such as paying operating expenses or purchasing inventories, during the previous year. Of those firms, 69 percent had relied on the owner’s personal funds to meet the financial challenge.
In mid-April 2020, it was unclear whether Congress might change the PPP to make it easier for small businesses to borrow through credit unions and other lenders that are not commercial banks. News reports indicated that a significant number of small businesses had exhausted the funds their owners had available and intended to permanently close. It’s not unusual for a small firm to fail. In a typical year, even when the economy is expanding, hundreds of thousands of businesses fail (and a similar number open). But some economists and policymakers were concerned that the effects of the pandemic might lead to a permanent reduction in the number of small firms, particularly so-called “Mom and Pop businesses”—sole proprietorships that employ fewer than 20 workers. (We discuss the differences between sole proprietorships and other ways of organizing a business in Chapter 8, Section 8.1)
The pandemic posed particular challenges for these businesses. Many small retailers, such as clothing stores, shoe stores, card shops, and toy stores, had already been hurt before the pandemic as consumers shopped at online sites such as Amazon. This trend increased during the pandemic. In addition, as many consumers shifted from eating in restaurants to buying groceries from supermarkets or online, the future of some small restaurants seemed in doubt.
Even as states and cities began to allow nonessential businesses to reopen, many consumers were reluctant to return to eating in restaurants, staying in hotels, and shopping in brick-and-mortar stores in the absence of a vaccine against the coronavirus. The shift to online buying was evident during March and April 2020 when, as many small businesses were laying off workers, Amazon was hiring an additional 175,000 workers and Walmart was hiring an additional 150,000. Some public health authorities and epidemiologists were suggesting that businesses take certain steps to reassure consumers, although doing so would raise the businesses’ costs of operating. For instance, Scott Gottlieb, former Food and Drug Administration commissioner, suggested that “businesses … should look at trying to bring testing on-site at the place of employment” to reassure customers that the businesses’ workers did not have the virus. He also suggested that restaurants print their menus on paper that could be thrown away after each use and commit to more frequent disinfecting. Clearly, the revenue earned by larger businesses would be better able to cover these costs while still at least breaking even.
If the world is entering a new period with more frequent epidemics of viruses to which most people lack immunity, small businesses will be at a further disadvantage. Although Congress and the president responded to the coronavirus with the PPP program, whether they would have funds to do so during future epidemics remained unclear. As a result, it may be of increased importance that firms have the resources to finance periods of closure without having to rely on government payments, loans from banks for which they may lack the necessary collateral, or running balances on high-interest rate credit cards. The survey by Alexander Bartik and colleagues referred to earlier indicated that the average small business has $10,000 in monthly costs and less than that amount readily available to use to pay those costs. In other words, many small businesses are dependent on paying their current costs from their current revenues.
Most small business owners are resourceful enough to respond to changing conditions, but the challenges posed by the coronavirus seemed likely to reshape the structure of some industries, including restaurants, small retail stores, gyms, non-chain hotels, and small medical and dental practices. When discussing the role that barriers to entry play in determining the level of competition and the size of firms in an industry, we emphasized the role played by physical economies of scale. For instance, we noted that:
A music streaming firm has the following high fixed costs: very large server capacity, large research and development costs for its app, and the cost of the complex accounting necessary to keep track of the payments to the musicians and other copyright holders whose songs are being streamed. A large streaming firm such as Spotify has much lower average costs than would a small music streaming firm, partly because a large firm can spread its fixed costs over a much larger quantity of subscriptions sold.
We also noted that economies of scale of this type did not exist in the restaurant industry. Prior to the pandemic, it was reasonable to argue that large restaurants were typically unable to serve meals at a lower average cost than smaller restaurants and that even if smaller restaurants faced higher average costs, by differentiating the meals they served, smaller restaurants could still attract customers despite charging a higher price than larger restaurants. But if small restaurants lack the ability to finance periods of closure during epidemics and have trouble breaking even due to the higher costs of printing paper menus, testing their employees onsite, and more frequent cleaning, they may struggle to survive. Larger restaurants can spread these costs over a larger number of meals, reducing the average cost of one meal compared with smaller restaurants. As more consumers avoid restaurants and eat more frequently at home, smaller restaurants may be pushed further up their average cost curves by being able to sell only a smaller quantity of meals.
The following figure illustrates how the pandemic may affect the costs of a typical restaurant. The long-run average cost curve LRACBP shows the situation before the pandemic. The higher costs necessary to operate after the pandemic, including printing paper menus and more frequent cleaning, shifts up the long-run average cost curve to LRACAP. Before the pandemic, the average total cost curve for the small restaurant is and for the large restaurant is
. Notice that even though the large restaurant serves Q2 meals per week and the small restaurant serves Q1 meals per week, they both have the same average total cost per meal, ATC1.
Also notice that before the pandemic, serving Q1 meals per week was the minimum efficient scale for a restaurant. Minimum efficient scale is the level of output at which all economies of scale are exhausted. The pandemic increases the costs of the small restaurant from to is
, and the costs of the large restaurant from
to
. Minimum efficient scale increases to Q3, which is more meals per week than a small restaurant can sell. As a result, the average total cost of small restaurant increases to ATC3. A larger restaurant is still selling a quantity of meals that is beyond minimum efficient scale, so its average cost only rises to ATC2. With higher average costs, smaller restaurants are less able to successfully compete with larger restaurants.
Small firms in other industries are likely to face similar challenges. The result could be a contraction in the number of firms in some industries. For instance, we may see franchised firms replacing Mom and Pop businesses—more Domino’s and Pizza Hut outlets and fewer independent pizza restaurants. Although it’s too early to tell the full effects of the coronavirus pandemic on U.S. businesses, the effects are likely to be far-reaching.
Sources: Ruth Simon, “For These Companies, Stimulus Was No Solution; ‘We Decided to Cut Our Losses,’” Wall Street Journal, April 15, 2020; Amara Omeokwe, “Small-Business Funding Dispute Challenges Community Lenders,” Wall Street Journal, April 14, 2020; Alexander W. Bartik, Marianne Bertrand, Zoë B. Cullen, Edward L. Glaeser, Michael Luca, and Christopher T. Stanton, “How Are Small Businesses Adjusting to Covid-19? Early Evidence from a Survey,” National Bureua of Economic Research, Working Paper 26989, April 2020 (https://www.nber.org/papers/w26989.pdf); Board of Governors of the Federal Reserve System, 2019 Report on Employer Firms: Small Business Credit Survey, https://www.fedsmallbusiness.org/medialibrary/fedsmallbusiness/files/2019/sbcs-employer-firms-report.pdf, 2019; Norah O’Donnell And Margaret Hynds, “5 Things to Know about Reopening the Country from Dr. Scott Gottlieb,” cbsnews.com, April 14, 2020.
Question:
Sendhil Mullainathann of the University of Chicago wrote an opinion column in the New York Times describing the situation facing the owner of a small restaurant:
She has little money in cash reserve; operating margins are thin … and her savings had already been spent on expanding the cramped kitchen. What was a thriving enterprise before the pandemic will emerge—if it emerges at all—as a hobbled business, which may well fail shortly thereafter.
A) What does Mullainathan mean by the restaurant’s “operating margins are thin”? Why would we expect the operating margins of a small restaurant to be thin?
B) If this restaurant was a “thriving enterprise” before the pandemic, why might it be likely to fail after the pandemic?
For Economics Instructors that would like the approved answers to the above questions, please email Christopher DeJohn from Pearson at christopher.dejohn@pearson.com and list your Institution and Course Number.
Supports: Econ and Micro: Chapter 8, “Firms, the Stock Market, and Corporate Governance” Macro Chapter 6; Essentials Chapter 6
The Futures market and the strange case of negative price of oil
There’s a point that seems so obvious that we haven’t explicitly mentioned it until now: The price of a good or service is always positive. After all, a price being negative means that a seller is paying a buyer to accept a good or service, which seems very unlikely. But this strange outcome did occur in the U.S. oil market during the economic upheaval caused by the coronavirus pandemic of 2020.
In the spring of 2020, there were two important developments in the world oil market:
Crude oil from different rock formations can vary in its characteristics, such as its sulfur content. Crude oil that requires more processing as it is being refined into gasoline, aviation fuel, or other products, sells for a lower price. The benchmark oil price in the United States is for a grade of crude oil called West Texas Intermediate. The following figure shows the fluctuations in the price per barrel of this type of oil from January 2018 through late April 2020.
After reaching a high of $63 per barrel in January 2020, the price of oil declined to negative $37 per barrel on April 20. In other words, sellers were willing to pay buyers $37 per barrel to accept delivery of oil. Why would a seller ever pay someone to accept a product? There are two related reasons. We can discuss the first reason using demand and supply analysis. The second reason requires a brief discussion of how the oil market is different from most other markets for goods.
Demand and Supply in the Spot Market for Oil
To understand how movements in demand and supply in the oil market resulted in a negative price, consider the following figure illustrating this situation. Before the coronavirus pandemic, the demand for oil is shown by demand curve D1 and the supply of oil by supply curve S1. The equilibrium price is P1. During the pandemic, the amount of oil demanded declined sharply from D1 to D2, and the supply of oil declined from S1 to S2. As a result, the new equilibrium price became negative at P2. We can see that for the equilibrium price to be negative, the demand curve and supply curve must intersect below the horizontal axis.
But why would a firm be willing to supply any oil at a negative price? The answer requires understanding how oil markets work. The spot price of oil is the price for oil that is available for immediate delivery. A seller at the spot price is typically a firm pumping oil, and a buyer is a firm that uses oil as an input, such as a firm that refines oil into gasoline. When you buy bread in the supermarket or a Big Mac at McDonald’s you are paying the spot price, which is the only price in the markets for most goods and services. In the figure we are showing the spot market for oil and the price is the spot price.
The Futures Market for Oil
But in addition to a spot market for oil, there is a futures market for oil, which allows individuals and firms to buy and sell futures contracts. A futures contract specifies the quantity of an asset—such as a barrel of oil—that will be delivered by the seller on a future date, the settlement date. Futures contracts exist for commodities such as oil, as well as for financial assets, such as Treasury bonds and stock indexes like the S&P 500. Futures contracts don’t set the price—the futures price—that the buyer will pay and the seller will receive on the settlement date. Instead, the price fluctuates as the contract is bought and sold on a futures exchange, such as the Chicago Board of Trade or the New York Mercantile Exchange, just as the price of a share of stock fluctuates as the stock is bought and sold in the stock market. Each oil futures contract represents 1,000 barrels (or 42,000 gallons) of oil.
The futures price of oil can differ from the spot price if people trading futures contracts expect that conditions in the oil market will differ on the settlement date from conditions today. For instance, on April 20, 2020, the date on which the spot price of oil was negative, the oil futures price on a contract with a settlement date in June was $22 per barrel and the price on a contract with a settlement date in November was $33 per barrel. The higher oil prices for June and November reflected the view among buyers and sellers and futures contracts that (1) the economy was likely to begin recovering from the worst of the pandemic by then, increasing the demand for oil and (2) the supply of oil was likely to decline further.
The spot price and the futures price are linked because it’s possible to store oil. So, the futures price should roughly equal the spot price plus the cost of storing oil between today and the settlement date of the futures contract. As the settlement date approaches, the futures price comes closer to the spot price, eventually equaling the spot price on the settlement date. Why must the spot price equal the futures price on the settlement date? Because if there were a difference between the two prices, it would be possible for an investor to make a profit. For instance, if the spot price of oil was $35 on the settlement date of the futures contract but the futures price was $40, an investor could buy oil on the spot market and simultaneously sell futures contracts. The buyers of the futures contract would have to accept delivery of oil at $40, which would allow the investor to make a risk-free profit of $5 per barrel. In practice, investors selling additional futures contracts would drive down the futures price until it equaled the spot price. Only then would the ability to make a profit disappear.
Unlike with the spot market, buyers and sellers in the futures market may not be involved with either pumping or using oil. Instead, they may be investors who hope to profit by placing a bet on which way the price of oil will change in the future. These market participants are called speculators. Speculators serve the useful purpose of adding to the number of buyers and sellers in the futures market, thereby increasing market liquidity, which is the ease with which a buyer or seller can sell an asset, such as a futures contract.
You can speculate on the price of oil using the futures market in oil. If you believe that the futures price is lower than the spot price of oil will be on the settlement date, you can hope to make a profit by buying futures contracts today and selling them after the price rises. Similarly, if you believe that the futures prices is higher than the price of oil will be in the spot market on the settlement date, you can sell futures contracts at the current high price and buy them back after the price has fallen. It’s important to understand that investors doing this type of buying and selling of futures contracts don’t expect to actually deliver or receive barrels of oil.
What Happened in the Oil Market in April 2020?
Ordinarily, when firms pumping oil expect prices to be significantly higher in the future, they can respond by withholding oil from the market in several ways: (1) They can reduce the quantity of oil they pump, in effect storing it in the ground until prices increase; (2) they can pump oil and store it until prices rise; and (3) they can store oil products like gasoline that are refined from oil on supertankers, which are capable of holding millions of barrels of oil, waiting for prices to rise.
But in the spring of 2020, the decline in demand was so large and so sudden that firms were uncertain how much to reduce the quantity of oil they were pumping. If the decline in demand was temporary, lasting only during the worst of the pandemic, firms that cut back too much would face both the cost of both closing and then reopening oil wells. In some cases, even temporarily stopping production from a well can permanently reduce how much oil can be recovered from the well. In addition, the usual places to store oil were rapidly reaching capacity. As an article in the Wall Street Journal put it: “The buildup of crude is overwhelming storage space and clogging pipelines. And in areas where tanker-ship storage isn’t readily available, producers could need to go to extremes to get rid of the excess.” The “extremes” included accepting negative prices.
On April 20, there was a second factor pushing oil prices into negative values. The May futures contract was expiring the next day, meaning that any buyer who had not sold the contract would legally have to pay for and accept delivery of 1,000 barrels of oil. As we’ve seen, some buyers and sellers of oil futures contracts are speculators who don’t intend to deliver or receive barrels of oil. Given the shortage of storage facilities, rather than accept delivery for oil with nowhere to put it, speculators were willing to take steep losses by selling their contracts at a negative price. In effect, a buyer of a contract received $37,000 ($37 per barrel × 1,000 barrels per contract) in addition to 1,000 barrels of oil—a great deal, but only if you had somewhere to store the oil.
If oil producers become convinced that the decline in demand is likely to be long-lived, they will reduce the supply of oil substantially and the spot price will rise enough to ensure that the producers are able to cover all of their costs. But the fact that the spot price of oil was briefly negative indicates the level of economic disruption the coronavirus caused.
Sources: Ryan Dezember, “U.S. Oil Costs Less Than Zero After a Sharp Monday Selloff,” Wall Street Journal, April 21, 2020; Neil Irwin, “What the Negative Price of Oil Is Telling Us,” New York Times, April 21, 2020; Myra P. Saefong, “Oil Market in ‘Super Contango’ Underlines Storage Fears as Coronavirus Destroys Crude Demand,” marketwatch.com, April 18, 2020; Benoit Faucon, Summer Said, and Timothy Puko, “U.S., Saudi Arabia, Russia Lead Pact for Record Cuts in Oil Output,” Wall Street Journal, April 12, 2020; Federal Reserve Bank of St. Louis; and U.S. Energy Information Administration.
Question:
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Supports: Chapter 2, Trade-offs, Comparative Advantage, and the Market System [Econ, Micro, Macro, and Essentials]; Chapter 9, Comparative Advantage and the Gains from International Trade [Econ and Micro; Macro Chapter 7; and Essentials Chapter 19]; Chapter 22, Aggregate Expenditure and Output in the Short Run [Macro Chapter 12].
WILL APPLE START MAKING IPHONES IN THE UNITED STATES?
Apple, like many U.S. firms, relies on a global supply chain (sometimes also called a global value chain) comprised of firms in dozens of countries to make the components used in Apple’s products. (See Hubbard/O’Brien Chapter 2, Section 2.3 of Hubbard and O’Brien Economics and Microeconomics). This strategy has allowed Apple to take advantage of both lower production costs and the engineering and manufacturing skills of firms in other countries to produce iPhones, iPads, iWatches, and MacBooks. But during the coronavirus pandemic, Apple found its supply chain disrupted because many of its suppliers located in China were forced to close for several months.
Because of the coronavirus pandemic and the trade war between the United States and China, many U.S. firms, including Apple, were considering moving some of their operations out of China. (The trade war is discussed in Chapter 9, section 9.5 of Hubbard and O’Brien Economics and Microeconomics, Chapter 7, Section 7.5 of Macroeconomics.) As an article on bloomberg.com put it, these firms were “actively seeking ways to diversify their supply chains and reduce their dependence on any single country, no matter how attractive.” For example, two Taiwanese firms, Wistron and Pegatron, which had used factories in China to assemble iPhones were moving some factories to India, Vietnam, and Taiwan.
It seemed unlikely, though, that production of iPhones would move back to the United States. Why not? First, manufacturing employment has been in decline in the United States since long before U.S. firms began using suppliers based in China. In 1947, shortly after the end of World War II, 33 percent of U.S. workers were employed in manufacturing. By 2001, when China became a member of the World Trade Organization, that percentage had already declined to 12 percent. In 2019, it was 9 percent.
Manufacturing production in the United States has held up better than manufacturing employment. The Federal Reserve’s index of manufacturing production increased more than 250 percent between the beginning of 1972 and the beginning of 2020. U.S. manufacturing has been able to increase output while employment has declined because of increases in productivity. The increases in productivity have relied, in part, on increased use of robotics, particularly in assembly line work, such as the production of automobiles. The United States has a comparative advantage in producing goods and services that require skilled labor and involve artificial intelligence, machine learning, and the use of other sophisticated computer programing. Manufacturing that relies on lower-skilled labor, such as textile and shoe production, has been mostly moved overseas.
The Taiwanese firms Foxconn, Wistron, and Pegatron assemble iPhones, primarily in factories in China and elsewhere in Asia where large quantities of unskilled labor are available. Some components of the iPhone that require skilled labor and sophisticated engineering, including the screens, the touchscreen controller, and the Wi-Fi chip, are produced by U.S. firms and shipped to China for final assembly. In fact, surprisingly, the value of the U.S.-made components exceeds the value of assembling the iPhone in Chinese factories. (See Hubbard and O’Brien Economics, Chapter 22, Section 22.3 and Macroeconomics, Chapter 12, Section 12.3).
Factory assembly lines, like those in China making iPhones, need to be flexible to respond quickly to Apple introducing new models. So, in addition, to hundreds of thousands of unskilled workers in its assembly plants, Foxconn and other firms operating in China hire thousands of engineers. Typically, these engineers do not have college degrees, but they have sufficient training to rapidly redesign and reconfigure assembly lines to produce new models. In 2010, when President Barack Obama pressed Steve Jobs, the late Apple CEO, to produce iPhones in the United States, Jobs pointed to lack of sufficient workers with engineering skills to make such production possible. Jobs stated that he would need 30,000 such engineers if Apple were to make iPhones in the United States, but “You can’t find that many in America to hire.”
The situation hasn’t changed much in the past 10 years. As an article in the Wall Street Journal observed in March 2020, in addition to a large number of unskilled workers, Foxconn employs in China, “Tens of thousands of experienced manufacturing engineers [to] oversee the [production] process. Finding a comparable amount of unskilled and skilled labor [elsewhere] is impossible.”
Although some firms were attempting to reduce their reliance on Chinese factories in response to the coronavirus pandemic, because the United States lacks a comparative advantage in the assembly of consumer electronics, it seemed unlikely that those factories would be relocated here. But the coronavirus pandemic may lead some U.S. firms to change their supply chains in other ways. For instance, firms may now put greater value on redundancy. Apple might underwrite the cost to its suppliers of building facilities in several Asian countries to assemble iPhones. In the event of problems occurring in one country, this redundant capacity would allow production to switch from factories in one country to factories in other countries.
Similarly, some firms may rethink their inventory management. Before the 1970s, most manufacturing firms kept substantial inventories of parts and components. Retail firms often kept substantial inventories of goods in warehouses. This approach began to change during the 1970s, as Toyota pioneered just-in-time inventory systems in which firms accept shipments from suppliers as close as possible to the time they will be needed. Most manufacturers in the United States and elsewhere adopted these systems, as did many retailers.
For example, at Walmart, as goods are sold in the stores, this point-of-sale information is sent electronically to the firm’s distribution centers to help managers determine what products to ship to each store. This distribution system allows Walmart to minimize its inventory holdings. Because Walmart sells 15 to 25 percent of all the toothpaste, disposable diapers, dog food, and other products sold in the United States, it has involved many manufacturers in its supply chain. For example, a company such as Procter & Gamble, one of the world’s largest manufacturers of toothpaste, laundry detergent, and toilet paper, receives Wal-Mart’s point-of-sale and inventory information electronically. Procter & Gamble uses that information to determine its production schedules and the quantities and timing of its shipments to Walmart’s distribution centers.
But as the pandemic disrupted supply chains, many manufacturers had to suspend production because they did not receive timely shipments of parts. Similarly, Walmart and other retailers experienced stockouts—sales lost because the goods consumer want to buy aren’t on the shelves.
In 2020, firms were reconsidering their supply chains as they evaluated whether to underwrite the building of redundant capacity among their suppliers and whether to reduce the extent to which they relied on just-in-time inventory systems.
Sources: Debby Wu, “Not Made in China Is Global Tech’s Next Big Trend,” bloomberg.com, March 31, 2020; Yossi Sheffi, “Commentary: Supply-Chain Risks From the Coronavirus Demand Immediate Action,” Wall Street Journal, February 18, 2020; Tripp Mickle and Yoko Kubota, “Tim Cook and Apple Bet Everything on China. Then Coronavirus Hit,” Wall Street, March 3, 2020; and Walter Isaacson, Steve Jobs, New York: Simon & Schuster, 2011, pp. 544-547.
Question: Suppose that you’re a manager at Apple. Given the coronavirus pandemic, Apple is considering whether to underwrite the cost to its suppliers, such as Foxconn, of building redundant factories in countries outside of China.. The goal is to reduce the production problems that occur when factories are concentrated in a single country during a pandemic or other disaster. Your manager asks you to prepare a brief evaluation of this idea. What factors should you take into account in your evaluation?
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