Ch11: Technology, Production, and Costs – HubbardOBrienEconomics.com Blog

The Economics of Apple’s Vision Pro

Photo from apple.com.

On Friday, February 2, Apple released Vision Pro, its long-awaited, much discussed virtual reality (VR) headset. The Vision Pro headset allows users to experience either VR, in which the user sees only virtual objects, as for instance when the user sees only images from a video game; or augmented reality (AR), in which the user sees virtual objects, such as icon apps or web pages superimposed on the real world (as in the two photos below). Apple refers to people using the headsets as being engaged in “spatial computing” and sometimes refers to the headsets as “face computers.”

Photo from Apple via the Wall Street Journal.

Photo from Apple via the Wall Street Journal.

Vision Pro has a price of $3,499, which can increase to more than $4,000 when including the cost of the insert necessary for anyone who wears prescription eyeglasses or contact lenses and who chooses to buy additional storage capacity. The price is much higher than Meta’s Quest Pro VR headset (shown in the photo below), which has a price of $999.

Photo from meta.com.

In this post, we can briefly discuss some of the economic issues raised by the Vision Pro. First, why would Apple charge such a high price? In her review of the Vision Pro in the Wall Street Journal, Joanna Stern, the site’s personal technology writer, speculated that: “You’re probably not going to buy the $3,500 Apple Vision Pro. Unless you’re an app developer or an Apple die-hard ….”

There are several reasons why Apple may believe that a price of $3,499 is profit maximizing. But we should bear in mind that pricing any new product is difficult because firms lack good data on the demand curve and are unsure how consumers will respond to changes in price. In our new ninth edition of Economics and Microeconomics, in Chapter 6 on price elasticity we discuss how Elon Musk and managers at Tesla experimented with the cutting the price of the Model 3 car as they attempted to discover the effect on price changes on the quantity demanded. Managers at Apple are in similar situation of lacking good data on how many headsets they are likely to sell at $3,499.

If Apple lacks good data on how consumers are likely to respond to different prices, why pick a price four times as high as Meta is charging for its Quest Pro VR headsets?

First, Apple expects to be able to clearly differentiate its headset from Meta’s headset. If consumers considered the two headsets to be close substitutes, the large price difference would make it unlikely that Apple would sell many headsets. Apple has several marketing advantages over Meta that make it likely that Apple can convince many consumers that the Meta headset is not a close substitute for the Vision Pro:

Apple has a history of selling popular electronic products, such as the iPhone, iPad, Air Pods, and the Apple Watch. It also owns the most popular app store. Apple has succeeded in seamlessly integrating these electronic products with each other and with use of the app store. As a result, a significant number of consumers have a strong preference for Apple products over competitors. Meta has a much more limited history of selling popular electronic products. For instance, it doesn’t produce its own smartphone.
Apple has an extensive network of retail stores inside and outside of the United States. The stores have been successful in giving consumers a chance to try a new electronic product before buying it and to receive help at the stores’ Genius Bars with setting up the device or dealing with any later problems. Meta operates few retail stores, relying instead on selling through other retailers, such as Best Buy, or through its online site. For some consumers Meta’s approach is less desirable than Apple’s.

Second, as we discuss in Economics and Microeconomics, Chapter 15, Section 15.5, charging a high price for a new electronic product is common, partly because doing so allows firms to price discriminate across time. With this strategy, firms charge a higher price for a product when it is first introduced and a lower price later. Some consumers are early adopters who will pay a high price to be among the first to own certain new products. Early adopers are a particularly large segment of buyers of Apple products, with long lines often forming at Apple stores on the days when a new product is released. That firms price discriminate over time helps explain why products such as Blu-ray players and 4K televisions sold for very high prices when they were first introduced. After the demand of the early adopters was satisfied, the companies reduced prices to attract more price-sensitive customers. For example, the price of Blu-ray players dropped by 95 percent within five years of their introduction. Similarly, we can expect that Apple will cut the price of Vision Pro significantly over time.

Third, because Apple is initially producing a relatively small number of units, it is likely experiencing a high average cost of producing the Vision Pro. The production of the components of the headset and the final assembly are likely to be subject to large economies of scale. (We discuss economies of scale in Economics and Microeconomics, Chapter 11, Section 11.6.) Apple hasn’t released information on how many units of the headset it intends to produce during 2024, but estimates are that it will be fewer than 400,000 and perhaps as few as 180,000. (Estimates can be found here, here, and here.) Compare that number to the 235 million iPhones Apple sold during 2023. We would expect as Apple’s suppliers increase their production runs, the average cost of production will decline as Apple moves down its long-run average cost curve. As a result, over time Apple is likely to cut the price.

In addition, when producing a new good, firms often experience learning as managers better understand the most efficient way to produce and assemble the new good. For example, the best method of assembling iPhones may not be the best method of assembling headsets, but this fact may only become clear after assembling several thousand headsets. Apple is likely to experience a learning curve with the average cost of producing headsets declining as the total number of headsets produced increases. While economies of scale involve a movement down a static long-run average cost curve, learning results in the long-run average cost curve shifting down. This second reason why Apple’s average cost of producing headsets will decline contributes to the liklihood that Apple will cut the price of the Vision Pro over time.

Finally, we can discuss a key factor that will determine how successful Apple is in selling headsets. In Chapter 11 of the new ninth edition of Economics and Microeconomics, we have a new Apply the Concept, “Mark Zuckerberg … Alone in the Metaverse?” In that feature, we note that Meta CEO Mark Zuckerberg has invested heavily in the metaverse, a word that typically means software programs that allow people to access either AR or VR images and information. Zuckerberg believed so strongly in the importance of the metaverse that he changed the name of the company from Facebook to Meta. The metaverse, which is accessed using headsets likes Meta’s Quest Pro or Apple’s Vision Pro, is subject to large network externalities—the usefulness of the headsets increases with the number of consumers who use them. The network externalities arise because many software applications, such as Meta’s Horizon World, depend on interactions among users and so are not very useful when there aren’t many users.

Meta hasn’t sold as many headsets as they expected because they have had difficulty attracting enough users to make their existing software useful and the failure to have enough users has reduced the incentive for other firms to develop apps for Meta’s headsets. Initially, some reviewers made similar comments about Apple’s Vision Pro. For instance, even though streaming films in 3D is one of the uses that Apple promotes, some streaming services, including Netflix and YouTube, have not yet released apps for Vision Pro. Some important business related apps, such as FaceTime and Zoom, aren’t yet available. There are also currently no workout apps. As one reviewer put it “there are few great apps” for Vision Pro. Another reviewer wondered whether the lack of compelling software and apps might result in the Vision Pro headset suffering the fate of “every headset I test [which] ends up in my closet collecting dust.”

So, a key to the success of the Vision Pro will be the ability of Apple to attract enough users to exploit the network externalities that exist with VR/AR headsets. If successful, the Vision Pro may represent an important development in the transition to spatial computing.

The Effect on a Firm’s Costs of Using a Generative AI Program

Supports: Microeconomics, Chapter 11, Section 11.5; Economics, Chapter 11, Section 11.5; and Essentials of Economics, Chapter 8, Section 8.5

Photo from the Wall Street Journal.

Imani owns a firm that sells payroll services to companies in the Atlanta area. Her largest cost is for labor. She employs workers who use software to prepare payroll reports and to handle texts and calls from client firms. She decides to begin using a generative AI program, like ChatGPT, which is capable of quickly composing thorough answers to many questions and write computer code. She will use the program to write the additional computer code needed to adapt the payroll software to individual client’s needs and to respond to clients seeking advice on payroll questions. Once the AI program is in place, she will need only half as many workers. The number of additional workers she needs to hire for every 20 additional firms that buy her service will fall from 5 to 1. She will have to pay a flat monthly licensing fee for the AI program; the fee will not change with the number of firms she sells her services to. Imani determines that making these changes will reduce her total cost of providing services to her current 2,000 clients from $2,000,000 per month to $1,600,000 per month

In answering the following questions, assume that, apart from the number of workers, none of the other inputs—such as the size of her firm’s office, the number of computers, or other software—change as a result of her leasing the AI program.

a. Briefly explain whether each of the following statements about the cost situation at Imani’s firm after she begins using the AI program is correct or incorrect.

Her firm’s average total cost, average variable cost, and average fixed cost curves will shift down, while her firm’s marginal cost curve will shift up.
Her firm’s average total cost, average variable cost, average fixed cost and marginal cost curves will all shift up.
Her firm’s average total cost, average variable cost, and marginal cost curves will shift down, while her average fixed cost curve will shift up.
Her firm’s average total cost, average variable cost, average fixed cost, and marginal cost curves will all shift down.
Her firm’s average fixed cost curve will shift up, but her other cost curves will be unchanged.

b. Draw a graph illustrating your answer to part a. Be sure to show the original average total cost, average variable cost, average fixed cost, and marginal cost curves. Also show the shifts—if any—in the curves after Imani begins using the AI program.

Solving the Problem

Step 1: Review the chapter material. This problem requires you to understand definitions of costs, so you may want to review the sections “The Difference between Fixed Costs and Variable Costs,” “Marginal Costs,” and “Graphing Cost Curves”

Step 2: Answer part (a) by explaining whether each of the five listed statements is correct or incorrect. The cost of the AI program is fixed because it doesn’t change with the quantity of her services that Imani sells. Her firm will have greater fixed costs after licensing the AI program but she will have lower variable costs because she is able to produce the same level of output with fewer workers. Her marginal cost will also decline because she needs to hire fewer workers as the quantity of services she sells increases. We know that the average total cost per month of providing her service to 2,000 clients has decreased because we are given the information that it changed from ($2,000,000/2,000) = $1,000 to ($1,600,000/2,000) = $800.

This statement is incorrect because her average fixed cost curve will shift up as a result of her total fixed cost having increased by the amount of the AI program license and because her marginal cost curve will shift down, not up.
This statement is incorrect because all of her cost curves, except for average fixed cost, will shift down, not up.
This statement is correct because it describes the actual shifts in her cost curves.
This statement is incorrect because her average fixed cost curve will shift up, not down.
This statement is incorrect because her rather than being unaffected, her average total cost, average variable cost, and marginal cost curves will shift down.

Step 3: Answer part (b) by drawing the cost curves for Imani’s firm before and after she begins using the AI program. Your graph should look like the following, where the curves representing the firm’s costs before Imani begins leasing the AI program are in blue and the costs after leasing the program are in red.

Economies of Scale in Ocean Shipping and U.S. Retailers’ Response to Pandemic Supply Chain Problems

Beginning in the 1950s, several companies pioneered in developing modern shipping containers that once arrived at docks can be lifted by cranes and directly attached to trucks or loaded on to trains for overland shipping. As economist Marc Levinson was the first to discuss in detail in his 2004 book, The Box, container shipping, by greatly reducing transportation costs, helped to make the modern global economy possible. (We discuss globalization in Economics, Chapter 9, Section 9.1 and Chapter 21, Section 21.4, and in Macroeconomics, Chapter 7, Section 7.1 and Chapter 11, Section 11.4.)

Lower transportation costs meant that small manufacturing firms and other small businesses that depended on selling in local markets faced much greater competition, including from firms located thousands of miles away. The number of dockworkers declined dramatically as the loading and unloading of cargo ships became automated. Ports such as New York City, San Francisco, and Liverpool that were not well suited for handling containers because they lacked sufficient space for the automated equipment and the warehouses, lost most of their shipping business to other ports, such as Los Angeles, Seattle, and London. Consumers in all countries benefited because lower transportation costs meant they were able to buy cheaper imported goods and had a much greater variety of goods to choose from.

In the decades since the 1950s, shipping firms have continued to exploit economies of scale in container ships. (We discuss the concept of economies of scale in Econimics and Microeconomics, Chapter 11, Section 11.6.) Today, shipping containers have been standardized at either 20 feet or 40 feet long and the largest ships can haul thousands of containers. Levinson explains why economies of scale are important in this industry:

“A vessel to carry 3,000 containers did not require twice as much steel or twice as large an engine as a vessel to carry 1,500. [Because of automation, a] larger ship did not require a larger crew, so crew wages per container were much lower. Fuel consumption did not increase proportionally with the vessel’s size.”

To take advantage of these economies of scale, the ships needed to sail fully loaded. The largest ships can sail fully loaded only on routes where shipping volumes are highest, such as between Asia and the United States or between the United States and Europe. As a result, as Levinson notes, the largest ships are “uneconomic to run on most of the world’s shipping lanes” because on most routes the costs per container are higher for the largest ships for smaller ships. (Note that even these “smaller ships” are still very large in absolute size, being able to haul 1,000 containers.)

Large U.S. retail firms, such as Walmart, Home Depot, and Target rely on imported goods from Asian countries, including China, Japan, and Vietnam. Ordinarily, they are importing goods in sufficient quantities that the goods are shipped on the largest vessels, which today have the capacity to haul 20,000 containers. But during the pandemic, a surge in demand for imported goods combined with disruptions caused by Covid outbreaks in some Asian ports and a shortage of truck drivers and some other workers in the United States, resulted in a backlog of ships waiting to disembark their cargoes at U.S. ports. The ports of Los Angeles and Long Beach in southern California were particularly affected. By October 2021, it was taking an average of 80 days for goods to be shipped across the Pacific, compared with an average of 40 days before the pandemic.

Some large U.S. firms responded to the shipping problems by chartering smaller ships that ordinarily would only make shorter voyages. According to an article in the Wall Street Journal, “the charters provide the big retailers with a way to work around bottlenecks at ports such as Los Angeles, by rerouting cargo to less congested docks such as Portland, Ore., Oakland, Calif., or the East Coast.” Unfortunately, because the smaller ships lacked the economies of scale of the larger ships, the cost the U.S. firms were paying per container were nearly twice as high. (Note that this result is similar to the cost difference between a large and a small automobile factory, which we illustrated in Economics and Microeconomics, Figure 11.6.)

Unfortunately for U.S. consumers, the higher costs U.S. retailers paid for transporting goods across the Pacific Ocean resulted in higher prices on store shelves. Shopping for presents during the 2021 holiday season turned out to be more expensive than in previous years.

Sources: Marc Levinson, The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger, Second edition, Princeton, NJ: Princeton University Press, 2016; Sarah Nassauer and Costas Paris, “Biggest U.S. Retailers Charter Private Cargo Ships to Sail Around Port Delays,” wsj.com, October 10, 2021; and Melissa Repko, “How Bad Are Global Shipping Snafus? Home Depot Contracted Its Own Container Ship as a Safeguard,” cnbc.com, June 13, 2021.

The Wall and the Bridge – an article from Glenn Hubbard in National Affairs.

Advances in technology and expanding international trade have disrupted some key U.S. industries. These developments have made new products available, lowered the prices of existing products, and fostered the creation of new companies and new jobs. Yet, there has also been a downside. Some U.S. manufacturing firms have disappeared and some workers have been left unemployed for long periods. How can economists help frame a discussion about policies that will help everyone participate as the economy continues to evolve? Glenn Hubbard discusses a new approach in his article “The Wall and the Bridge”, published in National Affairs in September 2020.

COVID-19 Update – Can Mom and Pop Businesses Survive the Coronavirus Pandemic?

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 LRAC_BP 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 LRAC_AP. 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.