Read this and answer questions at the bottom.
How Much of Your $355 Ticket Is Profit for Airlines_ - WSJ.pdf
How Much of Your $355 Ticket Is Profit for Airlines?
Airlines are healthierthan everinancially—and that’s why they add more fees and more seats
Next time you board a flight, just imagine you’re putting a $20 bill in the airline’s tip jar. Profit per passenger at the seven largest U.S. airlines averaged $19.65 over the past four years— record-setting profitable years for airlines. In 2017, it stood at $17.75, based on airline earnings reports. In truth, airlines now cover their costs with tickets and get their profits from baggage fees, seat fees, reservation-change fees and just about all the other nickel-and-diming that aggravates customers. You might also call those extra 12 to 15 passengers now crammed onto each flight “Andrew Jackson” for the profit they bring. It takes a lot to earn a little moving people. U.S. airlines experienced plenty of years of steep losses, when creditors were subsidizing tickets for travelers. But now, profit margins—about 9% in 2017—are healthy. Keeping $20 from every passenger is about twice the profit airlines in the rest of the world get, according to data from the International Air Transport Association. “It’s certainly high by airline historic standards. But it’s not high if you look across other companies in the U.S. economy. It’s average,” says Brian Pearce, IATA’s chief economist. U.S. airlines were on pace to take in more than $4 billion in baggage fees and $3 billion in reservation-change and cancellation penalties in 2017, according to Transportation Department data. (The full year hasn’t been tallied yet.) Most of that drops straight to the bottom line. The two categories add up to about more than half of the net profits airlines posted last year. Airline earnings are further boosted by other fees for things like seats assignments, extra legroom, early boarding and pets, plus sales of frequent flier miles to banks for credit-card rewards. Given the $20-per-passenger haul ($40 round-trip), it’s easy to see why airlines are so intent on cramming in more seats, even when they know travelers hate the lack of space and complain bitterly about shrunken bathrooms, slim seat padding and skinny rows. Last year, the average round-trip fare on the seven largest U.S. carriers— American , Delta , United, Southwest , Alaska , JetBlue and Spirit —was $355, based on their financial reports, up from $351 in 2016. Getting an extra two rows of seats on a plane can mean the difference between profit and loss. Of course, some passengers are far more profitable than others. First-class and businessclass travelers are more valuable when they pay for their tickets; less when they get a free upgrade. But even then, road warriors are often upgraded from high-dollar, last-minute coach tickets. Frequent travelers account for a large percentage of airline revenue—and profit. Low-fare passengers shoehorned into the back of the plane may not even be covering what it costs to transport them. But they scored a low fare because the airline was concerned it might not fill all the seats on a particular flight, and some fare is better than no fare. IATA’s Mr. Pearce says airline profits last year were squeezed by higher fuel and labor costs, and that trend is continuing in 2018. Jet fuel prices were up 26% last year compared with 2016, and prices are expected to be about 10% higher this year. Airline fuel efficiency has improved significantly world-wide as newer planes go into service, and older gasguzzlers are retired. But higher fuel prices have driven airline costs higher. At the same time, expanding competition from low-fare carriers has kept fare increases small. Big airlines are building up in competitive markets like Seattle, Boston and Los Angeles. Even some cities that saw dramatic air-service cuts are getting more flights now; Delta recently announced an expansion in Cincinnati, for example. With more empty seats to sell, airlines are finding it even harder to raise ticket prices. “Fares are too low for oil prices this high,” American Airlines Chief Executive Doug Parker said on an earnings call with analysts last month. “Over time you’ll see it adjust.” American spent $1.3 billion more on fuel in 2017 than the previous year, a 22% increase. The carrier also spent nearly $1 billion more on labor, a 9% increase. The airline grew only about 1% last year, so rising costs meant earnings were down $757 million. Thus Mr. Parker is pushing for higher fares. Among the big U.S. airlines, Southwest had the largest net profit margin last year, at 16.5%. Southwest continues to defy conventional airline wisdom. It doesn’t charge baggage fees; instead, it believes it attracts more passengers to each flight because many want to avoid the baggage fees charged by competitors. Alaska, JetBlue and Spirit all had higher profit margins than American, Delta and United. American had the lowest profit margin among the top carriers, at 4.5% in 2017. Airlines’ average profit margin of 9% is about average for a U.S. business. Last year McDonald’s posted a net profit margin of 23%; FedEx , 5%. But that average is a leap for an industry that had cumulative losses from 1979 to 2014 of $35 billion and suffered six major bankruptcies in the 2000s.
Questions.
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1. How profitable are airlines today in comparison to historical performance? In comparison to other industries? |
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2. What does the author mean when he states that airlines get their profits from fees rather than ticket sales? Is this based on the fact that there is no cost of goods sold as there is for ticket sales? Explain your answer. |
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3. What earnings metric is used to compare profits across airlines of different sizes? |
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4. Consider the note to the graphic entitled "Flight Change." How much difference exists in determining this metric across airlines? Do you think the differences hurt this comparison? Explain. |
In: Operations Management
The story of ZZZZ Best is one of greed and audaciousness. It is the story of a 15-year-old boy from Reseda, California, who was driven to be successful, regardless of the costs. His name is Barry Minkow. Although this case dates back over 30 years, it does serve as an example of what can happen when auditors do not look too hard to find fraud.
Minkow had high hopes to make it big—to be a millionaire very early in life. He started a carpet cleaning business in the garage of his home. Minkow realized early on that he was not going to become a millionaire cleaning other people’s carpets, but that he could in the insurance restoration business. In other words, ZZZZ Best would contract to do carpet and drapery cleaning jobs after a fire or flood. Because the damage from the fire or flood probably would be covered by insurance, the customer would be eager to have the work done, and perhaps not be all that concerned with how much it would cost. The only problem with Minkow’s insurance restoration idea was that it was all a fiction. Allegedly, over 80 percent of his revenue was from this work. In the process of creating the fraud, Minkow was able to dupe the auditors, Ernst & Whinney (now EY), into thinking the insurance restoration business was real. The auditors never caught on until it was too late.
How Barry Became a Fraudster
Minkow wrote a book, Clean Sweep: A Story of Compromise, Corruption, Collapse, and Comeback, that provides some insights into the mind of a 15-year-old kid who was called a “wonder boy” on Wall Street until the bubble burst. He was trying to find a way to drum up customers for his fledgling carpet cleaning business. One day, while he was alone in his garage-office, Minkow called Channel 4 in Los Angeles. He disguised his voice so he wouldn’t sound like a teenager and told a producer that he had just had his carpets cleaned by the 16-year-old owner of ZZZZ Best. He sold the producer on the idea that it would be good for society to hear the success story about a high school junior running his own business. The producer bought it lock, stock, and carpet cleaner. Minkow gave the producer the phone number of ZZZZ Best and waited. It took less than five minutes for the call to come in. Minkow answered the phone and when the producer asked to speak with Mr. Barry Minkow, Minkow said, “Who may I say is calling?” Within days, a film crew was in his garage shooting ZZZZ Best at work. The story aired that night, and it was followed by more calls from radio stations and other television shows wanting to do interviews. The calls flooded in with customers demanding that Barry Minkow personally clean their carpets.
As his income increased in the spring of 1983, Minkow found it increasingly difficult to run the company without a checking account. He managed to find a banker that was so moved by his story that the banker agreed to allow an underage customer to open a checking account. Minkow used the money to buy cleaning supplies and other necessities. Even though his business was growing, Minkow ran into trouble paying back loans and interest when due.
Minkow developed a plan of action. He was tired of worrying about not having enough money. He went to his garage—where all his great ideas first began—and looked at his bank account statement, which showed that he had more money than he thought he had based on his own records. Minkow soon realized it was because some checks he had written had not been cashed by customers, so they didn’t yet show up on the bank statement. Voilá! Minkow started to kite checks between two or more banks. He would write a check on one ZZZZ Best account on the last day of the reporting period and deposit it into another. The check wouldn't clear Bank # 1 for at least one day so he could count the cash in both accounts (back then, checks weren’t always processed in real time the way they are today).
It wasn’t long thereafter that Minkow realized he could kite checks big time. Not only that, he could make the transfer of funds at the end of a month or a year and show a higher balance than really existed in Bank #1 and carry it onto the balance sheet. Because Minkow did not count the check written on his account in Bank #1 as an outstanding check, he was able to double-count.
Time to Expand the Fraud
Over time, Minkow moved on to bigger and bigger frauds, like having his trusted cohorts confirm to banks and other interested parties that ZZZZ Best was doing insurance restoration jobs. Minkow used the phony jobs and phony revenue to convince bankers to make loans to ZZZZ Best. He had cash remittance forms made up from nonexistent customers with whatever sales amount he wanted to appear on the document. He even had a co-conspirator write on the bogus remittance form, “Job well done.” Minkow could then show a lot more revenue than he was really making.
Minkow’s phony financial statements enabled him to borrow more and more money and expand the number of carpet cleaning outlets. However, Minkow’s personal tastes had become increasingly more expensive, including purchasing a Ferrari with the borrowed funds and putting a down payment on a 5,000-square-foot home. So, the question was: How do you solve a perpetual cash flow problem? You go public! That’s right, Minkow made a public offering of stock in ZZZZ Best. Of course, he owned a majority of the stock to maintain control of the company.
Minkow had made it to the big leagues. He was on Wall Street. He had investment bankers, CPAs, and attorneys all working for him—the now 19-year-old kid from Reseda, California, who had turned a mom-and-pop operation into a publicly owned corporation.
Barry Goes Public
Pressured to get a big-time CPA firm to do his audit by the underwriting firm selling his stock, Minkow hired Ernst & Whinney to perform the April 30, 1987, fiscal year-end audit. Minkow continued to be one step ahead of the auditors—that is, until the Ernst & Whinney auditors insisted on going to see an insurance restoration site. They wanted to confirm that all the business—all the revenue—that Minkow had said was coming in to ZZZZ Best was real.
The engagement partner drove to an area in Sacramento, California, where Minkow did a lot of work—supposedly. He looked for a building that seemed to be a restoration job. Why he did that isn’t clear, but he identified a building that seemed to be the kind that would be a restoration job in progress.
Earlier in the week, Minkow had sent one of his cohorts to find a large building in Sacramento that appeared to be a restoration site. As luck would have it, Minkow’s associate picked out the same site as had the partner later on. Minkow’s cohorts found the leasing agent for the building. They convinced the agent to give them the keys so that they could show the building to some potential tenants over the weekend. Minkow’s helpers went up to the site before the arrival of the partner and placed placards on the walls that indicated ZZZZ Best was the contractor for the building restoration. In fact, the building was not fully constructed at the time, but it looked as if some restoration work was going on at the site.
Minkow was able to pull it off in part due to luck and in part because the Ernst & Whinney auditors did not want to lose the ZZZZ Best account. It had become a large revenue producer for the firm, and Minkow seemed destined for greater and greater achievements. Minkow was smart and used the leverage of the auditors not wanting to lose the ZZZZ Best account as a way to complain whenever they became too curious about the insurance restoration jobs. He would even threaten to take his business from Ernst & Whinney and give it to other auditors. To get on their good side, he would wine and dine the auditors and even invite them to his house.
Minkow also took a precaution with the site visit. He had the auditors sign a confidentiality agreement that they would not make any follow-up calls to any contractors, insurance companies, the building owner, or other individuals involved in the restoration work. This prevented the auditors from corroborating the insurance restoration contracts with independent third parties.
The Fraud Starts to Unravel
It was a Los Angeles housewife who started the problems for ZZZZ Best that would eventually lead to the company’s demise. Because Minkow was a well-known figure and flamboyant character, the Los Angeles Times did a story about the carpet cleaning business. The Los Angeles housewife read the story about Minkow and recalled that ZZZZ Best had overcharged her for services in the early years by increasing the amount of the credit card charge for its carpet cleaning services.
Minkow had gambled that most people don’t check their monthly statements, so he could get away with the petty fraud. However, the housewife did notice the overcharge and complained to Minkow, and eventually he returned the overpayment. She couldn’t understand why Minkow would have had to resort to such low levels back then if he was as successful as the Times article made him out to be. So she called the reporter to find out more, and that ultimately led to the investigation of ZZZZ Best and future stories that weren’t so flattering.
Because Minkow continued to spend lavishly on himself and his possessions, he always seemed to need more and more money. It got so bad over time that he was close to defaulting on loans and had to make up stories to keep the creditors at bay, and he couldn’t pay his suppliers. The complaints kept coming in, and eventually the house of cards that was ZZZZ Best came crashing down.
During the time that the fraud was unraveling, Ernst & Whinney decided to resign from the ZZZZ Best audit. It had started to doubt the veracity of Minkow and his business at ZZZZ Best. Of course, by then it mattered little because the firm had been a party to the cover-up for some time.
Legal Liability Issues
The ZZZZ Best fraud was one of the largest of its time. ZZZZ Best reportedly settled a shareholder class action lawsuit for $35 million. Ernst & Whinney was sued by a bank that had made a multimillion-dollar loan based on the financial statements for the three-month period ending July 31, 1986. The bank claimed that it had relied on the review report issued by Ernst & Whinney in granting the loan to ZZZZ Best. However, the firm had indicated in its review report that it was not issuing an opinion on the ZZZZ Best financial statements. The judge ruled that the bank was not justified in relying on the review report because Ernst & Whinney had expressly disclaimed issuing any opinion on the statements. The firm lucked out in that the judge understood that a review engagement only provides limited assurance rather than the reasonable assurance of the audit.
Barry Minkow was charged with engaging in a $100 million fraud scheme. He was sentenced to a term of 25 years.
The external auditors at Ernst and Whinney succumbed to which part of the fraud triangle?
A) Opportunity
B) Incentive pressure
C) Rationalization
D) Opportunity and rationalization
In: Accounting
[The following information applies to the questions displayed below.]
Canada-based Nortel Networks was one of the largest telecommunications equipment companies in the world prior to its filing for bankruptcy protection on January 14, 2009, in the United States, Canada, and Europe. The company had been subjected to several financial reporting investigations by U.S. and Canadian securities agencies in 2004. The accounting irregularities centered on premature revenue recognition and hidden cash reserves used to manipulate financial statements. The goal was to present the company in a positive light so that investors would buy (hold) Nortel stock, thereby inflating the stock price. Although Nortel was an international company, the listing of its securities on U.S. stock exchanges subjected it to all SEC regulations, along with the requirement to register its financial statements with the SEC and prepare them in accordance with U.S. GAAP.
The company had gambled by investing heavily in Code Division Multiple Access (CDMA) wireless cellular technology during the 1990s in an attempt to gain access to the growing European and Asian markets. However, many wireless carriers in the aforementioned markets opted for rival Global System Mobile (GSM) wireless technology instead. Coupled with a worldwide economic slowdown in the technology sector, Nortel’s losses mounted to $27.3 billion by 2001, resulting in the termination of two-thirds of its workforce.
The Nortel fraud primarily involved four members of Nortel’s senior management as follows: CEO Frank Dunn, CFO Douglas Beatty, controller Michael Gollogly, and assistant controller Maryanne Pahapill. At the time of the audit, Dunn was a certified management accountant, while Beatty, Gollogly, and Pahapill were chartered accountants in Canada.
Accounting Irregularities
On March 12, 2007, the SEC alleged the following in a complaint against Nortel:1
In late 2000, Beatty and Pahapill implemented changes to Nortel’s revenue recognition policies that violated U.S. GAAP, specifically to pull forward revenue to meet publicly announced revenue targets. These actions improperly boosted Nortel’s fourth quarter and fiscal 2000 revenue by over $1 billion, while at the same time allowing the company to meet, but not exceed, market expectations. However, because their efforts pulled in more revenue than needed to meet those targets, Dunn, Beatty, and Pahapill selectively reversed certain revenue entries during the 2000 year-end closing process.
In November 2002, Dunn, Beatty, and Gollogly learned that Nortel was carrying over $300 million in excess reserves. The three did not release these excess reserves into income as required under U.S. GAAP. Instead, they concealed their existence and maintained them for later use. Further, Beatty, Dunn, and Gollogly directed the establishment of yet another $151 million in unnecessary reserves during the 2002 year-end closing process to avoid posting a profit and paying bonuses earlier than Dunn had predicted publicly. These reserve manipulations erased Nortel’s pro forma profit for the fourth quarter of 2002 and caused it to report a loss instead.2
In the first and second quarters of 2003, Dunn, Beatty, and Gollogly directed the release of at least $490 million of excess reserves specifically to boost earnings, fabricate profits, and pay bonuses. These efforts turned Nortel’s first-quarter 2003 loss into a reported profit under U.S. GAAP, which allowed Dunn to claim that he had brought Nortel to profitability a quarter ahead of schedule. In the second quarter of 2003, their efforts largely erased Nortel’s quarterly loss and generated a pro forma profit. In both quarters, Nortel posted sufficient earnings to pay tens of millions of dollars in so-called return to profitability bonuses, largely to a select group of senior managers.
During the second half of 2003, Dunn and Beatty repeatedly misled investors as to why Nortel was conducting a purportedly “comprehensive review” of its assets and liabilities, which resulted in Nortel’s restatement of approximately $948 million in liabilities in November 2003. Dunn and Beatty falsely represented to the public that the restatement was caused solely by internal control mistakes. In reality, Nortel’s first restatement was necessitated by the intentional improper handling of reserves, which occurred throughout Nortel for several years, and the first restatement effort was sharply limited to avoid uncovering Dunn, Beatty, and Gollogly’s earnings management activities.
The complaint charged Dunn, Beatty, Gollogly, and Pahapill with violating and/or aiding and abetting violations of the antifraud, reporting, and books and records requirements. In addition, they were charged with violating the Securities Exchange Act Section 13(b)(2)(B) that requires issuers to devise and maintain a system of internal accounting controls sufficient to provide reasonable assurances that, among other things, transactions are recorded as necessary to permit the preparation of financial statements in conformity with U.S. GAAP and to maintain accountability for the issuer’s assets.
Dunn and Beatty were separately charged with violations of the officer certification provisions instituted by SOX under Section 302. The commission sought a permanent injunction, civil monetary penalties, officer and director bars, and disgorgement with prejudgment interest against all four defendants.
Specifics of Earnings Management Techniques
From the third quarter of 2000 through the first quarter of 2001, when Nortel reported its financial results for year-end 2000, Dunn, Beatty, and Pahapill altered Nortel’s revenue recognition policies to accelerate revenues as needed to meet Nortel’s quarterly and annual revenue guidance, and to hide the worsening condition of Nortel’s business. Techniques used to accomplish this goal include:
Reinstituting bill-and-hold transactions. The company tried to find a solution for the hundreds of millions of dollars in inventory that was sitting in Nortel’s warehouses and offsite storage locations. Revenues could not be recognized for this inventory because U.S. GAAP revenue recognition rules generally require goods to be delivered to the buyer before revenue can be recognized. This inventory grew, in part, because orders were slowing and, in June 2000, Nortel had banned bill-and-hold transactions from its sales and accounting practices. The company reinstituted bill-and-hold sales when it became clear that it fell short of earnings guidance. In all, Nortel accelerated into 2000 more than $1 billion in revenues through its improper use of bill-and-hold transactions.
Restructuring business-asset write-downs. Beginning in February 2001, Nortel suffered serious losses when it finally lowered its earnings guidance to account for the fact that its business was suffering from the same widespread economic downturn that affected the entire telecommunications industry. As Nortel’s business plummeted throughout the remainder of 2001, the company reacted by implementing a restructuring that, among other things, reduced its workforce by two-thirds and resulted in a significant write-down of assets.
Creating reserves. In relation to writing down the assets, Nortel established reserves that were used to manage earnings. Assisted by defendants Beatty and Gollogly, Dunn manipulated the company’s reserves to manage Nortel’s publicly reported earnings, create the false appearance that his leadership and business acumen was responsible for Nortel’s profitability, and pay bonuses to these three defendants and other Nortel executives.
Releasing reserves into income. From at least July 2002 through June 2003, Dunn, Beatty, and Gollogly released excess reserves to meet Dunn’s unrealistic and overly aggressive earnings targets. When Nortel internally (and unexpectedly) determined that it would return to profitability in the fourth quarter of 2002, the reserves were used to reduce earnings for the quarter, avoid reporting a profit earlier than Dunn had publicly predicted, and create a stockpile of reserves that could be (and were) released in the future as necessary to meet Dunn’s prediction of profitability by the second quarter of 2003. When 2003 turned out to be rockier than expected, Dunn, Beatty, and Gollogly orchestrated the release of excess reserves to cause Nortel to report a profit in the first quarter of 2003, a quarter earlier than the public expected, and to pay defendants and others substantial bonuses that were awarded for achieving profitability on a pro forma basis. Because their actions drew the attention of Nortel’s outside auditors, they made only a portion of the planned reserve releases. This allowed Nortel to report nearly break-even results (though not actual profit) and to show internally that the company had again reached profitability on a pro forma basis necessary to pay bonuses.
Siemens Reserve
During the fraud trial, former Nortel accountant Susan Shaw testified about one of the most controversial accounting provisions on the company’s books, relating to a 2001 lawsuit filed against Nortel by Siemens AG. It was long-standing practice across Nortel to establish reserves on a “worst case” basis, which meant at an amount equal to the maximum possible exposure.
Nortel had created an accounting reserve on its books at the time the Siemens lawsuit was filed to provide for a settlement in the case, but it was alleged that a portion of the provision was arbitrarily left on Nortel’s books long after the lawsuit was resolved in the fourth quarter of 2001. It became part of a group of extra head office, non-operating reserves that allegedly was reversed arbitrarily—and with no appropriate business trigger—to push the company into a profit in 2003 and earn “return to profitability” bonuses for executives.
The $4-million remaining Siemens provision was initially booked to be reversed into income in the first quarter of 2003, but then withdrawn, allegedly because it was not needed to push the company into a profitable position in the quarter. It was then booked to be used in the second quarter, and became the only head office non-operating reserve used in the quarter.
The contention was that the Siemens reserve was used in that quarter because Nortel needed almost exactly $4 million more income to reach the payout trigger for the company’s restricted share unit plan at that time. However, lawyer David Porter argued the Siemens amount was triggered in the second quarter because that is when the company believed it was no longer needed and should appropriately be reversed.
In cross-examination, Porter showed Shaw a working document recovered from the files of Nortel’s external auditors at Deloitte & Touche, showing the auditor reviewed Nortel’s justifications for keeping the Siemens reserve on the books until that time and for reversing it in the second quarter of 2003. Deloitte’s notes showed the auditor reviewed Nortel’s detailed rationale for the reserve and concluded its release in the second quarter was “reasonable.”3
The company said it was holding on to the reserve because the settlement with Siemens had been “rancorous” and Nortel wanted to be sure there would be no further claims made after the lawsuit was settled and $32 million was paid to Siemens in two installments in late 2001 and late 2002.
In its working notes, Deloitte recorded that Nortel felt it was “prudent” to keep the $4 million on the books until mid-2002. Shaw testified she felt the reserve was being reversed on schedule with the plan to keep it in place for the first two quarters of the year. Porter asked Shaw whether the auditors were satisfied at the time there was an appropriate triggering event to use the reserve in the second quarter of 2002, and she replied there was one.
However, the amount became part of a broad restatement of reserves announced at Nortel at the end of 2003. The company noted in the restatement that the Siemens reserve should have been reversed in the fourth quarter of 2001 when the lawsuit was settled.
Role of Auditors and Audit Committee
In late October 2000, as a first step toward reintroducing bill-and-hold transactions into Nortel’s sales and accounting practices, Nortel’s then controller and assistant controller asked Deloitte to explain, among other things, (1) “[u]nder what circumstances can revenue be recognized on product (merchandise) that has not been shipped to the end customer?” and (2) whether merchandise accounting can be used to recognized revenues “when installation is imminent” or “when installation is considered to be a minor portion of the contract”?4
On November 2, 2000, Deloitte presented Nortel with a set of charts that, among other things, explained the US GAAP criteria for revenues to be recognized prior to delivery (including additional factors to consider for a bill-and-hold transaction) and also provided an example of a customer request for a bill-and-hold sale “that would support the assertion that Nortel should recognize revenue” prior to delivery.
Nortel’s earnings management scheme began to unravel at the end
of the second quarter of 2003. On the morning of July 24, 2003, the
same day on which Nortel issued its second Quarter 2003 earnings
release, Deloitte informed Nortel’s audit committee that it had
found a “reportable condition” with respect to weaknesses in
Nortel’s accounting for the establishment and disposition of
reserves. Deloitte went on to explain that, in response to its
concerns, Nortel’s management had undertaken a project to gather
support and determine proper resolution of certain provision
balances. Management, in fact, had undertaken this project because
the auditor required adequate audit evidence for the upcoming
year-end 2003 audit. Nortel concealed its auditor’s concerns from
the public, instead disclosing the comprehensive review.
Shortly after Nortel’s announced restatement, the audit committee commenced an independent investigation and hired outside counsel to help it “gain a full understanding of the events that caused significant excess liabilities to be maintained on the balance sheet that needed to be restated,” as well as to recommend any necessary remedial measures. The investigation uncovered evidence that Dunn, Beatty, and Gollogly and certain other financial managers were responsible for Nortel’s improper use of reserves in the second half of 2002 and first half of 2003.
In March 2004, Nortel suspended Beatty and Gollogly and announced that it would “likely” need to revise and restate previously filed financial results further. Dunn, Beatty, and Gollogly were terminated for cause in April 2004.
On January 11, 2005, Nortel issued a second restatement that restated approximately $3.4 billion in misstated revenues and at least another $746 million in liabilities. All of the financial statement effects of the defendants’ two accounting fraud schemes were corrected as of this date, but there remained lingering effects from the defendants’ internal control and other nonfraud violations.
Nortel also disclosed the findings to date of the audit committee’s independent review, which concluded, among other things, that Dunn, Beatty, and Gollogly were responsible for Nortel’s improper use of reserves in the second half of 2002 and first half of 2003. The second restatement, however, did not reveal that Nortel’s top executives had also engaged in revenue recognition fraud in 2000.
In May 2006, in its Form 10-K for the period ending December 31, 2005, Nortel admitted for the first time that its restated revenues in part had resulted from management fraud, stating that “in an effort to meet internal and external targets, the senior corporate finance management team . . . changed the accounting policies of the company several times during 2000,” and that those changes were “driven by the need to close revenue and earnings gaps.”
Throughout their scheme, the defendants lied to Nortel’s independent auditor by making materially false and misleading statements and omissions in connection with the quarterly reviews and annual audits of the financial statements that were materially misstated. Among other things, each of the defendants submitted management representation letters to the auditors that concealed the fraud and made false statements, which included that the affected quarterly and annual financial statements were presented in conformity with U.S. GAAP and that they had no knowledge of any fraud that could have a material effect on the financial statements. Dunn, Beatty, and Gollogly also submitted a false management representation letter in connection with Nortel’s first restatement, and Pahapill likewise made false management representations in connection with Nortel’s second restatement.
The defendants’ scheme resulted in Nortel issuing materially false and misleading quarterly and annual financial statements and related disclosures for at least the financial reporting periods ending December 31, 2000, through December 31, 2003, and in all subsequent filings made with the SEC that incorporated those financial statements and related disclosures by reference.
On October 15, 2007, Nortel, without admitting or denying the SEC’s charges, agreed to settle the commission’s action by consenting to be enjoined permanently from violating the antifraud, reporting, books and records, and internal control provisions of the federal securities laws and by paying a $35 million civil penalty, which the commission placed in a Fair Fund5 for distribution to affected shareholders.6 Nortel also agreed to report periodically to the commission’s staff on its progress in implementing remedial measures and resolving an outstanding material weakness over its revenue recognition procedures.
On January 14, 2009, Nortel filed for protection from creditors in the United States, Canada, and the United Kingdom in order to restructure its debt and financial obligations. In June, the company announced that it no longer planned to continue operations and that it would sell off all of its business units. Nortel’s CDMA wireless business and long-term evolutionary access technology (LTE) were sold to Ericsson, and Avaya purchased its Enterprise business unit.
The final indignity for Nortel came on June 25, 2009, when
Nortel’s stock price dropped to 18.5¢ a share, down from a high of
$124.50 in 2000. Nortel’s battered and bruised stock was finally
delisted from the S&P/TSX composite index, a stock index for
the Canadian equity market, ending a colossal collapse on an
exchange on which the Canadian telecommunications giant’s stock
valuation once accounted for a third of its value.
Postscript
The three former top executives of Nortel Networks Corp. were found not guilty of fraud on January 14, 2013. In the court ruling, Justice Frank Marrocco of the Ontario Superior Court found that the accounting manipulations that caused the company to restate its earnings for 2002 and 2003 did not cross the line into criminal behavior.
Accounting experts said the case is sure to be closely watched by others in the business community for the message it sends about where the line lies between fraud and the acceptable use of discretion in accounting.
The decision underlines that management still has a duty to prepare financial statements that “present fairly the financial position and results of the company” according to a forensic accountant, Charles Smedmor, who followed the case. “Nothing in the judge’s decision diminished that duty.”
During the trial, lawyers for the accused said that the men believed that the accounting decisions they made were appropriate at the time, and that the accounting treatment was approved by Nortel’s auditors from Deloitte & Touche. Judge Marrocco accepted these arguments, noting many times in his ruling that bookkeeping decisions were reviewed and approved by auditors and were disclosed adequately to investors in press releases or notes added to the financial statements.
Nonetheless, the judge also said that he believed that the accused were attempting to “manage” Nortel’s financial results in both the fourth quarter of 2002 and in 2003, but he added he was not satisfied that the changes resulted in material misrepresentations. He said that except for $80 million of reserves released in the first quarter of 2003, the rest of the use of reserves was within “the normal course of business.” Judge Marrocco said the $80 million release, while clearly “unsupportable” and later reversed during a restatement of Nortel’s books, was disclosed properly in Nortel’s financial statements at the time and was not a material amount. He concluded that Beatty and Dunn “were prepared to go to considerable lengths” to use reserves to improve the bottom line in the second quarter of 2003, but he said the decision was reversed before the financial statements were completed because Gollogly challenged it.
In a surprising twist, Judge Marrocco also suggested the two devastating restatements of Nortel’s books in 2003 and 2005 were probably unnecessary in hindsight, although he said he understood why they were done in the context of the time. He said the original statements were arguably correct within a threshold of what was material for a company of that size.
Darren Henderson, an accounting professor at the Richard Ivey School of Business at the University of Western Ontario, said that a guilty verdict would have raised the bar for management to justify their accounting judgments. But the acquittal makes it clear that “management manipulation of financial statements is very difficult to prove beyond a reasonable doubt in a court of law,” he said.
It is clear that setting up reserves or provisions is still subject to management discretion, Henderson said. “The message . . . is that it is okay to use accounting judgments to achieve desired outcomes, [such as] a certain earnings target.”
___________________
1U.S. District Court for the Southern District of New York, U.S. Securities and Exchange Commission v. Frank A. Dunn, Douglas C. Beatty, Michael J. Gollogly, and Maryanne E. Pahapill, Civil Action No. 07-CV-2058, www.sec.gov/litigation/complaints/ 2007/comp20036.pdf .
2Pro forma means literally as a matter of form. Companies sometimes report income to the public and financial analysts that may not be calculated in accordance with GAAP. For example, a company might report pro forma earnings that exclude depreciation expense, amortization expense, and nonrecurring expenses such as restructuring costs. In general, pro forma earnings are reported in an effort to put a more positive spin on a company’s operations. Unfortunately, there are no accounting rules on just how pro forma should be calculated, so comparability is difficult at best, and investors may be misled as a result.
3Janet McFarland, “Nortel Accounting Reserve Reversal Deemed ‘Reasonable,’” The Globe and Mail, September 6, 2012, Available at:http://www.theglobeandmail.com/globe-investor/nortel-accounting-reserve-reversal-deemed-reasonable-by-auditors-court-told/article4171550/.
4U.S. SEC v. Nortel Networks Corporation and Nortel Networks Limited, Civil Action No. 07-CV-8851, October 15, 2007, Available at:https://www.sec.gov/litigation/complaints/2007/comp20333.pdf
5A Fair Fund is a fund established by the SEC to distribute “disgorgements” (returns of wrongful profits) and penalties (fines) to defrauded investors. Fair Funds hold money recovered from a specific SEC case. The commission chooses how to distribute the money to defrauded investors, and when completed, the fund terminates.
6Theresa Tedesco and Jamie Sturgeon, “Nortel: Cautionary Tale of a Former Canadian Titan,”Financial Post, June 27, 2009.
QUESTIONS
1. Discuss Nortel’s accounting for the following transactions and why they were not in conformity with GAAP:
-Revenue recognition
-Reserve accounting
-Accounting for contingent liabilities
2. The following two statements are made in the case:
Accounting experts said the case is sure to be closely watched by others in the business community for the message it sends about where the line lies between fraud and the acceptable use of discretion in accounting.
Darren Henderson opined that “The message . . . is that it is okay to use accounting judgments to achieve desired outcomes, [such as] a certain earnings target.”
Evaluate these statements from the perspectives of representational faithfulness and fair presentation of the financial results reported by Nortel.
In: Accounting
In line with South Bank’s current thrust to expand retail through its branches, Alex Roces, manager of the Marikina Branch, reviewed its list of depositors. Since Roces planned to offer South Bank’s loan services to its depositors, he inquired among the branch’s employees on potential loan clients. He was informed that Fe Javier, the owner of Darling Dolls Company (DCC), had plans to borrow money for use in her business.
Early in January 1995, Roces set up a meeting with Javier. During their meeting, Javier informed Roces that DDC was in need of P1 million for additional working capital during the year.
DDC had no formal accounting records. Javier confidentially informed Roces that its financial statements were only prepared when she had to report her income for tax puposes. In view of this, Roces wanted a new set of DDC’s financial statements prepared for his evaluation.
Company’s Background
Darling Dolls Company was a small manufacturer of stuffed dolls operating from 200-sq.m. leased building in Parang, Marikina. Fe Javier established the business in early 1992 with an initial capital of P2 million from her savings (P1 million) and from personal borrowings from relatives and friends (P1 million). Of the initial investment, about P500,000 was used for improvement of building. Sandee, one of her daughters and a Stuyvesant School of Fine Arts graduate, helped in the management of business and designed the dolls.
Javier started the business with only major customer, Martie Designs. After a year, she was able to ink contracts with four additional customers. DDC dolls were unique and appealing not only to children and teenagers but also to working ladies and young mothers.
DDC had 25 employees, two of whom handled administrative work. Its production process was simple, and its equipment were mainly high-speed sewing machines. In December 1994, Javier invested in 10 new high-speed sewing machines at a total cost of P270,000.
Dolls made by DDC soon became popular. During the fourth quarter of 1994, Javier was able to establish contact with three additional store chains based in Visayas and Mindanao. She believed that a lasting business relationship could be established with these prospective clients. She estimated that production would increase by 80 percent from the current annual level of 27,000 dolls. But as a result of the recent acquisition of 10 sewing machines, Javier did not have sufficient funds to cover the increase in working capital. Moreover, she anticipated that the prices of raw materials and factory supplies would also increase due to the expected implementation of new tax measures.
Up until this time, DDC had no bank loans of any other credit accommodation, except for suppliers’ credit.
Roces assigned a member of his staff to interview Javier, and visit her factory. Based on the results of the interview, Roces’ staff prepared a brief description of the company and summarized the financial data. (see Exhibit 1).
Exhibit 1
Darling Dolls Company
Interview Questions and Answers
|
Questions |
Answers |
||||||||||||||||||||||||
|
1. How much was the 1994 sales? |
P 4.32 million; 21, 600 dolls at P200/doll |
||||||||||||||||||||||||
|
2. Who were the major customers? How much in sales were registered per customer? |
5 major customers, namely: Customer % Sales Martie Designs 50 Sophie’s Gifts and Tags 10 Whims 15 Cuddles and Toys 15 Aspen Boutique 10 Total 100% |
||||||||||||||||||||||||
|
3. Was the company a depositor of other banks besides South Bank? |
No, maintains deposit with South Bank only. |
||||||||||||||||||||||||
|
4. What was its cash balance as of December 31, 1994? |
P 75,000 |
||||||||||||||||||||||||
|
5. How much was the amount collectible from customer? |
|
||||||||||||||||||||||||
|
6. How much in raw materials and factory supplies were on hand as of December 31, 1994 |
P 320,000 raw materials P 58,000 factory supplies |
||||||||||||||||||||||||
|
7. Were there any unfinished dolls as of December 31, 1994? How many were they and what is their average stage of completion? |
Yes, 3,600 dolls are still in process of which 2000 are 90 percent complete and 1,600 are 50 percent complete. |
||||||||||||||||||||||||
|
8. How many completed dolls remained unsold as of December 31, 1994 |
1,800 dolls |
||||||||||||||||||||||||
|
9. How much is the average production cost per doll? |
Production cost per doll: P140 |
||||||||||||||||||||||||
|
10. How much is the current balance of payable to suppliers? |
About P500,000 |
||||||||||||||||||||||||
|
11. What are Javier’s personal assets? Which of these assets are used by Darling Dolls Company? |
|
||||||||||||||||||||||||
|
12. When did Javier buy the assets used in the business? |
Early 1992, it is estimated that fixed assets would be operational for 10 years from their acquisition dates. |
||||||||||||||||||||||||
|
13. How long is the lease agreement? |
10 years |
||||||||||||||||||||||||
|
14. What major operating expenses were incurred for the year? |
|
||||||||||||||||||||||||
|
15. What other liablilities does Darling Dolls Company have besiudes the amount of payable to suppliers? |
Overtime pay of 10 workers for P26,000. All other operating expenses incurred have been paid as of December 31, 1994. |
||||||||||||||||||||||||
Guide Questions:
C. If you were Roces, would you favorably consider the P1 million loan requested by Darling Dolls Company? What assets can be used as collateral?
In: Accounting
The Volkswagen Group adopted International Accounting Standards (IAS, now International Financial Reporting, or IFRS) for its 2001 fiscal year. The following is taken from Volkswagen’s 2001 annual report. It discusses major differences between the German Commercial Code (HGB) and IAS as they apply to Volkswagen.
General:
In 2001 VOLKSWAGEN AG has for the first time published its
consolidated financial statements in accordance with International
Accounting Standards (IAS) and the interpretations of the Standing
Interpretations Committee (SIC). All mandatory International
Accounting Standards applicable to the financial year 2001 were
complied with. The previous year’s figures are also based on those
standards. IAS 12 (revised 2000) and IAS 39, in particular, were
already complied with in the year 2000 consolidated financial
statements. The financial statements thus give a true and fair view
of the net assets, financial position and earning performance of
the Volkswagen Group.
The consolidated financial statements were drawn up in Euros.
Unless otherwise stated, all amounts are quoted in millions of
Euros.
The income statement was produced in accordance with the
internationally accepted cost of sales method.
Preparation of the consolidated financial statements in accordance
with IAS requires assumptions regarding a number of line items that
affect the amounts entered in the consolidated balance sheet and
income statement as well as the disclosure of contingent assets and
liabilities.
The conditions laid down in Section 292a of the German Commercial
Code (HGB) for exemption from the obligation to draw up
consolidated financial statements in accordance with German
commercial law are met. Assessment of the said conditions is based
on German Accounting Standard No. 1 (DSR 1) published by the German
Accounting Standards Committee.
In order to ensure equivalence with consolidated financial statements produced in accordance with German commercial law, all disclosures and explanatory notes required by German commercial law beyond the scope of those required by IAS are published.
Transition to International Accounting
Standards:
The accounting valuation and consolidation methods previously
applied in the financial statements of VOLKSWAGEN AG as produced in
accordance with the German Commercial Code have been amended in
certain cases by the application of IAS.
Amended accounting, valuation and consolidation
methods in accordance with the German Commercial
Code:
• Tangible assets leased under finance leases are capitalized, and
the corresponding liability is recognized under liabilities in the
balance sheet, provided the risks and rewards of ownership are
substantially attributable to the companies of the Volkswagen Group
in accordance with IAS 17.
• As a finance lease lessor, leased assets are not capitalized, but
the discounted leasing installments are shown as receivables.
• Movable tangible assets are depreciated using the straight-line
method instead of the declining balance method; no half-year or
multi-shift depreciation is used. Furthermore, useful lives are now
based on commercial substance and no longer on tax law. Special
depreciation for tax reasons is not permitted with IAS.
• Goodwill from capital consolidation resulting from acquisition of
companies since 1995 is capitalized in accordance with IAS 22 and
amortized over its respective useful life.
• In accordance with IAS 2, inventories must be valued at full
cost. They were formerly capitalized only at direct cost within the
Volkswagen Group.
• Provisions are only created where obligations to third parties
exist.
• Differences from the translation of financial statements produced
in foreign currencies are not recorded in the income
statement.
• Mediumand long-term liabilities are entered in the balance sheet
including capital take-up costs, applying the effective interest
method.
Amended accounting, valuation and consolidation
methods that differ from the German Commercial
Code:
• In accordance with IAS 38, development costs are capitalized as
intangible assets provided it is likely that the manufacture of the
developed products will be of future economic benefit to the
Volkswagen Group.
• Pension provisions are determined according to the Projected Unit
Credit Method as set out in IAS 19, taking account of future salary
and pension increases.
• Provisions for deferred maintenance may not be created.
• Mediumand long-term provisions are shown at their present
value.
• Securities are recorded at their fair value, even if this exceeds
cost, with the corresponding effect in the income statement.
• Deferred taxes are determined according to the balance sheet
liability method. For losses carried forward deferred tax assets
are recognized, provided it is likely that they will be
usable.
• Derivative financial instruments are recognized at their fair
value, even if it exceeds cost. Gains and losses arising from the
valuation of financial instruments serving to hedge future cash
flows are recognized by way of a special reserve in equity. The
profit or loss from such contracts is not recorded in the income
statement until the corresponding due date. In contrast, gains and
losses arising from the valuation of derivative financial
instruments used to hedge balance sheet items are recorded in the
income statement immediately.
• Treasury shares are offset against capital and reserves.
• Receivables and payables denominated in foreign currencies are
valued at the middle rate on the balance sheet date, and not
according to the imparity principle.
• Minority interests of shareholders from outside the Group are
shown separately from capital and reserves.
The adjustment of the accounting and valuation policies to International Accounting Standards with effect from January 1, 2000 was undertaken in accordance with SIC 8, with no entry in the income statement, as an allocation to or withdrawal from revenue reserves, as if the accounts had always been produced in accordance with IAS.
The reconciliation of the capital and reserves to IAS in shown in the following table:
|
million Euros |
|
|
Capital and reserves according to the German Commercial Code as at January 1, 2000 |
9,811.00 |
|
Capitalization of development costs |
3,982.00 |
|
Amended useful lives and depreciation methods in respect of tangible and intangible assets |
3,483.00 |
|
Capitalization of overheads in inventories |
653.00 |
|
Different treatments of leasing contracts as lessor |
1,962.00 |
|
Differing valuation of financial instruments |
897.00 |
|
Effect of deferred taxes |
-1,345.00 |
|
Elimination of special items |
262.00 |
|
Amended valuation of pension and similar obligations |
-633.00 |
|
Amended accounting treatment of provisions |
2,022.00 |
|
Classification of minority interests not as part of equity |
-197.00 |
|
Other changes |
21.00 |
|
Capital and reserves according to IAS as at January 1, 2000 |
20,918.00 |
|
Source: Volkswagen AG Annual Report 2001, pp. 84–86. |
Question:
What differences between the accounting requirements in the HGB and IAS are highlighted in Volkswagen’s disclosure? Are the German requirements consistent with your characterizations in requirement 1?
In: Accounting
Find the mean, standard deviation, minimum, and maximum of these three variables and interpret briefly your findings
Test if there is a difference between the two political party affiliation of the administration in terms of the three variables.
|
Presidential Administrations, 1901-2000 |
2007 | ||||
| Annual Data Set | |||||
| PRESIDENT/TERM/PARTY | YEAR | GNP | UNMP | INF |
PARTY (R: Republican, D: Democrat) |
| McKinley-Roosevelt | 1901 | 11.429 | 4.0 | 0.000 | R |
| (1901-1904) | 1902 | 0.924 | 3.7 | 4.000 | R |
| Republican | 1903 | 4.993 | 3.9 | 3.846 | R |
| 1904 | 8.694 | 5.4 | 0.000 | R | |
| Roosevelt | 1905 | -2.433 | 4.3 | 0.000 | R |
| (1905-1908) | 1906 | 11.621 | 1.7 | 0.000 | R |
| Republican | 1907 | 1.593 | 2.8 | 3.704 | R |
| 1908 | -8.259 | 8.0 | -3.571 | R | |
| Taft | 1909 | 16.577 | 5.1 | 0.000 | R |
| (1909-1912) | 1910 | 2.822 | 5.9 | 3.704 | R |
| Republican | 1911 | 2.596 | 6.7 | 0.000 | R |
| 1912 | 5.662 | 4.6 | 3.571 | R | |
| Wilson | 1913 | 0.922 | 4.3 | 2.414 | D |
| (1913-1916) | 1914 | -4.415 | 7.9 | 1.347 | D |
| Democrat | 1915 | -0.875 | 8.5 | 0.997 | D |
| 1916 | 7.882 | 5.1 | 7.566 | D | |
| Wilson | 1917 | 0.666 | 4.6 | 17.431 | D |
| (1917-1920) | 1918 | 12.285 | 1.4 | 17.448 | D |
| Democrat | 1919 | -3.552 | 1.4 | 14.856 | D |
| 1920 | -4.380 | 5.2 | 15.830 | D | |
| Harding-Coolidge | 1921 | -8.706 | 11.7 | -10.667 | R |
| (1921-1924) | 1922 | 15.794 | 6.7 | -6.343 | R |
| Republican | 1923 | 12.103 | 2.4 | 1.793 | R |
| 1924 | -0.246 | 5.0 | 0.196 | R | |
| Coolidge | 1925 | 8.399 | 3.2 | 2.539 | R |
| (1925-1928) | 1926 | 5.911 | 1.8 | 0.952 | R |
| Republican | 1927 | -0.108 | 3.3 | -1.887 | R |
| 1928 | 0.579 | 4.2 | -1.346 | R | |
| Hoover | 1929 | 6.652 | 3.2 | 0.000 | R |
| (1929-1932) | 1930 | -8.961 | 8.7 | -2.534 | R |
| Republican | 1931 | -6.465 | 15.9 | -8.800 | R |
| 1932 | -13.338 | 23.6 | -10.307 | R | |
| Roosevelt | 1933 | -1.310 | 24.9 | -5.134 | D |
| (1933-1936) | 1934 | 10.925 | 21.7 | 3.351 | D |
| Democrat | 1935 | 8.964 | 20.1 | 2.494 | D |
| 1936 | 12.974 | 16.9 | 0.973 | D | |
| Roosevelt | 1937 | 5.376 | 14.3 | 3.614 | D |
| (1937-1940) | 1938 | -3.605 | 19.0 | -1.860 | D |
| Democrat | 1939 | 8.125 | 17.2 | -1.422 | D |
| 1940 | 8.491 | 14.6 | 0.962 | D | |
| Roosevelt | 1941 | 17.126 | 9.9 | 5.000 | D |
| (1941-1944) | 1942 | 18.700 | 4.7 | 10.658 | D |
| Democrat | 1943 | 16.272 | 1.9 | 6.148 | D |
| 1944 | 7.987 | 1.2 | 1.737 | D | |
| Roosevelt-Truman | 1945 | -1.147 | 1.9 | 2.277 | D |
| (1945-1948) | 1946 | -10.882 | 3.9 | 8.534 | D |
| Democrat | 1947 | -1.033 | 3.9 | 14.359 | D |
| 1948 | 4.301 | 3.8 | 7.773 | D | |
| Truman | 1949 | -0.801 | 5.9 | -0.971 | D |
| (1949-1952) | 1950 | 8.898 | 5.3 | 0.980 | D |
| Democrat | 1951 | 7.696 | 3.3 | 7.906 | D |
| 1952 | 3.745 | 3.0 | 2.185 | D | |
| Eisenhower | 1953 | 4.533 | 2.9 | 0.755 | R |
| (1953-1956) | 1954 | -0.656 | 5.5 | 0.373 | R |
| Republican | 1955 | 7.149 | 4.4 | -0.372 | R |
| 1956 | 2.002 | 4.1 | 1.493 | R | |
| Eisenhower | 1957 | 1.909 | 4.3 | 3.309 | R |
| (1957-1960) | 1958 | -1.109 | 6.8 | 2.847 | R |
| Republican | 1959 | 7.384 | 5.5 | 0.692 | R |
| 1960 | 2.430 | 5.5 | 1.718 | R | |
| Kennedy-Johnson | 1961 | 2.333 | 6.7 | 1.014 | D |
| (1961-1964) | 1962 | 6.114 | 5.5 | 1.003 | D |
| Democrat | 1963 | 4.281 | 5.7 | 1.325 | D |
| 1964 | 5.839 | 5.2 | 1.307 | D | |
| Johnson | 1965 | 6.364 | 4.5 | 1.613 | D |
| (1965-1968) | 1966 | 6.424 | 3.8 | 2.857 | D |
| Democrat | 1967 | 2.546 | 3.8 | 3.086 | D |
| 1968 | 4.677 | 3.6 | 4.192 | D | |
| Nixon | 1969 | 2.981 | 3.5 | 5.460 | R |
| (1969-1972) | 1970 | 0.111 | 4.9 | 5.722 | R |
| Republican | 1971 | 3.365 | 5.9 | 4.381 | R |
| 1972 | 5.498 | 5.6 | 3.210 | R | |
| Nixon-Ford | 1973 | 6.006 | 4.9 | 6.220 | R |
| (1973-1976) | 1974 | -0.504 | 5.6 | 11.036 | R |
| Republican | 1975 | -0.684 | 8.5 | 9.128 | R |
| 1976 | 5.521 | 7.7 | 5.762 | R | |
| Carter | 1977 | 4.751 | 7.1 | 6.503 | D |
| (1977-1980) | 1978 | 5.312 | 6.1 | 7.591 | D |
| Democrat | 1979 | 3.163 | 5.8 | 11.350 | D |
| 1980 | -0.354 | 7.1 | 13.499 | D | |
| Reagan | 1981 | 2.122 | 7.6 | 10.316 | R |
| (1981-1984) | 1982 | -2.262 | 9.7 | 6.161 | R |
| Republican | 1983 | 3.921 | 9.6 | 3.212 | R |
| 1984 | 6.877 | 7.5 | 4.317 | R | |
| Reagan | 1985 | 3.258 | 7.2 | 3.561 | R |
| (1985-1988) | 1986 | 2.890 | 7.0 | 1.859 | R |
| Republican | 1987 | 2.854 | 6.2 | 3.650 | R |
| 1988 | 3.893 | 5.5 | 4.137 | R | |
| Bush | 1989 | 3.355 | 5.3 | 4.818 | R |
| (1989-1992) | 1990 | 1.338 | 5.6 | 5.403 | R |
| Republican | 1991 | -1.009 | 6.8 | 4.208 | R |
| 1992 | 2.635 | 7.5 | 3.010 | R | |
| Clinton | 1993 | 2.438 | 6.9 | 2.994 | D |
| (1993-1996) | 1994 | 3.294 | 6.1 | 2.561 | D |
| Democrat | 1995 | 2.423 | 5.6 | 2.834 | D |
| 1996 | 3.376 | 5.4 | 2.953 | D | |
| Clinton | 1997 | 3.678 | 4.9 | 2.294 | D |
| (1997-2000) | 1998 | 2.400 | 4.9 | 2.243 | D |
| Democrat | 1999 | 2.000 | 5.1 | 2.194 | D |
| 2000 | 2.000 | 5.3 | 2.266 | D | |
| Bush (2001-2008) | 2001 | 1.870 | 4.7 | 1.600 | R |
| Republican | 2002 | 0.400 | 5.8 | 2.400 | R |
| 2003 | 1.000 | 6.0 | 1.900 | R | |
| 2004 | 1.800 | 5.5 | 3.300 | R | |
| 2005 | 2.000 | 5.1 | 3.400 | R | |
| 2006 | 1.700 | 4.6 | 2.500 | R | |
| 2007 | 0.300 | 4.6 | 4.100 | R |
In: Statistics and Probability
| HOUSE | PRICE | YRSOLD | HSQFT | LOTSFT | YRBUILT | PRICE_PER_SQFT | NEB |
| 1 | $536,000 | 2009.00 | 1,500 | 4,000 | 1930 | $357 | WESTERLEIGH |
| 2 | $498,000 | 2009.00 | 1,563 | 6,100 | 1950 | $318 | WESTERLEIGH |
| 3 | $506,500 | 2009.00 | 1,536 | 4,000 | 1950 | $329 | WESTERLEIGH |
| 4 | $630,000 | 2009.00 | 1,152 | 4,000 | 1949 | $546 | WESTERLEIGH |
| 5 | $455,000 | 2009.00 | 1,214 | 2,775 | 1925 | $374 | WESTERLEIGH |
| 6 | $265,000 | 2009.00 | 1,627 | 1,800 | 1985 | $190 | WESTERLEIGH |
| 7 | $347,500 | 2009.00 | 1,100 | 4,500 | 1950 | $315 | WESTERLEIGH |
| 8 | $320,000 | 2009.00 | 1,104 | 3,000 | 1925 | $289 | WESTERLEIGH |
| 9 | $535,000 | 2009.00 | 2,400 | 3,879 | 2000 | $222 | WESTERLEIGH |
| 10 | $456,300 | 2009.00 | 1,650 | 2,552 | 2007 | $277 | WESTERLEIGH |
| 11 | $440,000 | 2009.00 | 1,124 | 2,405 | 1930 | $391 | WESTERLEIGH |
| 12 | $413,000 | 2009.00 | 1,410 | 3,600 | 1955 | $292 | WESTERLEIGH |
| 13 | $320,000 | 2009.00 | 1,740 | 7,230 | 1950 | $183 | WESTERLEIGH |
| 14 | $270,000 | 2009.00 | 1,080 | 1,590 | 1925 | $250 | WESTERLEIGH |
| 15 | $375,000 | 2009.00 | 1,158 | 4,500 | 1920 | $323 | WESTERLEIGH |
| 16 | $485,000 | 2009.00 | 1,685 | 5,000 | 1925 | $287 | WESTERLEIGH |
| 17 | $448,000 | 2009.00 | 1,776 | 3,000 | 1915 | $252 | WESTERLEIGH |
| 18 | $425,000 | 2009.00 | 1,148 | 6,100 | 1955 | $370 | WESTERLEIGH |
| 19 | $376,500 | 2009.00 | 1,237 | 3,000 | 1920 | $304 | WESTERLEIGH |
| 20 | $350,000 | 2009.00 | 890 | 3,600 | 1920 | $393 | WESTERLEIGH |
| 21 | $470,000 | 2009.00 | 1,205 | 5,900 | 1955 | $390 | WESTERLEIGH |
| 22 | $420,000 | 2009.00 | 1,207 | 3,828 | 1945 | $347 | WESTERLEIGH |
| 23 | $410,000 | 2009.00 | 1,256 | 3,600 | 1930 | $342 | WESTERLEIGH |
| 24 | $440,000 | 2009.00 | 900 | 3,600 | 1960 | $488 | WESTERLEIGH |
| 25 | $395,000 | 2009.00 | 1,176 | 3,920 | 1930 | $335 | WESTERLEIGH |
| 26 | $355,000 | 2009.00 | 1,296 | 3,000 | 1940 | $304 | WESTERLEIGH |
| 27 | $415,000 | 2009.00 | 1,092 | 4,000 | 1960 | $380 | WESTERLEIGH |
| 28 | $495,000 | 2009.00 | 1,950 | 3,600 | 1920 | $253 | WESTERLEIGH |
| 29 | $355,425 | 2009.00 | 1,600 | 1,744 | 1993 | $222 | WESTERLEIGH |
| 30 | $410,000 | 2009.00 | 1,440 | 3,742 | 1965 | $284 | WESTERLEIGH |
| 31 | $447,500 | 2009.00 | 1,450 | 3,000 | 1970 | $308 | WESTERLEIGH |
| 32 | $420,000 | 2009.00 | 1,420 | 3,758 | 2006 | $296 | WESTERLEIGH |
| 33 | $455,000 | 2009.00 | 1,427 | 3,800 | 1920 | $318 | WESTERLEIGH |
| 34 | $380,000 | 2009.00 | 1,480 | 2,100 | 1970 | $256 | WESTERLEIGH |
| 35 | $400,000 | 2009.00 | 1,512 | 4,000 | 1960 | $264 | WESTERLEIGH |
| 36 | $310,000 | 2009.00 | 1,240 | 960 | 1993 | $250 | WESTERLEIGH |
| 37 | $365,000 | 2009.00 | 840 | 5,000 | 1955 | $434 | WESTERLEIGH |
| 38 | $370,000 | 2009.00 | 1,280 | 3,456 | 1965 | $289 | WESTERLEIGH |
| 39 | $415,000 | 2009.00 | 1,820 | 4,200 | 1960 | $228 | WESTERLEIGH |
| 40 | $419,796 | 2009.00 | 1,592 | 7,575 | 1930 | $263 | WESTERLEIGH |
| 41 | $380,000 | 2009.00 | 1,280 | 3,408 | 1965 | $296 | WESTERLEIGH |
| 42 | $410,000 | 2009.00 | 1,332 | 2,800 | 1970 | $307 | WESTERLEIGH |
| 43 | $435,000 | 2009.00 | 1,660 | 2,373 | 1995 | $262 | WESTERLEIGH |
| 44 | $515,000 | 2009.00 | 1,712 | 5,880 | 1930 | $300 | WESTERLEIGH |
| 45 | $370,000 | 2009.00 | 1,450 | 4,000 | 1955 | $255 | WESTERLEIGH |
| 46 | $429,000 | 2009.00 | 4,040 | 4,040 | 1950 | $106 | WESTERLEIGH |
| 47 | $295,000 | 2009.00 | 1,320 | 2,000 | 1940 | $223 | WESTERLEIGH |
| 48 | $520,000 | 2009.00 | 1,500 | 5,000 | 1960 | $346 | WESTERLEIGH |
| 49 | $410,000 | 2009.00 | 1,500 | 3,000 | 1925 | $273 | WESTERLEIGH |
| 50 | $379,000 | 2009.00 | 926 | 4,000 | 1955 | $409 | WESTERLEIGH |
| 51 | $487,500 | 2009.00 | 2,472 | 3,420 | 1970 | $197 | MARINER |
| 52 | $425,000 | 2009.00 | 2,400 | 3,800 | 1975 | $177 | MARINER |
| 53 | $370,000 | 2009.00 | 2,100 | 5,500 | 1935 | $176 | MARINER |
| 54 | $300,000 | 2009.00 | 1,870 | 2,500 | 1920 | $160 | MARINER |
| 55 | $385,000 | 2009.00 | 1,340 | 2,500 | 1925 | $287 | MARINER |
| 56 | $265,000 | 2009.00 | 1,992 | 3,591 | 1975 | $133 | MARINER |
| 57 | $300,000 | 2009.00 | 2,416 | 3,325 | 1980 | $124 | MARINER |
| 58 | $339,000 | 2009.00 | 1,820 | 2,850 | 1920 | $186 | MARINER |
| 59 | $350,000 | 2009.00 | 1,650 | 2,500 | 1903 | $212 | MARINER |
| 60 | $460,000 | 2009.00 | 1,744 | 4,419 | 2008 | $263 | MARINER |
| 61 | $214,200 | 2009.00 | 1,270 | 5,721 | 1925 | $168 | MARINER |
| 62 | $270,000 | 2009.00 | 2,200 | 1,512 | 1931 | $122 | MARINER |
| 63 | $220,000 | 2009.00 | 1,408 | 2,560 | 1901 | $156 | MARINER |
| 64 | $290,000 | 2009.00 | 1,540 | 4,950 | 1901 | $188 | MARINER |
| 65 | $335,000 | 2009.00 | 2,800 | 2,880 | 1920 | $119 | MARINER |
| 66 | $400,000 | 2009.00 | 2,052 | 5,900 | 1920 | $194 | MARINER |
| 67 | $485,000 | 2009.00 | 1,884 | 2,886 | 1975 | $257 | MARINER |
| 68 | $500,000 | 2009.00 | 2,080 | 4,326 | 1970 | $240 | MARINER |
| 69 | $414,726 | 2009.00 | 2100 | 3,594 | 2005 | $197 | MARINER |
| 70 | $415,740 | 2009.00 | 1,400 | 3,594 | 2005 | $296 | MARINER |
| 71 | $560,000 | 2009.00 | 2,568 | 4,000 | 1970 | $218 | MARINER |
| 72 | $390,100 | 2009.00 | 1,896 | 3,630 | 1970 | $205 | MARINER |
You have downloaded the MS_Excel file with data on the prices of homes in two neighborhoods around the City of New York. The data is taken from Staten Island.
Using the MS_Excel, calculate:
a. The Average and the Standard Deviation for Sale Price for houses in the two neighborhoods
b. The Average and the Standard Deviation for Sale Price Per Square Foot for houses in the two neighborhoods
c. The Average and the Standard Deviation for Age of houses in the two neighborhoods. Please note that you must calculate the Age of each house sold. Take note also that all houses were sold in 2009.
d. Present you results on the Averages in tables and a charts.
e. List at least four reasons that you think that the Average price of houses in one neighborhood will be different from the other neighborhood.
In: Statistics and Probability
Abstract
On September 20, 2016, Santosh Renjit, Senior Vice President of
Ebroo Clothing Company, sat in his office
pondering the new capital budgeting proposal for setting up a
product line of branded shirts. As per
standard company practice, he was required to evaluate the capital
budgeting project using the traditional
Net Present Value (NPV) approach and the Internal Rate of Return
(IRR) criterion and present his findings to
the management committee meeting scheduled for the next week.
Santosh wondered whether this new
proposal would turn out to be a good investment for his company,
which was looking to deploy funds in NPV
positive projects.
Introduction
Atop Santosh Ebroo’s desk was a capital budge5ng and investment
proposal – a new product line of branded
shirts that the committee was considering for launch. As the head
of the finance department, Santosh was
required to work along with his team on a detailed capital
budgeting analysis and present the findings to the
management committee for their approval. As per standard company
practice, each capital budgeting and
investment project was evaluated using the traditional Net Present
Value (NPV) approach and the Internal
Rate of Return (IRR) criterion for determining whether the company
would undertake the project or not.
budgeting traditional Net Present Value (NPV) approach and the
Internal Rate of Return (IRR) criterion. What would be
the basis for calculating the after-tax opera5ng cash flows for the
capital project? How would he arrive at
the depreciation and working capital requirements for computing the
NPV? What would be the basis for
calculating the terminal year cash flows? With all these questions
in mind, Santosh decided to focus on the
proposed capital budgeting project for the next few days.
Indian Retail Market
The Indian retail market is at the cusp of a sweet spot driven by
strong GDP (Gross Domestic Product)
growth, benign inflation, and rising per capita income and
purchasing power of consumers. Currently, the
retail industry accounts for more than ten percent of the Indian
Gross Domestic Product and approximately
eight percent of employment. The industry is expected to nearly
double, from US$600 billion in 2015 to
US$1 trillion by 2020, driven by income growth, urbanization, and
attitudinal shifts (Indian Terrain Annual
Report, 2015–16). It has been es5mated that, by 2030, the Indian
apparel market, in particular, is expected
to grow at a CAGR (compounded annual growth rate) of approximately
10–12%, backed by increasing
affordability on account of an increase in disposable incomes, an
increase in aspirations, and a shift from
unbranded to branded products by the burgeoning middle class. This
trend is likely to be further
accentuated by the rise of e-commerce companies that enable
shopping from anywhere, thereby leading to
increased penetration in small cities and towns (Indian Terrain
Annual Report, 2015–16).
Company Background
Ebroo Clothing is a small, privately-owned clothing company based
in New Delhi, India. It was founded in
1995 by Sumit Ebroo, a retired executive. Since then, the company
has grown steadily by catering to middle
to low income consumers in the Delhi-national Capital Region (NCR).
The company recorded a stellar
growth of 50% in its sales during the last financial year of
2015–16. With a healthy operating margin ratio
and low leverage levels, the company had been able to grow its
profits at a CAGR of 25% during the last 10
years. With a good brand name and healthy financial metrics, the
company was now looking to expand its
footprint to new product lines catering to middle to high income
customers.
Project Investment Proposal Details
The project is estimated to be of 10 years duration. It involves
setting up new machinery with an estimated
cost of as much as INR 500 million, including installation. This
amount could be depreciated using the
straight line method (SLM) over a period of 10 years with a resale
value of INR 15 million. The project would
require an initial working capital of INR 20 million with
cumulative investment in net working capital to be
maintained at 10% of each year’s projected revenue. With the
planned new capacity, the company would be
able to produce 240,000 pieces of shirts each year for the next 10
years. In terms of pricing, each shirt can
initially be sold at INR 1,300, which takes into account the target
segment and competitor pricing. The
project proposal incorporates an annual increase of 3% in the price
of the shirt to compensate for
inflationary impact. With regards to the raw material costs and
other expenses, the project estimated the
following details:
• Raw material cost for manufacturing shirts at INR 400 per shirt,
slated to rise by 5% per annum on
account of inflation.
• Other direct manufacturing costs at INR 125 per shirt with an
annual increase of 5% per annum on
account of inflation .
• Selling, general, and administrative expenses (including employee
expenses) at INR 35 million per annum,
expected to increase by 10% each year.
• Deprecia5on expense on the basis of SLM.
• Tax rate is assumed to be 25%.
Funding
For funding of the expansion project, the promoters agreed to
infuse 50% in the form of equity with the rest
(50%) being financed from issue of new debt. Based on the current
credit position and market scenario, new
debt can be raised by the company at 12% per annum. Cost of equity
was assumed to be 15% by Santosh.
He reckons the requisite discounting rate or weighted average cost
of capital (WACC) for NPV and IRR
calculations may be determined with the help of these
assumptions.
Demand Scenario
Although the project proposal estimates a maximum annual production
of 240,000 shirts, Santosh would
like the capital budgeting analysis to be done under two demand
scenarios: Optimistic and Expected. The
likely annual demand estimated under each scenario is as
follows:
Scenario Annual Demand
Optimistic: 240,000 shirts
Expected: 200,000 shirts
Your Mandate
I. On the basis of the financial information given in the case,
calculate the after-tax operating cash flows,
NPV, and IRR under the Optimistic and Expected scenarios. Clearly
specify the calculations applied.
II. Based on your analysis, what recommendation would you make on
whether the company should
undertake the project or not? Clearly specify the decision based on
both the NPV and the IRR criteria.
In: Finance
Decision
Do you believe that Nike should use marketing dollars to advance social issues?
Given the negative backlash to the Kaepernick advertisement, what should Nike do now?
Has Nike Gone too Far
The Colin Kaepernick Advertisement
During the opening weekend of the 2018 National Football League (NFL) season, Nike introduced an ad campaign featuring former NFL quarterback Colin Kaepernick. This ad appeared two years after Kaepernick knelt as the US national anthem was played before his team’s games. In Nike’s ad, Kaepernick stated, “Believe in something. Even if it means sacrificing everything,” as an explicit reference to the fact that Kaepernick was no longer playing in the NFL the season after his protest. The ad created a contentious reaction from viewers. Some consumers even posted videos burning Nike gear or cutting Nike’s swoosh (a well-known Nike symbol) off their shoes. Even President Trump tweeted, “Nike is getting absolutely killed with anger and boycotts” (Bieler, 2018). In the midst of the controversy, Nike’s long-running successful advertising campaign “Just Do It” even seemed in jeopardy.
Nike History
Nike was founded as Blue Ribbon Sports in 1964 by a University of Oregon track athlete and his coach to distribute a Japanese shoe. By 1971, the company was manufacturing its own running shoe. The name changed to Nike in 1973 – the same year a design student received $35 for creating the ‘swoosh logo’ and Nike signed its first athlete endorser, tennis player Ilie Nastase. Over the decades, Nike made numerous innovations to its shoes such as air bags and computer chips in the soles. By 2017, Nike, with a 2.8% market share, was the largest supplier and manufacturer of athletic shoes and apparel in the world with North American revenues over $15 billion (Statista, 2018).
Nike’s Socially Relevant Advertising
Nike had long developed advertisements with a social message. When the ‘Just Do It’ campaign first launched in 1988, it featured an 80 year athlete who ran approximately 62,000 miles throughout his lifetime. A year later Nike’s ads featured a Paralympian to advocate for people with disabilities. In 1995, Nike ads featured an HIV-positive runner. In the same year Nike advocated for organized sports for female athletes. More recently, in 2017, Nike featured five Middle Eastern women in sports like boxing and skateboarding. These advertisements enhanced Nike’s reputation as an agent of change through sports.
Colin Kaepernick and the National Anthem
In August 2016, after refusing to stand for the US national anthem before his San Francisco 49ers team exhibition game. Afterward, Kaepernick stated "I am not going to stand up to show pride in a flag for a country that oppresses black people and people of color" (Wyche, 2016). During that game, Kaepernick was booed at every turn - when he entered the field to warm up, when he took a knee, and virtually every time the 49ers offense broke its huddle (Witz-NY Times, 2016). After the game, some fans burned their Kaepernick jerseys. Many argued that, while Kaepernick may be right to be upset by the thousands of people of color killed by police in the US, protesting the flag was not the appropriate way to create change. Others asked why he hates veterans - still others, why he hates America. Yet more people asked why he couldn’t just stick to football (Oluo, Guardian, 2016). His actions reverberated throughout the country, even making it into a presidential campaign speech when Donald Trump said, "Wouldn’t you love to see one of these NFL owners, when somebody disrespects our flag, to say, 'Get that son of bi**h off the field right now. Out. He’s fired!' (Barca, Forbes, 2018).
Reaction to Kaepernick’s kneeling, however, was not universally negative. Numerous NFL players, coaches, and owners stood behind Kaepernick’s right to kneel in protest to acts of injustice against African-Americans. Dallas sportscaster Dale Hansen wrote, "The young, black athletes are not disrespecting America or the military by taking a knee during the anthem. They are respecting the best thing about America” (Willingham CNN 2017).
Consumer Research on the Effect of the Kaepernick Advertisement
As the controversy around Nike’s 2018 ad swirled, several marketing research companies and universities examined immediate effects of the ad on Nike’s reputation:
In the face of these opinion polling numbers however, sales appeared to be increasing rather than decreasing:
Decision
Do you believe that Nike should use marketing dollars to advance social issues?
Given the negative backlash to the Kaepernick advertisement, what should Nike do now?
In: Operations Management
I. You have studied the chapters on unemployment and business cycles. Please review those chapters before you answer this question
a) Find the time series data (quarterly or monthly) on the unemployment rate, inflation rate and real GDP growth in the U.S. from 1980 to 2005, and discuss whether the Okun’s Law is valid or not. Then, discuss whether the Phillips curve exists in the U.S. economy( you have to report your data source and or the website).
b) Which recession is most severe in terms of its depth and the duration of unemployment?
c) Why unemployment rises when the economic is recovering? what kinds of unemployment is it ?
II. Monetary policy will have different impact on the equilibrium rate of interest and GDP. Try to draw three different IS curves with different slopes and show
a) The different impact of the same easy money policy on interest rate and GDP in these different IS curves
b) Monetary policy is most effective under what conditions ( which IS curve). Why ?
c) What determine the slopes of IS curve. Review chapter 14 on sticky price and flexible price model to answer the percentage distribution of both types of firms ,i.e. s vs ( 1-s) under different IS curves( hint : refer to the equations on. P. 408 and p. 411 that
P=EP+{( 1-s)/a/s} ( ( Y-Y bar) p. 408 Y= Y bar + alpha ( P-EP). P. 411
| Year | Growth | Unemployment | Inflation | Business Cycle |
|---|---|---|---|---|
| 1929 | NA | 3.2% | 0.6% | Aug peak and Oct. market crash |
| 1930 | -8.5% | 8.7% | -6.4% | Contraction |
| 1931 | -6.4% | 15.9% | -9.3% | Contraction |
| 1932 | -12.9% | 23.6% | -10.3% | Contraction |
| 1933 | -1.2% | 24.9% | 0.8% | New Deal and March trough |
| 1934 | 10.8% | 21.7% | 1.5% | Expansion |
| 1935 | 8.9% | 20.1% | 3% | Expansion |
| 1936 | 12.9% | 16.9% | 1.4% | Expansion |
| 1937 | 5.1% | 14.3% | 2.9% | May peak |
| 1938 | -3.3% | 19% | -2.8% | June trough |
| 1939 | 8% | 17.2% | 0% | Expansion and Dust Bowl ended |
| 1940 | 8.8% | 14.6% | 0.7% | |
| 1941 | 17.7% | 9.9% | 9.9% | Expansion and WWII |
| 1942 | 18.9% | 4.7% | 9% | Expansion |
| 1943 | 17% | 1.9% | 3% | Expansion |
| 1944 | 8% | 1.2% | 2.3% | Bretton-Woods |
| 1945 | -1% | 1.9% | 2.2% | Feb. peak, recession, Oct. trough |
| 1946 | -11.6% | 3.9% | 18.1% | Expansion and Fed cuts |
| 1947 | -1.1% | 3.9% | 8.8% | Marshall Plan and Cold War |
| 1948 | 4.1% | 4% | 3% | Nov. peak |
| 1949 | -0.6% | 6.6% | -2.1% | Oct. trough and NATO |
| 1950 | 8.7% | 4.3% | 5.9% | Expansion and Korean War |
| 1951 | 8% | 3.1% | 6% | Expansion |
| 1952 | 4.1% | 2.7% | 0.8% | Expansion |
| 1953 | 4.7% | 4.5% | 0.7% | War ended and July peak |
| 1954 | -0.6% | 5% | -0.7% | May trough, Dow at 1929 level |
| 1955 | 7.1% | 4.2% | 0.4% | Expansion |
| 1956 | 2.1% | 4.2% | 3% | Expansion |
| 1957 | 2.1% | 5.2% | 2.9% | Aug peak |
| 1958 | -0.7% | 6.2% | 1.8% | April trough |
| 1959 | 6.9% | 5.3% | 1.7% | Fed raised rates |
| 1960 | 2.6% | 6.6% | 1.4% | April peak and Fed cut |
| 1961 | 2.6% | 6% | 0.7% | JFK spending and Feb. trough |
| 1962 | 6.1% | 5.5% | 1.3% | Cuban Missile Crisis |
| 1963 | 4.4% | 5.5% | 1.6% | LBJ spending, Fed raised rate |
| 1964 | 5.8% | 5% | 1% | Fed raised rate |
| 1965 | 6.5% | 4% | 1.9% | Vietnam War, Fed raised rate |
| 1966 | 6.6% | 3.8% | 3.5% | Expansion, Fed raised rate |
| 1967 | 2.7% | 3.8% | 3% | Expansion |
| 1968 | 4.9% | 3.4% | 4.7% | Fed raised rate |
| 1969 | 3.1% | 3.5% | 6.2% | Nixon, Fed raised rate, Dec. peak |
| 1970 | 0.2% | 6.1% | 5.6% | Nov. trough, Fed cut rate |
| 1971 | 3.3% | 6% | 3.3% | Expansion and Wage-price controls |
| 1972 | 5.3% | 5.2% | 3.4% | Expansion |
| 1973 | 5.6% | 4.9% | 8.7% | Vietnam War and gold standard ended, Nov. peak. |
| 1974 | -0.5% | 7.2% | 12.3% | Stagflation, Watergate, Fed raised rate |
| 1975 | -0.2% | 8.2% | 6.9% | March trough, Fed cut rate |
| 1976 | 5.4% | 7.8% | 4.9% | Expansion, Fed cut rate |
| 1977 | 4.6% | 6.4% | 6.7% | Carter |
| 1978 | 5.5% | 6% | 9% | Fed raised rate |
| 1979 | 3.2% | 6% | 13.3% | Fed raised then lowered rate |
| 1980 | -0.3% | 7.2% | 12.5% | Jan. peak, Fed raised rate, July trough |
| 1981 | 2.5% | 8.5% | 8.9% | Reagan, Expansion peaked in July |
| 1982 | -1.8% | 10.8% | 3.8% | Nov. trough, Fed cut rate |
| 1983 | 4.6% | 8.3% | 3.8% | Reagan spent on defense |
| 1984 | 7.2% | 7.3% | 3.9% | Expansion |
| 1985 | 4.2% | 7% | 3.8% | Expansion |
| 1986 | 3.5% | 6.6% | 1.1% | Reagan cut taxes |
| 1987 | 3.5% | 5.7% | 4.4% | Black Monday |
| 1988 | 4.2% | 5.3% | 4.4% | Expansion, Fed raised rate |
| 1989 | 3.7% | 5.4% | 4.6% | S&L Crisis |
| 1990 | 1.9% | 6.3% | 6.1% | July peak |
| 1991 | -0.1% | 7.3% | 3.1% | March trough |
| 1992 | 3.5% | 7.4% | 2.9% | Expansion, Fed cut rate |
| 1993 | 2.8% | 6.5% | 2.7% | Expansion |
| 1994 | 4% | 5.5% | 2.7% | Expansion |
| 1995 | 2.7% | 5.6% | 2.5% | Fed raised rate |
| 1996 | 3.8% | 5.4% | 3.3% | Fed cut rate |
| 1997 | 4.4% | 4.7% | 1.7% | Fed raised rate |
| 1998 | 4.5% | 4.4% | 1.6% | LTCM crisis |
| 1999 | 4.8% | 4% | 2.7% | Expansion |
| 2000 | 4.1% | 3.9% | 3.4% | Expansion |
| 2001 | 1% | 5.7% | 1.6% | March peak, 9/11, and Nov. trough |
| 2002 | 1.7% | 6% | 2.4% | Expansion |
| 2003 | 2.9% | 5.7% | 1.9% | JGTRRA |
| 2004 | 3.8% | 5.4% | 3.3% | Expansion |
| 2005 | 3.5% | 4.9% | 3.4% | Expansion |
| 2006 | 2.7% | 4.4% | 2.5% | Expansion |
In: Economics