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Long-term commitments, dynamic optimization, and the business cycle.

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Essays in business cycle economics

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Ubc theses and dissertations, essays in business cycle economics galizia, dana --> -->.

This thesis contains three distinct chapters that contribute to our understanding of the causes and consequences of business cycles. Modern business-cycle models generally feature several different random shock processes that drive business cycles. Being able to reliably evaluate the individual importance of any one these shocks depends importantly on having accurate estimates of the variances of the shocks. In the first chapter, it is shown that when a model is a poor approximation to the data, typical variance estimates are biased upward. A simple procedure to identify and partially correct for these effects is proposed. Applying this procedure to a recent paper from the literature reduces the estimated variances by as much as a third of their respective naive estimates. The second chapter explores a view of recessions (typically associated with Friedrich Hayek) whereby, after a period of rapid accumulation of houses, consumer durables and business capital, the economy goes through a period of needed liquidation that results in a decline in economic activity. An alternative (typically associated with Keynes) that is often contrasted with this liquidation view is that recessions are times of deficient demand. These two views have opposite implications for fiscal policy: in the first, fiscal policy simply prolongs the needed adjustment, while in the second fiscal policy can prop up demand. This chapter argues that the two views may be more closely linked than previously recognized, in that liquidations can produce periods where the economy is characterized by deficient demand. The final chapter presents a model in which business-cycle booms and busts are inherently related, whereby a boom causes a subsequent bust, which in turn leads to another boom, and so on. In particular, it is shown how a purely deterministic model can produce fluctuations that persist indefinitely. These cycles exactly repeat themselves, while in the data business cycles are somewhat irregular. It is shown that by adding a small amount of random variation to the model, it is capable of replicating business cycle features in the data well, including their irregularity.

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AP®︎/College Macroeconomics

Course: ap®︎/college macroeconomics > unit 2, the business cycle.

Business cycles and the production possibilities curve
Lesson summary: Business cycles
Business cycles

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What Is a Business Cycle?

Understanding the business cycle.

Measuring and Dating
Relationship With Stock Prices

The Bottom Line

Business cycle: what it is, how to measure it, the 4 phases.

Depression in the Economy: Definition and Example
Economic Collapse
Business Cycle CURRENT ARTICLE
Boom And Bust Cycle
Negative Growth
What Was the Great Depression?
Were There Any Periods of Major Deflation in U.S. History?
The Greatest Generation
U.S. Government Financial Bailouts
Austerity: When the Government Tightens Its Belt
The New Deal
The Economic Effects of the New Deal
Gold Reserve Act of 1934
Emergency Banking Act of 1933

Business cycles are a type of fluctuation found in the aggregate economic activity of a nation—a cycle that consists of expansions occurring at about the same time in many economic activities, followed by similarly general contractions. This sequence of changes is recurrent but not periodic.

The business cycle is also called the economic cycle .

Key Takeaways

Business cycles are composed of concerted cyclical upswings and downswings in the broad measures of economic activity—output, employment, income, and sales.
The alternating phases of the business cycle are expansions and contractions.
Contractions often lead to recessions, but the entire phase isn't always a recession.
Recessions often start at the peak of the business cycle—when an expansion ends—and end at the trough of the business cycle, when the next expansion begins.
The severity of a recession is measured by the three Ds: depth, diffusion, and duration.

Madelyn Goodnight / Investopedia

In essence, business cycles are marked by the alternation of the phases of expansion and contraction in aggregate economic activity and the co-movement among economic variables in each phase of the cycle. Aggregate economic activity is represented by not only real (i.e., inflation-adjusted) GDP—a measure of aggregate output—but also the aggregate measures of industrial production, employment, income, and sales, which are the key coincident economic indicators used for the official determination of U.S. business cycle peak and trough dates.

Popular misconceptions are that the contractionary phase is a recession and that two consecutive quarters of decline in real GDP (an informal rule of thumb) means a recession. It's important to note that recessions occur during contractions but are not always the entire contractionary phase. Also, consecutive declines in real GDP are one of the indicators used by the NBER, but it is not the definition the organization uses to determine recessionary periods.

On the flip side, a business cycle recovery begins when that recessionary vicious cycle reverses and becomes a virtuous cycle, with rising output triggering job gains, rising incomes, and increasing sales that feedback into a further rise in output . The recovery can persist and result in a sustained economic expansion only if it becomes self-feeding, which is ensured by this domino effect driving the diffusion of the revival across the economy.

Of course, the stock market is not the economy. Therefore, the business cycle should not be confused with market cycles , which are measured using broad stock price indices.

Measuring and Dating Business Cycles

The severity of a recession is measured by the three D's: depth, diffusion, and duration. A recession's depth is determined by the magnitude of the peak-to-trough decline in the broad measures of output, employment, income, and sales. Its diffusion is measured by the extent of its spread across economic activities, industries, and geographical regions. Its duration is determined by the time interval between the peak and the trough.

An expansion begins at the trough (or bottom) of a business cycle and continues until the next peak, while a recession starts at that peak and continues until the following trough.

The National Bureau of Economic Research (NBER) determines the business cycle chronology—the start and end dates of recessions and expansions for the United States. Accordingly, its Business Cycle Dating Committee considers a recession to be "a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial production, and wholesale-retail sales."

The Dating Committee typically determines recession start and end dates long after the fact. For instance, after the end of the 2007–09 recession, it "waited to make its decision until revisions in the National Income and Product Accounts [were] released on July 30 and Aug. 27, 2010," and announced the June 2009 recession end date on Sept. 20, 2010.

The average length of recessions in the U.S. since World War II has been around 11 months. The Great Recession was the longest one during this period, reaching 18 months.

U.S. expansions have typically lasted longer than U.S. contractions. From 1854–1899, they were almost equal in length, with contractions lasting about 25 months and expansions lasting about 29 months, on average. The average contraction duration then fell to 18 months in the 1900–1945 period and 11 months in the post-World War II period. Meanwhile, the average duration of expansions increased progressively, from 29 months in 1854–1899 to 30 months in 1900–1945, 43 months in 1945–1982, and 70 months in 1982–2009.

Stock Prices and the Business Cycle

The biggest stock price downturns tend to occur—but not always—around business cycle downturns (e.g., contractions and recessions). For example, the Dow Jones Industrial Average and the S&P 500 took steep dives during the Great Recession. The Dow fell 51.1%, and the S&P 500 fell 56.8% between Oct. 9, 2007 to March 9, 2009.

There are many reasons for this, but primarily, it is because businesses assume defensive measures and investor confidence falls during contractionary periods. Many events occur before those in an economy are aware they are in a contraction, but the stock market trails what is going on in the economy.

So, if there is speculation or rumors about a recession, mass layoffs, rising unemployment, decreasing output, or other indications, businesses and investors begin to fear a recession and act accordingly. Businesses assume defensive tactics, reducing their workforces and budgeting for an environment of falling revenues.

Investors flee to investments "known" to preserve capital, demand for expansionary investments falls, and stock prices drop.

It's important to remember that while stock prices tend to fall during economic contractions, the phase does not cause stock prices to fall—fear of a recession causes them to fall.

What Are the Stages of the Business Cycle?

In general, the business cycle consists of four distinct phases: expansion, peak, contraction, and trough.

How Long Does the Business Cycle Last?

According to U.S. government research, the business cycle in America takes, on average, around 6.33 years.

What Was the Longest Economic Expansion?

The 2009-2020 expansion was the longest on record at 128 months.

The business cycle is the time is takes the economy to go through all four phases of the cycle: expansion, peak, contraction, and trough. Expansions are times of increasing profits for businesses, rising economic output, and are the phase the U.S. economy spends the most time in. Contractions are times of decreasing profits and lower output, and is the phase the least amount of time is spent in.

St. Louis Federal Reserve. " All About the Business Cycle: Where Do Recessions Come From? "

The National Bureau of Economic Research. " Business Cycle Dating ."

National Bureau of Economic Research. “ Business Cycle Dating Procedure: Frequently Asked Questions. What is a Recession? What is an Expansion? ”

National Bureau of Economic Research. " The NBER's Recession Dating Procedure ."

National Bureau of Economic Research. " Business Cycle Dating Committee, National Bureau of Economic Research ."

National Bureau of Economic Research. " US Business Cycle Expansions and Contractions ."

Federal Reserve Bank of Atlanta. " Stock Prices in the Financial Crisis ."

Congressional Research Service. " Introduction to U.S. Economy: The Business Cycle and Growth ," Page 2.

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Essays on Business Cycles and the Causes and Consequences of Procyclical Policies

--> Ahmad, Asif (2017) Essays on Business Cycles and the Causes and Consequences of Procyclical Policies. PhD thesis, University of York.

The conventional wisdom regarding the cyclical behavior of macroeconomic policy is that both fiscal and monetary policies are countercyclical or acyclical in most advanced economies, but procyclical in many emerging and developing countries. Procyclical policies are conducted by fiscal authorities cutting (raising) budget deficits and by the monetary authorities raising (cutting) interest rates during recessions (booms). Such policies are deemed sub-optimal since they will tend to reinforce the cyclical fluctuations, aggravating the busts and exacerbating the booms. These characteristics have sparked a debate on how to achieve policy discipline to boost macroeconomic performance. Motivated by this debate, the main purpose of this thesis is to evaluate the core determinants of procyclical policies and to assess their consequences on macroeconomic performance. In Chapter 2, by using data from 137 countries for 1970-2014, we show that fiscal procyclicality has become the norm rather than the exception in many countries. More specifically, over the last 45 years, a substantial number of emerging and low-income developing countries are trapped within procyclical policy, in the sense of not being able to move from procyclical to countercyclical fiscal policy. We also show that even after controlling for the endogeneity of “government quality” and other determinants of procyclicality, there is a causal relation running from better “government quality” to more countercyclical or less procyclical policy. We then focus on the cyclical properties of monetary policy in Chapter 3. We find that many countries, specifically emerging and low-income developing countries have also faced challenges in implementing countercyclical monetary policies. We document that over the last 55 years, a large number of countries consistently followed procyclical monetary policy or have recently turned procyclical. We then aim to address the question, why this has been the case. We show that procyclical stop-and-go policies are intensified in the presence of “fear of free floating”, that is, monetary authorities’ reluctance to avoid large swings in the exchange rates. We also find that our results are robust to the endogeneity of “fear of free floating” and other determinants of procyclical monetary policy. In Chapter 4, we explore whether procyclical macroeconomic policy stances – being contractionary in bad times and expansionary in good times – have consequences for the rest of the economy. We provide empirical evidence that observed procyclical fiscal and monetary policy have significant macroeconomic costs; procyclical countries have lower rates of economic growth, higher rates of output volatility and inflation volatility. In Chapter 2 and 3, we also show that over the last decades some emerging countries have been able to escape the procyclicality trap and become countercyclical. During the global financial crisis 2008-09, these countries pursued countercyclical macroeconomic policy to counter the sharp drop in economic activity. However, our cross-country evidence in Chapter 5 provides little evidence for a central role of countercyclical policy to cushion against the global financial shock. We find that pre-crisis level of short-term external debt and collapse in export demand were the key factors determining the intensity of 2008-09 crisis.

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Is the Boom-and-Bust Business Cycle Dead?

There is a growing view that the U.S. business cycle has changed (for better) in a more diversified economy. To some, that sounds like tempting fate.

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An illustration of a person at a desk with a screen projecting coins as if they were phases of the moon.

By Talmon Joseph Smith

For much of modern history, even the richest nations have been subject to big perennial upswings and crashes in commercial activity almost as fixed as the four seasons.

Periods of economic growth get overstretched by increased risk-taking. Hiring and investment crest and fall into a contraction as consumer confidence wanes and spending craters. Sales fall, bankruptcies and unemployment rise. Then, in the depths of a recession, debts are settled, panic abates, green shoots appear, and banks begin lending more easily again — fueling a recovery that enables a new upswing.

But a brigade of academic economists and prominent voices on Wall Street are asking if the unruly business cycle they learned in school, and witnessed in practice, has fundamentally morphed into a tamer beast.

Rick Rieder, who manages about $3 trillion in assets at the investment firm BlackRock, is one of them.

“There is a lot of ink spilled on what type of landing we will see for the U.S. economy,” he wrote in a note to clients last summer — employing the common metaphor for whether the U.S. economy will crash or achieve a “soft landing” of lower inflation, slower growth and mild unemployment.

“But one point to keep in mind,” Mr. Rieder continued, “is that satellites don’t land and maybe that is a better analogy for a modern advanced economy” like the United States. In other words, dips in momentum will now happen within a steadier orbit.

And there is some evidence that the current spurt of economic growth may have not just months but several years to run, barring an external disruption (what economists call an “ exogenous shock ”) or a return of high inflation that prompts the Federal Reserve to push the economy into recession.

“Financial reporters and market strategists often argue about whether we are ‘early-cycle,’ ‘mid-cycle’ or ‘late-cycle,’” David Kelly, the chief global strategist at J.P. Morgan Asset Management, wrote in a March 11 note to investors that closely aligned with Mr. Rieder’s “satellite” thesis. “However, these perspectives are based on an outdated model of how the U.S. economy behaves.”

According to the National Bureau of Economic Research, the U.S. economy between the 1850s and the early 1980s experienced 30 recessions lasting an average of 18 months, with intervening periods of economic growth averaging only 33 months.

Helping drive this pattern, Mr. Kelly and other economists explain, were highly cyclical industries: Manufacturing and agriculture, now only a fraction of overall output, were once mainstays of the U.S. economy.

Today, manufacturing accounts for about $2.3 trillion of gross domestic product, employs about 12 million people and indirectly supports other local jobs. (Every manufacturing job, for instance, spurs seven to 12 new jobs in related industries, according to a McKinsey estimate.)

But the consumer-driven U.S. economy, mostly made up of services (health care, auto repair, nail salons, customer service, administration and so on), is almost $30 trillion in size. Uptrends and pullbacks in the production of goods have less impact now. The relative stability of total household spending in recent years is a key part of why the United States has avoided a recession.

America’s contemporary economy, Mr. Rieder argued in his note to clients, is less vulnerable to the boom-and-bust cycles of old — mainly because its prosperous consumers are service-oriented, less dependent than ever on factories or farms. Consumption spending makes up about 70 percent of the economy.

“Consumption doesn’t really adjust that dramatically without some major form of economic stress,” he added.

One piece of data in favor of Mr. Rieder’s “satellite” theory is the absence of any widespread weakness before the pandemic crippled economies worldwide.

That was consistent with a developing trend: Since the early 1980s, there have been only four recessions, lasting an average of nine months, with economic expansions averaging 104 months.

The current period of job growth is in its 40th month.

“You don’t want to jinx it,” Ann Harrison, the dean of the Haas School of Business at the University of California, Berkeley, said in an interview — noting that peak confidence in economic expansions frequently arrives right before their downfall. (Talk has picked up of a new “ Roaring Twenties ,” an era that didn’t end well.)

As ever, there are reasons to worry. The emergence and rapid growth of “shadow banks” operating in private markets with little oversight of their lending has concerned many economists and old-school regulators. And a range of industry insiders in commercial real estate say the negative effects of lower office occupancy rates — for local economies and government budgets — have only just begun.

Yet Mr. Kelly of J.P. Morgan lists various reasons that periods of U.S. economic growth may be elongated and less chaotic going forward. Federal deposit insurance, introduced after the Depression, sharply reduced bank panics and failures. Vastly improved information on inventory levels among goods-producing businesses, he said, has “tamed” the inventory cycle, preventing mismatches between supply and demand that can cause mass layoffs.

The rise of international trade, Mr. Kelly added, can often offset slowing domestic demand since businesses, enabled by the internet, can find customers throughout the globe. And the service sector’s growth, he concluded, has “made the economy more stable and, importantly, less sensitive to interest rates.”

Across the economics profession, many are not feeling as reassured.

When weighing recession risks, Thomas Herndon, a professor of economics at John Jay College of the City University of New York, doesn’t take much long-term solace in the growing sophistication of big business. There are, he said, “many, many, many causes” for downturns — some of which are not directly linked to financial instability.

Mr. Herndon noted the work of the 20th-century Polish economist Michal Kalecki, who argued that business leaders feel “undermined” by the maintenance of full employment. Using their substantial influence over policy, Kalecki argued, they can help institute restrictive economic policies that bring times of economic expansion to an end and reset them with softer, more tolerable labor power.

And Mr. Herndon said he thought old-fashioned “bubble” manias and “credit cycles” remained a danger, too.

Eliminating the longstanding economic cycle would be “the holy grail of central banking,” said James Knightley, chief international economist at ING, the global bank. “The Fed’s willingness to use innovative tools” — like its off-the-cuff creation of lending facilities to keep credit flowing on Main Street and heal bank balance sheets since 2020 — gives it “more levers to wiggle to help reduce the chance of a downturn,” Mr. Knightley said.

“Phrases like ‘This time it will be different’” generally have a bad track record, he said. “But maybe it will.”

In several ways, this time has been different so far.

Typically, the housing sector — and its interconnected industries, from construction and home improvement to real estate finance — accounts for nearly 20 percent of U.S. output . The Federal Reserve has more than quadrupled its interest-rate levels since the spring of 2022, bringing its key policy rate to over 5 percent from near zero. That drove mortgage rates to unaffordable highs and made financing new home building difficult. And the residential real estate sector, highly sensitive to interest rates, ground to a halt. But the economy as a whole continued to grow.

When in-person services plummeted during the pandemic, e-commerce and goods-buying picked up the slack. By the time millions of households were sated with goods purchases and manufacturing fell off, the in-person economy was reopening and in-person services began a booming recovery.

There are some market analysts, such as Jim Bianco of Bianco Research, who believe that the U.S. economy — in its dynamism, diversity and size — has in some respects begun to resemble the global economy itself, which typically contracts only when colossal shocks to output occur.

The global financial crisis and the Covid-19 pandemic — which were separated by only 10 years and did cause global recessions — show that while rare, such maelstroms can coincidentally occur back to back. So, long expansions are no guarantee. On the flip side, Australia went about three decades without a recession until Covid ended the streak .

Nina Eichacker, a professor of economics at the University of Rhode Island and the author of two recent papers about government responses to crises, cited another influence: a powerful school of thought that government interventions, even amid downturns, add “frictions and inefficiencies to markets” and “make us worse off overall.”

The robust federal response to the pandemic shock was enabled by a general view that it was an act of nature. Future financial stresses are more likely to have villains, which means proposed solutions are more likely to face division in Congress even if unemployment is notably rising.

But Ms. Eichacker thinks that those political limits to consensus may soften if this expansion rolls on and public opinion of the hefty federal response that helped foster it grows fonder.

“I am sometimes freaked out by how optimistic I feel about the state of things,” she said. “Economically anyway.”

Talmon Joseph Smith is a Times economics reporter, based in New York. More about Talmon Joseph Smith

Business Cycle Synchronisation and Regional Migration: Testing the OCA Criteria in the West African Region

Published: 21 May 2024

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Sodiq Olaiwola Jimoh 1 , 2 &
Soo Y. Chua 1

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The West African region is on the verge of forming a monetary union. Many studies have examined the feasibility of monetary unions using criteria such as trade and financial integrations. However, labour migration which is one of the criteria has been neglected in previous studies. This study filled the gap by using Abel and Cohen's (Bilateral international migration flow estimates for 200 countries 6(1):1–13, 2019) data between 1996–2019 to examine the impact of migration flows on business cycle synchronisation using the IV-2SLS technique in the West African region. The study reveals that migration flow, specialisation of industry, and financial integrations spur business cycle synchronisation, while regional trade integration does not significantly impact business cycle synchronisation. However, the interactive terms of trade integrations and migration flow positively influenced business cycle synchronisation in the region. These findings suggest a likelihood of optimum currency area in the West African region.

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India in the globalized economy : Growth spillovers & business cycle synchronization

Abel, G.J., and J.E. Cohen. 2019. Bilateral international migration flow estimates for 200 countries. Scientific Data 6 (1): 1–13. https://doi.org/10.1038/s41597-019-0089-3 .

Article Google Scholar

Acosta, P., C. Calderón, P. Fajnzylber, and H. Lopez. 2008. What is the impact of international remittances on poverty and inequality in Latin America? World Development 36 (1): 89–114. https://doi.org/10.1016/j.worlddev.2007.02.016 .

Agba, O., and I. Madueme. 2021. Economic community of west African State’s (ECOWAS) controversy: wither a need for single currency by 2021? Asian Themes in Social Sciences Research 4 (1): 1–12. https://doi.org/10.33094/journal.139.2021.41.1.12 .

Ahn, C., C. Dongkoo, and H.-B. Kim. 2006. Is East Asia fit for an optimum currency area? an assessment of the economic feasibility of a higher degree of monetary cooperation in East Asia. The Developing Economies 3 (September): 288–305. https://doi.org/10.1111/j.1746-1049.2006.00018.x .

Akin, C. 2011. Multiple determinants of business cycle synchronization. SSRN Electronic Journal . https://doi.org/10.2139/ssrn.1022648 .

Alimi, N. 2015. The effect of trade, specialization and financial integration on business cycles synchronization in some mediterranean countries. Asian Economical Financial Review 5 (1): 110–118. https://doi.org/10.18488/journal.aefr/2015.5.1/102.1.110.118 .

Antonakakis, N., and G. Tondl. 2014. Does integration and economic policy coordination promote business cycle synchronization in the EU? In Empirica . https://doi.org/10.1007/s10663-014-9254-2 .

Backus, D., P. Kehoe, and F. Kydland. 1992. International real business cycles. The Journal of Political Economy 100 (4): 745–775.

Baxter, M., and M.A. Kouparitsas. 2005. Determinants of business cycle comovement: A robust analysis. Journal of Monetary Economics 52 (1): 113–157. https://doi.org/10.1016/j.jmoneco.2004.08.002 .

Beck, K. 2013. Determinants of business cycles synchronization in the european union and the euro area. Equilibrium 8 (4): 25–48. https://doi.org/10.12775/equil.2013.025 .

Beck, K. 2019. What drives business cycle synchronization? BMA results from the European Union. Baltic Journal of Economics 19 (2): 248–275. https://doi.org/10.1080/1406099X.2019.1652393 .

Beck, K. 2021. Migration and business cycles: Testing the OCA theory predictions in the European union. Applied Economics Letters 28 (13): 1087–1091. https://doi.org/10.1080/13504851.2020.1798339 .

Beine, M., P. Bourgeon, and J.C. Bricongne. 2019. Aggregate fluctuations and international migration. The Scandinavian Journal of Economics 121 (1): 117–152. https://doi.org/10.1111/sjoe.12258 .

Calderón, C., A. Chong, and E. Stein. 2007. Trade intensity and business cycle synchronization: Are developing countries any different? Journal of International Economics 71 (1): 2–21. https://doi.org/10.1016/j.jinteco.2006.06.001 .

Carcel, H., L.A. Gil-Alana, and G. Madigu. 2015. Inflation convergence in the East African community: A fractional integration and cointegration study. Global Economy Journal 15 (4): 507–524. https://doi.org/10.1515/gej-2015-0002 .

Cham, T. 2020. Is the GCC an optimum currency area (OCA)? Empirical answers from co-movements. International Journal of Islamic and Middle Eastern Finance and Management 13 (5): 873–890. https://doi.org/10.1108/IMEFM-06-2018-0198 .

Debrun, X., P. Masson, and C. Pattillo. 2005. Monetary union in West Africa : Who might gain, who might lose, and why ? Canadian Journal of Economics 38 (2): 454–481.

Frankel, J., and A. Rose. 1998. The endogeneity of the optimum currency area criteria. The Economic Journal 108 (449): 1009–1025. https://doi.org/10.1016/j.econmod.2009.08.004 .

Habimana, O., V. Sesay, and Y. Umulisa. 2020. Business cycle synchronicity within ECOWAS: The eco-core and the eco- periphery. SSRN Electronic Journal, February . https://doi.org/10.2139/ssrn.3708812 .

Harvey, S.K., and M.J. Cushing. 2015. Is West African monetary zone ( WAMZ ) a common currency area ? Journal of Advanced Research 5 (1): 53–63. https://doi.org/10.1016/j.rdf.2015.05.001 .

Imbs, J. 2004. Trade, finance, specialization, and synchronization. Review of Economics and Statistics 86 (August): 723–734.

Kalemli-Ozcan, S., E. Papaioannou, and J.L. Peydró. 2013. Financial regulation, financial globalization, and the synchronization of economic activity. Journal of Finance 68 (3): 1179–1228. https://doi.org/10.1111/jofi.12025 .

Kao, C. 1999. Spurious regression and residual-based tests for cointegration in panel data. Journal of Economics 90 (1): 1–44. https://doi.org/10.1016/S0304-4076(98)00023-2 .

Kenen, P. 1969. The theory of optimum currency areas: an eclectic view. In Essays in International Economics , 163–182. Princeton University Press. https://doi.org/10.2307/j.ctvbcd28k.14.

Kose, M.A.A., and K.-M. Yi. 2002. The trade comovement problem in international macroeconomics. In SSRN Electronic Journal . https://doi.org/10.2139/ssrn.368201 .

Krugman, P. 1993. Lessons of massachusetts for EMU. International Library of Critical Writtings in Economics 134: 241–266. https://doi.org/10.1017/cbo9780511599231.016 .

Mckinnon, R. 1963. Optimum currency areas. The American Economic Review 53 (4): 718–725. https://doi.org/10.4135/9781412952613.n368 .

Mundell, R. 1961. American economic association a theory of optimum currency area. The American Economic Review 51 (4): 657–665.

Google Scholar

Pesaran, M.H. 2007. A simple panel unit root test in the presence of cross-secional dependence. Journal of Applied Economics 22: 265–312. https://doi.org/10.1002/jae .

Raheem, A.A., and I. Nurudeen. 2020. Assessing the feasibility of monetary union in terms of business cycle synchronization in West Africa: An Application of Factor Augmented Vector Autoregressive Model (FAVAR). American Journal of Humanities and Social Science Research 4 (11): 24–37.

Samba, M.C., and C. Mbassi. 2020. Business cycle synchronization: A reassessment of the optimum currency area theory within the CFA franc zone. Journal of African Business 21 (1): 126–144. https://doi.org/10.1080/15228916.2019.1607143 .

Wälti, S. 2011. Journal of international money stock market synchronization and monetary integration. Journal of International Money and Finance 30 (1): 96–110. https://doi.org/10.1016/j.jimonfin.2010.07.004 .

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Jimoh, S.O., Chua, S.Y. Business Cycle Synchronisation and Regional Migration: Testing the OCA Criteria in the West African Region. Ind. J. Labour Econ. (2024). https://doi.org/10.1007/s41027-024-00480-x

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Home > Honors Program > Thesis > 182

Honors Thesis

Evaluating morningstar wide moat stocks through the business cycle.

Zachary Bishkin Follow

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Joshua Spizman

The evaluation of stock selections by portfolio managers is a topic commonly addressed by academics in finance. In particular, there is great interest to find portfolio managers that consistently outperform the market. In this article, we evaluate the market returns of Morningstar’s “StockInvestor” Wide Moat portfolios: The Tortoise and the Hare. The Wide Moat portfolio stocks are companies that Morningstar analysts identify as having a sustainable advantage estimated to last at least 20 years. Comprised of these Wide Moat Stocks, the Tortoise portfolio is comprised of slow and steady growth stocks while the Hare portfolio is comprised of stocks with faster, but less steady growth. While portfolio returns are typically compared to the overall market index, this basic comparison ignores statistical factors in stocks that have been shown to produce above-average returns. This study evaluates Morningstar’s portfolios to determine if Morningstar’s portfolio managers select stocks that outperform through the business cycle, or if the returns are explained by the Fama-French 3-factor model. In this study, we analyze both portfolios from 2007 to 2012. In addition to looking at the entire period performance, this study also isolates the recessionary period from 2007 to 2009 to see if the Wide Moat portfolios outperform in a recession. Furthermore, in order to investigate what other factors may be underlying the identification and selection of wide moat stocks, an analysis is conducted to determine how industry competitiveness and concentration is reflected in the stock selection of Morningstar’s portfolio managers.

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Bishkin, Zachary, "Evaluating Morningstar Wide Moat Stocks through the Business Cycle" (2019). Honors Thesis . 182. https://digitalcommons.lmu.edu/honors-thesis/182

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How Your Business Should Tap into the Creator Economy

Rebecca Karp,
Carolyn Fu,
Simon Friis

Influencer marketing is upending established customer-facing businesses.

Creators aren’t just changing marketing. They’re transforming product development, too. Creators can drive demand for specialized products, accelerating product life cycles and even changing what customers actually value. Companies that recognize the power of creators can choose from four strategies, including partnering with creators or acting as suppliers.

Forget what you knew about creators, or influencers like Mr. Beast and Charli D’Amelio who make content for YouTube, Instagram, and TikTok. Content creators are silently rewriting the innovation and strategy rule book for a multitude of established companies, particularly in the consumer goods and services industries. By changing how consumers search for and use products, creators are: 1) driving demand for increasingly specialized products and services; 2) accelerating product life cycles; and 3) changing what customers actually value.

RK Rebecca Karp is an Assistant Professor in the Strategy Unit at Harvard Business School. Her research examines how firms execute on their strategies and grow. In particular, she focuses on the role innovation plays in supporting strategy execution, fostering change in organizational work practices and in shaping the way firms grow.
CF Carolyn Fu is an assistant professor of business administration in the Strategy Unit of Harvard Business School.
SF Simon Friis is a Research Scientist at the blackbox Lab at Harvard Business School, where he focuses on understanding the social and economic implications of artificial intelligence. He received his Ph.D. in Economic Sociology from the MIT Sloan School of Management and previously worked at Meta as a research scientist.

Partner Center

The S&P 500 could plunge as much as 70% this cycle as markets hit a 'motherlode' of FOMO extremes, famed fund manager says

Legendary investor John Hussman says the latest stock rally is rooted in the extreme fear of missing out.
FOMO factors have surged in markets, and stock prices could fall 50%-70% this cycle.
His firm's most reliable indicator now exceeds 1929 extremes.

All-time highs in the stock market give the impression of a runaway rally, but it's a bull run that will eventually come crashing down, John Hussman said in a new note .

The legendary bear, famed for predicting the 2000 and 2008 crashes, reiterated that equities could drop as much as 70% this cycle. It's a long-held take that may seem out of place amid the market's momentum, as the S&P 500 continues to breach record highs in 2024.

But to the Hussman Investment Trust president, the extreme runup is driven by investor impatience and a fear of missing out — key ingredients for a coming correction.

"There are certain features of valuation, investor psychology, and price behavior that tend to emerge when the fear of missing out becomes particularly extreme and the focus of speculation becomes particularly narrow. Last Friday, we hit a fresh 'motherlode' of these conditions," he wrote on Tuesday.

He said a combination of red-flag factors include overextended valuations, divergence among individual stock sectors, and lopsided sentiment. Another point of caution is the growing group of stocks hitting fresh 52-week lows, even as indexes themselves skyrocket.

"I continue to view the market advance of recent months as an attempt to 'grasp the suds of yesterday's bubble' rather than a new, durable bull market advance," he said. "I also believe that the S&P 500 could lose something on the order of 50-70% over the completion of this cycle, simply to bring long-term expected returns to run-of-the-mill norms that investors associate with stocks."

Hussman is one of the most bearish forecasters on Wall Street, and has for months repeated his view that stocks could fall more than 60%.

Most strategists at major Wall Street banks, meanwhile, generally see the S&P staying above 5,000 through 2024 .

This is in part because the macroeconomic outlook has brightened compared to the first half of 2023, when a recession was the base case for most economists.

Hussman has made headlines by predicting a massive stock-market decline and forecasting a full decade of negative equity returns , and as the stock market has kept grinding higher, he's persisted with his calls for a painful correction on the horizon.

In Tuesday's note, he also noted that his firm's most reliable measure — the ratio of nonfinancial market capitalization to corporate gross value-added — now exceeds the 1929 extremes , when the Dow plunged 89% peak-to-trough.

"Even the more conventional (but less reliable) S&P 500 price/forward operating earnings multiple is at levels that have no rivals except surrounding the 2000 and 2022 peaks," Hussman said. "Put simply, my impression is that the period since early-2022 comprises the extended peak of one of the three great speculative bubbles in U.S. history."

Main content

We had cellphones, then feature phones, then smartphones. Now, 'IntelliPhones' are coming.

Bank of America analysts predict AI will create a new class of devices called 'IntelliPhones.'
AI enhancements could make phones more context-aware and proactive.
There's a new battle brewing over who will create the most useful AI-powered phone.

The first cellphone came out in the early 1980s. It was connected to a cellular radio system and didn't require a physical connection to a network.

Then, we had feature phones . These connected to the internet and could store and play music.

Apple ushered in the smartphone era, with location data, fancy cameras, and the all-important App Store.

Is AI about to launch a new chapter? Analysts at Bank of America Securities think so. And they've come up with a new name for this future device.

The "IntelliPhone."

Yes, it's an awful name. Too many syllables. No one is ever going to say, "Ugh, I can't find my IntelliPhone. Have you seen it?"

However, artificial intelligence models, chatbots, and other AI-powered applications could get so useful that our current smartphones might look kinda dumb in the future.

Maybe no one will have to ask where their IntelliPhone is, because it will somehow find itself.

"Context awareness will be the key differentiator," Wamsi Mohan, an analyst at Bank of America Securities, wrote in a research note on Wednesday that listed a number of future capabilities that may take these gadgets way beyond current handsets.

Hype warning

A word of caution here. The AI hype cycle is in overdrive right now, and Mohan and his colleagues were writing a research note about Apple ahead of its WWDC conference next month.

The mother of all upgrade cycles

Still, Mohan makes some compelling arguments. If AI tools on phones can really set them apart from current devices, consumers have a new reason to buy a fresh handset.

"We see the introduction of AI smartphones (IntelliPhones) as a once in a decade upgrade event," Mohan wrote.

At Google's I/O conference earlier this month, the internet giant showed off several new AI capabilities for Pixel, Samsung, and other Android phones.

" It's a once-in-a-generation moment to reinvent what phones can do," Android chief Sameer Samat told Business Insider. "We are going to seize that moment."

Consumers will only embrace these new devices if they're actually useful in everyday situations. Google has already shown off some of these new killer applications for AI . Apple will have to show off more of these powerful use cases at WWDC if it's going to keep up.

Mohan at BofA describes a wide range of new capabilities that could set IntelliPhones apart from smartphones and fire up the mother of all upgrade cycles.

"We view the upcoming AI enabled phones (IntelliPhones) to drive a multi-year upgrade cycle similar to the step function improvement driven by the introduction of smartphones," he wrote, calling this a "once in a decade type of event."

IntelliPhone capabilities

Here are some of the potential capabilities of IntelliPhones, according to BofA:

Context aware assistance: AI-enabled phones will offer more advanced personal assistants that understand context better and provide more relevant and timely responses.

Proactive suggestions: These assistants could proactively suggest actions based on user patterns.

Object and scene recognition: These phones can identify objects, people, and scenes in photos and suggest actions like sharing, searching for more information, or buying related products.

Real-time translation: AI-capable phones offer real-time language translation making communication easier while traveling or interacting with people who speak different languages.

Predictive health alerts: AI could predict potential health issues by analyzing patterns in collected data and alert users to seek medical advice if needed.

AI driven content creation: Users may be able to create more immersive and engaging AR/VR content with the help of AI tools on phones that simplify the creation process and enhance the final output.

Music Haptics: AI could refine vibrations from music to improve the experience for phone users who are deaf or hard of hearing.

Vocal Shortcuts: AI could recognize speech patterns and improve speech recognition for users with conditions that affect speech such as cerebral palsy, or those who have suffered a stroke. Users could also assign custom utterances that Siri can understand to launch shortcuts and complete complex tasks.

On February 28, Axel Springer, Business Insider's parent company, joined 31 other media groups and filed a $2.3 billion suit against Google in Dutch court, alleging losses suffered due to the company's advertising practices.

Main content

Are electric cars better for the environment than fuel-powered cars? Here's the verdict

An illustration indicating a verdict of emissions between petrol cars and electric vehicles

Whether you drive an electric car or are considering making the switch, you've probably been drawn into a discussion about whether they are really better for the climate.

Electric cars are key to the world reducing emissions, with transport accounting for almost 20 per cent and rising, so you probably haven't had that debate for the last time.

To save you from your next barbecue encounter, we have turned to the EV Council, which has crunched the numbers for you.

We're comparing an electric car and a traditional petrol one and looking at the life-cycle emissions — that is, all the emissions produced from cradle to grave.

For both types of car, these are the key stages where emissions are produced:

manufacturing of the car,
production of the battery, especially for electric cars
running the cars over their life-cycle, either on petrol or electricity
disposal and recycling of the vehicle at the end of its life, including batteries

We'll also compare electric cars in different states because each state uses different amounts of fossil fuels for electricity, which affects how "clean" the car is.

To compare cars, we've chosen an average medium SUV, the sort of car you commonly see on Australian roads.

Some examples of a medium SUV are the electric Tesla Model Y, Toyota's RAV4 and the Mazda CX-5 on the petrol side.

So, buckle up and let's go.

Let's start at when the car is made

An illustration of a car being made with robot arms assembling parts.

Manufacturing covers the production of the raw materials in the car's metal body, interiors, tyres, seating, the whole bundle. At this first stage, all these cars come out with similar emissions profiles.

… adding batteries for EVs

Battery production is the stage where we start to see a split between petrol and electric cars.

Electric vehicles (EV) are powered by batteries, so their batteries are significantly larger and heavier, and use more critical minerals. Our electric SUV also needs a bigger battery than a small hatchback.

It's important to note that this is about life-cycle emissions, so we aren't evaluating other environmental or human rights impacts from battery production for EVs, and we're also not critiquing the oil industry in those areas for petrol cars. That barbecue debate is for another day.

Batteries produced in China have higher emissions than those produced in Europe, and as most Australian electric cars currently have Chinese-made batteries, that's what's used here.

Climate experts and even the latest Intergovernmental Panel on Climate Change expect these figures to drop as more renewable energy is used in the coming years to make the batteries.

"So the energy needed to produce batteries is decarbonised, and therefore has lower emissions," according to University of Technology Sydney transport researcher, Robin Smit.

So at this point, before the cars hit the road, electric cars have more embedded emissions.

But that all changes when you start driving …

Taking our cars on the road

An illustration of an electric car being charged and a fuel car getting petrol at the bowser.

It won't shock you to find out that most of a car's lifetime emissions come from powering it to drive.

"The fuel energy cycle is normally the most important part of the life-cycle assessment [and] that includes on-road driving, the maintenance, and of course, the production of the energy," Professor Smit said.

The Australian Bureau of Statistics (ABS) estimates the average Australian car drives about 12,600 kilometres a year, or 189,000 over its lifetime, so that is what's used in this modelling.

Petrol cars are dirty. That's a fact. Combustion cars are powered by burning petrol, which releases emissions into the atmosphere and is — pardon the pun — a major climate change driver. These are referred to as "tailpipe emissions".

The petrol SUV here is up against an electric SUV charged on the national grid, which has a mix of fossil fuels and renewables.

Our petrol SUV produces almost 46 tonnes of carbon over its lifetime on the road.

These figures also factor in the emissions coming from refining and transporting the fuel.

"When you look at fossil fuels, they need to be extracted, processed, and then transported to service stations, for example, to make them available. So there's a greenhouse gas emission costs associated with that," Professor Smit said.

The estimated petrol used here is 8.3 litres for 100km and comes from the Worldwide Harmonised Light Vehicle Test Procedure (WLTP). These figures are almost always lower than real-world petrol use.

So, a lot of energy is burnt to move petrol cars, but most of it is wasted.

"They are not efficient, about 70 to 80 per cent of the energy is wasted in heat. So you only use 20 to 30 per cent of the energy into fuels for actually driving around," Professor Smit said.

What's more, Australians typically drive heavier cars than other countries, especially in Europe. Heavier cars require more fuel to move them, resulting in higher emissions.

This all means that petrol cars start producing significantly more emissions during their use, leaving electric cars in the dust.

Let's look at a different view of our two cars as we drive them for 15 years or 189,000km. Petrol cars are displayed in the blue line, and electric cars in red .

Electric cars are powered by electricity (obviously!) but how that electricity is created makes a huge difference to the overall emissions profile of EVs.

You can see emissions for the petrol car rise while the electric car's life-cycle emissions curve is flattening. That's because the composition of our electricity grid is rapidly changing and more renewables are coming online.

To account for that, this modelling from the EV Council uses the scenario mapped out by the Australian Energy Market Operator (AEMO) which predicts the rate of new renewables coming into the grid and fossil fuel plants being decommissioned. That is, by 2030, the same electric car will be producing lower emissions because it will be charged with more renewable power.

So this is for Australia as a whole, but where you live can also have a big impact on how much cleaner an EV is.

Some Australian states already have mostly renewable energy powering their grids, while others still have lots of fossil fuels.

An illustration of a map of Australia with an electricity symbol.

A car that's charged off a grid with lots of fossil fuels produces much higher emissions than a car charged somewhere with mostly renewable energy.

Let's look at our electric SUV in Western Australia, where in 2022 more than 83 per cent of electricity came from fossil fuels, mostly gas.

Now this is what our SUV's emissions look like in Tasmania (shown in the green line) , which powers almost its entire electricity network on hydro.

It's the same in South Australia, which has lots of wind and solar energy in the grid. You can see here that no matter where the EV is, it saves tonnes of emissions overall compared to a petrol SUV.

This highlights the huge opportunity to reduce transport emissions with electric cars.

The cleaner the grid, the cleaner the electric car.

What about cars charged on rooftop solar?

An illustration of an electric car charged with rooftop solar. The car is parked next to the house.

More than 3 million Australian homes have rooftop solar and, according to a 2021 survey, most EV owners plug into their own set-up.

A car that's charged with rooftop solar produces even lower emissions over its lifetime.

"When you use solar panels, they basically have very small-to-negligible emissions," Professor Smit noted.

Less than a tonne of carbon over all those kilometres!

Now, it's time to say goodbye to our cars and send them to the car afterlife …

Getting rid of our cars

An illustration of a car being disposed onto a scrap heap.

According to Professor Smit, the greenhouse gas emissions from taking cars off the road are small compared to the overall driving life of a car.

What's more, most of the materials in a car can be recycled, so this offsets some of the emissions from the production of the car at the start of the cycle.

To complete our emission profile, let's add the emissions for the disposal of our cars.

There's a lot of potential for improvements here too.

It takes a lot of grunt to power a car, and when a battery can no longer do that and comes out of an electric car, it still holds a lot of value and charging potential.

It can be used as a backup household battery, for example. Some car companies like Tesla are already using old car batteries to power their factories.

It's estimated this second life for EV batteries could cut the carbon footprint of battery production by half.

At the finish line

Overall, every electric car will produce fewer emissions than its petrol equivalent, no matter where they are charged.

Even with an electricity grid that still uses some fossil fuels, electric cars have much lower overall carbon emissions, and that will continue to drop as the electricity gets greener.

And remember, this example uses SUVs, so lighter electric cars like hatchbacks have even lower emissions.

Hang on, what about hybrids?

Put simply, hybrids are complicated.

Plug-in hybrids can be run off either petrol or from a battery that's plugged in and charged. Therefore, the life-cycle emissions from a plug-in hybrid depend on the region where it gets charged but also on how diligent the driver is with charging. Remember, it can also run on petrol.

The European Union's Environment Agency recently found that emissions from plug-in hybrids were 3.5 times higher than reported.

It concluded that hybrids "are charged and driven in electric mode much less than how they were expected to be used".

Where we get our figures from

These figures come from the Electric Vehicle Council, which based its life-cycle emissions calculator on modelling from the European organisation Transport & Environment .

We got Professor Smit to look over the EV Council's modelling and he said while it was generous to petrol cars, it provided a good way to compare life-cycle emissions.

The inputs for petrol use are based on the WLTP . As mentioned in the story, this is likely to underestimate real-world petrol usage.

The modelling uses data for a Nickel-Mangenese-Cobalt NMC li-ion battery produced in China, as that's the most common type of battery in the Australian EV market.

It calculates 105kg CO2/KWh for the carbon produced from battery production .

This same study found that "producing batteries with photovoltaic electricity instead of Chinese coal-based electricity decreases climate impacts of battery production by 69 per cent". Considering this estimate would reduce the emissions calculation in the point we make about battery production.

For a medium electric SUV, the energy used is 17.3 KWh/100km and a battery size of 70.2 KWh average for cars available in that category.

The emissions factors for energy sources are based on data from the Intergovernmental Panel for Climate Change here.

To model the rate of renewables coming into the grid, the EV Council used the step-change scenario from the AEMO .

Statements about the composition of the electricity grids in different states come from 2022 numbers from the Department of Climate Change, Energy, the Environment and Water.

The estimate of recycling emissions comes from a study by Transport & Environment .

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