Authors Glenn Hubbard and Tony O’Brien follow up on last week’s fiscal policy podcast by discussing monetary policy in today’s world. The Fed’s role has changed significantly since it was first introduced. They keep an eye on inflation and employment but aren’t clear on which is their priority. The tools and models used by economists even a decade ago seem outdated in a world where these concepts of a previous generation may be outdated. But, are they? LIsten to Glenn & Tony discuss these issues in some depth as we navigate our way through a difficult financial time.
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Authors Glenn Hubbard and Tony O’Brien discuss the long-term impacts of recent fiscal policy decisions as well as the proposed infrastructure investment by the Biden administration. The most recent round of fiscal stimulus means that we’re spending almost 4.5 Trillion which is a high percentage of what we recently spent in an entire fiscal year. They deal with the question of if the infrastructure spending will increase future productivity or will just be spent on the social programs. Also, Glenn deals with the proposed corporate tax increase to 28% which has been designated to fund these programs but does have an impact on stock market values held by millions through 401K’s and IRA’s.
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Authors Glenn Hubbard and Tony O’Brien discuss early thoughts on the Biden Administration’s economic plan. They consider criticisms of the most recent stimulus packages price tag of $1.9B that it may spur inflation in future quarters. They offer thoughts on how this may become the primary legislative initiative of Biden’s first term as it crowds out other potential policy initiatives. Questions are asked about what bounce we may see for the economy and comparisons are made to the Post World War II era. Please listen and share with students!
The following editorials are mentioned in the podcast:
The recession that resulted from the Covid-19 pandemic affected most sectors of the U.S. economy, but some sectors of the economy fared better than others. As a broad generalization, we can say that online retailers, such as Amazon; delivery firms, such as FedEx and DoorDash; many manufacturers, including GM, Tesla, and other automobile firms; and firms, such as Zoom, that facilitate online meetings and lessons, have done well. Again, generalizing broadly, firms that supply a service, particularly if doing so requires in-person contact, have done poorly. Examples are restaurants, movie theaters, hotels, hair salons, and gyms.
The following figure uses data from the Federal Reserve Economic Data (FRED) website (fred.stlouisfed.org) on employment in several business sectors—note that the sectors shown in the figure do not account for all employment in the U.S. economy. For ease of comparison, total employment in each sector in February 2020 has been set equal to 100.
Employment in each sector dropped sharply between February and April as the pandemic began to spread throughout the United States, leading governors and mayors to order many businesses and schools closed. Even in areas where most businesses remained open, many people became reluctant to shop in stores, eat in restaurants, or exercise in gyms. From April to November, there were substantial employment gains in each sector, with employment in all goods-producing industries and employment in manufacturing (a subcategory of goods-producing industries) in November being just 5 percent less than in February. Employment in professional and business services (firms in this sector include legal, accounting, engineering, legal, consulting, and business software firms), rose to about the same level, but employment in all service industries was still 7 percent below its February level and employment in restaurants and bars was 17 percent below its February level.
Raj Chetty of Harvard University and colleagues have created the Opportunity Insights website that brings together data on a number of economic indicators that reflect employment, income, spending, and production in geographic areas down to the county or, for some cities, the ZIP code level. The Opportunity Insights website can be found HERE.
In a paper using these data, Chetty and colleagues find that during the pandemic “spending fell primarily because high-income households started spending much less.… Spending reductions were concentrated in services that require in-person physical interaction, such as hotels and restaurants …. These findings suggest that high-income households reduced spending primarily because of health concerns rather than a reduction in income or wealth, perhaps because they were able to self-isolate more easily than lower-income individuals (e.g., by substituting to remote work).”
As a result, “Small business revenues in the highest-income and highest-rent ZIP codes (e.g., the Upper East Side of Manhattan) fell by more than 65% between March and mid-April, compared with 30% in the least affluent ZIP codes. These reductions in revenue resulted in a much higher rate of small business closure in affluent areas within a given county than in less affluent areas.” As the revenues of small businesses declined, the businesses laid off workers and sometimes reduced the wages of workers they continued to employ. The employees of these small businesses, were typically lower- wage workers. The authors conclude from the data that: “Employment for high- wage workers also rebounded much more quickly: employment levels for workers in the top wage quartile [the top 20 percent of wages] were almost back to pre-COVID levels by the end of May, but remained 20% below baseline for low-wage workers even as of October 2020.”
The paper, which goes into much greater detail than the brief summary just given, can be found HERE.
Authors Glenn Hubbard and Tony O’Brien look at the economic outlook given the current status of the presidential election. Will a divided government lead to economic prosperity or result in more gridlock? They discuss how much the President actually controls economic policy by setting the tone but that other instruments of our government likely have more effect in creating long-term growth in the Economy.
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Glenn Hubbard and Tony O’Brien continue their podcast series with a first – hosing a guest – Penn State Economics Professor, James Tierney. We learn about the transition James had from an early return from spring break to now teaching hundreds of students exclusively online in response to the pandemic. Glenn and Tony also discuss with James the struggles of the housing market in a small college town like State College, PA. We also learn the reasons behind James becoming the founder of an adult Improv company in the State College-area and the impact it had on his teaching. Please listen and share!
Glenn Hubbard and Tony O’Brien continue their podcast series by spending just under 15 minutes discussing why it was so difficult for economists to see this pandemic and the associated economic downturn coming. Just as scientists lacked the indicators to see the pandemic coming, economists also didn’t have the tools available to see where the economy was headed even though some early signs were present. Please listen and SHARE with your students.
Glenn Hubbard and Tony O’Brien continued their podcast series by spending about 15 minutes discussing the impact of the Pandemic on the Mom and Pop Businesses across the country. Much of the stimulus package has been developed to save small business but might it be too late or just not enough? Please listen and SHARE with your students.
Supports: Econ (Chapter 20) & Macro (Chapter 10): Economics Growth, the Financial System, and Business Cycles; Essentials: Chapter 14.
Why Do Economists Have Trouble Predicting Recessions?
During the 2008 financial crisis,Queen Elizabeth of England visited the London School of Economics and famously asked the economists present, “Why did nobody notice it?” The queen is not alone in wondering why economists seem unable to predict when an economic crisis or financial crisis will hit.
There are three main reasons recessions are difficult for economists to predict:
Business Cycles are Not Uniform Although economists and policymakers often refer to the “business cycle,” in fact the recurring periods of economic expansion and economic contraction are not of uniform length or severity, so they do not resemble a sine wave from mathematics or other regular pattern. Because economic expansions have no set length, there is no reason to predict that an economic expansion that has lasted for a particular period of time will soon end in a recession.
Leading Economic Indicators are Not Reliable Economists haven’t found a consistent relationship between changes in any economic variable and later changes in real GDP and employment that would allow them to predict when a recession might begin. There are some variables, called leading economic indicators, that usually begin to decline before real GDP and employment decline. But those leading indicators are not completely reliable. For example, stock prices usually decline before a recession begins as investors anticipate the reduction in profits that occur during a recession. But although the largest one-day percentage decline in the S&P 500 stock index occurred on October 19, 1987, the next recession did not begin until nearly three years later. The late Nobel laureate Paul Samuelson of the Massachusetts Institute of Technology once joked that the stock market had predicted nine of the last five recessions.
Events That Trigger a Recession are Hard to Predict Perhaps most importantly, there are many different events that can trigger a recession and these triggering events are typically difficult to predict. For example, the answer to the Queen of England’s question about why economists failed to predict the financial crisis and recession of 2007-2009 is that very few economists recognized how vulnerable the U.S. financial system—and, therefore, the U.S. economy—was to a decline in housing prices.
Many economists believed that the doubling of housing prices between 2000 and 2006 was unsustainable. But few economists or policymakers realized that falling housing prices would lead many homeowners to default on their mortgages, particularly so-called subprime borrowers who had poor credit histories. Economists also didn’t realize these defaults would lead to falling prices of mortgage-backed and severe problems for financial firms that owned these securities. In a speech given in 2007, a few months before the Great Recession began, Federal Reserve Chair Ben Bernanke stated that: “We believe the effect of the troubles in the subprime sector on the broader housing market will likely be limited, and we do not expect significant spillovers from the subprime market to the rest of economy or to the financial system.” Bernanke’s opinion was shared by many other economists inside and outside the Fed. Because they didn’t fully understand that, given changes in the financial system over the previous 20 years, falling housing prices would lead to a financial crisis, most economists failed to predict the financial crisis that led to the Great Recession.
Similarly, most economists and policymakers underestimated the effects of Covid-19 when the disease first appeared in China at the end of 2019. In the past 20 years, the world has seen four similar viruses:
2002: Severe Acute Respiratory Syndrome (SARS)
2009: Swine flu
2012: Middle East Respiratory Syndrome (MERS)
For various reasons, none of these viruses reached the levels in the United States that required widespread quarantines or the closing of schools and other social distancing measures, although more than 12,000 people may have died of swine flu in the United States.
This experience led many economists, policymakers, firms, and investors to believe that the United States was unlikely to experience a significant economic disruption as a result of the coronavirus. From mid-December 2019 to mid-January 2020, none of the most widely followed forecasts of U.S. real GDP growth for the year 2020 indicated that a recession was likely. The real GDP forecasts from the Congressional Budget Office, the Federal Reserve’s Federal Open Market Committee, the Goldman Sachs investment bank, and 60 economists surveyed by the Wall Street Journal were all between 1.9 percent and 2.3 percent—comparable to the 2.3 percent increase in real GDP that the U.S. had experienced during 2019. The S&P 500 stock index reached a record high on February 19, 2020, despite China already having more than 50,000 cases of infection from the virus.
By mid-March, as cases of Covid-19 became common in the United States and most cities and states were announcing social distancing policies that included closing many non-essential businesses, the S&P 500 had declined by more than 30 percent and economists and policymakers all realized that the U.S. economy would be experiencing a substantial recession
That economists failed to predict the recessions of 2007-2009 and 2020 should probably not have been surprising. Economists Zidong An, João Tovar Jalles, and Prakash Loungani of the International Monetary Fund (IMF) studied how accurate economists were in forecasting recessions in 63 countries over the period from 1990 to 2014. They found that both economists in the private sector as well as the IMF’s own economists rarely succeeded in forecasting a recession before it had begun. On average during this period, real GDP declined by 2.8 percent during the first year of a recession. But in April of the year prior to the start of a recession, the average forecast from private sector economists and economists at the IMF was for an increase in real GDP of 3 percent. By October of the year prior to a recession, private economists had reduced their forecasts of real GDP for the following year on average to an increase of 2 percent and economists at the IMF had reduced their forecast to 2.5 percent but these forecasts were still well above the actual decline in real GDP of 2.8 percent.
In recent years, economists have devoted resources to forecasting how real GDP will change during the current quarter. This nowcasting, if accurate, can provide policymakers and economists information on how a recession is progressing while it is occurring. Nowcasting generally relies on identifying relationships between economic variables that have data available monthly or weekly and real GDP, which in the United States is calculated by the BEA quarterly. Because economists disagree on which data provide the most accurate forecasts of real GDP during the current quarter, their nowcasts can be strikingly different.
The following table shows seven nowcasts issued during mid-April 2020 of real GDP during the second quarter of 2020, during the recession caused by the coronavirus pandemic. The data are given as changes expressed at an annual rate, which means they should be interpreted as indicating what the change in real GDP would be if the rate at which GDP changed in that quarter were sustained for a year. (Note that the Weekly Economic Index (WEI) and the uncertainty based forecast were originally presented as the percentage change from the same quarter in the previous year and have been converted to an annual rate.) Six of the forecasts agree in predicting that real GDP would decline during the quarter at a very high rate of more than 25 percent. As a standard of comparison, before the second quarter of 2020, the largest two quarterly declines in real GDP since 1947 were the decline of 10.0 percent in the first quarter of 1958 and the decline of 8.4 percent in the fourth quarter of 2008. Even the more moderate decline predicted by the New York Fed’s Nowcast would be among the largest in the past 75 years.
Ultimately, the difficulty that macroeconomists encounter in forecasting changes in real GDP indicates the complexity of the macroeconomy. Economists have not yet succeeded in reducing this complexity to a statistical model that can reliably forecast changes in real GDP—particularly whether a recession is likely to occur.
Sources: Scott Baker, Nicholas Bloom, Steven Davis, and Stephen Terry, “Covid-Induced Economic Uncertainty,” National Bureau of Economic Research Working Paper 26983, April 2020; Zidong An, João Tovar Jalles, and Prakash Loungani, “How Well Do Economists Forecast Recessions?” IMF Working Paper, March 2018; Board of Governors of the Federal Reserve System, “Economic Projections of Federal Reserve Board Members and Federal Reserve Bank Presidents, under Their Individual Assumptions of Projected Appropriate Monetary Policy,” federalreserve.gov, December 11, 2019; Goldman Sachs, “What’s the Outlook for the U.S. Stock Market in 2020?” January 6, 2020; “Economic Forecasting Survey,” wsj.com; Lisa Beilfuss, “Why a 50% Drop in U.S. GDP Isn’t as Bad as It Seems, barrons.com, April 14, 2020; Andrew Pierce, “The Queen Asks Why No One Saw the Credit Crunch Coming,” telegraph.com.uk, November 5, 2008; Brian Domitrovic, “The Stock Market Has Predicted Nine of the Past Five Recessions,” forbes.com, November 22, 2018; and Federal Reserve Bank of St. Louis.
Question: During the coronavirus pandemic, some people wondered why biologists seemed unable to answer many questions about the virus, including why children appeared rarely to become ill, why men were more likely than women to die from the virus, and why there was great uncertainty about whether some existing pharmaceuticals would be effective in treating the disease. Briefly discuss similarities and differences between the problem biologists faced in understanding the coronavirus and the problem economists face in predicting recessions.
For Economics Instructors that would like the approved answers to the above questions, please email Christopher DeJohn from Pearson at email@example.com and list your Institution and Course Number.
On April 17th, Glenn Hubbard and Tony O’Brien continued their podcast series by spending just under 30 minutes discuss varied topics such as the Federal Reserve’s monetary response, record unemployment numbers, panic buying of toilet paper as compared to bank runs, as well as recent books they’ve been reading with increased downtime from the pandemic.