Did the US GDP Really Increase by 33% Last Quarter?
We’ve gone over this already… no!
The Commerce Department’s Bureau of Economic Analysis (BEA) released the first estimate of the 3rd quarter’s gross domestic product this morning — referred to more commonly as GDP, a topic covered at length in my macroeconomics classes.
GDP was reported to increase at a seasonally and inflation-adjusted 33.1% annual rate, a record increase. However, many will misinterpret this number. It does not mean that, since the last quarter, overall production in the United States has increased by a third. If you look at the data, you’ll see a 7.4% improvement compared with the prior quarter — much different than 33%.
Well then, James, what does it mean?
In July, I addressed this issue when the same report on the US GDP stated a decrease of 33%. However, that post was months ago and now buried in the depths of Medium. Hell, that was before the new logo! I believe it is vital that students, entering all sorts of fields from journalism to policy to business, understand how GDP data are collected and reported. Therefore, we’re writing about it again.
There are three things to know about how GDP is reported: The numbers are seasonally-adjusted, inflation-adjusted, and annualized. The reason for numbers being reported in these ways is to help with comparing data across time.
Seasonally Adjusted
When data are seasonally adjusted, they are adjusted to remove seasonal variation in the data. For example, overall consumer spending is higher in the fourth quarter of the year due to the holiday season. The reported numbers consider this.
Inflation-adjusted
Inflation occurs when prices in an economy rise as a whole (deflation is when they fall). There are many reasons why inflation may happen. Some examples include more money being circulated (not necessarily ‘printed’), increases in overall demand, or decreases in overall supply. Since prices change over time, and GDP is meant to measure the economy's production, the GDP data are reported as being adjusted for these changes. These numbers are referred to as the real GDP (RGDP). How they adjust these data are a whole nother story that I won’t cover today.
Annualized
When the BEA reports the GDP data from a quarter, they are not reporting the amount of production in those three months. They report what a full year would look like (again, adjusting for both inflation and seasonality effects) if this quarterly production occurred. The headline percentage-change number is also reported as the annualized change. This means that, if the trend continued for a year, how would the economy look?
To make this clearer, let’s look at some current numbers:
US RGDP Q4 2019: 19.254 trillion (annualized)
US RGDP Q1 2020: 19.011 trillion
US RGDP Q2 2020: 17.303 trillion
US RGDP Q3 2020 (a): 18.584 trillion
If you take the percentage change from Q2 2020 to Q3 2020, you’ll see that number is 7.4%.
Percentage change from Q2 2020 to Q3 2020
Today’s data shows the economy expanding by 7.4% in the 3rd quarter. It did not expand by 33%. The data show that, if this continues for a full year and adjusted for both seasonal differences and price changes, we would see a 33% increase in economic activity.
Boy, wouldn’t that be something! (Spoiler: It will not happen)
Written by Professor James Tierney
For more of Professor Tierney’s articles visit:
Winners and Losers: The Adoption of AI Technology in the Global Economy
Innovation through technological advancements and improvements has greatly improved the global economy while simultaneously making certain jobs archaic since the Industrial Revolution in eighteenth-century England. From the spinning jenny replacing factory weavers, to telephones replacing telegram operators, job loss at the hands of new technology is no new concept. With the outbreak of the coronavirus pandemic in March of 2020, firms unable to fill their operating needs with human employees began searching elsewhere to stay afloat amidst the global health crisis. Because of their increased speed, efficiency, and inability to spread COVID-19, firms looking to keep the virus at bay and operating costs low have turned towards automation in their production processes. At the onset of the pandemic in the US, approximately forty-million jobs were lost. Among these jobs, economists argue 42% of them are permanently etched out of the economy.
With this substantial loss in labor force because of the pandemic, the replacement of human employees with artificial intelligence (AI) was immediately seen in various locations. Suddenly, AI was responsible for checking people’s temperatures, cleaning airports, protecting uninhabited real estate properties, and producing direly-needed products like cotton swabs and face masks. With these new roles, AI is becoming an increasingly important component of operations within various sectors within the global economy. Rob Thomas, senior vice president of a cloud data platform at IBM, exclaimed “I really think this is the new normal- the pandemic accelerated what was going to happen anyway.” And while Thomas and those in highly digitalized environments benefit from this rising use of AI, significant disruptions for workers, companies, and economies have already occurred, and will continue with the technology’s spread.
According to a 2018 report on Artificial Intelligence written by the McKinsey Global Institute, AI has the potential to add $13 trillion, or 16% , to the global economic output. Between 2018 and 2030, AI is expected add an average annual 1.2% to productivity growth. McKinsey also reported that the rise and effect of AI can be compared to the absorption of previous technologies before it, like the introduction of steam engines in the 1800s. Following a s-shaped growth curve, AI is expected to grow slowly in its beginning phases, followed by a sharp growth increase as the technology is assimilated and its use optimized by firms, followed by growth leveling out in its later stages.
Source: MDPI
Also in McKinsey’s report on the technology of AI and its assimilation into our everyday world, the institute identifies multiple key factors in determining the economic influences caused by AI. While implementing AI into various supply chains, production, and maintenance lines, the technology has the potential to enhance the already-existing gaps between companies, countries, and workers. At the forefront of AI adoption is China and the US, the two countries responsible for most of the existing AI in our world now, as well as the AI that will be developed in the future. Following these two superpowers are countries such as Canada, Germany, and Sweden, who will also benefit from the use of AI. However, for developing countries who are already behind in digital infrastructure and investment capacity, AI poses yet another way that they can fall additionally behind.
Firms’ success with AI will be determined by the rate and manner at which they adopt the new technology. These adoption methods can fall into three categories. First, there are the front-runners. These are companies who have already integrated AI into their business somehow and will likely embrace the new technology even more within the next 5 to 7 years. Companies in this category have the possibility to capture a majority of their industry-profits using AI. The next category of AI adoption are the followers. Approximately 20% to 30% of firms, these companies are carefully accepting AI usage and have seen the successes of front-runners, as well as the threat of falling behind. The final category of adoption are laggards. Making up 60% to 70% of firms, these companies are not integrating or investing in the use of AI at all.
Source: McKinsey Global Institute
On top of this impact on firms, AI will likely cause a major shift in the demand for skilled workers. The McKinsey Report estimates 14% of the global workforce, 375 million workers, will require a change in occupation by 2030. Workers with the skills to work alongside AI and additional new technologies will see their value greatly increased. Thus, groups with reduced skills sets are at risk for more inequality because of AI.
The integration of artificial intelligence into our world has only just begun, and with a vaccine yet to be distributed to fight the coronavirus pandemic, AI’s impact will only be catalyzed further as it becomes adopted in more industries formerly staffed by humans. Firms already investing in and implementing AI will continue to see their profits grow from the technology, while those lacking the ability to adopt it at that rate will fall behind. With the potential of a major labor market disruption, firms must account for the impact AI could have on peoples’ lives. Overall, the growing use of AI will increase more and more until it is the standard among industries, much like the innovative technologies that have come before it.
Written by Colin Spellman
A Modern Look at Agricultural Subsidies
This past year saw the United States public debt to GDP as a percentage of GDP rise above 100%. With growing interest in public debt, its impact on the U.S. economy, and how much is sustainable in the long term, it becomes increasingly important to view controversial sectors of spending. One of these controversial areas is agricultural subsidies. The United States spends over $20 billion a year on agricultural subsidies, with supporters defending the subsidies using numerous arguments such as claiming that the agricultural subsidies help low-income farmers and stabilize the agricultural market. However, extensive economic research on the topic paints a largely negative picture of the welfare effects produced by these subsidies.
Today’s agricultural subsidies originated during the Great Depression as a part of Franklin D. Roosevelts New Deal policies with the Agricultural Adjustment Act. This act eventually developed into today’s Farm Bill, which is periodically renewed by Congress every 5 years. As commodity markets are notoriously volatile, the subsidies were intended to stabilize the price and help low-income farmers negatively affected by the Great Depression and the Dust Bowl of the early 1930s – a period of dust storms that lead to drought and greatly damaged American agriculture.
One of the chief arguments in support of farm subsidies is that it helps stabilize markets that would otherwise be volatile. Commodity markets tend to be volatile as a result of having highly inelastic supply and demand. This inelasticity is in part due to commodities often being necessities with few to no substitutes and changes in supply would take significant amount of time. Critics of the subsidies note that families today spend less of their income on food than previously. With households only spending 10% of their income on food today relative to 20% in the 1960s, any price instability would have a smaller impact on consumers than when these policies were instated.
In addition to this, research has shown that the subsidies produce a net negative effect on welfare through the effects of a dead weight loss. One paper published by economist Jason L. Lusk estimated that the removal of the subsidies had a potential net economic benefit of $622, $932, and $522 million in 2012 to 2014. These findings are consistent with economic theory, Lusk further noting that the cost of the subsidy can be seen through a higher tax burden on consumers.
At the time the subsidies were introduced, they were intended to support low income farm workers during the Great Depression, with 21.5% of the labor force employed in agriculture during 1930. Today however, only 1.9% of the labor force works in agriculture with farm households being overwhelmingly wealthy. A report by the Congressional Budget Office found that 97% of farm households were wealthier than the median US household. The median farm household had an income of $83,111 in 2019 compared the median US household income of $68,703. Critics of the farm subsidies argue that they effectively transfer wealth from the average US taxpayer to relatively wealthier farming households.
Agricultural subsidies also act as a form of protectionism. Protectionism is the practice of defending domestic industries from international competition. Agricultural subsidies allow domestic farmers to produce a greater quantity of their products which in turn reduces imports and boosts exports. This makes it difficult for farmers in poor countries to compete in the international market, with estimates that agricultural subsidies cost developing countries $24 billion in lost income.
Despite economic research displaying the net negative impacts of agricultural subsidies, they are unlikely to stop anytime soon. Researchers believe the reason for this can be found through Public Choice Theory. Public choice theorists point to the issue of “concentrated benefits and dispersed costs”. Essentially, as the cost of agricultural subsidies are dispersed over a range of taxpayers, no one taxpayer is affected enough to track their representatives votes on the issue, so they remain “rationally ignorant”. On the other hand, the farmers who benefit directly from agricultural subsidies are more likely to invest time and money to protect their interest. This leads to a situation where the incentive for farmers to defend the subsidies is greater than the incentive for consumers to fight them.
Over the past 90 years, subsidies have become an integral part the US agriculture industry. Despite their costs to taxpayers and their wealth redistribution effects, public choice theory shows that the subsidies are unlikely to stop in the near future. While $20 billion may not seem significant in a deficit rising over $3 trillion, it is always important nonetheless to identify areas of policy economists can research and offer solutions.
Written by Abdallah Al Rahbi
Antitrust in the Age of Technology
Google’s long-standing position as the dominant gatekeeper to the internet’s expansive reservoir of web pages has brought the company annual revenues in excess of $160 billion annually in 2019, a market capitalization of over $1 trillion, and as of October 20, a Department of Justice lawsuit alleging anticompetitive practices. The lawsuit, which has been expected following a lengthy Justice Department investigation, marks the biggest challenge the U.S. government has made against a technology company since the landmark Microsoft antitrust case brought over twenty years ago. The federal government’s complaint against Google comes as the government seeks to dial in the correct approach for regulating the new stalwarts of the digital age and it highlights the transformation of antitrust issues in the modern economy.
The Justice Department’s complaint against Google centers around the types of arrangements made between Google and other companies that the web giant pays to make its search engine the default option on their devices. This relationship is most notably seen between Google and its Silicon Valley neighbor Apple. The two companies previously entered into an agreement whereby Google’s search engine serves as the default option for iOS devices, directing nearly all of Apple’s lucrative mobile phone traffic to Google servers. While the official number is not disclosed, analysts estimate that this deal is worth between $8 and $12 billion annually – making up a significant portion of Apple’s business outside of its hardware sales. The Justice Department alleges that this high price paid by Google reaps major rewards for them as they are able to capture a larger share of total web traffic and in turn charge elevated, monopolistic prices to the advertisers who are seeking to promote their results. This continuous loop whereby Google pays for placement in operating systems and browsers contributes to concerns that the company will only continue to grow in size and dominance and further shut out potential competitors.
In responding to the lawsuit, the company’s legal chief likened this arrangement to a cereal company paying a grocery store to place its products in a more desirable location such as at the end of the aisle or on a shelf at eye-level, both legal practices that are widely accepted in the industry. He went on to state that if the government’s lawsuit were to succeed, and some of these business practices were found to be in violation of government regulations, consumers would in fact be harmed as Google would be forced to charge higher prices for its mobile software and hardware. As the company’s flagship search engine is currently offered as a free service to consumers, it would prove to be a counterproductive measure to harm the same consumers who are benefitting the most from Google’s business. Further, as antitrust cases of this magnitude and type are not litigated frequently, the results of this case will likely have a profound, precedent-setting effect on issues of this nature well into the future.
Although the Justice Department’s case was brought by the current Republican administration and co-sponsored by eleven state attorney generals – scrutiny against big technology companies has largely drawn bipartisan support. Joe Biden has not publicly stated his position on this specific charge, however, he did espouse his wariness at potential monopolization in technology, commenting, “growing economic concentration and monopoly power in our nation today threatens our American values of competition, choice, and shared prosperity. Our commitment to these values must compel us to do far more to ensure that excessive market power anywhere—across industries, from health care to agriculture to tech to banking and finance—is not hurting America’s families and workers,” The next administration might bring political uncertainty in a number of arenas, but the continued examination of antitrust issues in technology will likely continue on in some capacity.
While modern antitrust issues in the technology field bear little resemblance to the types of monopolies the government initially sought to curb with the passage of the landmark Sherman Antitrust Act in 1890, the effect on competition can be similar between the two eras. Past antitrust disputes generally focused on the adverse effects that monopolies can have on prices and consumers through the direct actions of the company. In the case of Standard Oil, concerns over the market size of the company and the resulting power it exerted over prices led the firm to be broken up into smaller components that could no longer act in concert. This situation differs significantly from the one that Google is facing, however, as the company’s services are generally priced either at low costs or are offered for free. In this situation, the consumer is not affected by a pricing barrier, but rather – the Justice Department alleges – by the possible failure of new competition to emerge and further enhance the technological landscape in the same fashion that Google did just over two decades ago. The loss of possible innovation through actions undertaken by one of the world’s largest companies is what is driving the Department of Justice’s lawsuit. Whether these concerns are unfounded or not will likely take years of litigation in some of the nation’s highest courts to decide.
Written by Josh Rudd
Innovation Slowdown: The Problematic Decline of New Ideas
What is and is not real in regard to the many topics of the world is in many cases up to how one wants to view it. Which side of the aisle, which school of study, optimistic or pessimistic. To be blunt, subjectively. An onlooker hailing from the first world today may view our present times as a period of rapid, unbridled innovation. Afterall, look at the internet, smart phones, electric self driving cars, and automated restaurants. This list goes on if naming the unimaginable luxuries that the 21st century has spurred out of thin air. However, from an economist’s point of view, is all this change true innovation? Or is this instead a process of extending or modifying existing product categories and services—in a way, businesses aiming to pick the lowest hanging fruit as opposed to planting new trees. Unfortunately for that first world onlooker the data has an answer that tends to be rather pessimistic and grim. The oft overlooked economic definition of innovation declares less of the 21st century’s new goods to be truly innovative than may meet the eye. This is because innovation is, in the economic sense, a process of discovering new ideas and realizing them on a large scale that changes the life and work of its human adopters. Both small and large changes can come as a result of innovation, however it is now widely agreed upon by economists that following 1970 the world’s largest economic engines—United States, Germany, and Japan—began to enter significant declines in the vital large innovative changes. Large significant innovations are the primary drivers of sustainable GDP per capita growth. They create more value for consumers’ lives as well as increasing overall productive or leisure time. Think for example, about the immense impact the steam engine had on production and travel. This is quantitatively more impactful than, say, the development of the consumer hybrid automobile—an innovation in its own right. To analyze the consequences of this slowdown, this article aims to answer the following questions; how innovation decline is accurately measured, why is it occurring, and what does it spell for the future of economies around the globe.
To begin, a simple comparison of two different consumer product innovations may help build the foundation of our innovation story. The first innovation: the invention of assembly line manufactured Ford Model-T automobiles. Their implementation changed the process of how all factories would thereafter create goods. The second, the invention of the fastest consumer car to date, the Bugatti Chiron Super Sport 300+ which can reach speeds of 304.77 miles per hour, something unheard of prior in consumer cars. Now it is of no question which car bests the other in a race, nor if there is any competition in regard to style or aesthetic where the Chiron is sleek and Model-T is boxy, and even in the case of build quality the Chiron is far superior. Both products are innovative, they were built in manners previously never explored. They led the field of their market and are considered the best product of their respective type. However, it should come as no surprise that the Ford Model-T, despite only topping out at speeds of 40 miles per hour, changed the way people lived and worked in far greater magnitude following the early 20th century than the introduction Bugatti Chiron in our current 21st. The manufacturing line used to build Model-T’s was inarguably even more influential. Our first innovation built something vastly differentiated from what was before, and our second innovation extended the product line of fastest cars manufactured. This is not to say there are no large innovations today. The internet and artificial intelligence have caused significant end roads to daily life. Yet economists, such as Nick Bloom of Stanford whose research will be used soon, argue these large innovative dynamic changes are now simply too few and far between. One needs to look no further than beyond their very own grandmother. A person who in all likelihood witnessed human beings for the first time in history take to the sky via airplane, travel across countries via automobile, remove food stored from electrically powered refrigeration and subsequently reheat it in a device that uses vibrating water molecules to cook—á la the microwave. There is a notable difference between electricity, the lightbulb, steam engines, and the atomic bomb when contrasted with modern day inventions. The leaps are not as vast, and the bounds are not as frequent.
To return as well as conclude with the notable findings of Stanford economist Nick Bloom. His seminal paper “Are Ideas Getting Harder to Find?” models the problems of slowing innovation by providing a meaningful look at various key innovation industries and their total productive output, number of researchers, research effort, and overall new ideas (measured by the variable of Total Factor Productivity). Findings are statistically profound and made even further striking when put graphically as seen below.
Visually in the above graphs it is clear that the total amount of researchers required to reach former levels of productive output has increased immensely. Dually, it is of note that this comes not as a result of fewer researchers working to innovate but instead as a result of the drastic problematic drop in productivity per researcher. This problem is compounded over time by further growth in overall number of researchers and further loss in marginal research productivity.
To use the famous Moore’s law as an example—which states that the total quantity of transistors on a microchip doubles every two years—in the world today it takes approximately 18 times as much research effort to continue theory of exponential growth of microchips. Put simply, the economy is growing not because of true innovative ideas invented by creative peoples but rather by the sheer quantity of researchers slaving away at an increasingly lower research productivity rate. To keep up the world’s advanced economies current GDP per capita growth (prior to COVID) the innovators and researchers must continue to add further researchers and work harder than it ever has before. One must run faster and harder to maintain the same speed as before in a sense. Total factor productivity prior to 1973 grew at an annual rate of 1.9% and following 1973 has grown at an annual rate of 0.7%. This goes hand in hand with a trio of other findings separate of Nick Bloom’s work. The first of which being that smaller firms have an increased chance of innovating in substantial ways than larger firms, or put another way, by increasing the number of people in a firm the number of substantial ideas and research productivity per researcher falls. As firm size goes up, patents per researcher falls dramatically past four employees. This occurs for a variety of reasons stemming from less navigability for larger firms, less incentive for research achievement, less accountability for researchers, and the ever-present Prices Law. So, in essence the problem of unproductive researchers grows worse as you acquire greater numbers, and yet the economy needs more as current researchers remain unproductive in their increasingly larger firms. The second finding is that in our current economy, both small and mid-size entrepreneurial ventures are increasingly put off by longer patent approval periods as well as overall increases in the overhead cost required in patent approval. From 1990 to 2010 the time elapsed between patent submission and approval nearly doubled from 18.3 months to 35.3 months. This creates a toxic and unfriendly environment for the potential small to mid-size innovator. The last finding is the decreasing number of innovators in the worlds advanced countries. The share of annual STEM college graduates (15% U.S.) in the United States, who produce the vast majority of innovation, continue to make up less than half of the world leader South Korea’s share of STEM graduates (35% S.K). Those that do pursue STEM fields are not all pursuing the typical innovator type of careers as less innovative private sector positions offer lucrative wages due to the low supply. This in many ways is a long way of saying, it takes far greater effort and far more researchers to field far less truly world-shaking economic innovations in the modern world. Even more frightening is that this looks to trend worse.
So, what does this mean for the future? Well, for one, it means that if human beings want to continue exponential unending growth then it will continue to take more work as a result of the continued decrease in Total Factor Productivity growth. Perhaps one way of helping change the tide could be policy that incorporates the new technological age in a more substantial manner. Policy that entices small to midsize entrepreneurial ventures instead of scaring them away with long tedious and expensive patent affirmations. Additionally, it may serve a practical purpose to further enforce and incentivize growth in annual share of STEM graduates from universities as they make up the greatest sector of innovation. To the current economy the problem of lacking innovation will undoubtably make itself known in the future in a very meaningful way. To make a poor analogy; once every low hanging fruit has been picked, it is to the dismay of an empty stomach that there is a great need for ladders which have yet to be invented.
Written by Tucker Pippin
Sources
Winners and Losers: The Adoption of AI Technology in the Global Economy:
A Modern Look at Agricultural Subsidies:
Antitrust in the Age of Technology:
Innovation Slowdown: The Problematic Decline of New Ideas:
https://www.brookings.edu/wp-content/uploads/2020/01/ProductivityComparisonsRD_final.pdf