Scientists rejoice: the UK rejoins the Horizon Europe programme
This general maxim can be applied to the growth of knowledge as well as the trade of physical goods. When researchers are allowed to specialize in their own topic areas and then collaborate with the other researchers around the world, knowledge – and therefore human capital – grows more than it would otherwise. Research and innovation can therefore be thought of similarly to the trade of physical goods; the more that is shared, the merrier. That’s part of why news about an agreement between the UK government and a prominent EU research program have given European and UK-based researchers – including many economists – renewed hope in the future of science. The Horizon Europe program On September 7, 2023, it was announced that the UK is set to rejoin the Horizon Europe research programme, after an agreement between the UK’s Prime Minister Rishi Sunak and European Commission president Ursula von der Leyen. It is expected that the UK will rejoin the programme effective January 1, 2024. The Horizon Europe programme is a framework for collaborating research across borders in the EU (and around the world) that includes researchers from top research institutes, technology companies and universities. The programme presents a framework of societal goals, some shared by member nations, and some (such as the UN’s Sustainable Development Goals) that are not just limited to relevance in the EU. The programme benefits researchers by streamlining complex administrative requirements and allowing access to a wide pool of potential funding; together, this makes it easier for a diverse body of researchers to work together, which lowers the barriers to advancing science. The programme notably features an open science mandate as well, helping to break down artificial barriers to sharing knowledge. According to a fact sheet released by the European Commission, as of 2021 the programme accounted for 17% of global R&D expenses and was at least partially responsible for 25% of the world’s top scientific publications. It has a budget of €95.5 billion across the years 2021-2027, which it grants to research projects across six different topic “clusters”. Funding in the programme is not just limited to EU countries. While a small proportion of each project’s team is usually required to be EU-based, researchers around the world are very much allowed to be part of research teams that receive funding from the programme. <11an>limit:3;categories:Jobs</11an> History with the UK Originally, the UK remained part of the Horizon programme even after the “no deal” Brexit situation came to pass. However, the UK left the programme after negotiations over the Northern Ireland Protocol caused relations to grow tense. This had several effects detrimental to the progress of science, particularly in the UK. It became more difficult for researchers in the UK to collaborate with colleagues in other parts of the EU through Horizon-funded research, and it cut off UK funding to Horizon Europe research projects. On top of the difficulties introduced by Brexit, this made it more difficult for scientists to conduct research in the UK, and less attractive for prospective scientists to settle in the UK or seek partnerships with UK-based institutions or researchers. Organizations based in Europe, uncertain about the future ability of their UK colleagues to cooperate in a post-Brexit landscape, were incentivized to find non-UK options for funding and research collaborations. As a result, the UK lost a significant number of researchers and received significantly less money from EU sources. What does this mean for economists in Europe? By rejoining Horizon, the UK is unlocking unparalleled research opportunities. This has the potential to alleviate much of the pain caused in the past few years. Economists in Europe, particularly those in the UK, should find that this change is positive or neutral for their work, with little downside. It will be easier for economists to collaborate with British or European colleagues, and funding might be more accessible for some projects. Moreover, science as a whole will benefit as researchers face fewer barriers to international collaboration and increased access to funding. To learn more about Horizon Europe, consider downloading a fact sheet about the programme, available at the European Commission’s website. Have you or your department been affected by the changes in the UK’s status in Horizon Europe, or have you been affected as an academic post-Brexit? Please share your experience in the comments below. References https://www.independent.co.uk/news/uk/politics/rishi-sunak-european-union-government-horizon-brexit-b2406606.html https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-europe_en Header image credit: vwalakte on Freepik/Magnific (free license)
International cooperation is important for economic growth, because it allows societies to grow more than they could on their own. When countries specialize in the economic areas they are relatively more productive in (utilizing their comparative advantages) and trade with other nations, everyone is made better off.
John Maynard Keynes was a philosopher and economist who made a massive impact on the field. He is often placed next to luminaries such as Adam Smith and Karl Marx as one of the great founding thinkers in economic theory, and for good reason. Keynes’ ideas formed the basis of Keynesianism, a school of economic thought that was the first to seriously challenge the classical way of thinking. Keynesianism is one of the major disciplines or philosophies of economics, as opposed to the classical, Neoclassical, or monetarist (and etc.) schools of thought. Until Keynes’ new theories, economists had been stuck with classical models of economics that were a great starting point for economic theory, but were ultimately too inflexible and unrealistic. (Eventually, economists who saw value in the classical models gave rise to the Neoclassical school of thought, which has updated and improved classical economic thinking to remedy some of the criticisms thrown at it). Economics was forever changed as a result of this new perspective, giving rise to many new models and theories and cementing Keynes’ place in the history books. <11an>limit:3;categories:Bachelor Programs, Master Programs;disciplines:Economics</11an> The life of Keynes Keynes was born in Cambridge, England, and remained there to study at King’s College in Cambridge. He received his degree in mathematics in 1905. There, he was influenced by the eminent economists Alfred Marshall and Arthur Cecil Pigou, whom he studied under. Keynes bounced around between academic and government employment during his adult life. In 1908, he became a lecturer at King’s College. He left to work for the British government in the India Office, which was tasked with overseeing British rule in India. Here he wrote his first major book, Indian Currency and Finance, in 1913. Later, he returned to the university to teach again until 1915. Keynes left university employment again to work for the British Treasury, where he was the chief representative during the peace talks that led to the Treaty of Versailles, which was signed in 1919. However, Keynes left the Treasury soon after, as he thought the Treaty was unnecessarily burdensome to the Germans. In fact, Keynes wrote his work The Economic Consequences of the Peace to state this, correctly predicting that the punitive measures levied by the Treaty would keep Germany poor and politically unstable. Famously, that political instability allowed the Nazis to rise to power less than twenty years later. Keynes returned to Cambridge as a professor after his career with the Treasury. Later, he contributed to both the Bretton Woods conference that helped to devise post-World War II international trade regulations, and the formation of the International Monetary Fund (IMF) at the same conference. Keynes passed away in 1946, just a few years after the Bretton Woods agreement. Keynes’ contributions to economics When the Great Depression hit in the 1930s, then-contemporary economic theory could not explain why the Depression was so severe. Classical economic models tend to explain how the economy self-corrects over time, and classical economists believed the market would self-correct and government intervention would do nothing at best. Yet, with the Depression, the economy continued to stagnate with massive unemployment and a lack of self-correcting market behavior that these models could not explain. Keynes’ initial theories were an attempt to explain the times. Beyond the issue of describing the Great Depression, he did not see a way for classical economic theory to explain how economies can come out of recessions. So, he reassessed and started to develop theories of economics that could account for the Depression, and that showed how governments could help their economies to recover. This new reasoning was readily accepted by political figures at the time, who embraced government spending as a policy tool. U.S. President Franklin D. Roosevelt’s “New Deal” policies, which involved much government spending as a way to spur the economy out of the Great Depression, were urged on by Keynes himself in a letter he wrote to the American president in 1933. In this line of reasoning, and with his works Tract on Monetary Reform and Treatise on Money, Keynes contributed to the theory of monetary policy. He believed that a stable economy required stable interest rates, so advocated for the central bank to adjust the interest rate based on the price level. If the price level rose, Keynes thought the central bank should lower the interest rate, and vice-versa. The basic idea behind this thinking is that as the interest rate rises, borrowing becomes more expensive, so individuals and businesses will consume less; this can counter inflation. But, it was Keynes’ work The General Theory of Employment, Interest and Money that revolutionized economics more than any of his other works. This book introduced many foundational concepts that have become important theories and given rise to much more economic thinking since. For example, the concept of aggregate demand – the principle that the overall demand in an economy is the sum of consumer demand, government spending, and investment – was created and popularized by this book. He also showed that unemployment was probably impossible to prevent without sufficient government spending, which later gave rise to the idea of a natural rate of unemployment. This was in direct opposition to classical economic models, which again assumed that the market would achieve full employment on its own via self-correcting behavior. Keynes’ The General Theory also advocated for government spending to stimulate the economy during economic downturns, to lessen the impact of the recession. Notably, Keynes argued that it would even be a good thing for governments to take on debt to do so, in an era where balancing the government budget was seen as crucially important. Despite this, Keynes was a proponent of a free, perfectly competitive market, believing in Adam Smith’s idea of the invisible hand. Keynes’ legacy Of course, Keynes’ ideas were eventually built upon and critiqued, for example that his models cannot account for sticky wages or prices, and that they would overstate the usefulness of government spending as that encourages crowding out. As a result, Keynesian economics has changed greatly since the titular economist introduced the ideas. In particular, Keynesian ideas have been expanded upon by economists such as John Hicks, Robert Solow, Paul Samuelson, and others - producing much of modern economic thought in the process. Through their work and that of still more economists, the New Keynesian field has emerged with models that can account for some of the criticisms levied at Keynes’ original work. Yet the revolution that Keynes started has retained his name, and rightfully so. References https://www.econlib.org/library/Enc/bios/Keynes.html https://www.britannica.com/biography/John-Maynard-Keynes Header image credit: IMF, Public domain, via Wikimedia Commons.
Students often learn about important figures in economics only briefly and in passing, yet the content taught in economics courses often comes from brilliant economists such as these.
Public Economics & Economic Policy (JEL H)
So, how do you find the exchange program that’s the right fit for you? It can be a tough decision and one you should deliberate properly, so read on for INOMICS' best tips to help you find the ideal exchange program tailor-made for you. <11an>limit:3;categories:Bachelor's Programs;disciplines:Economics</11an> Location, Location, Location One of the biggest issues to consider when thinking about an exchange program is – obviously – where you would like to stay. You should consider not only the country that you would like to visit, but also the specific city or region (and even different regions of your home country). Are you a fan of big, bustling cities? Or would you prefer a small town or somewhere in the countryside? Would you like to be in a cosmopolitan place, surrounded by people from all over the world, or would you prefer to be somewhere more homogeneous with a strong shared culture? The area around your university of choice will greatly affect your experience studying there, so be sure you research the region to know what you’re getting yourself into. Naturally, you need to think about language as well. You probably won’t have time to learn a whole new foreign language before your planned semester exchange – unless, of course, you plan it far enough in advance to take language courses one or two years before. This could be a fantastic way for you to solidify those skills and help you get the most out of your degree. But keep in mind that foreign universities may not only offer classes in the local language. For instance, you might be able to study entirely in English during a semester exchange while abroad in France, Brazil, or many other countries. Be sure to explore the options that you have with your current language skills even in other countries – you might be pleasantly surprised with the options. Naturally, if language remains a concern for you, it’s worth considering an exchange program that takes place in a country with the same mother tongue, or even within your home country. The National Student Exchange program in North America, for example, offers study away programs within the United States and Canada, potentially allowing you the benefits of a different perspective on your studies but without the cultural and linguistic challenges of living in another country. When and how long to go? The next big issue to consider is the length of time that you would like to spend on exchange. Short-term programs tend to run for a few weeks to three months, often over the summer break. They allow you to have the experiences of studying abroad (or just farther away from home), without interrupting or changing the schedule of your regular learning. These programs rarely include a full course-load compared to a normal semester, instead focusing intensively on a smaller handful of classes. However, don't assume that such a short-term program will be easy, or not require any work! Often short-term programs are the most study intensive, as all the materials must be compressed into a smaller number of hours. Although it may be less intimidating given the shorter time you will spend away, a short term trip can also have its drawbacks. Inevitably, you have less time to settle in, and often just as you feel like you’ve gotten used to the new setting, the trip is done and you are sent back off home. And, a short-term trip is less likely to be as much of a cornerstone of your life experience as a longer trip could be. A long-term exchange, on the other hand, typically lasts for six months to a year or more, and may include teaching from a local university which forms a part of your degree back at your home institution. So, with sufficient planning you won’t increase your overall semester count. This means that you get the true local's experience of attending university in your host country, and gain a different perspective on your subject. Such a longer term exchange can help you more fully experience a new part of your country or a foreign culture. It can allow you to develop new language skills, study your field under the guidance of experts with a different perspective, or with different strengths than the faculty at your home institution, and help you to network with colleagues from around the world. And, a longer term exchange abroad allows you to immerse yourself fully in a new culture and experience what studying abroad is like, while getting support on topics like visas and finding housing from your home institution. But longer exchanges come with their own drawbacks as well. A year can be a long time for an undergraduate student in particular to miss out socially at their home university – possibly some of the most formative years of your adult life. Not to mention the family, friends and traditions that might be left behind for a time. Plus, studying on exchange for a long time can put strain on your path to graduation if you aren’t careful, even if it’s at a university that partners with your home university, for example if you need to catch up on exams or coursework when you return. Degree Planning Exchange programs are usually not a core part of the degree experience you originally signed up for. They are typically not considered when university officials design curricula and schedule classes. Thus, it pays to be careful academically when considering an exchange program. When choosing a program, it might be exciting to jet off to the fanciest destination available. But, you must be aware of how the credits will transfer and what it will mean for the remainder of your degree. Exchange programs probably offer a limited selection of courses that your home university will accept as part of your degree program, and they might have prerequisites. Ensure you qualify for the courses you intend to take while on exchange. The last thing you want is for your exchange program to prevent you from graduating on time! Further, particularly when studying abroad, the course content in classes with the exact same name likely differs. To ensure you don’t miss any foundational topics, you should study the syllabi from your home institution’s course and your options on the exchange program to compare. Are there any major topics covered at one university, but not the other? Are there any topics missing from the exchange program? Checking the syllabi can ensure that you don’t accidentally put yourself behind your colleagues at home. There’s a chance that you could be the first person from your home university to take a specific class at your host institution while on exchange. Or, if you might even be the first person to go on exchange to that particular university in general. In both of these cases, you’ll need to work closely with administrative officials – and possibly class professors – from each institution. Be prepared to proactively ask questions about course content, fill out required forms, and argue the case for the new course credits you’d like to have transferred. Talk to other students who have done it before One important resource that’s easy to forget is those who have come before you: former exchange students! Universities will sometimes maintain a list of students who have studied abroad or done exchange programs at specific universities before, or organize an open-day or presentation where you can hear from study-abroad graduates. Alternatively, students who complete such a program can opt-in to such a list, and might be willing to talk to you about their experience. Don’t be afraid to ask around about students who have done the program before you – their advice will be invaluable. Funding Finally, it's important to consider how you will pay for the expenses of your exchange program. You will need to cover your travel expenses, insurance, accommodation costs, living costs, and in some cases university fees too. Generally, for short-term programs you will be expected to cover these costs yourself. Long-term programs, however, often have scholarships available which will cover these expenses. Be sure to check out the details of your program for specifics, as those programs which include scholarship funding often have lengthy application processes. Find out about them early to give yourself the best possible chance of securing one. An exchange program can be an important, unique, and awesome part of your university studies. We hope this article has helped you be inspired to discover which program is right for you. Header Image Credit: Hircus on Shutterstock (licensed image - copyright)
Exchange programs allow students to study at a different institution as part of their degree. Typically, students will use this opportunity to study abroad at a foreign partner of their home institution, though exchange programs can sometimes take place in the same country. Regardless, these programs are a fantastic way for students to broaden their horizons, take specific courses at another institution, and study abroad without committing to living multiple years in another country.
The INOMICS Questionnaire: Fratzscher vs Wursten
Jesse Wursten is a postdoctoral researcher at the Faculty of Economics and Business at KU Leuven in Belgium, and is funded by the Flemish Science Foundation (FWO); he is additionally affiliated with CWED-IRLE and UC Berkeley. Dr. Wursten’s main research focus is on applied labor economics. Other research interests of his include innovation economics and monetary policy. MF: What is your favorite place on earth? Jesse Wursten: Home. MF: Outside of economics, what occupation would you choose if you could be absolutely anything? JW: IT Entrepreneur. There's something exciting about owning your own business that is hard to match in a classic employer-employee relation. In a way, it is the ultimate sign that what you do is relevant to other people, otherwise you wouldn't have any customers. IT has the advantage of having relatively modest entry barriers, as you generally don't need expensive equipment or large teams to get to a first product (you could make a bad mobile app in a day so to speak, which is unheard of for physical products). I also feel like it’s an industry where I have the right skills to succeed: once you've identified a gap in the market, you need to figure out a technical solution (programming), but also interface that solution with the customer, especially if the solution is to show data of some sort. This is exactly what you do during an empirical economics PhD: you gather data and develop code to address an issue and then need to explain your solution as clearly as possible in a paper. So many apps fail at the customer interface aspect. For example, the app of an extremely popular brand of sports electronics produces post-workout graphs that are absolutely useless because a single outlier completely squashes all other data, or because the scales are not multiples of 5 (try interpolating between 13 and 20 on a smartphone screen). MF: What is the virtue you appreciate the most? JW: Honesty. MF: Your all-time favorite figure in economics? JW: Keynes. MF: Your ideal student? JW: Interested in the material, takes time to think things through beyond the obvious. MF: What should be done to address gender bias in research in economics? JW: I think there are two elements that make life especially hard for female researchers. One person (the supervisor) holds tremendous power over doctoral students. As long as this remains true, sexual harassment will remain problematic in the profession as victims are extremely disincentivized to speak up as it could literally end their career (need those recommendation letters). One option would be to require each student to have at least one co-supervisor, who is not necessarily actively involved in the research project, but is always available for meetings and questions and can become a second source of recommendation letters, funding, ... if issues arise with the main supervisor. The profession is horrible for anyone looking to start a family and have reasonable working hours. This also affects men of course, but they tend to realize that later in life (based on purely anecdotal evidence). Women are also still looked at first when it comes to taking care of children (although it seems to be changing, especially in higher educated circles). As long as making a career in econ requires moving thousands of miles and thus completely upending any local networks you may have, the profession is a nightmare for family oriented people. Men can sometimes choose to have kids later in life (= when they are tenured), women do not have that freedom. Likewise, combining research, teaching and admin with a healthy family life is almost impossible in most places. As long as the community as a whole considers 40+ hour/week workers as motivated rather than toxic, this will remain a problem. I say toxic because careers in econ are close to a zero sum game. If too many people raise the (working hours) bar, this puts pressure on all others. MF: What is the most promising current research field or issue in economics? JW: I'm biased as a labor economist, but I think one of the biggest questions of the coming decades is how we should structure our labor markets to maximize both efficiency and social welfare. The pandemic has shown that the demise of low-education jobs is not inevitable and the retirement boom catastrophe is still approaching without any sign of delay. What can be done to ensure that those who want to work, can do so, regardless of background and capabilities? How much should they earn for that work? Etc. MF: Where does economic research have the most influence on policy-making? JW: Monetary policy is extremely research-based, probably because it is the domain of technocrats rather than politics. I also believe policy is mostly affected by "simple" high-level theory, often so simple we take it for granted. Empirical evidence can then inform the details, especially for theoretically ambiguous situations (e.g. how high should minimum wages be?). I am not convinced that complicated models or overconfident empirical analyses contribute much to how we organize the world, though the former might still serve intermediate purposes within the academic community. MF: On what issues should policy listen more to economists? JW: Anything that involves potential externalities or second order effects. Economics offer simple yet potent frameworks to think about those situations, but these rarely seem to reach policymakers. The response to the gas crisis in Europe is a clear example. There are options there that bolster the purchasing power of the poor, reduce carbon emissions and prevent subsidies flowing into Russian coffers. Yet most countries went for simple but misguided policies that at best achieve the first and fail horribly at the latter two. MF: What is your career advice to a young economics researcher? JW: Keep an open mind about career opportunities. A recent statistic showed that less than 10%* of PhD students stay in academia, yet everyone considers this the norm. Instead, use the PhD to identify your skills and interests and do not be afraid to pivot towards alternative careers if research and teaching turn out not to be your comparative advantage. *The statistic came from our research support office, showing the share of FWO (the #1 science funder in Flanders) grantees that are still in academia a few years later. Images provided, with kind permission.
Professor Marcel Fratzscher, esteemed macroeconomist and president of the DIW Berlin, once again asks questions about economics and life in general to a peer in the field. This time, he has the pleasure of being joined by postdoctoral researcher Dr. Jesse Wursten, who generously agreed to take the hot seat in this exchange. Thus, the back-and-forth has been dubbed Fratzscher vs. Wursten, as is tradition. What follows is a conversation that offers insight into some of the challenges of balancing family with an economics career, the usefulness of economists when it comes to analyzing policy externalities, and more.
Club goods in economics are a type of good that is excludable, but non-rivalrous. This means that although using a club good doesn’t prevent others from enjoying it, and doesn’t reduce the amount available for others, it is possible to stop people from using the good in the first place. For this reason, club goods might occasionally be referred to as non-rival private goods. A classic example of a club good is membership in an exclusive organization such as a golf club or a gym. In this case, purchasing a membership doesn’t reduce the amount of memberships available for others, nor does using your membership reduce others’ ability to use their memberships. Astute students will notice that more specific parts of the club – for example, the golf course or specific gym equipment – might suffer if too many members try to use it at the same time, since the amount of space is limited. This problem is sometimes referred to as a congestion problem, since realistically there cannot be infinite users of the membership space. However, there could theoretically be infinite members, as the membership itself is not made more scarce when people sign up. So, economists would still classify a gym or golf club membership (and similar types of goods) as club goods. Another example of a club good that doesn’t suffer a congestion problem is a streaming service subscription. When you subscribe to a streaming service, you pay for access to a number of movies, TV shows, etc. Before you can access these goods, you must pay for the service, making the subscription excludable. Utilizing the service does not cause anyone else to enjoy the movies or shows on it less, nor does it cause fewer movies to be available to others, so the streaming service is also non-rival. Finally, using the service doesn’t crowd other people out of enjoying the movie as with a piece of gym equipment, so in this case this club good does not suffer a congestion problem. Good to Know Club goods that are deemed necessary for society are often provided via regulated natural monopolies. For example, electric utilities provide a very important service since power is necessary for many of the modern luxuries in our economies. But, high setup costs and relatively low costs of undercutting potential new entrants means it’s likely that a natural monopoly will form in the market. For example, setting up a power generator and electrical infrastructure to move that power into businesses and homes takes a lot of investment. And, once such a system is in place, it’s quite difficult for a new entrant to drum up enough initial investment to compete with the incumbent firm. This creates a natural monopoly situation where the incumbent firm can charge high prices, crowding out some end users of electricity. But, adding new users onto an existing electrical grid is relatively easy and cheap compared to making new electrical infrastructure, so the company can easily grow. These market characteristics – high start-up costs before any product or service can be sold, but relatively low cost of adding new users – tend to allow club goods to thrive. Unfortunately, monopolies (and in this case, even a perfectly competitive market) would under-provide electricity. In this type of situation, usually the government will step in to ensure incentives are properly aligned so that electricity is provided to everyone – typically involving the creation of a subsidy.
There are many different ways that economists classify the different types of goods and services sold in the economy. The characteristics of goods – for instance, whether they are rivalrous or excludable – help economists classify goods into one of four categories. These are club goods, private goods, public goods, and common resources.
In the traditional ultimatum game experiment, two players are randomly and anonymously matched. One person, the proposer, receives a fixed amount of money and must offer a suggested split of this money with another person, the responder. The responder must accept or reject the offer as it is presented. They are told they will play the game exactly one time. For example, assume Player 1, the proposer, receives $20 to split with Player 2, the responder. Figure 1 below illustrates the choices available to each player and payoff amounts associated with each choice. Player 1 may choose an even split, giving $10 to each person, or an uneven split, such as keeping $18 and offering $2. Player 2 may either accept or reject this offer. If Player 1 offers an even split, and Player 2 accepts it, both receive $10. If Player 1 offers an uneven split that Player 2 accepts, then Player 1 gets $18 and Player 2 gets $2. If Player 2 rejects the offer, both players receive $0. Figure 1: Illustration of payoffs in an Ultimatum Game Traditional economic theory suggests people are rational, self-interested, and seek to maximize their utility. In theory, proposers would offer the least amount of money they believe a responder would accept, while responders would accept any amount of money offered because a few dollars is better than nothing. The results from ultimatum game experiments used in a variety of real-life settings, however, suggest the potential for responders to reject an “unfair” offer encourages proposers to propose more even splits of the money. The degree of familiarity, or social distance, between two people may also affect their choices. When players come from a shared social group (e.g., a village or a class in school), offers tend to be more “fair” or evenly split. Additionally, responders often reject offers of 20% or less even though they experience a financial cost from this choice (Camerer, 2003; Oosterbeek, Sloof, and Van de Kuilen, 2003). These results challenge the expectation that traditional economic theory would give us, as discussed above. The results do this by suggesting that receivers gain some value in signaling that unfair offers are unacceptable, and proposers likely account for the probability that an unfair offer is rejected when making their proposal. Further Reading Hoffman et al. (1996) examined ultimatum game behavior when participant roles were determined by a contest. Before participating in the experiment, subjects took a current events quiz, and their scores were ranked. Higher scoring individuals became proposers who were matched with a lower-scoring responder. Results revealed proposers offered substantially less when they felt their roles were justified and legitimate compared to when roles were assigned randomly. Additionally, responders tended to accept lower offers when they were splitting $10. When the amount of money to split was $100, however, rejection rates for lower offers increased significantly. The authors concluded responders were willing to accept the proposer’s role as justifiable when the stakes are low, but they became less willing to accept the proposers earned their roles legitimately as the stakes increased. Good to Know A modified version of the ultimatum game is the Dictator Game. In this experimental setting, one person (the dictator) receives an endowment and must decide how much of it to offer to an anonymous, random recipient. Unlike in the ultimatum game, however, the recipient must accept the amount offered and has no ability to punish the dictator if the offer is unacceptable. Traditional economic theory suggests players acting as dictators would make offers of $0 since there are no consequences. But, real-life experimental results suggest when the players are unknown to each other, dictators’ offers are lower. As with the findings from ultimatum game experiments, when there is less social distance between participants, dictators often allocate some money to the recipients, reducing the amount for themselves. This tendency to offer a non-zero share of the endowment indicates people may consider not only self-interest, but also ideas of fairness and altruism in their decision-making, especially in organizations. Less social distance between organizational members may encourage more prosocial behavior, improving the welfare of the organization and organizational outcomes. Research on dictator game experiments suggests information about the recipient may affect how much a dictator offers, too. Brañas-Garza (2006) examined dictator behavior in three different information conditions. First, when dictators received no information about recipients, 71% of dictators donated nothing. The average donation was 10% of the endowment. Second, when dictators were informed recipients were poor and from underdeveloped countries where this money could be useful, 46% of dictators donated the full endowment and 22% donated nothing. Third, when dictators were told the recipients were poor and that donations would be in medicines rather than money, 72% of dictators donated the full amount, and the average donation was 65% of the endowment. The authors concluded that knowing recipients were poor encouraged more altruistic behavior from the dictators.
The ultimatum game is a variation of game theory that has become popular in the field of experimental economics. The game involves players making sequential moves in a simple take-it-or-leave-it bargaining environment.
Econometrics, Statistics and Quantitative Methods (JEL C)
Assessing Cryptocurrency's Potential to Overthrow the U.S. Dollar's Dominance in the Financial System
While it’s true that the United States wields considerable influence over the global financial system because it controls the dollar, it is not the sole determinant of the system’s direction and functioning. Other major economies, such as China, the European Union, and Japan, also play significant roles in shaping the global economic landscape. Additionally, international organizations like the International Monetary Fund (IMF) and the World Bank exert influence through their policies and lending practices. Central banks, such as the Federal Reserve in the United States and the European Central Bank in the Eurozone, have a pivotal role in the global financial system as well. They are responsible for managing monetary policy, regulating financial institutions, and maintaining financial stability. Central banks exert influence over the global economy indirectly through their control of domestic interest rates, the money supply, and exchange rates. Their decisions have far-reaching implications for inflation, employment, and economic growth. On a national scale, banks are also a key source of credit for households, businesses, and governments, and their lending activities have a crucial impact on the health of the economy. In fact, investment banking and investment firms alone make up a significant portion of the current financial system. These institutions not only provide access to capital, but they also play a key role in managing risk, influencing corporate governance, and contributing to market liquidity. Challenges and Limitations of the Current Financial System While the current financial system has served the global economy in roughly the same form since the 1950s, it is not without its challenges and limitations. One of the main criticisms is its vulnerability to financial crises and economic downturns. The global financial crisis of 2008, for example, exposed many of the weaknesses and risks inherent in the system. The interconnectedness of financial institutions, the lack of transparency, and the excessive risk-taking by banks (see moral hazard) were all factors that contributed to the crisis. Such interconnectedness means that shocks in one part of the world can quickly spread and impact the entire system. Additionally, the current system is often criticized for its lack of inclusivity and its unequal distribution of wealth. Many argue that the benefits of economic growth are not shared equitably, leading to social and economic disparities. The concentration of power in a few dominant currencies, like the U.S. dollar, can create imbalances and inequalities in the global economy. This creates a situation where countries and businesses that do not use those currencies (or peg their own currencies to the dollar) are at a disadvantage. First, if a significant portion of global trade and investment is conducted in a few dominant currencies, it can be challenging for smaller currencies to compete. This can make it harder for businesses and countries that use less ubiquitous currencies to access global markets, leading to economic disparities – especially if it’s difficult for these businesses and countries to buy the dominant currencies at affordable rates. Second, dominant currencies can create an uneven playing field in terms of access to credit and financing. Countries and businesses that have better access to the dominant currencies may be able to borrow money at lower interest rates, while those that do not may face higher borrowing costs. This can make it harder for smaller and less developed economies to access financing, exacerbating economic inequalities. Third, dominant currencies can influence global economic policies and standards. Countries that use the dominant currencies may have more influence over global institutions and policy decisions, while those that do not may have less of a voice. This can lead to asymmetric power dynamics and policy decisions that favor the dominant currencies and those that use them. The Use of Cryptocurrency as an Alternative to Traditional Currencies In recent years, cryptocurrencies have emerged as a potential alternative, providing a way to trade without using traditional currencies. Built on decentralized blockchain technology, cryptocurrencies offer the promise of secure, transparent, and efficient transactions without the need for financial intermediaries. Bitcoin, the first and most well-known cryptocurrency, paved the way for a wave of digital currencies that have gained traction among investors and consumers alike. Other commonly known cryptocurrencies include Ethereum, Tether, BNB, and XRP. New cryptocurrencies appear often, though few become popular enough to become household names. Cryptocurrencies are not controlled by any central authority, making them resistant to government interference and manipulation. They have been touted by many as a potential threat to the dominance of the US dollar in the global economy. One of the main ways that cryptocurrencies could challenge the dominance of the dollar is by reducing the reliance of other countries on the US financial system. Because the US dollar is currently the dominant global currency, many countries hold significant amounts of dollars in their foreign exchange reserves and conduct the majority of their international trade in that currency. This makes them vulnerable to fluctuations in the value of the dollar and to political pressures from the US government. Cryptocurrencies provide an alternative to the dollar – and to foreign exchange in general – that is not subject to the same political and regulatory pressures. This is because cryptocurrencies are decentralized, meaning that they are less vulnerable to political interference, such as government manipulation of interest rates or currency controls. By using cryptocurrencies for international trade and investment, countries can reduce their dependence on the US financial system and potentially increase their economic independence. Another way that cryptocurrencies could challenge the dominance of the US dollar is by providing a more efficient and cost-effective means of conducting cross-border transactions. Traditional cross-border transactions can be slow and expensive, with fees and exchange rates adding significant costs to the transaction. Cryptocurrencies, on the other hand, can facilitate instant, low-cost cross-border transactions, potentially making them a more attractive option for international trade and investment. Other advantages that make them appealing for global trade include: Global Accessibility: Cryptocurrencies can be accessed by anyone with an internet connection, regardless of their location. This enables cross-border transactions without the need for traditional banking infrastructure, making it easier for businesses in different countries to engage in trade. Security: Cryptocurrencies use advanced cryptographic techniques to secure transactions and protect against fraud. The use of blockchain technology ensures transparency and immutability, making it difficult to tamper with transaction records. This enhances trust and reduces the risk of fraud or counterfeiting. Faster Transactions: Traditional cross-border transactions can be time-consuming, involving multiple intermediaries and requiring several days for settlement. Cryptocurrency transactions, on the other hand, can be completed within minutes or even seconds, enabling faster trade and reducing delays. Lower Transaction Costs: Traditional financial institutions often charge high fees for cross-border transactions, which can be a barrier to global trade for small businesses. Cryptocurrencies eliminate the need for intermediaries, resulting in significantly lower transaction costs. Reduced impact of politically-motivated trade barriers: Cryptocurrencies can reduce the impact of political tensions between countries on trade and investment. For example, if two countries are facing a trade dispute but their populations use a common cryptocurrency, it could potentially make trade and investment between those countries less vulnerable to political tensions and costly trade barriers. Financial Inclusion: Cryptocurrencies have the potential to provide financial services to the unbanked population, which is estimated to be around 1.7 billion people globally. By bypassing traditional banking systems, cryptocurrencies can enable individuals and businesses in underserved regions to participate in global trade. This has the additional benefit of providing a means for people to participate in the financial system, even in times of political upheaval. Smart Contracts: Some cryptocurrencies, like Ethereum, support smart contracts. These self-executing contracts automatically enforce the terms and conditions of an agreement, eliminating the need for intermediaries and reducing the risk of fraud. Smart contracts have the potential to streamline complex international trade processes, such as supply chain management and customs clearance. Potential refuge from inflation: Cryptocurrencies can provide a hedge against inflation and currency devaluation. Some cryptocurrencies, such as Bitcoin, have a fixed supply, which means that they cannot be devalued through inflationary monetary policies. If the crypto market’s volatility can be reduced, this can provide a level of stability and predictability to the economy that is not always possible with traditional currencies. Challenges facing the adoption of cryptocurrencies Overall, cryptocurrencies offer a range of advantages that can revolutionize global trade by increasing efficiency, reducing costs, and improving accessibility. However, they still face significant hurdles before they can seriously augment or even replace traditional currencies. One of the main challenges is the volatility of cryptocurrencies. The value of cryptocurrencies can fluctuate wildly, which makes them a risky investment and can make it difficult to use them as a stable store of value. There are also concerns about the potential for fraud, money laundering, and illicit activities to be facilitated by the anonymous transactions that cryptocurrency allows for. Regulatory authorities around the world are grappling with how to strike the right balance between fostering innovation and protecting consumers and investors. Another of the main challenges is the current lack of widespread adoption and acceptance. While some businesses and individuals have embraced cryptocurrencies, many others remain skeptical and prefer to stick with traditional forms of payment. Unless cryptocurrencies are accepted as a form of payment in more day-to-day transactions, this problem is likely to remain. Another risk is that the lack of a regulating authority leaves the cryptocurrency market open to more market manipulation than would otherwise be possible. This is also a contributing factor to the market volatility of cryptocurrency. This includes familiar stock market schemes such as the “pump and dump”. Other schemes include “spoofing” which involves a market manipulator placing a large order to influence other traders while intending to cancel the order. Wash trading is another tactic where small groups of investors trade crypto back and forth to simulate a high trading volume, although “real” trades are not taking place. Policy Responses and Recommendations The key to the success of utilizing cryptocurrencies as a more widespread means of exchange lies in striking the right balance between innovation and regulation. As technology advances and cryptocurrencies become more mainstream, their impact on the financial system will become increasingly significant. To best take advantage of the potential upsides of cryptocurrencies, policymakers should consider implementing the following practices: Regulatory Frameworks: Establish comprehensive regulatory frameworks to govern the use and trading of cryptocurrencies. These frameworks should address risks such as market manipulation, fraud, and money laundering while providing clarity and protection for investors and users. It’s worth noting that these frameworks would exist to provide safety and stability to crypto users – they would not give politicians control over crypto itself in the same way that governments and central banks manage most currencies today. International Cooperation: Foster international cooperation among financial governing bodies to harmonize regulations and ensure consistent approaches to cryptocurrency oversight. Collaboration can help mitigate cross-border risks and promote global financial stability. Risk Assessment: Conduct thorough risk assessments of cryptocurrencies to identify potential systemic risks and develop appropriate mitigation strategies. These assessments should consider factors such as price volatility, market manipulation, and the potential for financial contagion (the spread of financial distress from one institution, market, region, to others, often resulting in a systemic crisis). Education and Awareness: Promote education and awareness programs to enhance public understanding of cryptocurrencies. This can help minimize misinformation and ensure informed decision-making among users and investors. Conclusion: Assessing the Potential Impact of Cryptocurrency on the Global Financial System If cryptocurrencies were to gain widespread adoption, it would have profound implications for the global banking system. Banks, as intermediaries in the current financial system, would need to adapt to the rise of digital currencies. They would have to develop new business models and explore ways to integrate cryptocurrencies into their existing infrastructure. Additionally, central banks would need to redefine their role in a world where traditional currencies are no longer the primary means of exchange if digital currencies overtook traditional ones in popularity. As the global financial system continues to evolve, the role of cryptocurrency is likely to become more prominent. And this rise presents both opportunities and challenges for the global financial system. While it is unlikely that cryptocurrencies will completely overthrow the U.S. dollar's dominance in the near future, they have the potential to complement traditional currencies and offer an alternative means of exchange. The key in utilizing them lies in addressing the concerns and limitations associated with cryptocurrencies while harnessing their potential benefits. Header image credit: fabrikasimf on Freepik / Magnific (free license)
For decades, the U.S. dollar has reigned supreme as the world's primary reserve currency. Its dominance can be attributed to several factors, including the size and stability of the U.S. economy, the political influence of the United States, and the widespread acceptance of the dollar in international trade and finance. The dollar's status as the de facto global currency has significant implications for the functioning of the global financial system.
Macroeconomics and Monetary Economics (JEL E)
A primer on how popular AI models work and their current limitations
As AI continues to feature prominently in the news cycle, there’s bound to be speculation about the future. Indeed, AI’s potential to disrupt the labor market has been perhaps the biggest subject of discussion. But often, these conversations are had by people who haven’t studied the actual workings of these new AI tools. In many news articles or public discussions, the actual capabilities of current AI tools can be poorly defined or understood, particularly the capabilities of large language models (LLMs) as ChatGPT has nearly become a household name. Therefore, it’s worth spending time to learn how current LLMs work, so that we will all have a better understanding of how LLMs might realistically shape the economy as these conversations continually arise. This article will therefore focus on LLMs, though there are other types of AI still being researched and developed. <11an>limit:3;categories:Conferences</11an> How do these LLMs work? ChatGPT, and many models like it – such as Google’s Bard (or LaMDA), Microsoft’s Bing AI, and a host of others – is a large language model (LLM). LLMs are algorithms that generate text based on training data that is given to the model during development. These models are usually made up of a neural network – a software structure modeled after the way human neurons function. Specifically, these models make use of transformer architecture, a specific type of neural network developed by data scientists interested in deep learning. These models can respond to questions that humans ask them, and generate (usually) accurate responses. They “learn” when people provide feedback, helping the model to re-weight certain responses if they were incorrect. The core process at work for all these activities is an algorithm that aims to accurately predict the most likely word that comes next. When queried, the model builds a response by using probabilities to determine those most likely next words. It will do this repeatedly until the response is finished. Once a response is finished, certain parameters can be changed by the professionals training the model to make it respond differently (i.e. more accurately) to the same queries. Over time, this training process results in the development of a complete and powerful model like ChatGPT-4 that has been trained with massive amounts of data (specifically 45 gigabytes, whereas GPT-3 was trained with "just" 17 gigabytes of data), and can answer many prompts in a useful way. Training data partially defines the usefulness and limitations of AI models Naturally then, training data is incredibly important for the development of AI models based on LLMs. That’s because the specific training data used is influential in determining what responses the model will produce. This has a few key implications for the limitations of these tools. First, human knowledge and expertise is required in order to build a useful LLM. People can speculate if AI tools will eventually be able to replace human workers – like replacing doctors’ diagnoses, for instance. But in order to create such an expert LLM, a large amount of medical information and knowledge (in this case) is needed. At least for now, this information must be compiled by humans. And, it pays to have subject-matter experts (such as medical doctors) test the output of any model to ensure it’s accurate. This suggests that there may be net-new jobs for subject matter experts to assist with the development of subject-specific AI tools. Another consequence of the importance of training data is that biases and prejudices can become internalized by AI models if not dealt with. LLMs don’t exhibit critical thinking skills in the way humans do (at least for now). This means that a new LLM will “learn” any bias, prejudice, or myth as fact if those biases are present in their training data. Clearly, this can produce incorrect or unfavorable results as the models are deployed, if the biases are not detected beforehand. This is another reason why carefully cultivated training data is valuable. The fact that useful training data is required to build a good LLM tool means that the intentional selection and maintenance of high-quality, relevant training data – and the ability to minimize any biases the tool might learn from that data – will become a critical need in the economy. This can create an important new role for human experts in various fields. And, certain companies might specialize in providing subject-matter specific training data for AI models that others can purchase or subscribe to. Will we ever develop an AI that’s as smart as we are? One common mistake that people make about AI models, in particular LLMs, at the moment is attributing too much independent intelligence to the tools. It’s easy to think that an AI model is a thinking being or individual without understanding how the model works, especially given people’s penchant for personifying things. However, no type of AI has yet reached the point where it can be considered an independently intelligent, thinking entity. AI experts have coined the term “artificial general intelligence” for such a theoretical entity, as opposed to “narrow” intelligence that is good at a specific task, like controlling a car, giving media recommendations based on a user profile, or responding to questions in a human-like way. If and when a more “general intelligence” AI does exist, it would theoretically be able to grow, evolve, and adapt to new functions beyond its basic structure. It would be able to “think” and learn, self-critically improve its own functioning, reason similar to how humans do, and tackle any problem a human can. Expert opinions vary on the likelihood of such a model being possible, and when it would be developed if so. Interested readers can check out this article on the Conversation to read a few experts’ thoughts on the subject. Other limitations: hallucinations and calculators Especially given that AI models have not reached a human level of intelligence (yet), they will continue to have clear limitations in practice. LLMs in particular occasionally struggle to differentiate between fact and fiction. It’s quite possible to convince an LLM of something patently false, which will potentially derail its future text generation. Sometimes, LLMs can even invent fake sources or facts; this is known as “hallucination”. Hallucination can be difficult to spot if the user doesn’t have expertise in that field of knowledge. And, this can cause serious problems; imagine if an LLM-based AI tool gave a medical diagnosis that was not only incorrect, but completely fabricated! New users often attempt to use LLMs like ChatGPT as a kind of search engine, as well. It may appear that these models can instantly search the Internet to provide an answer to any question. But, the hallucination problem, and understanding how the underlying algorithm works, quickly reveals that “search” results in an LLM cannot be trusted. This is because the models don’t actually search the Internet (at least, most of them at the time this article was written; in the future, it’s likely that many models will have full up-to-date Internet access). They simply generate words repeatedly using probabilities based on the training data that was used to build them; it’s entirely possible, even likely, that a search question posed to an LLM will be incorrect or entirely hallucinated. Moreover, the models were trained on a now-out-of-date block of text taken from the Internet, so even if the model does produce a correct answer, any time-sensitive information will quickly become obsolete without continual updates. A related issue is that LLMs are (again, at least for now) bad at math, and cannot be used as calculators. This is often surprising to new users, but it makes perfect sense when considering the actual algorithm that composes models like ChatGPT. These models, again, predict the next most likely word. They don’t recognize math symbols as being uniquely different than any other word in our everyday language. As such, these models don’t actually compute any math; rather, they create strings of responses that have a high likelihood of being “correct”. When that comes to regular language, this is often fine, allowing LLMs to generate large blocks of coherent text. But when it comes to the very precise, rules-based language of mathematics, this is a major limitation for LLMs. However, other AI models have been developed (and will be increasingly refined) that are optimized for math (and coding, though LLMs are better at coding than math at this moment). It’s possible that LLMs become more reliable in these capacities in the future, too, but at the moment their responses shouldn’t be blindly trusted. Update: 16 December 2023: Researchers have just successfully solved an "unsolvable" math problem using AI. The article "Mathematical discoveries from program search with large language models", early access to which was published in Nature on 14th December 2023 (the final paper is not published as of this writing) details how a team of researchers using Google's DeepMind used two AI tools in tandem to find the solution. It's noteworthy that this process still presented some of the above limitations of large language models. In short, the LLM tool used by the research team proposed millions of suggestions, and upon evaluation of those answers, only the best responses were kept. Then the problem was started anew. Over the course of several days, this eventually led the algorithm and the research team to a correct answer to the unsolvable problem. This demonstrates two things: first, the hallucination problem is still present, as millions of responses had to be thrown out until the right one was reached. This also demonstrates the emergence property that transformer models sometimes display; in other words, a functionality that was not explicitly coded (solving an unsolvable math problem) was nevertheless a function the model could do. Clearly, AI tools will continue to evolve well beyond the original scope of this article. Their usage in everyday organizations have the potential to greatly increase economic efficiency, though naturally they pose a creative destruction risk to many industries as well. So, what can AI do right now? As of this writing, LLM AI models are very good at rote tasks and producing messages. It can be quite useful to have an LLM generate an email or similar message quickly. It’s relatively straightforward to get them to write in a specific style, or emphasize a certain tone, as well. But these tasks aren’t the only thing LLMs can do. They can be used to automate customer service, write software, contribute to research and development, perform sales operations, summarize large datasets quickly, “read” and quickly digest any given block of text, and more. This has the potential to shake up many industries, including software development, call centers and customer support, and more. AI tools have also notoriously been used to generate images and art with large degrees of success. These models usually aren’t just LLMs; they use LLMs to help with natural language processing, then other algorithms to help generate images from text. It’s true that the limitations discussed above have prevented LLMs from completing more impressive tasks on their own, like writing a best-selling novel (though many AI-generated “nonsense” books have flooded digital book lists lately), or publishing research. However, these tools have already greatly diminished the work required for such tasks in many cases. AI writing tool assistants have already become fairly advanced, although they aren’t quite producing works independently yet. For example, several research papers published this year have noted that ChatGPT was used to help write them (although prominent journals like Science have declared that ChatGPT cannot be an author). These tools can also help someone write a (non-“nonsense”) book in mere days, by generating the foundation of a story that generally just needs editing. This could drastically change the writing and publishing industries, or cause writers and editors to start competing with one another as LLM tools perform much of the actual writing. Regardless, it may only be a matter of time before the next Game of Thrones is written by an LLM. Emergence and the future of AI Regardless of the current deficiencies or limitations, it’s clear that AI tools are becoming a permanent fixture of the economy. They have a wide array of applications and use cases as aforementioned. And, if history is any indication, AI tools will only get better from here. The idea of an artificial general intelligence was already discussed, and while current AI models do not exhibit this type of ability, they do embody another phenomenon like it. Emergence in computer science can be defined as a model demonstrating new abilities that it was not explicitly trained to do. For example, in this article one researcher writes about how complex LLMs were able to correctly identify movies based on only a set of emojis. Often, we don’t quite understand how the underlying mechanism – in this case, the neural network’s probability-based word selection – produces the emergent abilities. If the concept of emergence seems odd, consider it from a biological perspective. Humans are made up of trillions of cells, each of which has a defined structure and a specific set of tasks within the body. Biologists and chemists have described with great detail how proteins, carbohydrates, lipids, and nucleic acids (the four basic building blocks of biology) operate within our bodies. We understand how substances can move across cell membranes, how blood carries oxygen, etc. But, it’s extremely difficult to describe how consciousness develops from the basic biological and chemical processes occurring in our bodies. In this way, consciousness can be thought of as an emergent property derived from the physical biochemistry of a human being. In a similar way, LLMs have demonstrated some capabilities that are hard to trace back to the underlying neural network. These emergent capabilities tend to appear in large models, but not smaller ones. Often, AI researchers describe a tipping point where a large enough model can suddenly perform new tasks that weren’t possible before. Emergence – and the fact that widely used, publicly-available LLMs are relatively recent – suggests that AI models will only continue to improve in the future. It’s likely that the current limitations of LLMs and other types of AI models will be minimized over time as we get better and better at training them, and as we discover increasingly efficient means of building AI models. Like much technological progress in the economy, time will likely be kind to the growth of AI. But, it still pays to be informed about how these models actually work, in order to have meaningful conversations about their impact on the future economy. Other references https://www.mlq.ai/what-is-a-large-language-model-llm/ Header image credit: rawpixel.com on Freepik / Magnific (free license).
Artificial intelligence tools are becoming more and more ubiquitous with each passing week. The development of ChatGPT-3.5 in particular launched conversations about the capabilities of AI into the mainstream. Since then, news stories and speculation about AI supplanting (and sometimes replacing) human workers continue to be released. The economics of AI is, as a result, becoming an important topic in our field.
The GRE is changing: ETS to streamline the test in September 2023
As such, many of the most educated people in the world have spent time studying the GRE and taking the test. There’s a plethora of resources to help students study the test’s structure and the materials likely to be on it while they prepare to get the highest score possible. Because of the GRE’s importance in graduate admissions, it’s beneficial for educators, university staff, and prospective graduate students to stay up-to-date with the exam. On that note, a new announcement from ETS – the company that owns and administers the GRE – came out on May 31, 2023 with details on new changes that are coming to the test. GRE being shortened to quicken scoring time and reduce test-taking fatigue ETS is making significant changes to reduce the length of the GRE. Specifically, their press release states that the GRE (which currently takes about 4 hours to complete) “will take less than 2 hours to complete — roughly half the time of the current test”. Notably, this will make it one of the shortest major tests available in university admissions, particularly at the graduate level. This is being done for a few reasons. First, ETS is aiming to “offer candidates a better experience that values their time and reduces anxiety and fatigue”. With stress and anxiety prevalent in our society, this is a welcome change. The second major reason for introducing a shorter test is to provide a faster turnaround on scoring. The new test will reduce scoring time from 10-15 days to 8-10 days. This change will additionally help students complete and submit their graduate applications more quickly. Adjustments to GRE structure to allow for these changes You might be wondering how this new goal will impact the test structure; after all, cutting the time to take the test in half must involve some sort of sacrifice. To that end, ETS has described the actual test structure changes on their website. It appears that they have aimed to “trim the fat” by reducing the size of certain portions and eliminating non-scored sections, without reducing the GRE’s usefulness as a gauge of a student’s academic preparedness. First, the number of questions in both the Quantitative and Verbal Reasoning sections are being reduced by 46 questions (specifics are not given, but this is 46 among both sections; for example, perhaps 23 questions from each section will be cut). Further, the Analyze an Argument task is being cut from the writing section, there will be only one essay instead of two, and the unscored section is being removed from the test entirely. Despite featuring fewer questions, the test still aims to provide graduate admissions offices with the results and tools they need to assess applicant’s cognitive skills. The test will continue to measure the same things it always has; the question types are not being changed, and neither are the test sections. They’re only being streamlined. A full, more detailed breakdown of the new test’s exact structure can be also found on the ETS website. Note for students planning to take the GRE The fact that the questions themselves are not changing – only the test structure – means that GRE prep being done now is still valid for the shorter test. So, if you’re a student preparing for the GRE, keep doing what you have been already and you’ll be in good shape. Registration for the new GRE is already open. To sign up, simply register for a test date after the change takes effect on September 22, 2023. More details can be found in their new FAQ document available for download. — We would like to thank ETS Global for their support in the production of this INOMICS article.
The Graduate Record Examinations, more commonly known as the GRE, is one of the most important standardized tests in the world for admission to post-Baccalaureate programs. It’s very often required by universities when considering admission into their Master’s or even PhD programs.
The Challenges Faced by Small Island Economies
Although visiting an island might not inspire most people to think about economics (except, of course, for our inquisitive readers!), after reading this overview you will likely notice these challenges – and the ways that different islands have mitigated them – when visiting one. We suggest you find yourself a good, cozy spot on the beach as you read on. Prelude: extending these challenges to other areas This article is focused on smaller islands – for instance, in the Pacific or Caribbean. Larger islands (such as Japan, the UK or New Zealand) or those that are part of a major land-based nation typically do not face as many of these challenges. Nevertheless, many of the challenges discussed in this article are also applicable to small countries on the mainland, too. In 1984 Benito Legarda wrote the article “Small island economies” for the IMF, still relevant today. It gives an overview of some of the challenges that apply to both islands and other small economic areas. Interested readers can refer to Legarda’s article for more context on not just small islands, but other small economic areas too. Without further ado, read on for the economic challenges faced by small island economies. Natural resources are scarce on most islands When people think of small island economies, they often think of two things – beaches and tourists. While it’s true that some natural resources (such as fish and beautiful natural sights) abound for many islands, the reality is that other important natural resources are generally hard to come by. Most islands simply do not have much land area. Thus, the bounty of natural resources available tends to be severely limited compared to countries on the major continents. Many of the resources that allow societies to thrive – such as mineral deposits, nearby forests, abundant wild animals, freshwater sources, etc. – are much less likely to form on small landmasses. Indeed, somewhat ironically, freshwater availability can be a major problem for many islands. Of course, there are small land-locked countries as well – such as Liechtenstein – that may face a similar challenge. But, two factors make this likely less severe than for an island of similar size. First, small landlocked countries can still trade with their neighbors far easier than an island typically can since land routes are available. Second, the fact that a small landlocked nation is located on a major continent means that there will likely be relatively more natural abundance, as the landmass it’s situated on is likely to have substantial natural resources. Meanwhile, a small island might have never had enough area to sustain (for example) a major forest. This lack of land also severely limits the inhabitants’ ability to raise livestock and grow crops, which in turn limits the size of the population that can be independently supported on an island. Cultivation is sometimes difficult on smaller islands, too, due to rocky soil or lack of suitable climate conditions. Of course, some volcanic islands do have nutrient-rich soil for plants to thrive, but land availability is still a concern. As an example, even Hawaii – a relatively large and well-established island in the United States – faces concerns about optimizing land use to increase food security. To this end, Hawaii’s Department of Business Economic Development & Tourism produced a report titled “Increased Food Security and Food Self-Sufficiency Strategy” in 2012 outlining a plan to reduce reliance on food imports, among other things. Clearly then, even well-connected islands aren’t immune to geographically-related economic growth challenges. The local economy is usually not diversified Because of their small size and the lack of abundant natural resources, many islands are forced to build their economies off of tourism and one or two primary export products, typically some type of tropical produce, fish, or a particular natural resource that may be in relatively high supply. This lack of diversity can cause the local economy to be very sensitive to the market for one or two goods. If most of an island’s trade involves just two major exports, any negative shock to the market for one of those goods can cause a serious downturn in economic activity on the island. A severe enough shock could lead to a state of recession. This is especially difficult given that islands typically rely on imports; a reduction in exports means that the island must reduce imports or take on debt. The effects of the initial economic shock can therefore affect the local economy more than it would have otherwise, reducing overall economic welfare. Meanwhile, a dependency on tourism – while it can bring significant revenue during certain seasons – has its own drawbacks. Overcrowding or overtourism can stress the natural resources present on an island, particularly infrastructure. Excess tourism can degrade local infrastructure since tourists use it but don’t contribute to its upkeep or maintenance. Tourists’ lack of knowledge or care about proper disposal behavior on an island can create pollution, particularly during peak seasons. Tourists can also lower the welfare of local communities if they obstruct the lives of the permanent residents. Crowded towns, restaurants, beaches or other amenities can be a headache for the locals during peak seasons. Animosity between the two groups might form and influence social interactions in a negative way. Finally, a dependency on tourism can compound economic woes during events like COVID-19, making a recession even worse than it would have been otherwise. Transaction costs are often high for island economies The aforementioned lack of land and abundant natural resources means that islands must often import many of the goods that are necessary for daily life – such as food. A large portion of the goods sold on an island tend to be manufactured outside of the island and shipped there. But importing goods typically raises their price, even without factoring in the trade barriers (like tariffs) that could artificially increase the cost. This is because shipping goods, especially over longer distances, increases the costs producers must bear to bring their goods to the market. This in turn increases the price of the final good for consumers. Transportation methods also contribute to import costs. Most islands are small and relatively isolated from the major economies of the world, often even those that are part of a larger country. And most islands are reachable only by air or by ship, which severely limits the movement of people and goods into and out of them. Train and road travel is often not possible. This lack of options can raise transaction costs, even though shipping by sea is a relatively cheap way to trade. In the case of a small island with limited population, it may not be worth it for a large container ship to visit such a small market, compounding the issue. Local market size is limited, constraining growth of local businesses On a small island with scarce resources, the size of the population is bound to be small as well. Only with consistently supplied outside resources can the population continue to grow past a certain point. This means that island businesses face a long run growth challenge. The local market is easily saturated due to size constraints, at which point further growth can only be accomplished by developing a market presence elsewhere. But the high costs of shipping and lack of physical locations in other countries can make this very difficult. Due to this limited size, it’s unlikely that local businesses will grow beyond a certain point, and some sectors of the economy are unlikely to develop at all. To fill these gaps, foreign companies can ship goods into the island to be sold. But when locals buy these foreign products, the money leaves the island rather than staying in the local economy, as it would if there were local businesses providing the same goods or services. Infrastructure challenges Being located on an island comes with its own set of infrastructure challenges, too. Island infrastructure is a challenge to set up and maintain for several reasons. First, there is often a lack of immediately available heavy equipment or construction materials, which usually must be imported. Second, island infrastructure tends to be exposed to additional weathering elements than many continental locations. Intense sunlight, tropical storms, ocean tides, sea level rise, salty water and air, etc. all conspire to corrode and weather infrastructure more quickly than in most landlocked locations. Further, islands’ vulnerability to natural disasters like storms doesn’t help this fact. Storm surges and major hurricanes can be devastating to an island when they pass through. But physical infrastructure isn’t the only type of infrastructure that is costly to install and maintain on islands. Internet and payment infrastructure can be limited on islands, particularly those with smaller populations. Again, this is at least partially due to the naturally small size of island markets. However, recent years have seen an improvement in Internet connection speeds in many islands as undersea cables have been built to provide better service to remote regions, so this particular infrastructure challenge is increasingly being met. The importance of free trade agreements Due to their unique geography, free trade agreements can be very helpful for these island economies. These agreements typically include promises from members that tariffs and other trade barriers will be severely reduced or eliminated. For example, a 2016 IMF working paper, “The Impact of Trade Agreements: New Approach, New Insights”, found that free trade agreements could “generate substantial gains, on average an increase of exports by 80 percentage points over ten years”. Freer trade helps each member nation to leverage its comparative advantage with its trading partners as much as possible. In this way, the members in the trade agreement can boost their economies further collectively than each could do on their own. There are already a number of free trade agreements in effect among various island regions. For example, PICTA is a free trade agreement shared between 14 small island nations in the Pacific region that has been in effect since 2007. The much older CARIFTA agreement (which began in 1965) is a free trade agreement originally shared by 4 Caribbean islands, and has been gradually expanded to include most of the region – now 20 islands are a part of the agreement (some of which are independent nations, while others are overseas territories of larger nations). The agreement is now known as CARICOM. Next time you visit an island, keep an eye out for signs of these economic challenges, and the ways in which local society has adapted to them. You might discover a new research question, have an innovative idea of your own, or simply gain something to ponder while sipping from your freshly-cut coconut. Header image credit: Pixabay (free for use under the Pixabay Content License)
Islands bring to mind a particular vision of beaches, coconuts, and relaxation that’s hard to beat. Many people think of them as the ultimate vacation destination, and indeed tourism is important for many islands. Yet due to their unique geography, most islands in the world face a set of economic challenges that many mainland nations don’t experience.
Economic Development, Innovation and Growth (JEL O)
How to incorporate macroeconomics in environmental economics courses
Macroeconomic tools play an important role in addressing global environmental challenges, but they are not yet part of the standard environmental economics curriculum. This content deficit remains even as William Nordhaus won a Nobel Prize in 2018 for integrating climate change into long-run macroeconomic models. In this post, I outline teaching resources that will help instructors include macroeconomic content in undergraduate environmental economics courses. Textbooks Most environmental economics textbooks contain some coverage of macroeconomic topics. However, this content is typically covered in less detail than microeconomics topics, and often appears in chapters at the end of the book that are less likely to be assigned due to time constraints. One exception is the book titled Environmental and Natural Resource Economics: A Contemporary Approach by Harris and Roach (2023). This textbook includes macroeconomics content integrated throughout, with the second chapter focusing on the environment and economic development. The book also covers “green” national income accounting, climate change policy, and population and the environment. A unique aspect of this book is that the authors utilize a dual approach by including ecological economics, a perspective that treats the economy as a subset of the larger ecosystem, in addition to the traditional neoclassical economic framework. This comprehensive coverage makes the textbook suitable as either a primary text or supplemental resource. <11an>limit:3;categories:Conferences</11an> Empirics One way to introduce macroeconomic concepts into environmental and natural resource economics courses is to present timely empirical results and stylized facts. For example, recent research by Metcalf and Stock (2020) indicates that carbon taxes do not reduce GDP growth or employment. Instructors can present an overview of their empirical results, published in Resources Magazine, that is straightforward for students to understand. Some faculty may want students to practice collecting, synthesizing, and interpreting real world data. Adjusted net savings (ANS) is a national income accounting measure that accounts for resource depletion and pollution. It provides an estimate of whether savings and investment can compensate for depreciation of physical capital and degradation of natural capital. To that end, consider having students gather gross savings and resource depletion data from the World Bank World Development Indicators to compute ANS in Excel for a selection of different countries. Students can consider which countries have the highest rates of saving, resource use, and what these statistics actually mean in terms of how much each country is actually investing in their future. Theory Faculty set learning goals for students that extend beyond knowledge of specific content. In other words, it is important for students to work through economic models to develop critical thinking and analytical skills. Students can achieve this learning goal by – for instance – learning how pollution and resource constraints can be incorporated into macroeconomic models. Image credit: wirestock on Freepik.de. For example, Heyes (2000) adds an ecological constraint to the IS-LM model, a standard Keynesian tool that is commonly taught in principles and intermediate macroeconomics classes. Faculty can use this augmented model to illustrate the impacts of fiscal, monetary, and environmental policies through the usual comparative statics. Most textbooks include an overview of empirical evidence for the environmental Kuznets curve (EKC), the hypothesized inverted U-shaped relationship between per capita income and environmental quality, but offer few or no analytical exercises related to this subject. To remedy this gap, I proposed a simplified version of the “green” Solow model from Brock and Taylor (2010) that is accessible for undergraduate students. The “green” Solow model provides theoretical support for the EKC hypothesis by adding pollution and technological progress in abatement to the Solow growth model. My adaptation of the model does not require calculus or differential equations to understand and can be taught to students at various levels and in various formats (online, in-person, and flipped classroom). Conclusion According to a recent paper by González-Ramírez et al. (2021), climate change and sustainability are among the least developed topics in environmental economics pedagogy. Yet, student interest in these subjects is rising as the world changes around us – and these topics are becoming increasingly relevant to economics in general. Importantly, there are a variety of resources available for economics faculty to bring in macroeconomics content to build timely and effective courses. References Brock, W. A., & Taylor, M. S. (2010). The green Solow model. Journal of Economic Growth, 15, 127-153. González-Ramírez, J., Caviglia-Harris, J., & Whitehead, J. C. (2021). Teaching environmental and natural resource economics: A review of the economic education literature. International Review of Environmental and Resource Economics, 15(3), 235-369. Harris, J. M., & Roach, B. (2023). Environmental and natural resource economics: A contemporary approach. Routledge. Heyes, A. (2000). A proposal for the greening of textbook macro: IS-LM-EE. Ecological Economics, 32,1–7. Metcalf, G. E., & Stock, J. H. (2020). Measuring the macroeconomic impact of carbon taxes. American Economic Review Papers and Proceedings,110, 101-106. Milani, S. (2023). Teaching Environmental Macroeconomics to Undergraduate Students. Eastern Economic Journal, 1-17. Header image credit: onlyyouqj at Freepik.de.
At the undergraduate level, environmental economics is typically taught as an applied microeconomics course. However, while topics like externalities and common property resources are great for emphasizing efficiency, they don’t always prepare students to consider environmental concerns as part of the broader economy. Incorporating macroeconomics into these courses can help students understand problems that deal with both scale and efficiency, such as how to reconcile economic growth with environmental quality.
Agricultural and Environmental Economics (JEL Q)
Many great economists of the past didn’t limit their contributions to just economics. Instead, they often made advances in mathematics, physics, philosophy, or other fields too. Frank Plumpton Ramsey is one such brilliant mind. Equal parts mathematician, philosopher, and economist, he developed a cornerstone model of macroeconomics – the Ramsey model – among a number of other contributions. Ramsey’s life in brief The economist Frank Ramsey was born in 1903 in Cambridge, England. He was considered a genius, and was selected to translate a famous German philosophy text (Ludwig Wittgenstein’s Tractatus) into English at the age of 18. Famously an atheist, he was nevertheless fond of his brother Michael Ramsey, who was the Archbishop of Canterbury. Ramsey attended Winchester College in 1915, and soon went on to Trinity College, Cambridge in 1920. He graduated with high academic achievement in mathematics, got married in 1925, and was appointed as a university lecturer in mathematics in 1926 at King’s College. His friends described him as not only smart, but congenial and humble. During his professorship, Ramsey wrote and published several of his own, now-famous works. These included non-economics works such as The Foundations of Mathematics, Truth and Probability (which remained unpublished until after his death, but formed the foundation of modern decision theory), Facts and Propositions, and Universals. From these works and more, Ramsey is credited with major contributions in the fields of mathematics (leading to the development of Ramsey theory, now named after him, which also contributes to theoretical computer science), logic, philosophy, and of course economics. In fact, Ramsey met John Maynard Keynes himself and wrote a critique of Keynes’ Treatise on Probability, which appeared in the 1922 edition of The Cambridge Magazine. Not one to take it personally, Keynes later recommended Ramsey be inducted as a Fellow of Mathematics at King’s College (Keynes was a Fellow as well). Keynes’ praise of Ramsey did not stop there. Ramsey’s first major paper on economics was A contribution to the theory of taxation. Shortly after, Ramsey published his Mathematical Theory of Saving. These works made major contributions to economic theory, along with his Truth and Probability – which was not explicitly about economics, but nevertheless helped economists learn how to handle subjective expected utility. Keynes had the following to say about Ramsey’s Mathematical Theory of Saving, in an article simply titled “F. P. Ramsey” for the 1930 edition of the Economic Journal: [it is] one of the most remarkable contributions to mathematical economics ever made, both in respect of the intrinsic importance and difficulty of its subject, the power and elegance of the technical methods employed, and the clear purity of illumination with which the writer’s mind is felt by the reader to play about its subject. The Ramsey model Arguably the biggest contribution Ramsey made to economics was the development of the Ramsey model, also called the Ramsey-Cass-Koopmans model (as the latter economists extended Ramsey’s work to develop the model). This was one of the first economics models to heavily employ calculus in its derivation, which also helped to popularize including more mathematical logic into the field. The Ramsey model is an important neoclassical growth model, one of the cornerstone models of macroeconomics. It helps economists derive the relationship between the growth of the factors capital, labor, and output, capital intensity, population growth, and the optimal savings rate in a theoretical setting with an infinite time horizon. The model considers households as sorts of dynastic families, so that they form a single “agent” that then lives throughout many generations. This implies that each generation has a certain level of altruism about the well-being of the next generation. It also endogenizes the savings rate, which is an important improvement over earlier models that took the savings rate to be an exogenous, given fact. After all, individuals are the ones doing the saving, and they make these decisions based on their economic circumstances. This forms a powerful framework to examine how changing parameters – like the amount of altruism or patience each generation has – will affect the optimal savings (and thereby investment) rate for social welfare. A higher savings rate means future generations have more as the economy grows faster, but the current generations cannot consume as much. The model does have limitations, however. It’s built on some fairly idealized assumptions that may not hold true in reality. These include the fact that each generation is altruistic towards the next, the assumption that all households are representative of each other (and so do not conflict with one another), and the assumption that households have perfect foresight into the economy’s future and so can accurately choose the optimal level of savings. <11an>limit:3;categories:Master's Programs;disciplines:Economics</11an> Nevertheless, it remains a foundational model that helps economists study the behavior of different variables in a theoretical “vacuum”, and can be easily modified to include more realistic assumptions. The model is often compared to the Overlapping Generations (OLG) model, which features a finite time horizon and an infinite number of agents, as opposed to the Ramsey model’s finite agents and infinite time. Together, these two models have formed a strong foundation upon which macroeconomists can test theories and build new models. Conclusion Unfortunately for economics and the world, after his return to Cambridge Frank Ramsey died in January 1930 at the age of 26, most likely due to liver problems. His mathematical brilliance and enjoyment of economics could have developed economic theory faster than we were able to without him. With just a handful of years of scholarship, Ramsey left a lasting legacy that economists are still making use of today. His contemporary, the philosopher Richard B. Braithwaite, wrote the following for an obituary: His intellectual subtlety was combined with the most delightful simplicity and candour. Intolerant of fools, he inspired others by his mental fertility and integrity. To one at least of his friends his death is as if a lighthouse were extinguished and we were left to grope our way in the dark. References https://plato.stanford.edu/entries/ramsey/ https://mathshistory.st-andrews.ac.uk/Biographies/Ramsey/ https://www.hetwebsite.net/het/profiles/ramsey.htm Header image credit: public domain. Volsav, CC BY-SA 4.0, via Wikimedia Commons
The name is attributed to Sir Francis Galton, who lived in the late 19th century and coined the term while studying people’s heights. In his study, Galton collected the height measurements of parents and their children. He noticed that particularly tall parents tended to have children who were tall, but somewhat less so than their parents; meanwhile, short parents had children who were short, but still taller than they were. From these data points, Galton surmised that the heights of children tended to “regress” back towards the average adult height, rather than perfectly continue the height trend of their parents. Despite this word not really reflecting the actual statistical process of analyzing the variance of height data, it stuck. We use the word “regression” to describe a wide variety of models and analyses used by scientists – including economists – today. The basics of regression A regression is a method of analysis where an economist (or other scientist) uses data to measure the amount of variation in their topic of interest that is explained by various factors. This is often used as evidence to show that these factors affect the topic of interest, and how they do so. The most intuitive type of regression is a simple linear regression, explained as follows. The main subject the economist is interested in is (usually) the dependent, or y, variable (sometimes also called the response variable). This variable is something the economist wants to learn more about; for example, y could be test scores for students in a class. The various factors used to explain the variation in y – in our case, test scores – are the independent or x variables. These can be anything that might reasonably affect test scores, such as nutrition, IQ, age, hours spent studying, the parents’ level of education, and more. The economist then collects data on each of the variables. With the data, the economist constructs a matrix or table and uses their method of choice for calculating the amount of variation in y that the x variables explain. This is done by mathematically comparing how much y and a given x variable vary “together” or “at the same time” – in other words, how they co-vary. The economist takes this to mean that x can explain a certain amount of the variation in y, and probably has a meaningful real-world relationship with y. An easy way to get started is to view the data in a scatterplot to see if there appears to be a relationship. Figure 1 shows that there is an imperfect but probable linear relationship between y and x. Figure 1: A scatterplot of y and x made using R. This can be a good starting point to suggest, like Sir Galton, that there is a real phenomenon at work. In order to study this more intensely, an economist will go on to define an equation and do some math. A simple linear regression equation The regression is described by an equation. In the simple linear case, this is as follows: \begin{equation*} \mathit{y} = \beta_0+\beta(\mathit{x})+\epsilon \end{equation*} where y is the dependent variable and x is the independent variable that the economist believes influences y through an economically meaningful relationship, as described above. \(\beta_0\) is a Greek letter that will be a number once the equation is calculated, and is the y-intercept of the equation. \(\beta\) similarly stands for the numeric coefficient on x in this linear equation. Normally, the economist checks to see whether the \(\beta\) coefficient(s) on x are “statistically significant”. Those that are show evidence that they affect y in a non-random way. These numbers represented by \(\beta\) are calculated as a result of whichever statistical method the economist chooses to use for this equation. Recall our earlier example, where y is the student’s test score and a possible x variable is the student’s hours spent studying. Let’s suppose that calculating this regression equation results in the following: \begin{equation*} \mathit{y} = 25.00+15.67\mathit{x}+\epsilon \end{equation*} This equation can be interpreted as follows: if the student spends no time studying, x = 0 and the equation simplifies to y = 25.00 (plus \(\epsilon\), but this is expected to be zero; more on \(\epsilon\) later). This means a student who does not study at all is expected to score a 25 on the exam. For every 1-unit increase in x, the student is expected to earn 15.67 more points on the exam. This means that every extra hour spent studying is expected to raise the student’s exam score. It seems like studying is a useful activity, then. If a student studies for four hours, they’re expected to earn an 87.68 on the exam. Although there was only one x variable in this example, it’s important to know that multiple x variables can be used. When this is the case, the regression is known as a “multiple linear regression”. Finally, \(\epsilon\) is the “error term”. The error term accounts for all of the variation in y that is not explained by x, allowing this equation to hold true. Because of this, it’s often thought of as a variable that captures the effects of all other variables that affect y and aren’t included in the regression. Residuals are another important term related to \(\epsilon\) – each individual “error” data point is a residual, such that \(\epsilon_i\) is a residual. Residual analysis usually refers to looking at a chart of the residuals, which gives the economist an idea of how well-behaved the error term is – and if any corrections should be investigated for the model in question. The error term is a very important part of regression analysis. On the one hand, the goal of the regression method is usually to minimize error – as this results in an equation that most closely mimics the behavior of y in the data. Further, studying the error term for a specific regression model can give the economist evidence that the model is (in)correctly specified, suggest the presence of biases or missing variables in the model, and more. In order to conduct an acceptable econometric analysis, economists often must prove that the error term in their equation behaves as expected. This usually involves showing that the error term has an expectation of zero and can be thought of as random, patternless noise. Types of regression models The above example did not mention how to actually generate the numbers in the equation. There are many methods that an economist can use to do this, thereby calculating the regression. Normally, economists use software to quickly calculate their regression equations, but it’s possible to do many regressions by hand. In fact, many economics students will be taught to generate a regression in class using the common and foundational Ordinary Least Squares (OLS) method for a linear regression analysis. This method calculates the regression coefficients and the error term using the “sum of least squares”, which is a simple and surprisingly powerful way to find the regression equation that minimizes error. Other models commonly used in economics besides OLS include (Feasible) Generalized Least Squares (FGLS), probit and logit, Maximum Likelihood estimation (MLE), Ridge and Lasso regression, and polynomial regression. Econometrics can also blend into machine learning and data science, sometimes utilizing regression models like Decision Tree and Random Forest, depending on the goal of the analysis. Goodness-of-fit measures An economist can set up a regression equation for just about anything. For example, we could have used not just hours spent studying, but age, IQ, and parent’s education level in our linear regression model example above. In fact, nothing stops us from making multiple regressions with every combination of these variables to try and predict y. How does the economist decide what the best model to use is? The first step is that the economist should derive an equation from theory first. Whatever relationship the economist expects is true in reality is a very good starting point. There are numbers generated from statistical concepts called goodness-of-fit measures that can help economists understand which model generates the best fit for the data. The most commonly used measure, R2, is typically used for linear regressions. It describes how much variation in y is explained by the regression equation, on a scale from 0 to 1. Ceteris paribus, an economist would prefer their model to have a higher R2 than other models, if y is their main variable of interest and they’re trying to explain variation in it. However, a promising goodness-of-fit measure alone does not mean the regression is a good one. Every regression needs sound economic reasoning behind it to be considered valid. This idea is explored more fully in the following section. Limitations of regressions Once students learn how to run a regression, it’s easy to think that this type of analysis can answer all kinds of questions. And, regressions really do help economists answer many questions about economic theory and the real world. But there are important shortcomings to know about regressions before utilizing them. First, it’s useful to understand that regression analysis simply analyzes how much y co-varies with each x variable and the model as a whole. Often, students can internalize simple (but incorrect) shorthand, such as “x causes y because the regression results are significant”. While this interpretation might end up being true, regression significance is not sufficient evidence to prove causation. Additional proof is needed. For that reason, regressions require sound theory behind them in order to convincingly show any economic relationship. It’s easy to design regressions that have amazing statistical qualities, highly significant variables, and large R2 values – but are ultimately meaningless. This is often due to a problem known as “spurious correlation”, which means two variables that have nothing to do with each other show a high degree of covariance anyway. For example, the following humorous chart from former Harvard student Tyler Vigen shows that the number of movies Nicolas Cage appeared in is highly correlated to the number of people who die by drowning: If one were to run a regression of this data, where deaths by drowning were coded as the y variable and Nic Cage movies were the x variable, the results would show a relatively high R2 and a significant effect of x on y. In this way, simply looking at the regression results of y on x without considering economic theory, it would be easy and understandable to think that x must be an important cause of y. But clearly, Nicolas Cage appearing in movies has (almost certainly) nothing to do with the risk of people drowning! Regression analysis is one of the main tools that economists use to conduct research, test economic theory, and learn about the real world. It’s an invaluable skill for students of economics to learn. Those who are very interested in regressions should consider majoring in econometrics, economic statistics, or a similarly quantitative option. Further Reading This article has only covered the tip of the iceberg when it comes to regression analysis. And, for the interested student, good news – there are literally thousands of articles and books written on the subject. Some classic introductory texts that don’t require too much math expertise include Regression Analysis and Linear Models: Concepts, Applications, and Implementation by Darlington and Hayes, and Applied Linear Statistical Models by Neter, Kutner, Nachtsheim, and Li. Good to Know Regressions in economics literature are very important. Essentially all serious empirical economics research includes a regression analysis, which is typically presented alongside a lengthy theoretical explanation of the expected relationships at hand. The best papers include convincing justifications for why the model fits the data, what it means, and discussions of weaknesses and drawbacks to the authors’ approach. Students who are interested in economics research would be well served finding a good empirical economics paper to learn from. Additionally, the following recommendations from the German IZA Institute of Labor Economics and Plamen Nikolov give a detailed and helpful breakdown about what’s expected of an empirical economics paper. Graph Image Credit (Nicholas Cage): Tyler Vigen (published under CC BY 4.0)
Regression is a word commonly used in econometrics, statistics, and many other sciences. It describes a widespread technique used by scientists of all kinds to empirically test theories using available data.
10 Tips to Make Your Classes More Engaging for Students
As if this wasn’t hard enough, it can be very difficult to keep students’ attention during class time. We live in a world of constant distraction, and often it’s difficult for students to engage in classroom material – especially difficult material – for an entire classroom session. The very best teachers know that engaged students learn well, and aim to make their classes not just informative, but also interesting and engaging. This is no easy feat; how can instructors make their economics classes more engaging? INOMICS has collected some tips and tricks, some of which were inspired through our time in economics classrooms. Read on for our top 10 tips on how to better engage your students to help them stay focused and learn. 1. Ask questions and seek your student's opinions One of the best ways to increase student engagement is to directly solicit their thoughts on the material at hand. Giving your students the expectation that you might call on them will inevitably cause them to handle the materials more critically, and pay more attention. It’s an excellent way of focusing students’ minds and instilling in them a healthy scepticism that’s essential to all good study. Be wary, though, some students can be shy when it comes to contributing to class discussions. To counter this, try and create an atmosphere in which questioning is encouraged and students feel comfortable offering an opinion, even if they're unsure. If a student answers a question incorrectly, but elements of their answer are correct, be sure to acknowledge the good parts of their answer before calling on the next student. This will help all of your students recognize that participation won’t punish them. Another tip - your more confident students are likely to be constantly participating while your more quiet students won’t get the chance to talk. To balance this out, ask for hands raised and call first on those students who don’t participate as much; consider “cold calling” students on occasion (but make sure this expectation is set beforehand); and do your best to respond encouragingly when the quieter students do choose to participate. Image credit: pressfoto on Freepik.de. 2. Assess the level of knowledge in the room and tailor your teaching accordingly Most classes that you’ll teach probably come with certain requirements about course content, including necessary prerequisites that students must pass first. Even so, your students will quickly grow bored and disengaged if your lecture material is either too basic or too advanced for them. Mitigate this by ascertaining the class’ general level of ability, and adjusting the complexity of your teaching accordingly. For instance, this could be done by getting your students to do a short introductory quiz before your first class. This type of differentiation (or differentiated instruction) can help students stay engaged in various ways. For example, advanced students will likely appreciate additional content (like proofs) that may not be core exam material. These types of students will typically ask questions proactively during the normal lecture to ask “why”, as they enjoy knowing the inner workings of the course’s content. These students might also appreciate assignments that include one or two very difficult questions that might be too hard for an exam, but great learning material for a more relaxed setting. Meanwhile, students who might not be comfortable with prerequisite material would greatly benefit from quick refreshers. This can help them remember older material before learning new concepts that build on that older material. They might also appreciate a slower pace of lecturing that allows them time to take sufficient notes. To this end, consider providing printable notes (with a few blank spaces to fill in) that students can bring to lecture. When students are merely copying down everything they hear, they might not have mental space to truly engage critically with the material. Pre-written notes or copies of your slides can make students feel more free to question, comment, and think about the material you're teaching, without missing important notes. 3. Get students to present work themselves It's said that one of the best ways to understand something is to teach it, and you can use this to help your students learn. Including student presentations will work better for classes that have material that can be dissected and spark discussion, as opposed to classes that teach irrefutable truths. For example, a course about economic history or behavioral economics – where economic theories are still being tested and debated – will probably have more opportunities for good presentations than an advanced econometrics course, where quantitative truths are more or less irrefutable. If time allows, consider asking each student to prepare a short presentation on each topic you plan to teach. You can use this as an introduction to your classes throughout the semester. For example, a course that discusses macroeconomic models or schools of thought (i.e., neoclassical vs. Keynesian theories) can feature a short student presentation about each model. This can give a high-level overview for the whole class, before you dive into the details. 4. Use multimedia like video or audio clips Dropping a short video, image or audio clip into your presentations can help freshen the heavily text-based format of most lectures, and will help those students who are more visual or auditory-based learners. Video clips of interviews with prominent economists, about relevant historical events, or the like can be particularly effective. Humorous but relevant videos or images can also be highly effective. For example, consider the below xkcd comic, shared during an intermediate economic statistics course: Image credit: xkcd. This comic is effective and engaging for a few reasons. First, for advanced students who already understand the basic differences between Bayesian and frequentist statistics (i.e., the fact that Bayesian statisticians use a prior distribution), this comic is pretty funny. It points out the absurdity of blindly trusting a frequentist approach all the time. Second, for students who don’t get the comic, explaining the joke helps them understand the main difference between Bayesian and frequentist statisticians, at which point the comic becomes funny to them as well. Wanting to understand the joke also gives students motivation to think critically and engage with the learning process, so they can join in the fun. Finally, the joke is actually very relevant to the class material. In this case, in order to understand the joke, the student must understand an important fact about Bayesian statistics and how it’s different than the frequentist methods. Breaking up the monotony of a lecture with something humorous or interesting, but also informative and relevant, is a great way to keep students engaged. 5. Encourage group discussion Consider breaking up your lectures by having a segment in which the class splits into small groups of 3-6 and discusses a topic or specific question amongst themselves. Good examples can include coming up with critiques of a specific economic model, attempting to derive a specific result from a model or a proof, listing examples of relevant economic policies, etc. After 10 or so minutes of discussion each group should then report back the most interesting points their conversation brought up, hopefully then facilitating further class discussion. This also helps engage students who might be too shy to engage proactively with the entire class, as point number 1 discusses. Image credit: cookie_studio on Freepik.de. 6. Change up the format of your classes As countless studies have proven, it's difficult for any of us to concentrate for longer than an hour (many actually suggest the limit is closer to 45 minutes), so try breaking your classes into manageable chunks. For example, if you have an hour to teach, you could give an introduction to the topic for 15 minutes, then give students 10 minutes to re-read the class material, follow this with a 20 minute discussion in small groups, and finally finish off with a 15 minute class discussion at the end. Changing format frequently will help to keep students engaged. It might even benefit you to completely change the class format from one week to another. Consider which types of exercises or discussions lend themselves to the different topics in your course – group discussions might make a lot of sense for some topics, but perhaps short presentations or a pop quiz work better for others. 7. Set up a debate In any field, there will be theories, models, or concepts which are contentious. Try splitting your class into small groups and asking them to present each side of an issue in a debate. In economics, this can include topics like the value of the different economic schools of thought, pros and cons of the minimum wage (or other economic policy proposals), whether technological progress is good or bad for the labor market, etc. Even if students don't agree with the side that they've been asked to represent, this is a great way for them to practice argumentation and critical thinking skills, as well as learning the material at hand. And it can help to engage the class, breaking up the rhythm of typical lectures and notes. 8. Allow breaks or changes of setting in longer classes It's a rare student who is capable of concentrating for the full length of a three hour lecture. Be realistic about the needs of your students (and of yourself as a teacher!) and allow short 5-10 minute breaks every hour or so, so people can stretch their legs, use the bathroom, and get a (possibly much needed) cup of coffee. 9. Work on your presentation skills Many of the tips for giving a great presentation – having an engaging voice and attitude, knowing your material inside and out, engaging your audience with a bit of humor, asking questions, etc. – apply to teaching in the classroom too. Great instructors have mastered the art of giving a great presentation, and students absolutely notice which instructors are good at this type of public speaking versus those who are not. 10. Make use of technology Don’t forget all that you learned during the pandemic! Continue to make use of the terrific technological tools that help make your teaching more engaging. For instance, your institution may have an electronic content management system like Moodle or Blackboard where you can share materials and set up discussions for your class. Instant polls have become quite common in recent years, using apps like Socrative, Poll Everywhere, or Kahoot!. Using games to teach economics is also becoming quite popular, and can go a long way to helping your students stay focused. It pays to try and stay abreast of new ways technology can be brought into the classroom to liven things up. Header image credit: Pixabay.
Teaching is an honorable, but difficult, job to do. Economics instructors working in higher education must rapidly and thoroughly communicate complex concepts and theories within tight semester time frames, effectively enough that most students will learn the concepts and pass the course.
AI supports the case to introduce a Universal Basic Income (UBI)
This economic growth is seen as a good thing by economists, because it theoretically empowers us to satisfy our needs with less effort, and frees us up to enjoy our lives more. As our economies have become increasingly efficient over the past several decades, some have increasingly called for shorter work weeks to take advantage of this increased productivity. The advent of new and useful AI tools only strengthens this call. The link between economic growth and leisure time Typically, two main factors contribute to economic growth; increasing population and improving technology. Both of these factors are represented by inputs in the standard Cobb-Douglas model of the economy (population is represented by labor, L, which will tend to increase as the population grows). But it’s the latter factor, technological progress, that ties AI to the idea of a universal basic income (UBI). Technological progress – represented by the multiplicative factor A in basic Cobb-Douglas models – allows society to produce more with the exact same levels of employment and capital stock. John Maynard Keynes, one of the great historical figures in economics, predicted that by 2030 people would work for only 15 hours a week. He believed this because he expected that the increase in economic productivity, largely in part due to improving technology, would allow people to produce more in less time. This would then allow for workers to have much more leisure time, which would increase overall welfare and happiness. Thinkers and philosophers in history have often viewed leisure time as the ultimate goal of increasing productivity. For example, Aristotle, in his work titled Nicomachean Ethics, once said that “the end of labor is to gain leisure” (though he also advised that we use our leisure time wisely, stating “...the objective of leisure can and should be to sustain other aspects of our lives which make us uniquely human: our souls, our minds, our personal and civic relationships”). This view makes sense. What is the point of toil if not to provide for ourselves? And if we are sufficiently provided for, why should we continue to toil needlessly? As technology advances to the point where we can produce enough goods and services for everyone in record time, it seems only fair that everyone should have their basic needs met. This would then allow people the freedom to pursue their own passions and interests – seemingly a great human achievement. UBI and AI This sort of vision of a human-centric utopia begins to point to the need for a systematic way to ensure everyone is provided for fairly. One idea that may accomplish this is, of course, implementing a universal basic income (or UBI). The development of (potentially) transformative AI tools lends much weight to the theoretical arguments around implementing a UBI – and thus increases the need to seriously discuss the merits and drawbacks of such a system. The basic idea of a UBI is that the government would pay everyone a basic stipend to live on. Then, generally, people would be free to continue pursuing business enterprises or working careers as they saw fit to earn extra money or work on a passion project. Notably, this situation differs from communism in that public ownership of everything is not implied or even desirable in such a situation. Certainly, a society with a UBI could be considered some flavor of socialist, but it’s not necessarily anti-capitalist. UBI itself would not change the normal functioning of capitalistic markets. Therefore, capitalist structures and the rewards it gives to innovators and efficient business leaders could remain, yet the UBI would grant individuals a greater degree of personal freedom. How AI can lessen some arguments against a UBI One common argument against a UBI is the idea that having a UBI will make people not want to work. If everyone made enough money to live comfortably without doing anything, lots of people would possibly choose to stop contributing to society. Further, if a UBI is substantial enough, it might crowd out certain lower-income professions entirely. If people could make as much money as a fast food worker, librarian, or computer repair technician (for example) without doing any work, it’s very likely that nobody would choose to work in those roles. This could either inflate the pay for these roles to unsustainable levels (as demand outstripped the supply of labor), or it could cause these services to disappear entirely. The solution to this problem is not a lower UBI. If the payments weren’t substantial enough to provide for the basic needs of the recipients, they would not achieve the intended goal of a UBI, which is to do just that. Proponents of a UBI wouldn’t be satisfied with only a small income that left people still unable to provide for themselves. However, advanced AI might provide a solution to this potential labor supply problem, at least in some industries. If AI advances enough to allow machines to replace humans in these roles, suddenly the idea of a UBI seems quite desirable. Humans wouldn’t have to work these types of jobs at all, but society could still benefit from them. In fact, AI is already starting to transform some of these roles. The first level of customer or IT support in many industries often takes the form of an AI chatbot to diagnose the issue, provide an appropriate answer, and escalate to a human professional if help is still needed. What’s more, a recent Wall Street Journal article revealed that several fast food chains are already replacing humans with AI that will take your order in the drive-thru. Wendy’s announced in mid-2023 that they would be partnering with Google Cloud to do the same. Meanwhile, news about AI replacing librarians has yet to come – but certainly many functions of a librarian could be automated by generative AI, including searching for books, directing people to specific amenities, reserving rooms, checking out books, and more. In the perhaps not-so-distant future, then, people who would formerly have worked in these roles could instead pursue their own passions – like producing music, writing, furthering their education, or simply spending time with their families. It’s not hard to imagine society becoming more fulfilled, happy, and even more healthy in this case. Indeed, one common argument in favor of a UBI is that it would free up citizens to pursue their passions and enjoy life rather than being slaves to their desk jobs. Since the COVID-19 pandemic, trends like quiet quitting have shown that modern workers are attempting to rebalance the scales in their favor, and would like to enjoy the benefits of economic growth a bit more in their own personal lives. Advanced AI tools could help make this a reality without reducing economic output. How much productivity is enough? While our current slate of AI tools cannot do everything, and certainly haven’t displaced most workers, they have the potential to massively increase human productivity. Especially as these tools become more sophisticated, specialized, and powerful (perhaps culminating in the development of more advanced and human-like AI), larger segments of the economy may become dominated by them – potentially costing people jobs as well as creating new ones via the process of creative destruction. And many jobs, even if they’re not fully automated, will experience a potentially huge increase in efficiency as specialized AI tools are developed for their fields. Which begs the question: at what point has society achieved enough productivity? The idea that profits and output will grow forever, infinitely, is ludicrous when considered for any length of time. Yet capitalism has no built-in ceiling, or “off” switch, and continues to prioritize growth of the bottom line. Therefore, a purely capitalist society where growth and returns are valued above all else may not be the best system forever. Indeed, it may have already worn out its welcome. Many would argue that rising wealth inequality and global issues like climate change are fairly direct results of the unsustainable pursuit of profit margins that capitalism has championed. What, then, should take its place? One possible answer could be a society with a somewhat capitalist structure, where sustainable provision is provided by a UBI. One where people are more free to develop their careers, forge new businesses as entrepreneurs, and make extra money how they see fit, but where society no longer deifies the paradigm of infinite, quarter-over-quarter growth. In such a system, the basic gears of the economy would continue to turn as AI-assisted or even entirely automated occupations produce as much as we do now with far fewer labor hours. This would free up people to live more fulfilling lives. This includes people whose fulfillment comes from work: a UBI would give people the flexibility to pursue job training and advanced education for the jobs they want to try, or give them a great safety net as they try to develop their entrepreneurial ideas. Advanced AI capabilities lend a lot of weight and potential realism to these ideals, and the straightforward idea that everyone should have a basic income to take care of these needs. If it becomes possible in the coming decades, why shouldn’t we give it a shot? AI does not automatically solve the challenges of fairly distributing economic gains As aforementioned, AI signifies yet another massive leap forward in potential productivity since Keynes made his original “15-hour work week by 2030” prediction in 1930. In that regard, how have we been doing over the past century? A graph put together by the site Our World in Data – using data from the World Bank and Maddison (2017) – shows the incredible exponential increase in world GDP, especially since 1900. Yet, working hours in developed countries have remained at roughly 40 hours per week for decades. In several developed nations, work weeks of more than 40 hours per week have even become more common than they were in the 1990s, according to the London School of Economics’ blog. Clearly, the massive increases in productivity haven’t exactly freed up the average working person as Keynes predicted. This is because increased growth doesn’t automatically distribute itself fairly. As productivity has increased over the past century, there have been modest gains in leisure time. But, wealth inequality has risen dramatically. Increased productivity will change the economy, and a UBI is just one possible way that productivity can trickle throughout the economy. But there are other ways productivity could contribute: wealth inequality is the natural result if nothing is done to ensure that increased prosperity is distributed throughout society. The reason for this is that the existing structures of power in the capitalist system are bent towards infinite growth. Those at the top are benefitted when productivity increases, and have no proper incentives to share the wealth. Instead, like metaphorical dragons, they’re able to hoard their wealth to ludicrous levels. Again, there is no productivity target or goal in our current economic system; if we become more productive, the economic engine we’ve created is designed to continue shooting for the moon, not help us all live happier lives. It’s up to us to reassess our goals, take stock of the world around us, and pivot. If AI creates enough production to keep society running without most of us needing to work so much, or even at all, then there’s a much stronger case to be made that people should be given a basic living stipend and allowed to pursue their own lives with a greater degree of freedom. Louis O. Kelso once said in his co-authored book Two-Factor Theory: the Economics of Reality, “The sooner the world solves its economic problems, the sooner its inhabitants can afford leisure and peace and get on with the non-material things that are inherently important: the work of mind and spirit that is gloriously and uniquely human, the work that no machine can ever do”. Perhaps it’s nearly time to let those machines do the material work for us; after all, we’ve got to live our lives to the fullest. Header image credit: Pixabay.
One of the key features of the global economy is that it tends to grow over time. In fact, that growth has become something of an expectation in the modern capitalist system, where the success of corporations is often judged by their growth, even over relatively short time horizons.
Which Concentration Should You Choose For Your Master's Degree in Economics?
A degree concentration in economics is an area of specialist study within the field of economics which you give particular attention to. Specializing in a particular sub-field can boost your already high employability as an economist even further, and pursuing a concentration is a first step in that direction. To help you decide whether a concentration is right for you – and which one – this article will provide a list of common economics degree concentrations and a brief overview of each. Hopefully, you find one that inspires you! Bear in mind that in certain economics departments, some concentrations may have specific entrance requirements above and beyond the entrance requirements for the economics Master's. Be sure to check the websites of the universities that you’re applying to for more details. Applied Economics Applied Economics, unlike other concentrations on this list, is not truly its own sub-field. Rather, applied economics concentrations teach students to develop and interpret econometric models that can be used to make decisions about specific subject areas – like national and foreign policy, energy strategy, environmental or health economics, etc. As opposed to a more theoretical approach, applied economics is all about the practical application of economic concepts in the real world. Certain institutions might have more of a focus on some of these areas, but not others, depending on their strengths. If you’re very interested in health economics (for example), be sure to search for institutions that offer coursework in health economics specifically. An “Applied Economics” concentration typically requires a solid knowledge of mathematics and the ability to reason about economics, and will appeal to those who want to make concretely useful policy suggestions which are based on economic knowledge. This concentration is a great idea for students who wish to become an industry economist. However, this might not be the best approach for students who are more interested in research, as the concentration typically focuses more on applied methods and real-world applications than theory, as its name suggests. Econometrics / Quantitative Methods An Econometrics or Quantitative Methods concentration focuses heavily on the mathematical and statistical side of economics. While every economist is going to need some familiarity with econometrics in order to do their jobs, this concentration dives deep. Students are highly encouraged to come with at least some background in statistics or calculus in order to succeed in this concentration. Students who complete an econometrics concentration may develop less specific “real world” subject matter expertise than others, so this may not be a great choice for students who have a clearly defined research interest (unless that interest is in econometrics, of course!). However, this concentration provides an extremely solid foundation for future research or PhD studies, since often the hardest part about conducting economic research is doing an appropriate quantitative analysis. Econometricians who do not specialize in a particular real-world application nevertheless lay the groundwork for other economists’ research. They are instrumental to the development of economics as a serious research discipline – just look to the accomplishments of Dr. Wooldridge. And, it’s relatively easier to pivot from a quantitative methods focus into any other economic subfield than to do the same pivot from other concentrations. That’s because econometric methods are the foundation of solid, repeatable, trustworthy economic research, and form the backbone of knowledge generation for economists. Economic History For students who want to combine the study of history with economics, good news! Economic history is an established subfield that is often offered as a concentration. Study in economic history involves using modern economic methods to examine historical situations and institutions. While this deepens our understanding of historical events, another main purpose of this field is to learn about how economic relationships work in the real world and test economic theory, so that contemporary economists can apply those findings to modern situations. This is important and useful work, because it’s usually difficult to test economic theories directly. Economists often cannot create experiments as easily as other scientists, due to moral and logistical concerns. Thus, using historical events as sorts of case studies allows economists to test economic theory in a real-world situation. There are plenty of academic opportunities for economic historians, though students interested in an industry economist job might be better served focusing on a concentration like applied economics instead. Health Economics Health Economics is a concentration that looks at how the principles of economics are applied to health in our society, including but certainly not limited to the functioning of the healthcare industry. Students in this concentration willI examine topics such as the tradeoffs between different types of healthcare systems, the effects of health problems or healthcare availability on economic outcomes, the behavioral modeling of healthcare use, and more. This concentration is particularly well-suited to students interested in healthcare, of course. But it’s also a useful concentration to consider for students interested in developmental economics and gender economics. Research in this field is alive and well, and there are plenty of opportunities for economists with this concentration to work in either academia or industry. International Economics For those economics students with an interest in international relations, foreign policy, trade and foreign direct investment, and/or globalization, the concentration of International Economics should be considered. Although every institution has its own unique take on teaching these subjects, this concentration commonly includes subjects such as international trade, foreign investment, and international political economy. Check the specific course offerings of the institution you’re considering to see which elements of international economics are emphasized. This concentration should be strongly considered by any students who wish to work in a role that involves government policy or policy analysis, international trade regulation, market integration across regions, or possibly even international development. Labor Economics Labor Economics is a branch that focuses on the functioning of the labor market. This is perhaps one of the oldest and most traditional fields of study for economists, though that doesn’t mean it’s outdated; study of systems of labor is alive and well. This sub-field is all about the study of how employers and employees react to changes in the work environment – including wages, prices, regulations, etc. This typically includes study on subjects such as minimum wages, labor regulations and their economic consequences, unionization, unemployment, worker migrations, and possibly even unpaid work like household labor (after all, one valid response to lowered wages is to stay home instead!). Labor economists can find themselves working for a wide variety of employers, including universities, think tanks, consulting firms, governments, and more. This is a very flexible sub-field that can even be combined with others – for example, the more specialized sub-field of international labor economics studies the movements of workers between countries. Finance / Financial Management Those who want to work in financial regulation, in public finance roles or in the finance industry, – for example in a bank or an investment group – should consider taking a concentration in finance or in financial management. The jobs which this can lead to are typically very well compensated, and a finance specialization offers much real-world applicability. Many economics departments include monetary economics coursework options within their financial economics concentrations. Some offer monetary economics concentrations that typically deviate from the core financial economics coursework somewhat, but still share many classes with the standard financial economics degree. So ,students who are interested in central banking ought to look for financial economics concentrations that include monetary economics coursework. It’s worth noting that many MBA programs offer finance concentrations as well. The advantage you’ll have coming from an economics background is that you’ll understand markets and financial decisions from an economic standpoint, and you’ll likely have a better quantitative foundation. Your analysis would arguably be more in-depth compared to the average MBA. Meanwhile, MBAs will give you a greater understanding about the business world and related functions, like corporate finance and marketing; these degrees are typically broader, while an economics-based finance degree is typically deeper. For economics students who love finances, financial markets, and how money works in the economy, look no further than a concentration in financial economics. There are many industry opportunities for economists with such training. But, there are also academic research opportunities for the more research-inclined – research on emerging areas of finance and new instruments being created are always in demand. Developmental Economics / International Development Students who wish to follow in the footsteps of economists like Dr. Esther Duflo, and use their knowledge to promote social good, may be interested in a concentration in Developmental Economics. Also sometimes referred to as international development, this concentration studies poverty and its causes, and how development interventions can improve quality of life for people around the world. It includes topics like policy planning and advocacy, the study of foreign aid interventions, and health, education, and finance-related programs that can assist the world’s poor. Other topics that might be included under this concentration include more general studies of how economic growth occurs and how policy contributes to growth. Economics students who want to work in an NGO or at a major aid organization like the IMF or the World Bank should strongly consider this type of concentration. Research opportunities in this field abound, as well; randomized controlled trials have become popularized by the 2019 Nobel Prize winners in economics, and are extensively used in this sub-field to research how economic theory works out in low-income and developing economy settings. Environmental Economics Environmental economics has become an increasingly popular topic as the impacts of global warming have been felt over the years. This sub-field studies the effects of climate and climate change on our societies and the economic systems that run in them. It also deals with sustainability concerns; expect to study topics like the appropriate interventions that can be made to account for externalities across global supply chains to reduce negative environmental impacts. Environmental economics is ripe for research, and industry positions are becoming more in demand. However, this field is much younger than the others on this list. This means that there are fewer established career paths in the field, which is exciting and challenging for aspiring environmental economists. Additionally, environmental economics programs are mostly more recent additions, so it might be necessary to double check if the university you’re interested in has one. If you’re looking to make your mark on a relatively newer field of economics, are interested in climate change, and care for sustainability, look no further than a concentration in environmental economics. Behavioral Economics This sub-field is the intersection between economics and psychology. It studies decision-making behavior and dares to ask the question: what if our assumptions about rational economic man are wrong? Behavioral economists often conduct experiments that are very similar to those used in psychology studies, though usually with distinctly economics themes (i.e., people’s lying or truth-telling behavior when anonymously sending or receiving money from others). Academic research in this field is quite vibrant, and insights from this sub-field routinely improve the economic models used by micro- and even macroeconomists. As such, expect a behavioral economics concentration to include a large amount of psychology. These courses also typically include deep study of foundational microeconomics concepts, like preference relations. While behavioral insights are increasingly changing macroeconomic models, this is a distinctly microeconomics sub-field. Academic research in this field is vibrant, but there are still many industry economist opportunities for behavioral economists. Non-academic career options for a behavioral economist include consulting, market research and advertising, and even jobs in behavioral finance. Urban Economics Do you love city planning, resource management, policy analysis, and economics? Urban economics is a sub-field that studies our societies from the perspective of cities, towns and smaller communities. Urban economists focus on studies of crime, public education, municipal resource management and distribution, regulation at the city level, housing, public transportation, agglomeration economies, and more. Because urban economists specialize in cities, towns and similar societal structures, they often touch many different areas of economics, though these are usually microeconomics focused. So, students who are interested in a broad swath of economics topics might find an interesting home in this sub-field. For example, an urban economist might need finance experience to help analyze municipal budgets or monetary policies. They might benefit from some environmental economics knowledge to study urban sustainability. Or, they might need experience with developmental economics or health economics to help analyze the availability of and improvements for public services. Research and academic positions (like an economics professor position) are of course available for urban economists. Non-academic positions most often include positions in local government or policy analysis roles. <11an>limit:5;categories:Courses|Programs;disciplines:Econometrics, Statistics and Quantitative Methods (JEL C)|Economic History (JEL N)| Agricultural and Environmental Economics (JEL Q)| Urban, Rural and Transportation Economics (JEL R)</11an> Conclusions These concentrations are some of those most commonly offered, though of course this is not an exhaustive list. Part of the appeal of higher education is the opportunity to learn from leading economists and researchers about their interests and field of expertise, and these intellectuals routinely help to shape and design their institutions’ course catalog. Use these descriptions as a guideline, but you should still do your own research into the right economics program for you. Happy studying! Header Image Credit: by Arek Socha from Pixabay (free for use under the Pixabay content license)
If you're planning to study economics at a Master's level, then you may have the opportunity to pursue a concentration, sometimes also referred to as a major. While rarer, some PhD programs may also offer concentrations, though many are already specialized degrees (or require you to have your own research agenda).
Urban, Rural and Transportation Economics (JEL R)
Studying in Germany: How to apply for a student visa
If you’re a citizen of the EU, Iceland, Switzerland, Liechtenstein, or Norway, good news! You won’t need any type of visa to study in the country. Prost, indeed! Citizens of some other countries don’t need a student visa to enter the country, but will need one to complete their studies in Germany. These include citizens of the United States, Great Britain, New Zealand, Australia, Canada, Israel, Japan, and South Korea. If you aren’t from the Schengen area, applying for Germany’s student visa might seem to be a daunting process, but we’re here to help make sense of it. The process is relatively straightforward, although it has many pieces. Read on to learn about how to apply for the student visa in Germany and our tips for making the application process easier for you. Note that this information is accurate as of the publish date above. Some of these requirements could be changed by the German authorities over time, however. Be sure to double check with the references provided at the end of this article. Note that this article does not cover work visa requirements for Germany. But fear not – we have another article for just that! Applying for a student visa The exact requirements for a student visa are subject to vary depending on the country you’re applying from. Check with your local German embassy or consulate for exact details. You can search for the nearest embassy or consulate that will process visa applications on this page at the German Federal Foreign Office’s website. In most cases, the following guidelines apply. You will need to make an in-person appointment at an embassy that is able to process visa applications and provide several documents for them to take and/or copy. The following documents are typically necessary: A completed visa application Your valid passport Proof that you have German health insurance Proof that you have sufficient funding Proof of acceptance into a German university Proof that you have sufficient language skills Only if applying for a prospective student visa: a recognised higher education entrance qualification A fee (typically; check with your embassy or consulate) We’ll walk through each of these documents below. Completed student visa application This document should be available to download from the website of the embassy you’ll submit the application to. It may require some additional documents not listed in this article – such as a certified copy of your birth certificate – but these documents will often be required when processing other documents on this list, such as your passport. Be sure to download and read the application form that your nearest German embassy provides for more specifics. Valid passport Naturally, you must have a valid passport in order to apply for a student visa as a foreigner. Make sure that you apply for your passport as early as possible. Some countries – or certain seasons – can take a long time to process passports, especially new ones. If you already have a passport, it’s also wise to check the expiration date on it to ensure that your passport will not expire during your intended period of study. You should get it renewed if there’s a chance it could expire during your normal course of study. If you find yourself in Germany and worrying about your passport expiring, do note that some embassies – such as the U.S. embassy in Frankfurt – will allow you to renew your passport while you are in Germany. However, this often requires you to fulfill additional criteria. It’s easiest to renew your passport in your home country, but if you’re facing an impending emergency, check with your country’s embassy in Germany to see if they can help. Proof of health insurance In Germany, students are required to have health insurance. This means that you will most likely have to apply for and be approved for health insurance in Germany before you arrive. Certain international students can continue to use their public health insurance from their home country while in Germany, and do not need to take out German health insurance. This includes students from other EU countries, and additionally Switzerland, Iceland, Macedonia, Norway, Liechtenstein, Tunisia, Israel, Morocco, Bosnia and Herzegovina, Montenegro, and Serbia. Be sure to check with your current health insurance provider to confirm that they will continue to cover you in Germany. Public health insurance is available to university students under the age of 30 who have not completed more than 14 semesters of school in Germany; costs are usually around €110 per month. If you don’t qualify for public insurance, you’ll have to take out private insurance for the duration of your studies. Fortunately, applying for German student health insurance is not overly difficult, and several providers maintain English translations on their websites. Two notable and popular options for foreigner’s student health insurance include Techniker Krankenkasse (or just TK) and Barmer. Both feature English translations of their websites. One complication that may arise: some insurance providers might ask for proof of your German residence (though as of this writing, it’s possible to register for insurance with both Barmer and TK without this). However, this is an obstacle that can be overcome even if you don’t have an address or proof of one before you arrive in Germany. It’s usually possible to enroll in a health insurance plan using your proof of acceptance to a German university instead. It may also be possible to find a place to live online, and receive appropriate documentation from your landlord fulfilling this requirement before you move to the country. But, if you take this route, you ought to be careful and use reputable sources when pursuing this option. INOMICS has previously written about how you can find lodging in a foreign country when planning to study abroad; these resources can help. Additionally, your university might provide student housing options, particularly if you’re pursuing a Bachelor’s degree. You can also look for student housing that isn’t necessarily attached to a university, for instance through the DAAD’s website (the German academic foreign exchange service). Check with the specific health insurance provider you plan to use for options if they need proof of your German residence. If you can’t get out of that requirement and decide not to use a provider that doesn’t need that proof, these options should work for you. Even if not, there are usually expat websites from your country that can help you. Proof of sufficient funds You’ll need to provide proof that you have funding to support yourself through your studies in Germany before you can be issued a student visa. This requirement can be fulfilled in a few ways. If you are not funding your own studies, options for proving you have sufficient funds include providing proof of your scholarship, grant, or other financial aid, or submitting documents that prove your parents or legal guardians can pay for your living expenses. Again, the exact documents required to prove these options may vary, but your nearest embassy or consulate should provide a list of specifics. If you are planning to pay for your own living expenses, you should open a blocked bank account (Sperrkonto) and store the required amount of savings before you apply. The amount required is intended to ensure you have at least a year’s worth of savings to cover your living expenses in Germany. As of 2023, the amount required is €11,208, though this is subject to increase every few years depending on inflation. The blocked account, once opened, is not easily accessed. It does not function like a savings account. Instead, the German government issues you payments from your blocked account savings as if it were a stipend. All of the money continues to belong to you during this time, and you will receive all of your money back, but you won’t be able to withdraw from the account as you please. As a side note: keep in mind that students are allowed to work, but not for more than 20 hours per week, on a German student visa. So, it’s possible to earn more money to support yourself – even after the blocked account is depleted – but you will have to plan ahead. Proof of acceptance into a German university This document is technically not required to obtain a student visa. If you’re planning to study in Germany but have not yet been accepted into a university, you can still obtain a prospective student visa instead. You can find more information about this below. But, if you have been accepted into a German university already – great! Providing proof of your acceptance will help the student visa process go smoothly. This will usually take the form of an acceptance letter sent by the university where you plan to study. The next requirement applies to you if you do not have a formal acceptance to a German university. If you do have one, you can safely ignore them. Proof of sufficient academic qualifications If you haven’t been accepted to a German university yet, you’ll need to show proof that you have the minimum academic requirements to be admitted to one. This means that you have completed the necessary prerequisite levels of education. For example, if you’re applying for a Master’s degree, you can show proof that you completed a Bachelor’s degree and are therefore eligible for admittance to a Master’s program. Proof of sufficient language skills If you haven’t been accepted to a German university – or if you have, but the language is not your native one – you’ll need to submit proof that you’re proficient in the language of instruction. This most often takes the form of a language test, but your embassy or consulate might accept alternative documents as well. A commonly taken German language test is the TestDAF, while a common English language test is the TOEFL. On this note – while many German degree programs are offered with German as the language of instruction, several major universities – like the University of Cologne and Humboldt University in Berlin – offer certain degree programs in English. It is possible to study in Germany without a high level of German language proficiency, though of course a basic level of proficiency will be instrumental in navigating daily life in Germany. Plus, knowing (or learning) some German will make your time there more fun! Prospective student visas Have you not yet been accepted into a university, but are moving to Germany anyway? Or are you applying for a German preparatory language course before you apply to a university? If yes, then the prospective student visa (sometimes called a student applicant visa) is the type you should be applying for. It has slightly different requirements than the full student visa, and is only valid for three months (though it can be extended for up to six months), whereas the student visa is valid for up to four years. You will still need to apply for a residence permit and student visa if you’re accepted into a full university program at some point. So, it’s worth it to start preparing with the other documents mentioned in this article. Entering Germany without a visa Citizens of certain countries are allowed to enter Germany without having a visa issued. These include but are not limited to Australia, New Zealand, the United States, Great Britain, Israel, Japan, and South Korea. The full list of visa entry requirements by country can be found at the Federal Foreign Office’s website. Despite this, it’s still useful to be prepared and apply for your visa before you leave for Germany. Entering the country without a visa does not mean you’re qualified to live there long-term. You’ll still need to apply for a student visa and a residence permit if you plan to stay for longer than 3 months. If you fail to acquire your visa (or fail to have a visa appointment scheduled) before that time expires, you’ll be forced to return home. If the student visa process seems complicated, just remember that many people have done this before you, and it is very possible to do! This article should help you get started. Although there are many things to think about, and many steps, gathering the required documents and applying is a straightforward process. It just takes some planning. So be encouraged, and remember that it is possible – and worth the effort. Many foreigners have successfully studied in Germany, and valued the experience highly. Viel Erfolg! References Germany’s DAAD website: https://www.daad.de/en/study-and-research-in-germany/plan-your-studies/visas/ Germany’s Federal Foreign Office website: https://www.auswaertiges-amt.de/en/visa-service Header Image Credit: Nikolaus Bader from Pixabay (Free for use under the Pixabay Content License)
So you want to study abroad in Germany, the largest economy in Europe. It’s a great country filled with many high-quality, internationally competitive universities. Plus, lovers of pretzels and sausages will never find a better place to be. Of course, if you’re an international student, you’ll probably need to get a visa before you can go.
Working in Germany: How to apply for a work visa
But, now you might be wondering how to apply for a work visa in Germany if you hope to transition from student to economist, so you can pursue your career while remaining in Deutschland. We’re here to help you begin tackling the process. Read on for information about getting your work visa in Germany, and our tips for making the process go smoothly. But before we start, first note that residents of the European Union, the European Economic Area, and the European Free Trade Association do not need any visa to work in Germany. If you’re from one of these regions, simply find a job, start working, and enjoy life in the largest economy in Europe. First step: Job seeker’s visa Fortunately, Germany has made the process of finding a job in the country after you graduate an available and fairly straightforward option. After you graduate from a German university in the country, you’re eligible to apply for a job seeker’s visa. This grants you a minimum of six months (up to a maximum of 18 months) of stay in the country after you graduate, during which time you can look for a job. Recently graduated students aren’t the only people who qualify for a job seeker’s visa – any reasonably skilled professional has a chance at securing one. But, being a recent graduate of a German university increases the chances that your application will be successful – especially if you have proof of German language skills, too. The basic eligibility criteria to be awarded a job seeker’s visa are as follows: Hold a Bachelor or Master’s Degree. Have a minimum of 5 years’ experience in your field of interest or study (for those who haven’t graduated from a German university). Proof of health insurance; all residents of Germany are mandated to have health insurance. Foreigners should look into health insurance for job seekers, or health insurance for foreigners. Student insurance only lasts through your studies, so once you graduate, you’ll have to re-apply for insurance. Proof of sufficient funds; this means you can prove that you have enough savings or income to afford your living expenses. For job seekers, this takes the form of a blocked account (just as with students), letter of sponsorship from someone promising to pay for your expenses, or a bank statement showing sufficient funds. Language proficiency in either English or German. While only English language proficiency is enough to qualify for this type of visa, German proficiency is desired and will certainly help your chances. Documents needed to apply for this type of visa usually include the following list. But, please note that this list might not be exhaustive for every country. Check with your local Germany embassy to check what their requirements are. They will probably require: A completed German long-stay visa application form. Your valid passport that has at least six months before it expires. Three passport-style photos; these can be easily taken at a photo kiosk in Germany. If you’re not in Germany, many convenience stores and drugstores tend to offer these types of photos. Proof that you have a valid German address to stay in during your job-seeking period. Proof that you have health insurance (you’ll likely have to get foreign workers’ health insurance) in Germany. A cover letter explaining the purpose of your time in Germany, how you plan to find a job, and your backup plans if you don’t find one. Proof of academic qualification, which is typically proof of your previous diploma. If you aren’t a recent graduate or a current student, you’ll need to attach proof of work experience in the field you intend to work in. Students can also attach work experience to improve their chances of being granted a visa, too. Your curriculum vitae (CV). As stated above, proof of financial resources. This could be one of the following: a bank statement, a letter of sponsorship by another person, or a blocked bank account. Nationals of the EU, Australia, Canada, Japan, Israel, South Korea, New Zealand, Norway, Liechtenstein, Iceland, Switzerland, and the USA do not need to apply for a job seeker’s visa. They can enter the country without one (although they could choose to apply for a job seeker’s visa, too), but must obtain the appropriate residence visa to remain in Germany long-term. So, if you’re from one of these regions and already in Germany, you should instead apply for a temporary residence permit at the immigration authority. This office is officially called the Landesamt für Einwanderung, but is also known as the Ausländerbehörde. Nationals of the UK must acquire a job seeker’s visa as of this writing, though they can enter the country without one. Nationals of Turkey must obtain a job seeker’s visa before entering Germany as of this writing. How to apply for a job seeker’s visa To apply for the job seeker’s visa, you’ll need to visit your nearest German embassy or the Federal Foreign Office (Auswärtiges Amt) if you’re already inside Germany. To apply, book an appointment at the appropriate office, bring the required documents, and pay the fee. Then, you must wait for the visa to be processed, which can take up to 3 months according to the German Missions in the United States (although this may vary by country). Of course, be sure to check the list of required documents when you go; our list is representative, but does not cover possible deviations by country. Important information on applying for a permanent worker’s visa If you intend to work in Germany long-term, you’ll need a German “long stay” employment visa. If you find – or already found – a job with a German employer, they’ll sponsor this so that you can remain in the country. You should talk to your employer about the process if this is the case for you. You should also know that if you stay in Germany on an employment visa for at least five years, you’ll then qualify for a permanent residence permit (for more information on this permit, see the Federal Office for Migration and Refugees' website). Germany has three types of long stay work visas that will allow you to stay in the country and work long-term. These are the general employment visa, the special employment visa, and the self-employed visa. Requirements for each of these visas vary. As with the job seeker’s visa, please note: if you’re a citizen of the USA, Australia, Switzerland, South Korea, Israel, Japan, Canada, New Zealand, or an EU country, you can enter Germany without a visa and start the application process after you arrive in Germany. However, you’ll have a limited window to start the process (up to 90 days). It’s never a bad idea to begin the process earlier. How to apply for a German work visa (long stay) To apply for your employment visa in Germany, simply register for an appointment at your nearest German embassy (or, if you’re already in Germany, the Landesamt für Einwanderung or Ausländerbehörde), bring the necessary documents, and pay the fee. Then, you’ll have to wait for your visa to be processed. Remember to check the final, official list of documents with whatever office you intend to apply in; our list includes the usual requirements, but some offices might have varying requirements. Importantly, if you work as a teacher or other educator, doctor, nurse, engineer, or lawyer, or sometimes other positions*, you’ll also need to prove your vocational qualification showing that you are competently and sufficiently trained in addition to the normal documents. Hopefully, this article will help you get started on launching your career in Germany. Remember that many people have completed the process before you; don’t get discouraged if it takes some time. Best of luck! *Other positions include professions related to those listed, master craftspersons of certain fields, and others. You can search for your specific profession at the Bundesministerium für Bildung und Forschung’s website. Alternatively, you can search a list of regulated professions in all EU countries – including Germany – here. However, the best way to check if your specific role is regulated or not is to ask your local German embassy. Sources: https://www.germany.info/us-en/service/visa/employment-visa/922292 https://www.schengenvisainfo.com/germany/visa/employment-visa/ https://visaguide.world/europe/germany-visa/long-stay/job-seeker/ https://visaguide.world/europe/germany-visa/long-stay/employment/ https://visaguide.world/europe/germany-visa/long-stay/employment/ https://www.auswaertiges-amt.de/en/visa-service/buergerservice/faq/weiteres-box/230198 https://www.germany.info/blob/902660/13b92beb6cbf3257cc066e1f212ab853/employment-data.pdf https://www.anerkennung-in-deutschland.de/en/interest/finder/notice?profession=1752 https://eurohealthobservatory.who.int/countries/germany Header image credit: Peter Dargatz from Pixabay (Free for use under the Pixabay Content License)
So, you studied abroad, got your economics degree in Germany, and you’re ready to look for a job in the country. First of all, congratulations! You’re on your way to becoming a full-fledged economist.
In Rousseau’s original theory, a group of hunters track a large stag, finding that it follows a certain path. One hunter alone cannot kill the stag, but if they work together, they can trap the stag and all of them will eat well. However, if their trap is discovered, the stag will flee, and none of them will eat. The hunters agree to lay the trap and wait for the stag. After waiting for several hours with no sign of the stag, along comes a rabbit. The rabbit presents an opportunity for an individual hunter to eat, and it is easy prey. While the rabbit is worth less than the stag, it is easier to hunt, so its payoff in terms of utility is more certain. But if one of them leaps out of hiding to hunt the rabbit, the trap for the stag will be wasted, and the others will starve. Thus, the risk for each hunter is two-fold. Each risks not only that the stag will never appear but also that another hunter will secure the rabbit for themselves. Each hunter must make a choice: trust the others and hunt the stag for a potentially greater payoff, or hunt the rabbit for a smaller but more certain payoff. This scenario can be represented in game theory with a payoff matrix. Let’s look at a simple case of two hunters, or “players”, who face the payoff matrix below. If both players hunt the stag, they will each receive a payoff of 5. If player 1 hunts the rabbit, while player 2 hunts the stag, player 1’s payoff is 4, and player 2’s payoff is 0. Alternatively, if player 1 hunts the stag and player 2 hunts the rabbit, player 1’s payoff is 0, and player 2’s payoff is 4. If both hunt the rabbit, each will receive a payoff of 2. Each player must choose a strategy in the face of uncertainty about the actions of the other player. Player 2 Hunt Stag Hunt Rabbit Player 1 Hunt Stag 5, 5 0, 4 Hunt Rabbit 4, 0 2, 2 A stag hunt dilemma results in two pure Nash equilibria. One Nash equilibrium (Stag, Stag) is Pareto optimal and is the most preferred outcome. This outcome is payoff dominant since it has the highest expected payoff for both hunters. It is also risky because the other hunter may defect and hunt rabbits. The less risky strategy Nash equilibrium (Rabbit, Rabbit) is risk dominant. If one hunter decides to hunt rabbits, the other hunter’s best strategy is to hunt rabbits, too. This outcome is associated with the uncertainty each hunter has about the other hunter’s actions. For these reasons, the stag hunt dilemma is sometimes referred to as a coordination game, assurance game, or trust dilemma. The main obstacle is finding a way to coordinate individual decisions and strategies to achieve the best outcome. The greater the level of uncertainty between the players, the more likely that each individual will choose the less risky strategy, leading to an inefficient outcome. When players trust each other more or are able to establish strong agreements, they are more likely to cooperate. This last point is important for larger Stag Hunts. The more players are in the Stag Hunt game, the harder it is for players to trust one another and establish strong agreements. Therefore, the most socially optimal outcome (Stag, Stag) is harder to achieve as more people are added to the game. Good to Know One example of a stag hunt dilemma may be seen in international politics related to climate change mitigation. Suppose countries are discussing a way to curb carbon emissions. These nations may initially agree upon a particular strategy to reduce emissions. However, each nation faces an individual set of costs and benefits associated with following the agreed upon strategy. Nations then decide between a strategy of “cooperation” and one of “defection”. In 2016, the United Nations Climate Change Conference adopted the Paris Agreement, a legally binding international treaty to reduce greenhouse gas emissions and the global temperature. The agreement required countries to establish five-year national climate action plans. The agreeing countries must also submit reports to an international climate panel about their efforts, progress, and actions taken to achieve the long-term climate goals beginning in 2024. These reports will be used to develop recommendations for countries as they develop strategies for the next five-year cycle. But, even if many countries sign the agreement, some nations may not cooperate because they would receive benefits without having to pay the costs of climate change mitigation. And if nations don’t trust that others will sufficiently reduce their emissions, they may choose to “hunt the rabbit” themselves. Indeed, the Paris Agreement has been so far met with limited success. While many of these nations have taken steps to reduce their carbon emissions, many of them have missed their reduction targets over time. According to data published by the Climate Action Tracker research group, none of the world’s biggest emitters have reduced their emissions enough to stay on pace for the original 1.5 degrees Celsius goal. It seems that the stag remains just out of reach.
The stag hunt dilemma in game theory is a variation on the prisoner’s dilemma. It was developed by the French philosopher Jean-Jacques Rousseau and represents the conflict between social cooperation and personal security.
Sunk costs are by definition a past event, as they’re costs that the individual has already incurred and cannot recover. When you buy a good or service, that purchase becomes a sunk cost as soon as you finish the transaction (assuming that warranties and similar agreements don’t exist, in which case the transaction is finished once these “services” expire). Because the money is gone, it shouldn’t matter for any future decision-making. It’s important to note that sunk costs don’t just have to be monetary expenses. Expenditures of time and effort are also classic examples of sunk costs. For example, if someone starts an engineering degree but realizes they don’t want to become an engineer, the time, effort, and any money spent on the degree become sunk costs for the individual. Ideally, this person should realize they don’t want to be an engineer and choose a degree that will make them better off in the long run, no matter how long they’d been studying engineering. What is the sunk cost fallacy? The sunk cost fallacy is when individuals irrationally factor their sunk costs into their current decision-making. This can cause people (or businesses) to choose sub-optimal outcomes that don’t maximize their utility (or profits) – all because of a decision made in the past that can’t be changed. For example, imagine that you go to a theme park. You buy the weekend pass tickets in advance, and they cover park entrance fees for Saturday and Sunday (assume that they are non-refundable tickets). You spend your Saturday at the park and have a great time – let’s say that you gain 50 units of utility from this. Unfortunately, on Sunday it is forecasted to rain all day. Rain would ruin your park experience since it’s mostly outdoors and you hate rain. You would gain 0 utility from going to the park in the rain. But you’re an avid movie fan, and know that you could gain 10 units of utility from staying home and seeing a movie, avoiding the rain entirely. Knowing this, you, being a fully rational economic agent, choose to spend your Sunday not going to the park. You stay home and watch a movie instead. In this scenario, you end up with 50 + 10 = 60 utility for your weekend activities. It was unfortunate that it rained on Sunday, but you assessed your options and made the best of a bad scenario. But, if you fall prey to the sunk cost fallacy, you might go to the theme park on a rainy day anyway, have a bad day, and come out with less utility than you could have otherwise. This is an irrational decision. Since rain reduces your theme park utility on that day to 0 in this example, your total utility for the weekend ends up being 50 + 0 = 50 if you still go on Sunday. You’d have been better off ignoring your pre-paid Sunday ticket and doing something else instead! It’s psychologically difficult for most people to cut their losses and move on, causing many to become victims of this fallacy. Ironically, this is due to the loss aversion desire most decision-makers share. Most of us probably imagine that it would be difficult to give up on the pre-bought tickets for the second day, even if the rain was certain to come and ruin the experience. That’s because it feels like we’re losing the Sunday ticket – even though we already lost the money used to pay for it. But most economists would agree that giving up on the park and doing something more enjoyable instead is the right thing to do for a rational, utility-maximizing individual. It seems odd to watch a movie when the theme park ticket was already paid for – isn’t it a waste if the ticket goes unused? Our psychology often answers “yes” to this question. But, again, the economically correct answer is “no, because you can’t change the weather and your Sunday park ticket is now a sub-optimal usage of your time”. You must make the best of your current situation given the options and tradeoffs you currently face – past decisions should not affect the rational economic agent because they cannot be changed. Sunk costs in real-world business decisions Sunk costs don’t just factor into individual decision making, of course. They’re also important in business contexts, and shrewd managers will be on the lookout for the sunk cost fallacy in their decision making. Consider the market for cameras. Before digital cameras were invented, people relied on film to develop their pictures. These physical rolls of film had to be developed and processed, usually by a company offering film development services. Clearly, when digital cameras were invented, they greatly improved the photo industry. People could instantly develop and view their photographs without needing to waste money and time developing film. Kodak was once a giant in the camera and film industry. But, in the 1970s a Kodak employee developed the first digital camera and successfully earned Kodak a patent for the technology in 1977. This patent gave Kodak the ability to revolutionize the camera industry and establish itself as a leader in the digital camera market. Instead, Kodak decided to stick with film production and development, as the company already made a lot of money on film. They did not use their digital camera patent until far too late, when other companies had already established themselves as market leaders. It should have been clear to business leaders at Kodak that digital cameras were the future, and that they could have made massive profits by leveraging their digital camera patent. But instead, Kodak leadership considered the sunk costs – their familiarity with and dependence on film – and decided that they shouldn’t do anything. Despite eventually starting to sell digital cameras, Kodak was too far behind other companies. They never recovered their market share and filed for bankruptcy in 2012. It’s easy for a manager – and therefore, a business – to refuse to back out of a certain market or give up on a product when a lot of investment has already gone into it, just like Kodak managers did. When time and effort has been put into something, it’s difficult to take another course of action. Another prime example of the sunk cost fallacy is investment behavior in the stock market. Often, amateur investors believe that a stock will perform well, so they invest their money into the stock. When the stock unexpectedly falls, the amateur investor might still believe that it will do well, and has a desire to “recoup their loss” by waiting until the stock price recovers. Unfortunately, this might never happen, particularly when a company goes out of business. Rather than admit the mistake and reclaim their money at a loss, the amateur investor loses all of their money. Of course, other factors – like a lack of perfect information, and false hope – factor into this kind of scenario as well. But the sunk cost fallacy contributes to situations like these, and it pays to be aware of the mistake. Further Reading For a worthwhile book on sunk costs, look no further than John Sutton’s 1991 Sunk Costs and Market Structure: Price Competition, Advertising and the Evolution of Concentration. In this volume, Sutton uses economic theory alongside econometric evidence to examine the classic assumptions about market structure. Specifically, he examines the game theory-informed oligopoly models that were then advancing the theory of industrial organization. Sunk costs, along with a few other factors (like the intensity of competition) are an important determinant of market structure, according to Sutton. Good to Know This concept also begins to demonstrate how the traditional neoclassical assumptions made in economics are unrealistic. If such a widespread and relatively simple phenomenon has been widely observed, how could individuals be economically rational in every situation? Indeed, behavioral economics asks the simple question: what if humans (as individuals, but also in groups) fail to live up to these classic economic assumptions? The field is a vibrant one that brings economics and psychology together, seeking to augment economic models with deeper understandings of human behavior.
Sunk costs are an important concept in economics. A sunk cost is an expense (of money or potentially time) that someone has already paid in exchange for a good or service; sunk costs cannot be recovered. This cost should therefore not feature in any decision making process, but often individuals fall victim to the “sunk cost fallacy” and factor these costs into their decisions anyway. This article will dive into sunk costs and explain how this fallacy reveals our sometimes irrational human nature.