Which economists are paid the most, and where?
Around the world, economists are paid well compared to other occupations. This may not be a surprise, but how much economists are paid, how different employers compare in terms of pay, and other factors (such as “is an economics PhD worth the pay increase?”) may be less clear to burgeoning economists. This article will shed some light on these questions and more using our data from the 2022 INOMICS Salary Report. Read on to learn more about which employers pay economists the most, regional differences in economist salaries, and more. This article will discuss both academic and non-academic (or “industry”) economists. If you’re curious about the differences between these two general types of economists, you should read our article written by an economist who has worked in both spheres, “Policy or academic economist: which should I become?”. Regardless of an economists’ chosen path, how much can one expect to earn, and which economists earn the most? An Overview of Economist Salaries Globally As mentioned above, many organizations value the specialized skills that economists bring to the table. The below graph constructed from our 2022 Salary Report data shows how average economist pay varies by these different types of employer around the world: Figure 1: Regional average salaries by employer type (USD, PPP-adjusted, thousands) Figure 1 shows average economist salaries by each type of employer in different regions around the world (note that a handful of series are excluded due to sample size issues, i.e. NGO in East Asia & Australasia). Two things stand out from this figure. First, average pay in North America is very high, while average pay in Western Europe & Scandinavia and East Asia & Australasia are the next highest on average. The other regions of the world are more comparable with each other (we will explore each region individually later on in the article). Second, central banks appear to pay economists the most on average. Readers might be interested in the very high central bank salaries in East Asia & Australasia; the entire sample of central bank economists from the region in our survey are located in Hong Kong, which is a high-paying city in its part of the world. Private businesses and governments also pay quite well in general, with the exception that government pay in North America appears to be lower than other options there. Meanwhile, research institutions and NGOs appear to pay the least, though the difference is not stark. While this graph is interesting, one important detail is left out that can skew the results. More educated economists are paid more highly, so the proportion of PhD-holding economists in each role should be accounted for as well to get an even more accurate picture of economist pay. Salary Breakdown by Type of Employer and Level of Education Some employers, like central banks, are more likely to require an economics PhD. Thus, on average these employers offer higher salaries for their highly educated workforce. On this basis, it is useful to differentiate between the level of education when comparing salaries offered by different types of employers. This breakdown can be seen for each region in the following Figures 2 – 9. Note that our survey data lacks a sufficient sample size of Bachelor’s degree respondents to subdivide Bachelor’s economists by employer type. This is partially because most economists attain at least a Master’s degree; it is rare, though not impossible, for an economist to develop their career with only a Bachelor’s degree. These salaries are presented in thousands of USD, and were converted using purchasing power parity data taken from the World Bank1 (PPP conversion accurate as of January 20, 2023). Figure 2: Average salary by position and degree in North America (USD, PPP-adjusted, thousands) In North America, a PhD in economics has a clear payoff in terms of salary, especially for university and private business positions. Government, NGO, and research institution roles pay less of a premium for PhDs, but even these still pay roughly 35-40% higher salaries to PhDs than for Master’s degree holders. The lowest pay gap is at central banks, but these institutions tend to hire only accomplished economists with many years of experience. Getting a job at a central bank with only a Master’s degree likely requires extensive years of experience that early-career economists don’t have. Figure 3: Average salary by position and degree in Western Europe and Scandinavia (USD, PPP-adjusted, thousands) In Western Europe and Scandinavia, a PhD in economics also has a clear payoff in terms of salary for university, research institution, and private business positions. However, other roles feature less pronounced differences. Economists who wish to work in government or in an NGO in Western Europe ought to examine the local conditions and the payoff of a PhD in their country and subdiscipline to assess if it’s worth it. Central banks also do not appear to pay a premium for PhD economists in this region, but again these institutions tend to hire economists with many years of experience, so getting a job at one with only a Master’s degree as an early-career economist might be difficult. Figure 4: Average salary by position and degree in East Asia & Australasia (USD, PPP-adjusted, thousands) In East Asia and Australasia, economists with a PhD enjoy a significant pay increase in university, research institution, and private business positions. Central banks once again pay the most for economists in this region, though no central bankers with a Master’s degree responded to the survey in this region, perhaps suggesting that central banks are less likely to hire economists without a PhD in East Asian / Australasian countries. In this region, a PhD appears to be well worth the investment of time and effort. NGO or charity and government roles are not included due to small sample size. Figure 5: Average salary by position and degree in Central, Southern & Eastern Europe (USD, PPP-adjusted, thousands) In Central, Southern and Eastern Europe, starting a career as an economist with only a Master’s degree is feasible, but a PhD is an excellent investment in terms of salary. Almost every employer type in this region pays a premium for an economics PhD. An interesting exception are central banks, which actually feature higher average pay for economists with a Master’s degree. Again, it’s important to note that getting a job at a central bank usually requires years of experience and demonstrated expertise; it’s possible that central banks in this region do not emphasize a PhD as strongly as extensive work experience when recruiting economists. NGO and charity roles are excluded due to small sample size. Figure 6: Average salary by position and degree in South Asia (USD, PPP-adjusted, thousands) In South Asia, universities and private businesses pay a (relative) premium for economists with a PhD. Economists in these roles stand to gain much from pursuing a PhD. Meanwhile, Research institution pay is about equal for economists with a Master’s or a PhD. A large amount of highly-paid, Master’s degree-holding economists in NGO and charity roles work in this region. In fact, the highest paid role in these regions appear to be for those types of economists. This could be due to foreign investment or aid programs, which typically spend money on projects that industry economists – not academic ones – would manage, or other factors. Central bank roles are not reported here due to small sample size. Figure 7: Average salary by position and degree in Caribbean, South & Central America (USD, PPP-adjusted, thousands) In the Caribbean, South America, and Central America, a PhD in economics appears to be a worthwhile investment. Almost every position pays a premium for an economist with a PhD in this region; those at private businesses and NGOs or charities stand to gain the most from attaining a PhD. One exception is government roles, where economists with a Master’s degree slightly out-earn PhD economists on average. Figure 8: Average salary by position and degree in Middle East, Central Asia & North Africa (USD, PPP-adjusted, thousands) The Middle East, Central Asia, and North Africa is similar to the Caribbean, Central and South America region. Here too, a PhD in economics pays off very well. Every employer except for NGOs pay a premium for an economist with a PhD in this region. The highest earners appear to be PhD economists in universities and in government, alongside Master’s degree holders in NGOs. But, in this region NGO pay is very high. Like with South Asia, it’s possible this is due to foreign aid or investment being sent for projects or investments that are closely related to industry economists’ jobs, which in general may not require as much education as academic economist roles. Figure 9: Average salary by position and degree in Africa (USD, PPP-adjusted, thousands) Africa is a unique region when it comes to economist pay. Pay in government and for private companies follows a similar pattern as other regions, where a PhD in economics grants a sizeable increase in pay. Universities still follow this pattern, though pay at universities in African countries typically appears lower compared to other economist jobs in Africa relative to the rest of the world. Besides this, economists with a Master’s degree earn decent pay in other roles. Unless one wishes to work for the government or a private organization in Africa, a Master’s degree in economics might be sufficient. The most highly paid academic economists out-earn most industry economists It may appear from these graphs that academic economists earn less money than their counterparts in industry. While the value of a PhD is clear in certain cases, like with high private company pay, it might not be clear whether it’s worth it pay-wise to enter academia. However, these averages by employer type mask one important fact: professors of economics earn much more money than non-professor-level economists employed at universities. In fact, professors of economics earn salaries that are comparable to the highest earners in industry. This can be seen below in Figure 10: Figure 10: Average salaries for economist jobs globally (USD, thousands, PPP-adjusted) Figure 10 shows that industry positions pay more than academic positions on average, but economics professor (and to a lesser extent, associate professor) salaries are comparable to high-paying industry positions. Professors of economics on average are only outpaid by executive leadership roles. Thus, new economics PhDs should not be discouraged from entering academia by somewhat lower salaries shown in the regional breakdowns. Although industry economists will out-earn most academics in junior roles, a full professor of economics salary makes up the difference, only out-earned by executive leadership roles. Are you curious to learn more about economist salaries? Help INOMICS analyze even more about the state of pay in economics by answering our anonymous Salary Survey. It only takes a couple of minutes and is available here: https://inomics.com/salary-survey. After answering the survey, you’ll have the option to subscribe for early access to the results, published in the fourth quarter of each year. And if you’re looking to take the next step in your career as an economist, we can help. Check out available courses, jobs, and programs to find the next skill, degree, or job in your path as an economist. No matter your choice of degree or position, economists have much to offer – and their compensation often reflects their valuable skills, and the contributions they make to the economy, and society, around them. The above article first appeared in the INOMICS Handbook 2023, which you can download on our site. Sources: 1: https://data.worldbank.org/indicator/PA.NUS.PPP. PPP data originally accessed on January 20, 2023. PPP data may have changed since that date. Header image credit: wirestock on Freepik/Magnific (free license)
The following article first appeared in the INOMICS Handbook 2023. Download the INOMICS Handbook
The INOMICS Questionnaire: Fratzscher vs Gómez Pineda
The interview with Dr. Gómez Pineda offers an interesting look into the thoughts of an accomplished central banker. For early-career economists in particular, it is not only enlightening but full of essential advice, not least of which is the importance of continuous learning and reading. Our advice – start your reading here! Javier G. Gómez Pineda is Senior Economist (Investigador Principal) at Banco de la República (the central bank of Colombia). He also teaches Monetary Economics at Universidad del Rosario in Bogotá. His research interests are in Monetary Economics and International Economics; he is author of the textbook Dinero, banca y mercados emergentes, los países emergentes en la economía global, 2010, Ed. Alfaomega; and he holds a PhD in Economics from the University of Chicago. His interview responses to Dr. Fratzscher’s queries are below. Marcel Fratscher: What is your favorite place on earth? Javier Gómez Pineda: To start with, I would like to express my gratitude for this interview and having the opportunity to share my thoughts. My favorite place on earth is where you can share with your loved ones. To me, it is home. As for places you get to be around as an economist, I would say my favorite place would be the macro seminar at the University of Chicago. As a student at Chicago, I had the chance to see several papers being greatly improved by comments from the audience. I recall once or twice Gary Becker gave incredible micro feedback to two macro papers. MF: Outside of economics, what occupation would you choose if you could be absolutely anything? JGP: I think I would be a civil engineer to help improve infrastructure in Colombia. As an economist, in a way I happened to be sort of a civil engineer when I got involved in the implementation of the inflation targeting framework in Colombia back in 2000. However, I would choose in the first, second and third place to be an economist. MF: What is the virtue you appreciate the most? JGP: An important virtue is that of studiousness. At whatever level you consider, studiousness enables you to better understand and help improve the world you live in. Working in research and teaching is a privilege and a continuous opportunity to exercise this virtue. Students should keep in mind that knowledge is not something that ends at graduation, you always have to keep learning and maintain yourself actively, even if you are not in a research or teaching job. MF: Your all-time favorite figure in economics? JGP: Robert Lucas. Thanks to the Lucas critique, we no longer rely on those unsafe reduced-form econometric equations. It is also thanks to the rational expectations revolution that we now routinely use rational expectations DSGE monetary policy models, although we have had to amend them with frictions so that they are not too forward-looking. Finally, I think the methodological approach of welfare evaluation is one that continues to bear fruit as progress continues in macroeconomics. MF: Your #1 economics blog? JGP: I read VoxEU CEPR to learn about the work of several macroeconomists who share their views there. Also, as I drive to teach my course on Monetary Theory, I listen to the Macro Musings podcasts of the Mercatus Center of George Mason University. MF: Your ideal student? JGP: Every student is special and different in his or her own way and worth the best teaching effort. That said, in my opinion, the ideal student is the one that later becomes your co-author. That turn of the matters means that the student had been motivated enough to learn the material and develop his or her vocation, hopefully becoming a better version of him or herself. MF: What should be done to address gender bias in research in economics? JGP: Although I am not very knowledgeable about this topic, in my humble opinion I understand that the gender bias in research in economics could be expected to improve as a consequence of the influence of current female role models on school enrollment. There are currently outstanding role models in academia, such as Esther Duflo, as well as in policy institutions such as the IMF, the Fed and the ECB, such as Kristalina Georgieva, Gita Gopinath, Janet Yellen, and even cases of lawyers working on economic issues, such as Christine Lagarde. MF: What is the most misguided research agenda in economics? JGP: Misguided literally means with the wrong guide. When we listen to the weather forecast in the morning, we do not get yesterday’s weather, but a forecast for the future of the day or the week. Yet our models and analysis have too often been retrospective, backward looking. Thanks to the rational expectations revolution and the view of economics as something you can put in a computer and run, as Robert Lucas has said, we have come to routinely run prospective, forward-looking models that enable us to situate ourselves in what matters. At the other extreme, we have also had to amend overly forward-looking models because they lose touch with reality, with the data. In that sense, a well-guided research agenda means a fair amount of forward-looking weight in our models and analyses. MF: What is the most promising current research field or issue in economics? JGP: Macrofinancial policy and its effect on financial deepening would be an area with high potential, particularly in emerging markets and developing economies. We saw the cost of loose macroprudential standards on financial crises in emerging and developing economies in the 1997-1999 financial crisis and in advanced economies in the 2008-2009 financial crisis. Since then, several macroprudential instruments have been put in place and the amplitude of the financial cycle has been tamed. Although good in themselves, these policies could have subdued financial deepening and hence growth. Then, the challenge is two-fold: a stable financial system and progress in financial deepening. MF: Where does economic research have the most influence on policy-making? JGP: The most influence has definitely been in monetary policy. The controversy between monetarists and Keynesians that lasted for about the complete second half of the past century led to a fruitful synthesis, the New Neoclassical Synthesis (NNS). It is a practical theory for monetary policy making, a language for communication between monetary policymakers and the core of the forward looking operative procedure of central banks. As someone [ed: the psychologist Kurt Lewin in 1952] once said, there is nothing more practical than a good theory; this point of view I think applies very well to the NNS and its practical use in monetary policy. MF: On what issues should policy listen more to economists? JGP: Economics has much to contribute to any field that involves incentives. Rational choice is our grand piece of theory that we can export to contribute to other disciplines. The homo economicus behaves rationally and can also respond to changes in incentives, as dictated by policy. One policy field where incentives can induce change in behavior is in climate policy. Incentives should be paramount in articulating and implementing tax and subsidy climate policies and in inducing change in behavior. Another area where incentives can be put to work at great benefit is road traffic. Congestion taxes can contribute to a more efficient use of roads as a public good that is in short supply. I am sensitive to this issue given my long commuting times in Bogotá. Finally, market competition can help improve living standards in all markets that are not natural monopolies. Examples are the educational and health systems. MF: What is your career advice to a young economics researcher? JGP: My advice would be to always read with a humble attitude rather than being too critical. Read, always aiming to learn from your colleagues. Read and read a lot. Then you will find where you would like to put your effort. Then think, think about your arguments and theses, and then, only then, be critical - of your own work. To improve your thinking, engage with others and work in groups. The above article first appeared in the INOMICS Handbook 2023, which you can download on our site.
The following article first appeared in the INOMICS Handbook 2023. Download the INOMICS Handbook President of the DIW Berlin and well-known macroeconomist, Prof. Dr. Marcel Fratzscher poses the questions for accomplished central banker and author Dr. Javier G. Gómez Pineda in this latest INOMICS interview, where we ask economists for their thoughts about life and economics. Dr. Gómez Pineda graciously took to the spotlight in this latest round. The interview, dubbed Fratzscher vs. Gómez Pineda, dives into the importance of the Lucas critique, role models for women in economics, the challenges with maintaining global financial market stability (while still allowing for growth for emerging economies), how economics can contribute to climate policy, and more.
When goods can only be enjoyed by the buyer – or the intended gift recipient – after it’s been paid for, as is the case for most goods, the good is considered excludable. It might seem that almost every good is excludable. After all, when you buy something, it’s yours to use. But, there are goods where access by non-payers cannot be prevented, often because it is prohibitively expensive to do so. Economists call these non-excludable goods. Examples of non-excludable goods include many publicly available goods and services, like public roads, beaches, and national defense. These are widely accessible to everyone, even to people who don’t pay for the good or service in question, and it is prohibitively difficult to prevent any specific individuals from accessing them. For example, although some individuals dodge or underpay their taxes, they still benefit from their nation’s national defense spending, and can’t be easily excluded from that. And they can still access public roads at any time. Likewise, air is nearly impossible to exclude from specific individuals. Air is present everywhere and is necessary for life. To charge for the right to breathe air would be very difficult to enforce, probably more trouble than it would be worth, and (of course) morally wrong. When goods are non-excludable like this, it can create certain problems. For instance, a Tragedy of the Commons situation may arise when a shared space is overused. Because nobody can be prevented from using it, ownership is unclear, so there is a lack of responsibility in cleaning and maintenance of that space. Over time, the space deteriorates due to overuse and neglect. An example of a non-excludable resource that might experience a Tragedy of the Commons situation is fish in a lake. As more people fish in the lake, there are fewer fish for others to enjoy. The water might also become more polluted from fuel runoff and plastic waste products as people carelessly use the space. But, it is extremely difficult and probably not feasible to prevent specific individuals from going to the lake and fishing. Of course, much of the time goods have limited access that is enforceable. This means that the only way to enjoy the good is by paying for it; those who do not pay cannot access the good (again, unless someone else pays and gifts it to them), and it’s easy enough for the producer to prevent non-payers from accessing the good. Examples include golf club memberships, cable TV subscriptions, bananas, and shoes. You cannot legally enjoy a Nike Air Jordan shoe without first buying it, and it’s easy for Nike to prevent you from wearing Air Jordans unless you pay for it. Thus, shoes are an excludable good. Good to Know While the distinction between excludable and non-excludable may seem cut and dry, it’s possible that non-excludable goods can become excludable. And, different goods might be more or less excludable than others. To continue using the lake example, a lake located on publicly accessible land would be non-excludable as discussed. However, if the land was purchased, made private, and fenced in, that same lake could be considered excludable. This process would probably be expensive, though it is technically possible; many resorts, golf clubs, or wealthy landowners enjoy private property that may feature a lake. Small bodies of water are typically excludable in this manner. But, very large lakes would probably not be worth fencing in or blocking off due to their size. Therefore, one would expect a large body of water to be “more excludable” than a small one, despite the fact that both could theoretically be fenced off. This is often the case with excludable goods – some are more excludable than others. When economists describe a good as excludable it’s often not worth the cost of preventing others from accessing the good – even if it’s theoretically possible. Further Reading Excludability is just one characteristic that defines certain types of goods. Another closely related concept is rivalry. Together, rivalry and excludability define four categories of goods: public goods, private goods, common goods and club goods. Read the linked articles for more information on each of these.
Ordinarily, people buy goods in the market, and then they consume those goods for themselves. This increases their utility and generates consumer surplus. Usually, this process only requires a willing consumer and producer who agree upon a price. Other individuals aren’t benefited or harmed from this exchange (unless externalities are present), nor can they enjoy the good or service that the buyer paid for (unless the buyer gives it away as a gift).
But elasticity is not the only way economists classify goods. Another important characteristic to consider is how consumption of a good affects its ability to be consumed by others. Specifically, if consuming a good reduces the ability of other people to consume it – or if a good cannot be enjoyed by more than one person at a time – it’s called a rival good. Economists might also say that this good exhibits “rivalry in consumption”. Rival goods include many everyday items, like drinks and food. As someone drinks their beer, there is less of that beer for someone else to consume. Similarly, if your friend eats a cookie at a party, you cannot enjoy that cookie – it’s gone. Clothing items are also rival. Even though you could lend your favorite scarf to a friend, when you’re wearing the scarf, nobody else can. Therefore scarves (and most other clothing items) are considered rival goods. Other examples of rival goods include tickets to a concert, seats in a restaurant, and booking air travel. When you purchase or reserve one of these goods, you consume a spot that another person cannot claim. It might seem like every good is rival - after all, if you buy something, it’s yours. But there are many goods and services that don’t follow this pattern. Consider a streaming service. When you pay for a subscription to a streaming service, you’re able to consume as many movies or TV shows from that service as you want. But no matter how much you watch, it will not diminish the amount of movies left for other people to enjoy. Goods like this that lack rival characteristics are simply known as non-rival goods. Other examples of non-rival goods include a fireworks display, music albums, and national defense. In each of these cases, enjoying the good or service provided does not diminish the amount available for others to enjoy as well, nor does it prevent another person from enjoying the good at the same time. Good to Know This rival or non-rival characteristic of goods may seem similar to the concept of externalities, but they’re not the same. For example, it might be argued that a negative externality is produced when someone consumes a cup of coffee, leaving less coffee for others. But this logic is flawed. Someone enjoying their cup of coffee does not produce a negative externality (such as loud noise, pollution, etc.) for others. While the cup of coffee is rival – once consumed by its buyer, it cannot be enjoyed by anyone else – it does not actually affect others outside of this interaction. Consider an individual wandering by who isn’t involved in the market for coffee; the coffee lover finishing their cup doesn’t harm or benefit this individual in any way. Further, recall that the definition of an externality is a benefit or cost that is not factored into the market price. When private goods (like coffee) that do not otherwise create externalities are sold to an individual consumer, the market price already reflects the cost of production and overall demand from every individual participating in the market. Barring situations like monopoly, price ceilings, or other deadweight loss-causing market interventions, the perfectly competitive market price will nudge individuals to consume the socially optimal amount of coffee. This means that an externality is not present. Further Reading Just as goods can be rival or non-rival, goods can also be excludable or non-excludable. While these may sound like similar terms, they measure different things. Together, rivalry and excludability define four different types of goods. These are private goods, public goods, club goods, and common goods. See the article on excludable and non-excludable goods for more information about this characteristic.
In the modern economy, consumers exchange money to acquire goods and services that increase their utility. There are many different kinds of goods and services, and many ways that economists can classify them. For example, price elasticity of demand and income elasticity of demand can tell economists whether goods should be considered normal, luxury, Veblen, inferior, or Giffen goods.
Why are top management consulting firms increasingly hiring Economics PhDs?
Every Economics PhD student has contemplated a career outside academia at least once. There are multiple alternative options available to trained economists, and the INOMICS Salary Report shows that about 30% eventually opt for the private sector (though the true number may be higher, as INOMICS has a high proportion of academic users). In recent years, top consulting firms (such as the “Big 4”: KPMG, PwC, Deloitte, and EY) have increasingly been hiring Economics PhDs, many through specifically designed advanced degree pipelines – a trend that may surprise some. But why are these firms seeking out economists for their consulting teams, and what benefits do economists bring to the table? I spoke with a human resources manager from one of the Big 4 firms to learn more on the matter, and to help thousands of Economics PhDs like myself know our options better. First, it's important to reiterate what an Economics PhD entails to figure out why these students are in demand. Economics is the study of how societies allocate scarce resources to satisfy unlimited wants and needs. An Economics PhD program involves advanced coursework in microeconomics (the study of individual decision-making) and macroeconomics (the study of the economy as a whole), as well as training in statistics, econometrics (the application of statistical methods to economic data), and mathematical modeling. PhD students also typically conduct independent research, which requires them to develop analytical skills, conceptual thinking, and the ability to identify patterns and trends in large amounts of data. Management consulting firms are known for their ability to help businesses solve complex problems and achieve their strategic objectives. Therefore, the interview process typically includes several rounds with at least one case interview; this type of on-the-spot analysis isn’t a skill that’s traditionally taught in economics courses. So why are they interested in hiring Economics PhDs? Here are a few key reasons: Strong analytical skills Economics PhDs are trained to analyze data and identify patterns in the economy and society, discovering and testing trends that may not be immediately apparent. They are also skilled in developing hypotheses and testing them using statistical models. Economics PhDs are trained to make sure no assumption is left untested, and no conclusion is reached unproved. This makes them valuable assets to consulting teams, who often work with large amounts of information and data, and need to make sense of it quickly in order to provide actionable insights to clients. Image credit: our-team on Freepik.de Familiarity with economic theory Thanks to their rigorous training, Economics PhDs deeply understand economic theory. It provides them with a framework for understanding how different factors may impact a client’s business on both the microeconomic (individuals and firms) and macroeconomic (industry and economy) levels. This theoretical background can be especially valuable when working with clients in industries that are undergoing significant structural changes or facing new challenges, such as disruptive technology or geopolitical tensions. Someone who studied economics would be able to identify these changes and predict future impact on business. Data science skills PhDs with a degree in Economics gain diverse data science skills in graduate school, including quantitative modeling and data visualization skills. They are trained to solve problems while ensuring that the results generated from statistical models are valid and reliable. Articulating methodology (‘Why should we employ this model?’) and conducting a series of robustness checks (‘Can we trust the results?’) are standard tools used by Economics PhD students when doing economic analysis. These skills can be especially valuable when working with clients who need data-driven insights to make key business decisions. Ability to conduct rigorous research Doctorate programs in economics typically require students to conduct independent research, which takes several years to complete. Economics PhD students design and manage their own research projects (or parts of them) as well as their own personal time and resources to keep the work going. This is a crucial skill for a consultant, as the nature of their job dictates independent work and the ability to multitask between projects. Economics PhD graduates come already prepared for this challenge. Strong communication skills Effective communication is key in consulting work, as consultants need to be able to clearly explain complex concepts and findings to clients who may not have a background in economics. Economics PhDs are often skilled communicators, as they are used to presenting their research to both academic audiences and non-experts during graduate studies. Breadth of knowledge While Economics PhDs are often experts in their particular field, they also have broad knowledge of other areas of economics, and related fields like finance and statistics. This breadth of knowledge can be valuable when working with clients who operate in diverse industries or who face complex challenges that require a multidisciplinary approach. Last but not least, corporate clients like working with smart people, and having a PhD on the team can be a big boost to credibility. Several qualities set consultants with a PhD degree in Economics apart: rigorous field knowledge that Economics PhD students acquire during their training and through their independent research, scientific integrity, global outlook, and a curious mind that is on a constant search for an intellectual challenge. Seeking a consulting job as an Economics PhD Given these benefits, it's not surprising that consulting firms are increasingly seeking out Economics PhDs for their teams. In fact, some firms have even started recruiting directly from PhD programs, offering students the opportunity to transition their economics career from academia to consulting. If you’re coming from an economics PhD program and interested in this type of position, be sure to highlight these skills on your resume. The interview process for consulting positions typically includes several rounds with at least one case interview, where you will be put on the spot to solve one or more hypothetical business challenges. There are numerous books and online resources to help prepare for these specifically. As businesses face increasingly complex challenges, the need for data-driven insights and rigorous analysis will only continue to grow. In that sense, Economics PhDs bring unique skills and expertise to the table. Be sure to fully consider your employment options, and consider whether a consulting firm hiring economics PhDs could be the right place for you. The above article first appeared in the INOMICS Handbook 2023, which you can download on our site. Header image credit: Drazen Zigic on Freepik.de.
So what are indifference curves exactly, how are they created, and how should they be interpreted? Indifference curves are usually drawn for individuals. It is assumed that the individual is rational, has consistent preferences that don’t change, seeks to maximize utility, and that their utility increases with more consumption. These assumptions are useful because they allow us to draw usable and meaningful indifference curves where each curve represents the same level of utility at every point on the curve. This is an important point that bears repeating: individuals achieve the same level of utility at any point along a single indifference curve. As can be seen in Figure 1, each indifference curve is a line on a graph, where the axes represent goods or services that the consumer must choose between. Each line plots the combinations of products that would offer a specific level of utility for the individual. In this case, the indifference curves drawn are U and U’. Figure 1: Standard indifference curves with budget constraint Usually, the axes represent two different products or services the consumer can spend their budget on, often labeled Good A and Good B or X1 and X2. But sometimes, economists lump together “all products except X1” as one axis, and X1 as the other axis. This setup allows economists to study a consumer’s demand for X1 in relation to everything else the individual could spend their money on. The points in the graph, and on each indifference curve, represent different mixes of products that the individual can consume. For example, point (qX1,qX2) is the point where the individual consumes qX1 units of good X1, and qX2 units of good X2. Economists call points like these “product bundles” or just “bundles”. Every point in the graph represents a combination of two goods that constitutes a bundle. As another example, the origin – the point (0,0) – is the product bundle where the individual consumes 0 units of good X1 and 0 units of good X2. An important point to know about indifference curves is that curves higher and to the right are always better (more desirable; yield higher utility) than curves lower and to the left. This is because higher indifference curves contain larger, better bundles that the individual can consume (remember that we assume individuals get more utility from consuming more). Therefore, every point on indifference curve U’ is more preferred to any point on curve U, because any point on curve U’ yields more utility than any point on U. In more mathematical terms: because the axes are increasing in X, and because utility increases as the individual consumes more (or, as X increases), indifference curves further from the origin of the graph represent higher levels of utility. Some indifference curves are more preferable than others. But are some bundles on a given curve better than any other bundles on that curve? No – recall that the individual achieves the same level of utility for the various bundles along a single indifference curve. This is where indifference curves get their name from; because the individual’s utility is the same at every point along the curve, they are indifferent between consuming any combination of X1 and X2 that places them on the same curve. For example, consider someone – Paula – who’s deciding between bundles of apples and oranges, and values them equally. Paula would equally enjoy eating 4 apples and 2 oranges as eating 2 apples and 4 oranges, so both of these points would be on the same indifference curve – perhaps like U. But, she would strictly prefer eating 6 apples and 4 oranges to either of those earlier options, so this point is on a new, higher indifference curve – like U’. Finally, included in the graph is a straight, linear line. This represents the consumer’s budget. People can only consume what they can afford; this is represented by the budget line. As noted before, a person will choose the highest indifference curve they can reach given their budget. For the indifference curve to be affordable, it must touch the budget line at one point at least. This means that the individual represented by our graph will choose the optimal consumption bundle (qX1,qX2), resulting in utility U. To get to this point, the person will choose to buy qX1 units of X1 and qX2 units of X2. On the indifference curve IC’ the individual would obtain even higher utility U’, but unfortunately this indifference curve is not attainable given the individual’s current budget M; it does not touch the budget line anywhere. Good to Know This still leaves the question of how indifference curves are made. How do economists draw one in real life? Indifference curves are generated from a utility function. These are mathematical formulae that represent the preferences of a single individual. To make an indifference curve for a consumer, an economist sets the consumer’s utility function equal to a constant, and plots every point in the function equal to that constant. This maps out a curve like U’. Of course, it’s difficult to know people’s utility functions in real life. The best method for discovering them is to observe the ways that people spend their money and their time. This is partly why marketing and market research are so important for many businesses. If companies can learn people’s preferences (or influence them), they can attract more customers by designing products they enjoy the most. Further Reading Indifference curves are a foundational concept, particularly in microeconomics, partly because they can actually be used to create demand curves! To see how, consider again the graph above. If X1 represents oranges, and X2 represents every other good in the economy, the indifference curves represent a single consumer’s preferences for oranges compared to everything else they could buy. In other words, this is the consumer’s demand for oranges! So, to calculate a demand curve for a good or service, an economist can combine every individual’s indifference curves for good X1. The resulting curve incorporates everyone’s preferences, and so tells the economist how much of X1 will be demanded compared to every other good in the economy. Of course, this process can be more difficult than it sounds. To learn more about the relationship between indifference curves and the demand curve, check out Chapter 6.4 of Principles of Microeconomics by the University of Victoria.
Indifference curves are a common sight in economics courses. They’re a foundational and helpful concept for economics students because they help economists easily depict people’s preferences. This can show the economist how someone is likely to spend their budget, what they’ll prioritize in order to maximize their overall happiness and well-being (or utility), and more.
But this is not a smooth process; jobs are lost and industries are destroyed as new jobs and new industries are created. The concept of creative destruction is best illustrated with an example. Creative destruction in action Consider the market for movies. In the past, movies were viewed in the theater or purchased on VHS or on a DVD. There was an industry built around renting or buying movies in VHS and later DVD format for home viewing. Blockbuster was a major retailer that had a big movie rental business, though they sold other goods and services as well. At its peak in 2004, the chain had over 9,000 stores and was worth more than $5.9 billion (USD). But today, Blockbuster has just one store left in the entire world (located in Bend, Oregon in the US). The store even draws tourists who remember the iconic chain and want to visit!1 So how does a massive, successful, multinational business almost entirely disappear in just a few years? Creative destruction is to blame. Netflix was founded in 1997 and at first was in the business of sending DVDs by mail. In 2007, Netflix launched its online movie streaming service, which allowed customers to watch movies on demand without leaving the comfort of their homes. It also eliminated the need to return a DVD, which was a chore many people disliked doing. While streaming over the Internet is incredibly common today, Netflix was the first major company to succeed at offering online streaming video services. Streaming a TV show or movie over the Internet is more convenient than renting a DVD for the vast majority of people. As such, when the technology became widespread, people flocked to online streaming services and abandoned DVD rentals. This caused companies like Blockbuster to lose money and go (almost completely) out of business. The movie rental business today is a shadow of its former self, having been replaced by online streaming. The pros and cons of innovation The advent of streaming resulted in an increase in overall welfare for society. It made movies more accessible for everyone and decreased the time investment required to get a new movie as well. This might sound like a Pareto improvement, but it wasn’t. That’s because people who relied on the old movie rental industry for their livelihoods were potentially harmed more than helped by the rise of streaming. As old, now-obsolete industries go out of business because of new, better technologies or services that are introduced, many people in the old industries lose their jobs. This period of unemployment is hard for most people since it results in a utility-reducing loss of income and a period of uncertainty when looking for a new job. Some of these workers might not recover their original level of utility, especially if they had specialized skills that are no longer needed. Therefore, some people are made worse off even if society overall is made better off. This is why Joseph Schumpeter named the process “creative destruction”. While new things are introduced and invented that improve society, in a capitalist system there are ultimately individuals who lose out because of this progress, too. And there is no guarantee that displaced workers will find new careers that are as fulfilling as their previous ones. To recap, innovation successfully permeates markets and has positive overall welfare effects, but it comes at a cost. Elements of this cost are, for example, unemployment and loss of capital as mentioned above. Thus, the term “creative destruction” tries to convey both meanings. Innovation is the utility-improving fruit of creativeness, and destruction is its utility-diminishing by-product. Creative destruction is not all bad. In fact, innovation is one of the core ingredients of the Cobb-Douglas production function. Economists agree that technological progress created by innovation is a good thing for society, as the positive effects of innovation almost always outweigh the destructive aspects. Overall, innovation and the process of creative destruction allow our economies to grow and be made better off overall. Further Reading The phrase “creative destruction” is attributed to Austrian economist Joseph Schumpeter, who coined the term in his 1942 book Capitalism, Socialism, and Democracy. He described capitalism as “the perennial gale of creative destruction”, referring to how the progress of innovation and economic growth causes upheaval in certain economic sectors and can create misfortune for some even as it improves society overall. His work is worth a read; it’s considered a classic not only in economics but also in the social sciences in general. References 1: https://www.businessinsider.com/rise-and-fall-of-blockbuster
“Creative destruction” in economics is a phrase that describes how the economy reacts to change. When innovation introduces new technologies, the economy moves to phase out outdated or obsolete goods and services in favor of new, more efficient ones.
Economic Development, Innovation and Growth (JEL O)
Silent Success: How Quiet Quitting Can Boost the Economy
Rather than pushing ourselves to the brink of exhaustion, quiet quitting involves recognizing when something is not productive and making the decision to step back and reassess. This can lead to greater productivity, increased creativity, and ultimately, a stronger economy. In this article, I'll explore how quiet quitting can affect the economy. I'll delve into the benefits of taking a step back, the impact it can have on our mental health, and the potential economic benefits of a more balanced approach to work. So sit back, take a deep breath, and let's explore the power of quiet quitting. Understanding quiet quitting Quiet quitting involves a strategic and intentional decision to let go of unnecessary tasks, projects, or overtime work in order to redirect time and energy towards more fulfilling or productive endeavors. At its core, the concept refers to withdrawing from tasks beyond one’s assigned duties and becoming less personally invested in work. Quiet quitters continue to fulfill their main job responsibilities, but they turn down activities that involve going above and beyond. No more working late, showing up early, or participating in non-mandatory tasks. Simply no extras. It’s worth mentioning that there's an irony in calling it "quitting" when employees are still showing up for their jobs and doing their work. It seems unreasonable that current society glorifies constant work and a hustle culture mentality, to the extent that performing the tasks expected of you within your designated work hours and then leaving is now being referred to as "quitting". The quiet quitting trend did not appear by accident; its emergence is linked to the COVID-19 pandemic. Due to the pandemic, many individuals lost their jobs, resulting in a smaller workforce than before the outbreak. Although some people have secured new employment or been rehired, existing workers have been experiencing more pressure as some have been tasked with additional responsibilities that laid off workers used to fulfill. In other words, the concept of quiet quitting seems to be an extension of the Great Resignation, where people are standing up (and walking out) against the expectation of working longer hours without any extra pay. In contrast to the short-lived phenomenon of the Great Resignation, it remains to be seen whether the quiet quitting trend will become a more permanent movement that will bring about changes in the way people perceive work and labor practices. The eventual impact of quiet quitting may depend on whether workers can hold leverage over employers for long enough to embed some of these practices into the workplace. The economic benefits of quiet quitting The traditional view of quiet quitting states that it is bad for the economy, which makes sense on a surface level. When people become disengaged from their jobs, it can lead to decreased productivity and therefore lower economic growth. However, this view ignores the potential benefits of quiet quitting. When individuals withdraw from unnecessary tasks or projects that are not aligned with their job description or goals, they are able to redirect their energy and skills. This can lead to increased mastery over their role, heightened creativity, and more opportunity for innovation, which can ultimately benefit their organization and by extension the economy, even leading to the creation of new businesses or industries. When individuals quit tasks or unnecessary work projects, this gives them more space and time to develop their skills and pursue their passions. In other words, when individuals allocate their time and effort towards more significant endeavors, it can potentially result in the creation of fresh business ventures and inventive personal projects. This shift in focus has the potential to cultivate a thriving entrepreneurial culture, which can lead to increased national productivity, creativity, and innovation on the macro-level. Furthermore, quiet quitting can lead to increased happiness and well-being for workers, which can have positive economic effects. When individuals are happier and more fulfilled, they are more productive and perform better in their jobs. By letting go of unnecessary tasks and being more psychologically invested in their core responsibilities, employees could experience an improvement in performance. Balancing work and life improves mental health and wellbeing The World Health Organization acknowledges burnout as a work-related condition that manifests as feelings of depletion, exhaustion, cynicism, mental detachment from work, and reduced productivity. Burnout is a severe consequence of excessive work and can cause lasting physical, emotional, and mental health problems. Of course, overworking will lead to increased production levels which can be observed immediately in the short-run. However, in the long-run when employees suffer burnout, the impact of such a mental state is likely to cancel out any positive outcomes reaped in the short-run. Therefore, we can safely say that overworking is likely to cause a long-term decline in performance due to eventual burnout. Preventing employee burnout is extremely important for all organizations, because its repercussions can be destructive. Establishing a healthy working environment where both employers and employees embrace the concept of “quiet quitting” – or stated another way, where the work relationship is clearly defined and where overwork is discouraged – could cause major improvements in the workplace as well as our personal lives. With a mindset that is not driven by stress, work pressure, and unhealthy levels of overworking, employees would find themselves performing better and less likely to burn out. This would lead to increased innovation, economic growth, and better mental health and wellbeing. The benefits of improved work-life balance Quiet quitting aims to provide healthy boundaries between work and personal life, so that there is clearly delimited time for both. Studies have found that work-life balance is linked to better mental health overall. Some of the most prominent studies showing this relationship include the following: A study published in the International Journal of Environmental Research and Public Health in 2020 found that employees with better work-life balance reported lower levels of psychological distress and higher levels of life satisfaction (Shimazu, Schaufeli, Kamiyama, & Kawakami, 2020). A research paper published in the Journal of Applied Psychology in 2017 found that employees who had greater control over their work schedules and who were able to take time off when needed experienced less psychological strain and burnout (Hill, Hawkins, Ferris, & Weitzman, 2017). A study published in the Journal of Occupational Health Psychology in 2008 found that employees who perceived their work as interfering with their personal and family life experienced higher levels of emotional exhaustion and lower levels of job satisfaction (Greenhaus & Powell, 2006). Better work-life balance also involves disconnecting your self-worth from your job. This can be difficult because when work is your primary focus, it’s hard not to associate your value as a person with it. Yet, it’s important to realize that work failures or achievements do not necessarily define you. Identifying yourself so closely with work achievements or promotions can lead to increased levels of stress. People who rely on work for self-worth or fulfillment can often react to work stresses by anxiously overworking themselves into a burnout. But, when employees work less and engage in mandatory tasks only, work becomes much less pressuring and stress levels decline. As a result they will be able to think clearer, be more creative, be less distracted and perform better at work. When they go home, they will show up the next day well-rested and ready to put in more effort for better outcomes. Increased well-being is a worthy goal that also has economic benefits Employees who are happy tend to display higher levels of productivity and commitment in their work. Such positive emotions can also help reduce instances of distraction or disengagement. Additionally, when individuals experience happiness, they tend to exhibit greater sociability and willingness to build relationships with colleagues, which can contribute to their overall job satisfaction. By prioritizing their main task at hand, employees can avoid the negative effects of feeling like they are constantly competing with their peers, instead building these relationships. In fact, the desire for workplace friendships is ingrained in our basic human desire for a sense of belonging. This in turn can enhance loyalty towards the workplace and improve job performance, leading to greater productivity and higher profits. As a response to the "great resignation," quiet quitting has become a liberating choice for people who prioritize balance instead of overwork and burnout. By setting boundaries and not tying their self-worth to work productivity, workers are taking care of their well-being. Employers should see this as an opportunity to support their staff's overall well-being by encouraging a better work-life balance. This will communicate to employees that they are valued, leading to greater employee engagement, productivity, and loyalty – a win-win situation for everyone involved. New employer practices that embrace the concept of quiet quitting or other methods of healthy focus in the workplace could include anything from adopting a 4-day work week to incorporating mental and physical well-being practices, allowing flexibility in schedules, supporting remote work, agreeing to reasonable workloads, or supporting frequent breaks during the work day. The Bigger Picture: how quiet quitting can promote the UN’s SDGs Encouraging the notion of quiet quitting as a normalized, standard mentality in the workplace has the potential to boost national progress towards the achievement of the UN Sustainable Development Goals (SDGs). SDG 3: Good Health and Wellbeing Adopting the concept of quiet quitting empowers individuals to devote more attention and effort towards their dietary habits, fitness regime, relationships, hobbies, and interests, which collectively contribute to enhancing their overall wellness and leading a healthier lifestyle. SDG 5: Gender Equality Embracing quiet quitting could facilitate the achievement of goal five, which is gender equality. With the provision of reasonable workloads and flexible schedules, women can adjust their work hours according to their convenience and can balance their professional and personal lives more efficiently, resulting in better job performance. This is especially necessary for working mothers. Such flexibility prevents the forced choice between work and home, for both men and women. SDG 8: Decent Work and Economic Growth Quiet quitting has the potential to encourage more innovation in society, as discussed above. It is important to advocate for policies that prioritize the growth of productive activities, promote job creation, and foster innovation and entrepreneurship. These policies should also address labor market challenges and ensure development-oriented policies. References Greenhaus, J. H., & Powell, G. N. (2006). When work and family are allies: A theory of work-family enrichment. Academy of Management Review, 31(1), 72–92. https://doi.org/10.5465/amr.2006.19379625 Hill, E. J., Hawkins, A. J., Ferris, M., & Weitzman, M. (2017). Finding an extra day a week: The positive influence of perceived job flexibility on work and family life balance. Journal of Applied Psychology, 102(8), 1346–1364. https://doi.org/10.1037/apl0000225 Shimazu, A., Schaufeli, W. B., Kamiyama, K., & Kawakami, N. (2020). Work–life balance as a predictor of recovery experiences and well-being: A cross-sectional study. International Journal of Environmental Research and Public Health, 17(4), 1282. https://doi.org/10.3390/ijerph17041282 Header image credit: Racool_studio on Freepik.com.
In a world where we are constantly told to hustle, grind, and push ourselves to the limit, the idea of taking it easy can seem counterintuitive. However, there is a growing movement suggesting that doing only what’s necessary at work is the best thing we can do for ourselves and for the economy. This is known as the concept of "quiet quitting".
How will the development of AI affect the labor market?
It’s expected that AI will change the economy and the world, though few have answers as to how. News stories continue to be written as companies, governments, researchers, and students grapple with AI and learn how to adopt it or respond to it. In this article, we’ll explore this question from an economic standpoint, focusing on the human side of the economy: the labor market. How will AI affect people’s jobs and the future of work? How disruptive technologies generally affect the economy AI in this massively available and accessible form seems truly new and unique. But economically speaking, it could just be considered another advancement in technology that can improve our productivity. This scenario has been happening in our economies since the dawn of civilization. So, what economic impact do these advancements tend to have? Consider the classic Cobb-Douglas production function, shown below: \begin{equation*} \mathit{Y} = \mathit{A}\mathit{L}^{\alpha}\mathit{K}^{\beta} \end{equation*} In this equation, K stands for capital, L stands for labor, and A stands for “technological progress”. A is often glossed over in introductory courses, but is generally described as a “good thing”. When this factor increases, it means that even with the exact same inputs, the economy can produce more. In other words, technological advancement leaves room for Pareto improvements. The development of AI can be thought of as an increase in A. Everyone is theoretically made better off due to this increase in A; this is why economists typically consider technological progress to be a good thing. To see why, consider previous inventions that have changed our daily lives and made certain careers obsolete. One such example is the invention of the printing press. Before it was available, books had to be copied by hand, which professional scribes were hired to do. As books were hand-copied, they were quite scarce, and the cost of books was much higher (relatively speaking) than they are today. Undoubtedly, the invention of the printing press was a boon for society. It allowed a greater quantity and wider range of books to be printed, which enabled more people to become literate, and for those who were literate to make use of their literacy more often. It also caused scribe careers to become obsolete. But nobody would argue that we should re-introduce those jobs, and stop typing or printing. AI tools could have similarly beneficial effects as other disruptive technologies like the printing press did in the past. It can potentially help us create things much faster and more cheaply, resulting in a productivity boom. The hidden cost of progress But, innovation has a cost that the simple Cobb-Douglas model of the economy does not capture. As mentioned, professional scribes barely exist today due to technological progress. But, once books were easier to produce and literacy was more widespread, becoming an author became accessible and doable. This process of new technology creating new opportunities while making old jobs obsolete is known as “creative destruction” in economics. This is one of the main reasons why people may be hesitant about a new technology’s impact on the economy. Nobody wants to become unemployed and (temporarily) lose their source of income, even if it means that society overall is becoming more efficient and productive. Another valid concern is the ability of workers to find new employment. This is especially concerning for people who were working in a now-obsolete job. Finding new work takes time and might require retraining, which can be costly. Workers also may have liked their now-obsolete jobs, and might not enjoy being forced to find a new career. Some workers close to retirement age might struggle to find new employment at all. <11an>limit:3;categories:Jobs</11an> The impact of artificial intelligence on the labor market Some fears of losing jobs to AI have already proved valid. In the first half of 2023, AI quickly started to impact the labor market as businesses looked to it as a revolutionary cost-cutting tool. For example, IBM announced that up to 7,800 jobs could be replaced by AI, and instituted a hiring freeze on those positions, presumably until AI is advanced enough to eliminate those jobs entirely. Other companies, including DropBox and Buzzfeed, announced job cuts. DropBox alluded to AI, citing “developing technology” as one reason for its job cuts, while Buzzfeed explicitly cited AI as one of the reasons they were letting workers go. In a similar vein, Wendy’s announced a partnership with Google to replace human employees with an AI chatbot for its drive-through ordering system. The system is expected to begin launching in the summer of 2023 after being trained sufficiently. In response to situations like these, some workers are fighting to gain assurances that their jobs won’t be replaced by AI. A major writer’s strike enacted by the Writers Guild of America, the union that oversees writers across most of Hollywood, began in early May 2023. Interestingly, the writers did not demand for AI to be banned completely. Rather, they began to strike for better working conditions in general, including the promise that humans would be prioritized in the creative process. The Guild made it clear that AI can be a useful aid in the writer’s room, but should not be seen as a replacement for human professionals. As of this writing, negotiations are ongoing. Some firms have banned the use of AI, for marketing or for safety It’s clear that some firms aim to use AI to cut costs, increase productivity, and even replace workers. At the same time, some companies see value in promoting their lack of AI usage – or are holding off for safety reasons. For example, the tabletop game company Paizo made waves when it announced a ban on the usage of AI-generated content in all of its products. Paizo employs many writers and artists – which fulfill two functions that AI is able to replicate. Paizo’s announcement was seen as a good thing by fans and hobbyists, and has helped to drive record interest in their products in early 2023. Typically, the adoption of new technology is needed to remain competitive. It’s possible that Paizo’s competitors end up utilizing AI to produce quality content much faster and cheaper than Paizo can, eventually forcing them to adopt AI or driving them out of business. But, if having 100% human-made content becomes important for product differentiation, or as a signal of the company's values – similar to the fair trade label in chocolate – then companies like Paizo could carve a niche for themselves and remain competitive even without utilizing AI. Other firms have moved to ban the usage of AI for data privacy or security concerns. Because these tools are hosted by other companies and connected to the Internet, sharing sensitive information with them could pose a security risk. Samsung is an example of this, as the firm banned AI on its company devices after employees leaked sensitive information to an AI tool. In the future, firms like Samsung could opt to develop their own internal AI tool for their employees to use. This would allow employees the benefits of an AI tool without running the risk of sensitive company information leaking. But developing and training a useful AI takes time, development expertise, and training data, which can be expensive. And, inference costs mean that using an AI tool can be expensive, too – one estimate puts the daily cost of running ChatGPT at about $700,000. The creative side of creative destruction: new income streams from Internet text AI must be trained on data. For these large language models (LLMs) specifically, this usually involves massive volumes of text taken from the Internet. Normally this text doesn’t belong to the companies developing these AI tools. Consequently, some large websites like StackOverflow and Reddit have made plans to start charging AI developers for using their data, which so far they’ve been doing without paying for it. These types of sites are also beginning to charge for access to their data for future developers, which could become a new income stream for these companies. The CEO of Stack Overflow, Prashanth Chandrasekar, said it well himself: “Community platforms that fuel LLMs absolutely should be compensated for their contributions so that companies like us can reinvest back into our communities to continue to make them thrive”1. Indeed, this new paradigm of charging for text data could even create jobs to carefully build and maintain forums (or other content databases) that would be sold to developers as training data. In this way, human-only online spaces could become an important and lucrative new aspect of the digital economy. Certainly, other new services and careers will appear due to the widespread usage of AI – such as possible AI detection tools and “prompt engineer” job positions. There is already some disruption in the labor market due to AI, and there’s likely to be more coming. As with every instance of creative destruction, there will be some growing pains while society and the economy is restructured to take advantage of the new technology. But, it’s also highly likely that new careers will emerge as the dust settles. On the way, people will claim that artificial intelligence is going to impact the economy in transformative ways, while others will view it as a threat to their livelihoods. The true answer likely lies somewhere in the middle, though only time will tell. Notes 1: https://gizmodo.com/stack-overflow-charging-ai-companies-for-training-data-1850362500
Artificial intelligence appears to be the next truly disruptive technology poised to rock our global economy. In December 2022, ChatGPT-3 made headlines. It represented a leap forward in the capabilities of generative AI technology, pushing conversations about this new tool into the mainstream as people began to question how ChatGPT will affect the economy.
Econometrics is the application of statistical rigor to economics that allows economists to test economic theory. It is the backbone of modern economic research; any empirical paper that lacked solid econometric reasoning (and preferably repeatable, data-based analysis) would probably not be taken seriously. While it’s possible to theorize and contribute to economics through the development of new theoretical models (especially by introducing science from related fields, like psychology), most serious economists must be comfortable with basic econometrics. Enter Dr. Wooldridge’s research and his seminal text, Introductory Econometrics: A Modern Approach, first published in 1999 and now with over 6 editions, still widely used around the world. Dr. Wooldridge is a prolific researcher who has published more than forty articles in top economics journals and has helped advance econometric theory significantly. Chances are, if you’re a serious student of economics, you’ll end up using his material in some of your courses. Dr. Wooldridge’s contributions to advancing econometric rigor Dr. Wooldridge’s main research focus is in microeconometrics, a sub-field of econometrics that works with individual-level data. He specializes in the study of panel and cross-sectional data, researching and promoting the best econometric methods for researchers to use with these types of datasets. This work is important. One of the cornerstones of the scientific method is the use of repeatable experiments that can be measured. Unfortunately, in economics, it’s very difficult to conduct a repeatable experiment. After all, we study the decisions that people make with limited resources, and it would be impossible to dictate people’s lives just to study their outcomes. Therefore, in economics, historical data is used quite often (though randomized controlled trials have become increasingly common, thanks to the work of certain economists). Because of this, economists often do not have control over how the data was collected, or what specific measurements were used to record it. This makes measurement, and statistical testing, a complicated and precarious process for many researchers. For these reasons, it is often misleading or impossible to use the most straightforward methods of statistical analysis when studying economic data. Further, due to the types of analyses economists like to conduct, there are frequently situations where economists must employ models that violate some of the classic linear regression model assumptions. Therefore, it’s important to have pioneers in the econometric space who can devise methods for properly studying atypical datasets, and techniques for accurately conducting statistical tests in these atypical settings. Further, these pioneers must be adept at teaching others to do the same. This empowers other economics researchers to focus on their actual specialties and research questions, while enabling them to produce the most accurate results possible from their work. This is exactly what Dr. Wooldridge has been able to do over the course of his career. His work has been cited over 130,000 times1 because it has helped form the empirical backbone for many other studies. Without someone to break new ground and pioneer a new, useful econometric approach, some types of analyses are just not possible. Dr. Wooldridge’s research has been distilled into actionable findings that other economists can make use of in their research. Its importance cannot be overstated. Dr. Wooldridge’s professional achievements Jeffrey M. Wooldridge is University Distinguished Professor of Economics at Michigan State University, where he has been teaching since 1991. He is a fellow of multiple prestigious societies, including the Econometric Society and the Journal of Econometrics. He is additionally a research fellow at IZA. Besides his most famous work, (Introductory Econometrics: A Modern Approach), he has also authored another important text for economists, titled Econometric Analysis of Cross Section and Panel Data. Dr. Wooldridge has served on the editorial boards of several journals, including the Journal of Economic Literature, the Journal of Business and Economic Statistics, the Review of Economics and Statistics, and the Journal of Econometrics. He is currently an editor for the Stata Journal. He has also been co-editor of Econometric Theory, an econometrics co-editor of Economics Letters. He previously served as an editor for the Journal of Business and Economic Statistics. In addition to more than forty articles published in internationally recognized journals, he has written several book chapters. These include articles in the Handbook of Econometrics and the Handbook of Applied Econometrics. Dr. Wooldridge received his Ph.D. in economics in 1986 from the University of California, San Diego. Notes 1: Dr. Wooldridge’s work has been cited 138,755 times according to Google Scholar as of May 10, 2023. Header image credit: Global Labor Organization https://glabor.org/glo-recommends-take-a-microeconometrics-class-with-professor-jeffrey-m-wooldridge-at-kent-university-deadline-is-end-of-april/. References http://econ.msu.edu/faculty/wooldridge/jmwvita.pdf https://www.iza.org/de/person/4582/jeffrey-m-wooldridge
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.
Econometrics, Statistics and Quantitative Methods (JEL C)
A quick guide to math symbols in economics
As such, economists need to have some quantitative skills. The more comfortable they are with math and econometrics, the better for their research and career opportunities. But, economists are not mathematicians. So, when students of economics take Bachelor’s or Master’s courses while studying for their economics degree, they might be presented with symbol-heavy lecture notes. Without understanding these symbols, students will probably struggle to read them, leaving their meaning unclear. This article aims to fill that gap. What are the most commonly used math symbols in economics, and what do they mean? Symbols and definitions Math symbols \(\pm\) - this symbol means “plus or minus”. It’s most often used when describing an interval of some sort, such as a confidence interval. \(\preceq\) - this symbol, and others like it, are used often in economics to describe preference relations. Preferences are the building blocks of the demand curve. This symbol is seldom used outside of microeconomics courses that specifically focus on preferences. \(\propto\) - this symbol means that the variable on the left side is proportional to the variable on the right side. \(\sim\) - this symbol means “similar to”. \(\approx\) - this symbol means “approximately”, which means something is almost, but not quite, equal to something else. \(\parallel\) - parallel. In economics, this is used most often in econometrics when describing how things relate to each other geometrically. \(\perp\) - this means perpendicular or “orthogonal”. Perpendicular means two things intersect at a 90 degree angle in geometry. In econometrics, orthogonal means that one variable has zero power to explain another variable, because they have a covariance equal to zero. \(\in\) - this means “in”, that a variable on the left side is contained within a variable, group, or concept on the right side. It can be reversed to mean the opposite. For example, often in economics, a theory will describe which values of x are possible. If x can only take on real number values, the description might start with x \(\in\) \(\mathbb{R}\). This means that x can only be a real number, because it is “in” the set of \(\mathbb{R}\). \(\otimes\) - this symbol is used to describe the Kronecker product, which is a matrix algebra concept that comes up occasionally in econometrics. \(\partial\) means “partial”, and is used to denote a partial derivative. IN is often used to denote the identity matrix with dimension N; it’s used frequently in statistics and econometrics. \(\cdot\) this symbol is placed above a variable to signify the derivative with respect to time of that variable. This symbol is commonly used in macroeconomics, but seldom outside of that context. Greek letters These are often used to denote variables, but some carry special meaning because of how often they’ve been used in certain contexts. \(\alpha\) - the letter alpha, often used with Cobb-Douglas functions to denote the exponents. Also used when discussing p-values in hypothesis testing; the “alpha” level sets the number that you compare the hypothesis test’s result to, in order to determine if the result is statistically significant (such as 0.05 for 5% significance, which is often the default). \(\beta\) - the letter beta, also used as an exponent in Cobb-Douglas functions. But, it’s most famously used when describing regression formulae. In that context, this letter usually has a subscript and is the shorthand way of saying “the regression coefficient on the variable it’s being multiplied with”. \(\epsilon\) - the letter epsilon. This letter is also commonly used in regression analysis, and usually denotes the error term of the regression. Many introductory econometrics classes, and any other course that showcases regression analysis, will make frequent use of this symbol. Many of the assumptions that allow economists to justify using a regression model involve statements made about the error term. \(\delta\) - the letter delta. This symbol is used often to denote the change in a variable, or depreciation in macroeconomics. It’s often confused with the symbol for partial derivatives, which looks very similar! \(\lambda\) - the letter lambda. It is used most often when solving constrained optimization problems using the Lagrangian method; in this case it stands for the shadow price of the budget constraint. This letter will be seen very often by microeconomics students. \(\mu\) - the letter mu. This letter is used often in statistics and usually denotes the mean, or average, of something. \(\rho\) - the letter rho. Often used to indicate the correlation coefficient between two variables. \(\Sigma\) - the capital letter sigma. Used frequently to denote the sum of things. \(\sigma\) - the lower case sigma. Used often in regression analysis and statistics to denote standard deviation; when squared, it is the variance of the subject in question. \(\Phi\) - the capital letter phi. Usually used to denote a probability distribution in statistics, most commonly the cumulative distribution function (cdf) of the normal distribution. \(\phi\) - the lower case phi. Often used to denote the probability distribution function (pdf) of the normal distribution in statistics. But, this letter is frequently used outside of this context too, unlike the capital version described above. \(\chi\) - the letter chi. Used in statistics to denote the chi-squared distribution, which is a probability distribution that is used a lot in regression analysis. \(\Omega\) - the capital letter omega. Used often in econometrics to be the symbol for a matrix. The following letters usually don’t carry special meaning on their own, but are often used in economics regardless. They are commonly used as placeholders for a variable when discussing a theory or equation. \(\gamma\) - the letter gamma. \(\eta\) - the letter eta. \(\kappa\) - the letter kappa. \(\nu\) - the letter nu. \(\tau\) - the letter tau. \(\upsilon\) - the letter upsilon. \(\Psi\) - the capital letter psi. \(\psi\) - the lower case letter psi. \(\omega\) - the lower case letter omega. Other statistics symbols The following symbols are often used in economic statistics contexts. Note that the Greek letters above contain many symbols used in these contexts as well. | means “given that” in a statistics sense, i.e., X | Y = 2 means “X given the fact that Y equals 2”. \(\mathbb{E}\) means “the expectation of”. Typically there is a defined variable, matrix, etc. placed in brackets next to it (for example, X); then, this means the expectation, or expected value, of X. This symbol is used extremely often in statistics. \(\mathbb{V}\) means “the variance of”. It’s used in the same way as the expectation symbol above, so when something is placed in brackets next to this, it means the variance of that variable, matrix, etc. Not to be confused with \(\sigma\)2, which stands for a specific number. \(\sigma\)2 is the symbol for the variance of a variable, matrix, etc. This stands for the actual number that is the variance of something. \(\overline{X}\): the bar above a variable denotes the average. This symbol is used very often in economic formulae, for example when describing the sum of least squares. Set theory symbols Set theory is used to describe how groups of things relate to one another. They’re similar to a Venn diagram, but in the language of math. \(\subset\) - this symbol shows that the variable or group on the left side of it is a subset of (included in) the group on the right side of it. With a slash through it, it means the opposite. \(\subseteq\) - the same as the above symbol, except that the subset it describes can also be equal to the variable or group on the right side. It does not have to be completely contained within the second group. \(\supset\) - this symbol denotes a superset, which is the opposite of a subset. It means that the group on the left side of this symbol contains the group on the right side. \(\cap\) - this is the symbol for the intersection of two sets, or the things they both contain that are the same. \(\cup\) - this is the symbol for the union of two sets, or everything that is contained in at least one of the sets. \(\emptyset\) - this is the “empty set” symbol, which is simply a set that contains nothing. Sets of numbers The following symbols are still technically sets as they describe groups of numbers, like “rational numbers” or “natural numbers”. These are used very often in economic formulae even when other set symbols might not appear. \(\mathbb{N}\) is the symbol for natural numbers. \(\mathbb{Z}\) is the symbol for the set including all integers. \(\mathbb{Q}\) is the symbol for the set of all rational numbers. \(\mathbb{R}\) is the symbol for the set of all real numbers. Other useful symbols \(\exists\) means “there exists at least one”. It’s commonly seen in proofs, which tend to be used in econometrics- or statistics-heavy courses. \(\exists!\) is a variation on the symbol above that means “there exists one and only one”. \(\forall\) means “for all”, usually in the context of stating some truth in an econometric context, i.e., stating that a particular equation is true for all i in some set of observed values N. \(\implies\) means “implies”; the function, formula, or variable on the left side implies some relationship written on the right side. \(\iff\) means “if and only if”. Reading economic formulae Now that the commonly used symbols have been introduced, we can use them to read and interpret an economic formula. The below example is the Goldsmith equation, used in macroeconomics to describe the growth of capital stock over time: \begin{equation*} \dot{K_t} = \mathit{I_t}-\delta\mathit{K_t} = \mathit{s}F(\mathit{K_t},\mathit{A_t},\mathit{L_t}) - \delta\mathit{K_t} \end{equation*} The first variable in this formula stands for the derivative of capital with respect to time, signified by the dot above the Kt. Recall from the list of math symbols above that the dot means the derivative of something with respect to time. This is equivalent to the investment (which here is defined as It) at a point in time minus the depreciation times the capital stock at a point in time. Recall that the symbol \(\delta\) from above is often used to denote depreciation. Then, on the far right-hand side, it is broken down further. It’s multiplied by s, which stands for the savings rate. This is multiplied by a function of capital, labor, and technological growth. The function’s exact form is not defined for us yet, so it’s simply written as F(Kt,At,Lt), which is common practice in math. \begin{equation*} \mathit{YED}_{A} = \frac{\Delta\mathit{q}_{A}}{\Delta\mathit{Y}} = \frac{\frac{\partial{q}_{A}}{\mathit{q}_{A}}}{\frac{\partial{Y}}{Y}} \end{equation*} This equation, meanwhile, describes the income elasticity of demand with respect to good A. It tells us exactly what this elasticity is and how to calculate it. The income elasticity of demand YEDA is equal to the change in the quantity demanded divided by the change in income. \begin{equation*} \mathbb{E}[X] = \mathbb{E}[\mathbb{E}[X|Y]] \end{equation*} This formula is a foundational theorem in econometrics, known as the Law of Iterated Expectations. Recall that the \(\mathbb{E}\) symbol means “expectation”. This formula states the following in mathematical shorthand. Our expectation of X in general is equal to our expectation of the value of X that is expected given some value that the variable Y could take on. In other words, we have some general idea of what X should be over the whole range of possible Y values (which have not been defined yet). This expectation is the same as what we generally expect X to be. In more precise statistical language, this formula means that the expected value of X is equal to the expectation of the conditional expectation of X given Y. It took many words to describe what a simple formula could convey with only a few symbols. Clearly, using these symbols can help economists communicate ideas much more effectively than by just using words! Header Image Credit: geralt on Pixabay (free for use under the Pixabay Content License)
Studying economic theories and methods requires an understanding of mathematical symbols. These symbols are used as shorthand to describe theoretical concepts in economics textbooks, theories, and research papers.
What degree do I need to succeed as an economist?
Generally speaking, there are two career paths one can pursue with an economics degree. Academic economists work for universities and usually combine research with teaching responsibilities. Non-academic economists (sometimes referred to as economists in industry, or “industry economists”) are hired by a variety of employers, including financial institutions, think tanks, NGOs, governments, and more. Some of these economists conduct research much like their academic counterparts, while others have jobs that are far from academia. Industry roles can be further subdivided into public sector (i.e., government) or private sector (i.e., an investment bank) positions. We have previously covered some of the key differences between these two paths beyond what is obvious on the surface. If you’re curious about the difference in the actual work between these different types of economists, check out the linked article. It offers advice written by an economist who has worked in a think tank and later returned to academia for her economics PhD: “Policy or academic economist: which should I become?”. How many years of schooling should I complete to become an economist? As an economist, it’s possible to find an industry job with just a Bachelor’s degree, but these are almost entirely entry-level roles. This can make good sense for a student who recently graduated with a Bachelor’s in economics and wants to work for a few years before pursuing more education. However, a majority of economists have a PhD in economics, and an overwhelming majority have at least a Master’s degree. According to our Salary Survey results in 2022, fully 92% of economists had either a Master’s degree or a PhD (61.3% had PhDs and 30.9% had a Master’s). Only 6.3% of economists who responded had just a Bachelor’s degree. A career as an academic economist often requires a PhD Almost every successful academic economist has a PhD. It would be very difficult to gain academic employment without one, especially since you’d likely be competing with economics PhDs for most positions at universities. According to the Economist, “Nabbing a top academic job in America requires obtaining a PhD, preferably from a good university”1. Full professor of economics positions (which pay very highly) often require not just a PhD, but work experience and research credentials. More junior academic positions may not explicitly require a PhD, but are usually inundated with applications from young economists who have recently completed theirs. It can be difficult to compete without equivalent academic qualifications, or lots of relevant work experience. A Master’s degree at minimum is suggested for a career as an industry economist Even outside of academia, to truly advance in your career as an economist, a Master’s degree or a PhD are very helpful. A Master’s degree in economics should be considered a minimum educational requirement for most economist jobs. As the US Bureau of Labor Statistics states, “Economists typically need at least a master’s degree to enter the occupation”2. This appears to be broadly true across regions, not just in the United States. Many senior economist positions are only open to those who have a PhD. Further, perusing job postings for economists will reveal a whole host of opportunities for economists with a PhD and a specialization in a subfield. This is because for many industry roles, organizations have a very specific need for an economist and the future hire must have relevant experience. For example, NGOs that compete for development projects often do so via a “request for proposal” or RFP process, where the funding government solicits RFP responses and selects the best offer. These competing NGOs therefore often need an economist with a PhD and proven experience in that project’s specific topic area (i.e., a certain region or type of infrastructure) in order to successfully win the contract from a government agency. This is because part of the NGO’s pitch is the quality of economist staff who would be assigned to the project. Becoming an economist without an economics degree Of course, not everyone recognized as a brilliant economist was trained as such. In fact, some of the most famous economists – like John Nash, winner of the Nobel Prize in economics in 1994 – studied other fields first. Nash was a mathematician by training. Degrees from other fields can allow someone to shift their career into economics, but this will often limit the economics subdiscipline they can work in. As with John Nash, a successful mathematician can quite certainly become an econometrician or similarly quantitatively-focused economist with their background. Statistics, political science, and finance are other examples of fields that allow one to pivot into an economics career. But, these professionals will have the highest chance of success by working in related subdisciplines – such as policy analysis or financial economics. This, however, is not easy, nor is it a standard method to becoming an economist. If you are interested in economics specifically, it’s better to decide on a specialization and pursue a relevant degree program in economics based on those interests. The value of an economics PhD After reading all of this, the value of an economics PhD might seem important, but difficult to quantify. Not so. Our Salary Survey allows us to estimate the return on a PhD in economics; it turns out that these economists enjoy a much higher average salary than Master’s degree economists. Last year, PhD economists earned 50% more on average than economists with a Master’s degree, globally. Clearly, it’s an investment that pays off. Naturally, this figure varies by region. The graph included below shows the increase in average pay for an economist with a PhD compared to one with only a Master’s degree in each region. Average pay for an economist with a PhD compared to one with a Master’s, by region There are many career options to pursue with a degree in economics. When planning yours, we highly recommend that you search for economics jobs that interest you. Learn their requirements and check the qualifications of professionals who are currently employed in those jobs. Doing this will help you learn what education, skills, and experiences you still need in order to be a competitive candidate for those positions. Then, you can take economics courses, get your next degree, or attend conferences to acquire the skills and experience you need. Whatever your chosen path, you can find resources on INOMICS to help you achieve your goals. We wish you the best of luck on your career journey! References 1. https://www.economist.com/finance-and-economics/2020/08/08/what-it-takes-to-become-an-academic-economist-is-changing 2. https://www.bls.gov/ooh/life-physical-and-social-science/economists.htm Header image credit: greymatters on Pixabay (free for use under the Pixabay Content License)
It might be unclear to new students of economics how much schooling is necessary to succeed as an economist. For some careers, a Bachelor’s degree is sufficient. In others, a PhD is a near-necessity. This article will discuss how much education successful economists typically have.
The INOMICS Questionnaire: Fratzscher vs. Ditzen
Jan Ditzen is an Assistant Professor (RTD-A) in Econometrics at the Free University of Bozen-Bolzano, in Bolzano, Italy, where he was previously a postdoc. Since 2021 he is serving as Co-Editor/Digital editor of the economics journal Spatial Economic Analysis, responsible for the Replication Studies Section among other responsibilities. From 2017 to 2020 he was a Research Associate at the Centre for Energy Economics Research and Policy (CEERP) at Heriot-Watt University, where he was internally responsible for assisting BP plc with the BP Energy Outlook, and one of the fuel leads for the BP Statistical Review of World Energy. He obtained a PhD from Heriot-Watt University, a Master in Economics from Hamburg University and a Bachelor in Economics from Mannheim University. Dr. Ditzen’s research interests are in the field of Applied Econometrics with a focus on Panel-Time Series, Cross-Sectional Dependence, Spatial Econometrics, and Growth Empirics. He has also an interest in Simulation Studies and the implementation of econometric methods into statistical software. Marcel Fratzscher: What is your favourite place on earth? Jan Ditzen: Definitely a place out in the hills or mountains. My favourite two would be Grimentz in the Swiss mountains. It is a beautiful place with amazing views and has many good and happy memories. The second one is a remote cabin in the Norwegian mountains. It is a very peaceful and quiet place. MF: Outside of economics, what occupation would you choose if you could be absolutely anything? JD: That's a hard question, there are so many exciting and interesting occupations. An alternative would have been engineering; it must be great to see one’s projects in real life. I usually joke that if I have enough of academia, I plan to become a shepherd in the Alps or a mountain guide. MF: What is the virtue you appreciate the most? JD: Honesty and being straight forward without too many words. MF: Your all-time favourite figure in economics? JD: As an econometrician I (have to) name one as well: Hashem Pesaran. His work on panel data and time series econometrics is unprecedented. Additionally he has some important work on empirical finance and macro models. Beyond that his influence on the profession, for example in the form of his involvement in the International Association for Applied Econometrics, will be lasting. MF: Your #1 economics blog? JD: Surprisingly, I am not following many blogs, but I enjoy reading Daniel L. Millimet's blog "How the (Econometrics) Sausage is Made". Daniel offers easy to read articles on econometrics and related current topics. What I enjoy is that his blog connects well to recent contributions or debates in the literature and outside of it. MF: Your ideal student? JD: A student who asks the "right" questions. The "right" questions are those which make you rethink the material you teach, or even give you ideas for new research. MF: What should be done to address a gender bias in research in economics? JD: I am a fairly junior researcher, so my influence in hiring and strategic decisions is relatively minor. However I think as a profession we need to be more inclusive. In particular we need to motivate female students to pursue PhDs in areas which are male dominated. Too often I end up in conference sessions which consist almost exclusively of male presenters. MF: What is the most misguided research agenda in economics? JD: It is not really a research agenda, but we need to improve on our empirical work. At the end of the day economics is a social science and empirics is the vehicle to validate economic theories. Therefore we have to take it very seriously. From my perspective there are currently two weaknesses. The first one is a technology gap between empirics and econometric theory. Academic papers should try to use the latest econometric methods because those are either solving issues or shortcomings in existing methods, or are a better fit for a specific problem. On the other hand, there are many elegant and beautiful econometric methods which will hardly be used in applied work. The reason for this gap is that many methods don't find their way into statistical software, which manifests a disconnect between the two sides. For econometric theorists, it is often not interesting to follow up on the implementation of their methods into mainstream software. Practitioners often do not cite software or packages, which removes incentives for the original authors of the methods or 3rd parties to invest time into transforming econometric methods into statistical software- from my own experience I know how long developing a well working package takes. This leads to the next weakness: reproducibility of existing studies. The data collection and processing, and production of results are too intransparent in too many papers. If results cannot be validated and reproduced, how can we be sure that their conclusions are sound? Luckily journals have started putting more effort into this. The Journal of Applied Econometrics or the American Economic Association are pioneers, and the Royal Economic Society is currently looking for a data manager. MF: What is the most promising current research field or issue in economics? JD: There is the saying that "Data is the new oil" and we economists know how to handle data and draw conclusions from it. Thus I think there is a lot to learn from the combination of machine learning, big data and economics. There are still a lot of gaps in the theoretical literature and the topics only slowly find their way into more general questions and journals. Using data in the right way can improve the lives of many humans and our planet. Related to this, the use of data itself for a society or economy is also an under-researched topic in economics. MF: Where does economic research have the most influence on policy-making? JD: Certainly monetary economics and central banking. There is also a large influence of development economics and of course competition economics. MF: On what issues should policy listen more to economists? JD: To be honest, this is a hard question. Out of my head, there are a lot of issues from different fields. In general I believe policy should listen more to science. With respect to economics, outcomes in economics can be driven by the author's perception, or even ideology. This can be a problem when it comes to funded research activities, especially done by some research institutes. I think a big issue is that policy makers need to understand better from whom the research comes, and what are the background and limitations of the research. Science is complicated and there is no simple answer. As an econometrician, I would hope for better openness and quality of data. Data can inform in so many ways, but before that, it needs to be collected, processed and analyzed. A slightly German-centric view: There was a recent initiative by German economists for an improvement on data quality and accessibility in Germany which I hope policy makers will follow. MF: What is your career advice to a young economics researcher? JD: Be curious and don't be shy to ask questions, no matter about what or to whom. Follow your own interest and instincts, even if it might not produce the greatest outcome. Finally, don't forget your private life, the persons and activities you love and enjoy.
In the INOMICS interview series, Prof. Dr. Marcel Fratzscher asks economists questions about their field, their opinions on economics, some of their favorite things, and more. Today we took the chance to interview Dr. Jan Ditzen, an econometrician with a robust research presence. The interview, named Fratzscher vs. Ditzen (as is tradition), enlightens us on the contributions of Hashem Pesaran, the beauty of mountain scenery, details about econometrics and why its rigor is important for economics, and more.
Publication behavior in economics – Reputation, visibility, and the gender gap
There exists a body of research that shows how women in economics face more obstacles than men when trying to make their way: Papers are less cited if the corresponding author is female (Maddi & Gingras, 2021). Further, women are confronted with higher standards in publishing compared to men (Hengel, 2022), a more hostile environment (Dupas et al., 2021; Wu, 2018), and they are less well-connected in their discipline, according to the count of women compared to men in the acknowledgments of published papers (Rose & Georg, 2021). Publication differences by gender in economics To further understand the gender gap in the discipline, it is also important to look at publication behavior, acknowledging, of course, that this can only be another puzzle piece in understanding the gap as a whole. This holds especially true for economics, as it is a discipline heavily driven by journal publications and the relative ranking of outlets in which a researcher’s papers appear. In our recent working paper, Justus Haucap, Leon Knoke, and I use the negotiations for large-scale open access agreements between German research institutions and the leading academic publishers to study two unique natural experiments that answer the question: How do changes in the attractiveness of publishers and their journals affect the publication behavior of researchers in economics and adjacent fields? Wiley and Springer Nature closed DEAL agreements that came into practice in 2019 and 2020, respectively. Under the conditions of these contracts, all submissions from authors affiliated with a German research institution are immediately published as open-access without further costs or paperwork for the researchers. In contrast to the former two academic publishers, the negotiations with Elsevier were suspended in the autumn of 2016. As a consequence, 74 institutions canceled their Elsevier journal subscriptions. After a short break, Elsevier decided to continue granting access to institutions without contracts. At the end of 2017, a further 110 institutions terminated their contracts. Again, Elsevier continued to provide access to its outlets. The conflict ended with the German research alliance announcing its withdrawal from the negotiations in July 2018. Elsevier then cut off all institutions without a contract from access to its journals. If you want to access a publication now, you see something similar to the screenshot below that highlights that your institution does not subscribe to the content, and adds a prominent “purchase PDF” button. Results of our study: women react differently than men to open access changes In our working paper, we estimate a difference-in-differences model that looks at the effect of the varying publication incentives on the publication behavior of affected economists. While the two natural experiments (enacting DEAL and the end of negotiations with Elsevier) solely affected Germany, all other countries serve as a reliable control group. We decompose our effects by gender and the presence of co-authors and look at the effect across the quality scale. To do that, we rely on a dataset of scientific publications in economics ranging from 2015 to 2022 that contains some 240,000 observations. For both events, we find significant baseline reactions. While the DEAL caused an increase in publications from authors based in Germany by +4.67%, the cut-off from Elsevier together with the negative press for the publisher reduced publications by -3.91% (both significant at the 5% level). Looking closer at the gender differences, we find for the DEAL a larger effect for women than for men (at least significant at the 10% level) as the upper panel shows. In contrast, the lower panel for the Elsevier cut-off highlights that males do not significantly react (at the 5% level), but females do. Comparing the estimates also shows that they significantly differ for the comparison between male and mixed teams as well as male and female teams. Here, we can already see that different gender compositions affect publication behavior in economics. Further decomposing the mixed-gender group, we are able to identify an almost steadily decreasing pattern in the point estimates for the Elsevier effect. While fully male authorships only show a decrease in Elsevier publications by some 2%, mostly and fully female research groups have an effect size approximately three times the size of their male colleagues, showing that they have reacted to the changes by publishing less in Elsevier. When comparing behavior across the reputation or impact scale – using the Scimago Journal Rank criterion as a measure, we find important differences between men and women. We separate our data into four quartiles. The first quartile includes the journals with the lowest impact, and the fourth quartile, in turn, includes those with the highest. While researchers of both genders drop out of lower-tier Elsevier journals, men actually opt in to those Elsevier journals with the strongest impact, as the panels below show. Based on these findings and further ones presented in our working paper, we conclude that women have a higher interest in the visibility of their research. As such, they contribute to the public good of open science freely accessible to all. In contrast, men seem to value reputation (of the higher-ranked Elsevier journals) more, which is clearly a private good. The implications for gender differences in economics The implications of these behavioral differences are twofold and, especially in academia, potentially severe. First, if the objective is to transform the market for academic publications, the `Elsevier experiment' raises doubts about the extent to which male researchers – who are predominant in most academic disciplines – contribute to this goal. Second, even though we observe a tendency toward open access in the lower ranks of the quality distribution, the behavior at the top appears to perpetuate not only the role of Elsevier, but the position of incumbent journals and publication patterns more generally. Sticking to the status quo bears important advantages: Shifting away from well-off outlets may (negatively) affect the comparative career opportunities of women. In economics, publishing in the highest-ranked journal possible is of high importance. Excluding a publisher that hosts many influential journals may ultimately backfire on an individual’s career. It is even more severe for women who do this as publications have a larger impact on the careers of women than men (Lutter et al, 2022) and because women publish less than men (Xie & Shauman, 1998, Prpic, 2002). To read more about the topic and view additional analysis, see the working paper: Schmal, W. B., Haucap, J., Knoke, L. (2023). "The role of gender and coauthors in academic publication behavior". DICE Discussion Paper No. 397. https://www.econstor.eu/handle/10419/270608/ References: Dupas, P., A. Sasser Modestino, M. Niederle, J. Wolfers, and T. S. D. Collective (2021). “Gender and the Dynamics of Economics Seminars”. NBER Working Paper 28494. Hengel, E. (2022). “Publishing While Female: are Women Held to Higher Standards? Evidence from Peer Review”. The Economic Journal 132.648, 2951-2991 Lutter, M., I. M. Habicht, and M. Schröder (2022). “Gender differences in the determinants of becoming a professor in Germany. An event history analysis of academic psychologists from 1980 to 2019”. Research Policy 51.6. 104506 Maddi, A. and Y. Gingras (2021). “Gender diversity in research teams and citation impact in Economics and Management”. Journal of Economic Surveys 35.5, 1381–1404 Prpic, K. (2002). “Gender and productivity differentials in science”. Scientometrics 55, 27–58 Rose, M. E. and C.-P. Georg (2021). “What 5,000 acknowledgments tell us about informal collaboration in financial economics”. Research Policy 50.6, 104236 Wu, A. H. (2018). “Gendered language on the economics job market rumors forum”. AEA Papers and Proceedings 108, 175–179 Xie, Y. and K. A. Shauman (1998). “Sex Differences in Research Productivity: New Evidence about an Old Puzzle”. American Sociological Review 63.6, 847-870 Header image picture credit: Viarami on Pixabay.com (free for use under the Pixabay Content License)
In recent times, debates on gender inequality among researchers at universities have emerged, in particular in economics. Even though leading academic societies have addressed these issues already for many years – for example, the American Economic Association has run the “Committee on the Status of Women in the Economics Profession” (CSWEP) since 1971, and the European Economic Association established its “Standing Committee on Women in Economics” (WinE) in 2003 – they appear to be persistent.
The INOMICS Questionnaire: Fratzscher vs. Tol
Dr. Richard S.J. Tol MAE is a Professor at the Department of Economics at the University of Sussex, the Professor of the Economics of Climate Change at the Institute for Environmental Studies and Department of Spatial Economics at Vrije Universiteit in Amsterdam, the Netherlands, and a Research Fellow of the Tinbergen Institute, CESifo, and the Payne Institute for Public Policy. He is an elected Member of the European Academy. Formerly, he was a Research Professor at the Economic and Social Research Institute in Dublin, the Michael Otto Professor of Sustainability and Global Change at Hamburg University, and an Adjunct Professor at the Department of Engineering and Public Policy at Carnegie Mellon University in Pittsburgh, PA, USA. He has had visiting appointments at the Canadian Centre for Climate Research, the University of Victoria in British Colombia, at the Centre for Social and Economic Research on the Global Environment at University College London, and at the Princeton Environmental Institute and the Department of Economics at Princeton University. He received an M.Sc. in econometrics (1992) and a Ph.D. in economics (1997) from the Vrije Universiteit Amsterdam. He is among the top 100 most-cited climate scholars. He has 299 publications in learned journals (with 100+ co-authors). He specializes in the economics of energy, environment, and climate, and is interested in integrated assessment modeling. He is the editor-in-chief for Energy Economics, a top field journal. He is, to date, the author of the only major English-language textbook on the economics of climate change. He was an author of Working Groups I, II and III of the Intergovernmental Panel on Climate Change (IPCC), and by extension a member of the winning institution of the Nobel Peace Prize in 2007. Marcel Fratzscher: What is your favourite place on earth? Richard Tol: Wherever the wife and kids are, but I would like them to be in County Clare, Ireland. MF: Outside of economics, what occupation would you choose if you could be absolutely anything? RT: I'd grow fruit. MF: What is the virtue you appreciate the most? RT: Intelligence (it's not a virtue, I know) MF: Your all-time favourite figure in economics? RT: Tom Schelling MF: Your #1 economics blog? RT: What's a blog? MF: Your ideal student? RT: The ideal student is the one who teaches me. MF: What should be done to address gender bias in research in economics? RT: That is a hard one. We're only just beginning to understand the extent of sexism in economics. As a start, we all need to examine our own biases. It would help if some people would retire. Some argue for role models, but I think that poses an unfair burden on the few candidates. It will take a while, but we should remove all that holds women back, from aggression in seminars and harassment at conferences, to delays in review and different treatment in hiring and promotion. MF: What is the most misguided research agenda in economics? RT: I really do not understand macroeconomics. All they seem to do is construct models that have a superficial resemblance to some observations. They seem to have forgotten that John von Neumann could make an elephant wriggle its trunk with five parameters. MF: What is the most promising current research field or issue in economics? RT: I am most impressed with the rapidly expanding availability of historical and pre-historical data. This is not just interesting in its own right, but it also exposes blind spots in our understanding of the institutional and technical context in which economics happens. MF: Where does economic research have the most influence on policy-making? RT: Monetary policy is by and large outsourced to economists. MF: On what issues should policy listen more to economists? RT: Climate policy is at odds with economic research in almost every respect, from target setting to instrument choice. Anne Krueger should have shared Bill Nordhaus' Nobel. Climate policy is first and foremost about snouts at the trough. MF: What is your career advice to a young economics researcher? RT: Be yourself. There are more than enough plastic phonies already.
In this article, INOMICS interviews Dr. Richard S.J. Tol, member of the Intergovernmental Panel on Climate Change (IPCC) when it was awarded the 2007 Nobel Peace Prize and a researcher at the forefront of economics and climate policy. Dubbed Fratzscher vs. Tol as Prof. Dr. Marcel Fratzscher resumed his role as interviewer, the conversation touches on gender discrimination in economics, the increasing availability of historical data, and how climate policy can clash with economic research.
Agricultural and Environmental Economics (JEL Q)
This article will dive into the economics of the Star Wars galaxy implied by the franchise, mainly from the movies and some of the TV series. As such, fairly mild spoilers abound; beware if you intend to watch some Star Wars movies or shows, but haven’t yet. Money in the Galaxy Far, Far Away In Star Wars, people typically conduct transactions using “credits”, which amount to some futuristic-looking cash. This currency is used almost everywhere in the galaxy, to the point that most citizens only comment on it when certain transactions don’t accept credits. For example, in The Force Awakens, Daisy Ridley’s Rey is paid in food on a bartering basis rather than being paid with money, which tells us how much of a backwater she lives in. Similarly, after an emergency landing on a different backwater planet in The Phantom Menace, Liam Neeson’s Qui-Gon Jinn is forced to engage in some good old sports betting to muster up needed cash. Other than scenes such as these, which serve to highlight certain dire economic situations, credits are used and talked about by almost everyone. This widespread credit usage immediately raises two major questions. First, how did the galaxy unify its form of currency across planets, cultures and languages, and how is that currency controlled? Second, why are electronic payment methods seemingly unused? We can look to one real-life example of currency consolidation – the European Union – to perhaps answer the first question. Upon induction, member states in the EU must transition to using euros rather than their original sovereign currencies. While this prevents each individual nation from having complete control over their monetary policy, becoming part of the EU trading bloc opens up a host of other opportunities for the country and its citizens. It is entirely possible in Star Wars that the many planets making up the Galactic Republic agreed to create an economic bloc like the EU, giving up their original currencies and adopting galactic credits instead. These are presumably controlled by the galaxy’s central bank on the capital planet Coruscant, where the Senate, with representatives from every planet, governs. Of course, when the Empire took over in Revenge of the Sith, it seemingly just changed the name from galactic to imperial credits and the payment infrastructure probably remained the same. It is also possible, though unlikely, that currencies were consolidated because of financial instability. When a country experiences hyperinflation, one solution to break the doom spiral of runaway inflation is to simply stop using the local currency and adopt a foreign one. This has happened before in our history, for example when Ecuador adopted the US Dollar as its official currency in the year 2000 (this process is known as “full dollarization”). If multiple Star Wars planets underwent “full creditization”, it may have started a gradual process of galactic transition to credit usage for ease of transactions. So, where are all the electronic payments? Electronic payments seem to be very seldom used in Star Wars, and almost never on-screen. One of the few times we know for certain that electronic payments did occur are during Senator Mon Mothma’s scenes in the acclaimed series Andor. In several of her scenes, she must support the nascent Rebellion with electronic transfers without being traced by Imperial intelligence. Despite the rarity of references to electronic transfers on-screen, it’s possible that electronic payments are widespread, and viewers are simply not exposed to them very often due to the nature of the typical Star Wars protagonist. Many of the characters we see are either poor, Jedi, government agents, or people conducting illegal activity. For some, like perhaps Luke Skywalker and his Uncle Owen and Aunt Beru, electronic payments may be unaffordable or impractical (maybe they can’t afford or don’t need to transfer funds as moisture farmers in the desert). For other characters, like most of the Jedi, payment is often an unnecessary affair; Jedi’s living expenses are presumably sponsored by the government or the Jedi Council. Moreover, Jedi had to renounce all attachments as part of their training, so it’s unlikely that any of them would be seen paying for an elaborate meal or other luxuries. For other characters, electronic payments might even be dangerous. Members of the Rebellion in the Empire era – as well as The Mandalorian’s title character – would probably want to avoid using traceable payment methods so they can avoid being tracked down by their enemies. An example supporting this theory is the aforementioned Mon Mothma scenes in Andor. So, it seems that electronic payment methods do exist in Star Wars. But, much like Germany in our world, for various reasons cash payments continue to thrive. Regardless of the payment method, the galaxy’s economy appears to be quite a hospitable place for conducting business… Corporations in Star Wars Capitalism is an oft-praised, oft-derided economic system that is currently the most common form of economic organization around the world. One of the key complaints that people may have about capitalism is that it can sometimes put profit and the rights of corporations above other things, including the environment. It can lead to seeming excess in certain areas, like inflated executive pay and increasing wealth inequality, as well. In Star Wars, corporations wield immense power in a seemingly capitalist system that features very little regulation. This is shown even at the very start of the saga, in Star Wars Episode I: The Phantom Menace, where a corporation (the Trade Federation) blockades an entire planet (Naboo) with its own private military force, and even begins to arrest the citizens and send them to labor camps. Meanwhile, this same corporation has a seat in the Galactic Senate on Coruscant, where Trade Federation representatives are apparently treated just the same as any other senator – including the senator from Naboo, the not-yet-Emperor Palpatine. Other corporations have a large impact on the saga as well. The Trade Federation is one of several corporations that form the economic backbone of the separatist movement in the Clone Wars. The Galactic Republic itself, fighting against the separatists in the war, accepted the help of a large corporate enterprise to do so; the Republic’s army of clone soldiers was built at the request of a Jedi Master by Kaminoan cloning services. Although a formal company name is never given in the movies, it’s clear that the Kaminoans are cloners for profit – they produced the units for the Republic and did it for money. But, unlike the separatists, the society on Kamino appears to have no political motives, only profit. Certainly, the activity of corporations on such a scale is something that has become normal to the galactic population. One reason that corporations have probably been able to grow so large and powerful is the lack of trade barriers or serious roadblocks to growing business across the galaxy. This is due to a few factors that will be discussed further below… Trade Barriers in the Galaxy In economic theory, trade barriers increase transaction costs and lower overall economic welfare by lowering economic surplus. So, when transaction costs are lower, ceteris paribus, the economy is much more efficient because comparative advantage is made easier to benefit from. Nations can trade much more freely, which increases everyone’s utility since goods are being made relatively cheaper than they would in the presence of higher transaction costs. So, how do the people of the Star Wars galaxy experience trade barriers and transaction costs? Language & Communication Economies, at their core, consist of people conducting transactions. Common language allows these transactions to grow beyond two people grunting at one another and handing over a few chickens for some beans. Moreover, a lack of common language or the need for translation services increases transaction costs and can inefficiently reduce trade. Therefore, lack of common language is a good example of a naturally-occurring trade barrier. In Star Wars, almost everyone speaks the same language. The few major exceptions to this rule include the well-known Wookiee race, who speak in growls and whimpers (like Chewbacca), some forms of droid (like R2-D2), and a few cultures or species like the Tusken Raiders or the Hutts that seem to have their own entrenched culture. But even in these cases where someone isn’t speaking the common language, either everyone else in civilized society understands them just fine, or translators are able to pick up the slack quite easily (we see C-3PO translating for Jabba the Hutt in Return of the Jedi even though he wasn’t built to be a Hutt translator, for example). This suggests that in Star Wars, language barriers are functionally extinct. This common language across species and planets clearly serves to unify society and massively reduce transaction costs across the galaxy, greatly encouraging prosperity. The lack of conflict we see along ethnic or species lines in Star Wars reinforces the idea that the galaxy has been generally unified through common language and economic activity. Distances & Transportation Transportation cost is another major barrier to trade. It’s difficult to transport goods across long distances and keep them in good enough condition to sell, especially for perishables like food. Historically, trade routes across mountains and deserts are perilous and more rare than routes across easily navigable terrain. And, until the proliferation of better sailing technology, the western and eastern hemispheres were largely cut off from one another. For a galaxy with entire planets separated by the vacuum of space, one would expect transportation costs to be very high. But in Star Wars, travel between planets is easy, fast, and cheap, thanks to hyperdrive technology that even single-person spaceships often have access to. Hyperdrive enables faster-than-light (FTL) travel, which allows ships to travel across the galaxy in a matter of…hours? It’s never made perfectly clear to viewers, though certainly travelers can get to almost any planet in under a day with this technology, with no obvious downside. However, hyperdrive isn’t free - certain spaceships, like the Empire’s TIE fighters, don’t have it. Moreover, the galactic poor are seldom seen leaving their home regions, and local starports like Mos Eisley on Tatooine allow average people to book offworld transportation for a price – which is exactly how Luke Skywalker and Ben Kenobi meet Han Solo and Chewbacca. If hyperdrive technology were free, Han and Chewie would certainly not be able to charge Luke and Ben a high price for transport. Still, the availability of cheap and widely available FTL technology that can be utilized via small spacecraft has clearly done wonders for the galactic economy. Planets, rather than being separated by millions of years of slow travel or prohibitively expensive technology, can be reached in hours or days at most. Combined with the aforementioned fact that language barriers don’t really exist, transaction costs appear to be very low in Star Wars. The galaxy thus appears to be a beacon of economic productivity. It may come as no surprise, then, that the Empire was able to produce not one, but two moon-sized Death Stars in the span of only a few years. That’s certainly a feat that would require a high level of productivity! The Shadow Economy in Star Wars However, the ease of cheap faster-than-light travel and lack of barriers to communication have clearly allowed criminal elements to flourish in the galaxy. The aforementioned Jabba the Hutt is a member of the Hutt family, who are depicted as cartel-like. But their family isn’t the only criminal enterprise shown. In Star Wars: The Clone Wars and Disney’s The Book of Boba Fett, viewers are introduced to the Pyke Syndicate, who threaten to fill the power vacuum on Tatooine after Jabba’s death (not to mention that Fett tries to launch a criminal empire in the latter series). Several other powerful criminal organizations are seen across Star Wars properties, such as the Crimson Dawn syndicate that features prominently in the movie Solo: A Star Wars story. Bounty hunters also feature often in Star Wars, starting with the motley assortment of hunters hired by Darth Vader in The Empire Strikes Back and recently portrayed by Disney’s popular The Mandalorian. By definition, these bounty hunters operate mostly outside of the law, taking jobs to assassinate, smuggle, escort, hunt, or otherwise accomplish things by force – for a price. Moreover, forced labor and slavery form the backbone of the immoral Empire’s economic machine in some areas. The TV series Andor showcases how the Empire rounded up civilians on trumped-up false charges and kept them in a rotating prison labor system. This is one of the ways that the Empire was seemingly able to churn out the massively expensive Death Star project, as parts for the machine were made in forced labor systems such as these. Not paying for labor (one of the major factors of production) of course lowers the cost of output quite a lot! We don’t have access to reliable measures of the Star Wars galaxy’s total economic output, which may be measurable by GDP as it is in real life. However, it’s likely that just as in our world, the galaxy’s total GDP is probably underreported because of these illegal activities. This is because illegal activities, while they do produce economic value, are not represented in official counts of GDP. In both our world and in Star Wars, illegal products and services create consumer and producer surplus. But, because the good (or service) is illegal, the market occurs in secret and thus the economic value it produces is not reported. These unreported transactions are known as the “shadow economy” in economics, and it is clear that the shadow economy in Star Wars is quite large. Whether legal or not, economic activity around the galaxy is depicted in many ways in Star Wars. Are there other examples we haven’t touched on? What implications do they have for the galactic population? Feel free to introduce your own examples in the comments below! Header image picture credit: gromit15 from Pixabay
Star Wars probably needs no introduction here. One of the largest entertainment properties of all time, it has grown far beyond its (humble?) beginnings on the movie screen. Now, we can learn about “a galaxy far, far away” through books, comics, TV series, video games, and more.
For the first article in the series, in recognition of International Women's Day, we have decided to feature one of the most prominent contemporary female economists, Dr. Esther Duflo. She has become famous among economists for her studies on global poverty alleviation, and she has pioneered the practice of using randomized control trials in development economics. Her studies and experiments have studied health, education, microfinance, and more in the context of global poverty. Dr. Duflo won the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2019 alongside colleagues Abhijit Banerjee and Michael Kremer “for their experimental approach to alleviating global poverty”1, becoming not only the second woman in history, but also the youngest person ever to win the Nobel Prize in economics. The key word in that explanation is “experimental”. Her approach with using experiments to help us understand global poverty has paved the way for more effective policy design. With these experiments, economists have been able to learn more of what truly works to help alleviate poverty, rather than relying on theory. Indeed, the Nobel Prize’s original press release had this to say about Dr. Duflo and her colleagues: “In just two decades, their new experiment-based approach has transformed development economics, which is now a flourishing field of research”2. The difficulty with experiments in economics Economists are similar to scientists in that we attempt to use empirical rigor while learning about the world around us. But, unfortunately, it is often extremely difficult or immoral to conduct experiments about economics. People must have the freedom to live their lives without having their economic situation in life dictated by a curious economist. As an example illustrating why this is difficult, imagine if an economist was interested in the effects of early childhood education (such as preschool) on development, and designed an experiment where certain children were placed in preschool, while others were left at home and did not receive the same educational opportunities. When controlling for other factors, this would help the economist learn about the effectiveness of early childhood education, and could help us design better policies to aid families with accessing the right type of services for their children. But what parent would willingly force a potentially huge disadvantage upon their child (being behind in early learning)? Making an experiment that studied real people and dictated this course of action would be immoral. Thus, experiments in economics are often very difficult to design or conduct, and can be overlooked as it’s often easier to rely on theory. Dr. Esther Duflo’s contributions Despite those typical challenges, Dr. Duflo won her Nobel Prize because she was able to design and implement experiments that teach us more about how poverty works, how people respond to it, and how it can be overcome. She helped pave the way for economists to be bolder with designing field experiments that both aid people and help advance our knowledge, while avoiding moral quandaries; many of these experiments involve providing an economic benefit to a group of people that otherwise wouldn’t have had it. To preserve experimental purity, often the choice of recipient for the intervention is randomly chosen. To aid in systematically conducting such experiments, Dr. Duflo co-founded the Abdul Latif Jameel Poverty Action Lab (or J-PAL for short) with Dr. Abhijit Banerjee and Dr. Sendhil Mullainathan. The Lab’s purpose is to break down the problem of global poverty into smaller, more manageable pieces that can be studied and used to build policy. It does so by conducting randomized control experiments with the global poor in various developing countries and studying the results, much like a natural scientist might do. An example of a study conducted by J-PAL involved building rainwater cisterns to study how having additional resources reduced individuals’ motivations to conduct political clientelism. The experiment randomly chose communities to receive the cisterns, and studied the effect on the democratic process. You can read more about this particular study at J-PAL’s website. Experiments such as these allow economists to learn how to design more effective policies, in this case, how to avoid future clientelism in a developing economy’s democracy3. Read More from Dr. Esther Duflo Besides contributing to developmental economics with these experiments, Dr. Duflo has also published a number of books and contributed to a number of economics texts. One well-known book, Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty (published in 2011) is an excellent read for students of economics. It also exemplifies the reason why Dr. Duflo won her Nobel Prize. The book raises questions about the behavior of the global poor, such as: Why do these people make decisions that seem wrong to many of us in developed countries (such as having so many children)? Why don’t they save more? Then, the book explains how these behaviors are often rational from the perspective of someone who is living in poverty and dealing with challenges many of us are unaware of. For instance, children can be viewed as a vehicle for financial security, especially in areas where child mortality is higher and children are expected to care for their parents as they age. In some parts of the world, children – not a 401(k) – are the default retirement plan. This stands in stark contrast to many developed nations, where children are often viewed as a financial burden due to the cost of childcare. The book additionally examines other questions and concepts (such as if nutritional poverty traps exist) that students of microeconomics may be familiar with. It’s an excellent read that we can heartily recommend. Other books Dr. Duflo has written and contributed to include Good Economics for Hard Times, Elsevier’s Handbook of Field Experiments, Vol. 1 and Vol. 2, and several books in French including two volumes of Lutter contre la pauvrete, Le Développment Humain and La polique de l'autonomie. She has contributed to chapters in books such as the World Bank’s The Influence of Randomized Controlled Trials on Development Economics Research and on Development Policy, Aging and Death Under a Dollar a Day, Field Experiments in Development Economics, and more. Dr. Duflo is currently the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics at the Massachusetts Institute of Technology. She received her PhD in economics from MIT in 1999. She has also received a number of other awards, including a "MacArthur Foundation fellowship (2009), the John Bates Clark Medal from the American Economic Association (2010), and…the BBVA Foundation Frontiers of Knowledge Award for Development Cooperation”4 in 2009. To read more about Dr. Duflo, you can visit the National Women’s History Museum article about her, or read the 2019 Nobel Prize in economics press release. References 1: Esther Duflo – Facts – 2019. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 7 Mar 2023. <https://www.nobelprize.org/prizes/economic-sciences/2019/duflo/facts/> 2: Press release. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 7 Mar 2023. <https://www.nobelprize.org/prizes/economic-sciences/2019/press-release/> 3: Harvesting rainfall: Experimental evidence from Cistern deployment in Northeast Brazil: The abdul latif jameel poverty action lab. The Abdul Latif Jameel Poverty Action Lab (J-PAL). (n.d.). Retrieved March 7, 2023, from https://www.povertyactionlab.org/evaluation/harvesting-rainfall-experimental-evidence-cistern-deployment-northeast-brazil 4: Dizikes, P. (2019, October 14). MIT economists Esther Duflo and Abhijit Banerjee win Nobel prize. MIT News | Massachusetts Institute of Technology. Retrieved March 7, 2023, from https://news.mit.edu/2019/esther-duflo-abhijit-banerjee-win-2019-nobel-prize-economics-1014 Header image attribution: Kris Krüg via Wikimedia Commons, CC BY-SA 2.0 <https://creativecommons.org/licenses/by-sa/2.0>
In this series of articles, INOMICS will highlight the accomplishments of particular economists who have contributed greatly to the field. Students often learn about the great figures in economics only briefly and in passing, but the content taught in economics courses comes from brilliant economists such as these.
Using data visualization as a learning tool One way of motivating students to engage with economic concepts is to begin by showing a visualization of the data, to stimulate students’ interest. Evidence suggests that these visualizations can increase student learning and engagement and deepen their understanding of economics, particularly at an introductory level. An important aspect of the visualization is that there needs to be a striking feature to draw the student’s attention to an issue, concept, or theory, creating a narrative for students to investigate. A time series graph with spikes or trends in the series can be a useful way of drawing the eye and stimulating interest. The visualization should prompt questions that start the learning process: what is going on? Why is this happening? Data visualization is a powerful tool to raise awareness and interest in many economic concepts, topics and theories. It facilitates the application of economic analysis and therefore aids with the consideration of debates, controversies and alternative schools of thought around those issues. As an example, Figure 1 shows one important macroeconomic indicator: the rate of Consumer Prices Index including owner occupiers' housing costs (CPIH) inflation in the UK. The CPIH is the preferred inflation measure of the Office for National Statistics (ONS). Figure 1: UK rate of CPIH inflation Note: CPIH is CPI plus owner-occupied housing costs and council tax. Source: Based on time series data, ONS (series L55O) In the graph above, student’s attention will probably be drawn to the sharp uptick in inflation from 2021. They should be suitably intrigued and quickly follow up with the question as to why this is happening. Sometimes a chart that shows a contrast between two economic data series can be a powerful tool for illustrating changing relationships. For instance, Figure 2 shows the term structure of interest rates (yield curve) for the United States (US) at two different points in time. Figure 2: US yield curves on 1/4/2021 and 1/4/2022 Source: US Treasury When addressing that first question in the learning process, students should see that at the start of April 2021 the relationship between yield and maturity was positive, while a year later it was very different. The visible difference in the graph can be used to prompt students to consider why the relationship changed. In both cases above, answering why this relationship exists involves developing a conceptual understanding of the economic phenomena observed. For example, after students understand the reasons for the inflation shock shown in Figure 1 or the changing slope of the term structure in Figure 2, formal economic models can be introduced to develop students’ conceptual understanding. The intention is that when confronted with economic data in the future, students can intuitively apply the underlying economic theory. The importance of data analysis The analysis of data is one of three core competencies, alongside the application of findings and the effective communication of knowledge, that is identified by the Government Economic Service (GES) technical framework 2022. This document details the technical standards expected from UK government economists. Components of this core competency include the sourcing, organizing, interpreting and presentation of data, and the application of appropriate statistical and spreadsheet software. Data-based projects that require students to source and analyze their own dataset will help to teach them key employment skills, and align with the practice of authentic assessment. There are important pedagogical benefits from encouraging students to identify and source their own unique evidence to demonstrate their understanding of a particular issue or economic concept. Firstly, working with data can foster student confidence and help them to overcome any data-related anxieties that could be detrimental to their development as economists and interest in the subject. Secondly, data-based projects can enable students to feel that they are discovering things for themselves and constructing their knowledge and understanding as they do so. Consequently, they may develop a potentially unique perspective or research process to bring to discussions on a particular topic. Such active assessment has been found to improve engagement and academic performance. To illustrate the latter, consider CPIH inflation further. We can decompose movements in the CPIH inflation by reference to 12 broad divisions based on the Classification of Individual Consumption According to Purpose (COICOP). Students could, for example, look at rates of inflation in particular divisions, such, as transport (Division 7) and housing, water and fuels (Division 4), alongside the overall rate of CPIH inflation. This is illustrated in Figure 3. Students could also analyze inflation rates of classes within the broad divisions. The key is that students are able to take ownership of the task and, through research and enquiry, deepen their understanding. Figure 3: Rates of inflation by specific divisions Notes: CPIH is CPI plus owner-occupied housing costs and council tax; core inflation is CPIH inflation excluding energy, food, alcoholic beverages and tobacco. Source: Based on time series data, ONS (series L55O, L55S and L55V) Conclusion By incorporating data visualization and analysis in our teaching, we provide an authentic learning and assessment experience for students. This will help to further develop the competencies demanded by employers of economics graduates, such as the Government Economic Service in the UK. Further, it will stimulate student interest in the subject – principally students see the relevance of the discipline and its tools of analysis by working with data in an active way. This article was produced in cooperation with the Economics Network, the largest and longest-established academic organisation devoted to improving the teaching and learning of economics in higher education. Learn more about the Economics Network here. Header image picture credit: Pixabay.com
Real-world data in their varied forms are the authentic artifacts through which we observe economic phenomena. Such data can be used in economics courses as part of learning and assessment activities to help students construct economic meaning and develop important employment skills in organizing, interpreting and presenting quantitative data.
Pop Economics: Economics through the lens of pop culture
And those cries for attention seem to be working. We have politicians, policymakers, environmentalists, lawyers, global action groups, local community groups, writers, actors, singers, and talk show hosts talking about the state of the economy. Interestingly, these groups of non-experts seem to understand the economics of daily life better than their accomplished counterparts, or at least they have a knack presenting the ideas more easily. This realization dawned on me when I started my economics PhD on the nexus between debt and the real economy, at which time I had an existing specialization in marketing and only an elementary knowledge of financial concepts. As I read through books, reports and academic papers, I found myself on a perilous expedition with complicated models, charts, techniques and a lexicon that left me baffled. It took me months of annotations, underlining and highlights to make sense of economic text, which continues to date. During this time, I came across multiple pop culture economics references that were closely associated with daily life, more so than tortuous journal papers which often focus on very specific areas of research that aren’t very relatable. It seems impressive how pop culture references integrate the intricacies and complexities of economic concepts and principles into our daily experiences, while economic texts and journal articles feel distant and notional. <11an>limit:3;categories:PhD Programs;disciplines:Economics</11an> So, I got insights into economics’ most debated topics from philosophy, poetry, jazz, rap, satire, movies, podcasts, etc. For starters, consider the statement "Inflation is when you pay fifteen dollars for the ten-dollar haircut you used to get for five dollars when you had hair" which comes from a former baseball player, Sam Ewing. This humorous quote fits the general sentiment very well during times of inflation. We also have the Beatles singing about the government's tax policies, a topic you least expect to make for a good gig, with the catchphrase, "Let me tell you how it will be, there's one for you, nineteen for me". Meanwhile, the line "the way the taxes are, you might as well marry for love" by Joe E. Lewis is another comical take on the grave issue of high taxation. These statements seem to traverse the boundaries of politics and time, remaining relevant to people and groups throughout the eras. Though pop culture has touched all significant economic areas, two trends that tend to be prevalent are consumer sentiments and widening inequality. Time and again, messages about economics in pop culture has represented the aspirations, problems and expectations of the general populace, and when an economic crisis hits (which is often), it highlights the on-the-ground realities better than the designated indexes compiled by economists to represent sentiments. Famous 18th-century philosopher and composer Jean Jacques Rousseau observed, "When the people shall have nothing more to eat, they'll eat the rich", accurately representing the kind of animosity behind growing populism and cynicism towards the elite class. A similar point was put forward in the 1970s by Gil Scott-Heron in his song “Whitey on the moon” , where he blatantly points out the partisan policies of the US government. He writes, "I can't pay no doctor bills, But whitey's on the moon. Ten years from now, I'll be payin' still, While whitey's on the moon.” Similarly, in his satirical take on the government's policies, comedian Will Rogers comments "The money was all appropriated for the top in the hopes that it would trickle down to the needy. Mr. Hoover didn't know that money trickled up." We also have prose and poems commenting on the economy and offering suggestions. The 1980s rock band Dire Straits provided an accurate description of the state of affairs when they sang, "these are class symptoms of a monetary squeeze…sociologists invent words that mean industrial disease". Then we have the 2008 song “Circulate” by Jeezy. "Sound like the country's going broke. The industry's going up in smoke…Please (please), Please (please) Let the dollar circulate", a seemingly workable solution to the liquidity crisis faced by the countries then. In the drama realm, we have popular movies such as Modern Times, Mother India, The Wizard of Oz, Robin Hood, and more recently, The Pursuit of Happyness, Sorry to Bother You, Parasite, Inception, Born Equal, Nightcrawler, High Rise, and Squid Game. There are also dystopian movies like The Hunger Games, The Age of Stupid, and Atlas Shrugged which explain the dynamics of the economy, though they are not a part of the typical wall street genre. So, while you are going over your economic textbooks and journal articles again and again, it might be nice to take a step back and reflect on how these topics affect the average person. And, while you’re at it, you might as well play some good records. Header image picture credit: Pexels via Pixabay.com
So, the economy is in crisis. Well, when is it not? The global economy is becoming like that one histrionic person that is always miserable, in shambles and crying for attention.
If you have your own insights about the #EconMeToo movement and would like to write a blog post about it, we invite you to contact us at submissions@inomics.com. Discrimination in Economics Not only are women outnumbered and underpaid in economics, they also face a disproportionate amount of harassment and discrimination within the field. These issues are unfortunately very common; an AEA survey found that 48% of female economists reported they had experienced discrimination based on their sex, compared to just 3% of male respondents. Some of these other forms of discrimination include not being invited to speak at panels as often as men, and receiving extra scrutiny during presentations relative to their male peers. Harassment in Economics A recent movement, dubbed #EconMeToo on Twitter, has drawn renewed attention to the sexual harassment, assault, and other abuses faced primarily by women in economics. This recent movement began when a professor of economics at an American university spoke out publicly against specific economists. They did so after allegedly being in conversation with a number of female economists who complained about sexual harassment and even assault. These public accusations have been controversial, but the accusers have alleged that very little was accomplished through official channels, and they had no other choice but to escalate. Part of the lingering frustration that has led to this movement is that even despite prior efforts to combat sexual harassment, there are a lack of meaningful consequences for perpetrators in certain spaces in economics. For example, in 2019, the AEA implemented a policy that allows economists to file complaints about sexual misconduct from others, particularly at conferences. Conferences are a realm where university policies often do not help prevent misconduct or punish perpetrators, because attendees are usually from different universities. However, since the AEA is a professional organization and does not have authority over economists’ actual jobs or employers, its policies have little power to enforce consequences. Unsurprisingly, those who have complained through the AEA policy have expressed that problems have persisted due to the lack of consequences for perpetrators. It is unclear how the recent resurgence in attention on gender inequality in economics will affect the field. We hope the environment improves, though time will tell. If you have an opinion about discrimination or harassment in economics, and the issues outlined above, then join the discussion in the comments below. We also invite well-written articles or research summaries that deal with these topics. If you have an insight or case study that you would like to share, we invite you to contact us at submissions@inomics.com. Header Image Credit: Viarami on Pixabay (free for use under the Pixabay Content License)
We have previously written about the gender pay gap and the leaky pipeline in economics. This article highlights other gender-related issues within the field, particularly around gender-based harassment and discrimination in economics.