Sustainability May Be Bolstered By Income: Household Cooking Fuel Choice in a Developing Country
The analysis revealed that an increase in durable asset accumulation heightens the likelihood of households adopting cleaner cooking fuels. Therefore, I find that the Ghanaian government could incentivize the adoption of clean fuels, consequently mitigating environmental pollution, by implementing policies aimed at augmenting household income. More broadly, this means that economic development can have positive effects on sustainability, something that policymakers in other regions should take note of. Introduction The seventh Sustainable Development Goal aims to ensure access to clean and affordable energy by 2030. This goal is crucial because reliance on unclean energy sources like firewood, charcoal, and kerosene cause significant environmental and health issues, including air pollution, deforestation, soil degradation, and harmful emissions that contribute to climate change. These sources emit harmful gasses such as CO2, methane, and nitrogen oxides, which adversely impact human health. Studies by Younger et al. (2022) and Amegah et al. (2012) reveal detrimental health effects from exposure to these gasses, including reduced birth weight and increased neonatal mortality in low-income countries like Ghana). In Ghana, the use of unclean energy stems from “energy poverty”, where households lack access to modern, clean and affordable energy sources. This forces them to resort to dirty and inefficient fuel sources. Factors contributing to this lack of access include low income levels, high prices of modern energy sources, and geographic location. Shockingly, energy poverty in Ghana is reported to be at a staggering 82.5% (Adusah-Poku and Takeuchi, 2019). This study aims to ascertain the impact of durable asset accumulation on the selection of household cooking fuels in Ghana. It posits that durable assets afford households greater financial capacity and purchasing power, enabling them to meet various needs, including access to cleaner fuels. The analysis distinguishes between rural-urban households and households headed by males versus females. The study acknowledges that the main obstacle hindering households from adopting clean fuels is their relatively higher cost. Consequently, households with elevated wages are more inclined to utilize clean fuels owing to their affordability. Moreover, the energy ladder hypothesis posits that as household wages rise, there is a corresponding transition towards cleaner fuel usage. In essence, lower-wage households tend to resort to dirty fuels, whereas those with higher incomes opt for clean fuels (Alem et al. 2016; Bofah, Appiah-Konadu, and Ngwu 2022). Thus, an upsurge in household wages is anticipated to increase the probability of households opting for clean fuels. Methodology Data The investigation relies on microdata extracted from the Ghana Living Standards Survey (GLSS) conducted in 2013 and 2017 by the Ghana Statistical Service (GSS). The sample size comprises 25,569 observations. The study categorizes various fuel types into two groups: dirty and clean fuels. The primary metric for gauging asset accumulation adopts the approach advocated by Filmer and Pritchett (2001), akin to the methodology employed in formulating the wealth index within the Demographic and Health Surveys (DHS). Empirical Model The study regresses the fuel choice of households on the durable asset accumulation index, controlling for household characteristics such as wage, size, location, and poverty status. The logistic regression technique is employed, with average marginal estimates. An instrumental variable estimation (IV) addresses the potential endogeneity problem, using the two-year lag of theft incidents as an instrument. To streamline the analysis, various fuel types were categorized into two groups: dirty and clean fuels. The dirty fuel category encompasses fossil fuel-derived sources such as firewood, charcoal, kerosene, sawdust, and crop and animal residue, while the clean fuel category comprises LPG and electricity. The study aims to discern how durable asset accumulation influences the probability of households opting for clean fuels, with a focus on facilitating the transition towards cleaner energy sources. An asset accumulation index was constructed by amalgamating various forms of durable assets with potential monetary value. These encompass items such as televisions, radios, sewing machines, refrigerators, fans, computers, cars, plots of land, and more outlined in Sections 12.4 and 12.5 of the GLSS. To ensure the index's consistency and avoid negative values, standardization was applied, rendering the index to range between 0 and 1. A model explaining the fuel choice of a household against factors that might influence this choice is given by: E(Fuel choices | Asset accumulation, Age of household’s head, Gender of household’s head, Household size, Household wage income, Geographical location, Father’s education, Household poverty status, Marital status, Expenditure on electricity) which leads to the following functional form: 𝑦 = 𝛽0 + 𝛽1asset_accumulation + 𝛽2age_head + 𝛿3female_head + ⋯ +𝜉i where 𝑦 represents fuel choice, and all other factors mentioned are represented in the ellipsis. Since the dependent variable is a dichotomous variable that lies between 1 and 0, that is, whether a household uses clean fuel or not, I use a logistic regression (Rodriguez, 2007). Supposing a linear model where the probability of 𝑦I is a linear function of its predictors, I estimate the log odds of energy fuel choice given by the following: logit(𝑦i) = 𝛽pXi+ 𝜉I As a result, the model assumes that the linear probability model is a function of natural log odds. To address the potential endogeneity problem associated with asset accumulation, a two-year lag of theft incidents is used. I argue that suffering caused by a theft case two years ago is associated with the current value of total household assets, but not directly on fuel choice in the present. The two-year lag of theft incidents will influence fuel choice only through its influence on the current value of assets. After fitting the model, the Pearson or Hosmer-Lemeshow goodness-of-fit test (gof) suggested that there is no significant difference between the observed and the expected values, indicating a good fit for the model. Further, the Link test returns a p-value of 0.000 for the variable of prediction, indicating that the model is properly specified. The same test also returns a p-value of 0.486 for the variable of squared prediction, suggesting no evidence of model misspecification since it is insignificant. These results suggest that the model does not suffer from specification errors. Results and Discussion The analysis revealed that a one-unit increase in the asset accumulation index increases the household’s likelihood of adopting clean fuels by approximately 7.32 percentage points. Higher income levels enable households to afford cleaner and more efficient cooking fuels like LPG or electricity. This finding is statistically significant at the 5% level. To ensure robustness and accuracy of this result, a bootstrapping procedure with 1000 replications was conducted. The bootstrapped standard errors and confidence intervals further validated the consistency of the estimated coefficient, confirming the reliability of the conclusion. Therefore, policies aimed at increasing household income and assets can incentivize the adoption of clean fuels, thereby mitigating environmental pollution and improving public health. A good strategy for achieving clean energy usage in low-income countries should therefore include economic development aspects. These findings provide valuable insights for policymakers and stakeholders working towards achieving sustainable energy goals; sustainability can be more easily achieved when the households making energy decisions have a sufficient level of income. The author is conducting more research into a related topic to deepen our understanding of the link between sustainability and other factors like education and inequality. First, with the upcoming paper “Female educational inequality and household cooking fuel choice: Evidence from the Ghana Demographic and Health Survey (2022)”, the author hopes to uncover whether better educational outcomes for women correlates with a higher likelihood of adopting cleaner cooking fuels. It is hypothesized that greater inequality in education would likely result in a continued reliance on traditional, unclean cooking fuels due to financial constraints. The author is also working on another upcoming paper, “Educational inequality and Child Stunting: Evidence from the Multiple Indicator Cluster Survey (MICS, 2018) in Ghana”. The study will investigate how education equips parents with better knowledge and resources to provide adequate nutrition and healthcare for their children, potentially reducing the incidence of child stunting. By focusing on these dynamics, the study aims to highlight the critical role of education in improving child health and development outcomes. References Adusah-Poku, F., & Takeuchi, K. (2019). Energy poverty in Ghana: any progress so far? Renewable and Sustainable Energy Reviews, 112, 853-864. Alem, Y., Beyene, A. D., Köhlin, G., & Mekonnen, A. (2016). Modeling household cooking fuel choice: A panel multinomial logit approach. Energy Economics, 59, 129-137. Amegah, A. K., Jaakkola, J. J., Quansah, R., Norgbe, G. K., & Dzodzomenyo, M. (2012). Cooking fuel choices and garbage burning practices as determinants of birth weight: a cross-sectional study in Accra, Ghana. Environmental Health, 11, 1-10. Ansong, E. (2015). The association between household consumer durable assets and maternal health-seeking behavior in Ghana. Women & Health, 55(5), 485-504. Bofah, R. O., Appiah-Konadu, P., & Ngwu, F. N. (2022). Transition to cleaner cooking energy in Ghana. Clean Energy, 6(1), 193-201. Filmer, D., & Pritchett, L. (2001). The effect of household wealth on educational attainment: evidence from 35 countries. Population and development review, 25(1), 85-120. Kafle, K. R., & Dean, J. (2015). Effects of asset ownership on child health indicators and educational performance in Tanzania. Rodriguez, G. (2007). Logit Models for Binary Data (p. Chapter 3). Retrieved from http://data.princeton.edu/wws509/notes/ Younger, A., Alkon, A., Harknett, K., Louis, R. J., & Thompson, L. M. (2022). Adverse birth outcomes associated with household air pollution from unclean cooking fuels in low-and middle-income countries: a systematic review. Environmental research, 204, 112274. Header image credit: Pexels from Pixabay (Free for use under the Pixabay Content License)
The Sustainable Development Goals advocate ensuring universal access to clean and affordable energy by 2030, prompting a global push toward transitioning from unclean energy sources to cleaner alternatives. In response, Ghana has subsidized the cost of clean energy; however, the financial burden of this transition remains substantial for households. The role of household asset accumulation in facilitating this transition has been underexplored in existing literature; examples include Kafle and Dean (2015) and Ansong (2015). Utilizing logistic and instrumental variables (IV) regression methods along with data from the Ghana Living Standards Survey (round 6 & 7), I investigated how durable asset accumulation influences households' choice of cooking fuels in the research paper "The Nexus Between Household Durable Asset Accumulation And Household Cooking Fuel Choice in a Developing Country".
Economic Development, Innovation and Growth (JEL O)
Agricultural and Environmental Economics (JEL Q)
Extracurricular activities to help your economics career while at university
Being involved in extracurriculars at university can make your time there more enjoyable by enabling you to meet friends, develop intellectually, and stay fit. You may not have considered it, but relevant hobbies for economists can even be advantages in your career development, too! This article explores some suitable economics hobby ideas that you might find beneficial. Although lots of these suggestions will help you whatever career you decide to pursue, some may be a little more useful specifically for a career in economics. Browse our program listings for economics opportunities 1. Debate team Joining the debate team will give you the chance to practice your oral presentation, argumentation, and critical thinking skills – all of which will be a big asset to you in any economics job search. It's also a great way to practice your public speaking, which can be a helpful advantage in job interviews. The ability to think through a position and support it with facts and logic is incredibly relevant to any research you do, too. On a fundamental level, research is posing a question, and either supporting or detracting from that question using facts and logic – just like debate! In economics research, the facts may need to be taken from a literature review or generated by your own econometric analysis, but the fundamentals are remarkably similar. Debate will also help your communication skills, which are one of the most important soft skills to have, useful in all aspects of life. Being able to communicate your ideas and research effectively, or back up your economics findings in your career, is essential to being successful. 2. Student governance Almost every university will have some kind of students' union or student council which you could join. Doing so shows future employers that you are responsible and engaged with political and practical issues. It also gives you the chance to make real changes to the way that your university is run. Being a part of the students' union shows proactivity and leadership – that you have (productive) opinions and aren't afraid to voice them and fight for them. It implies you can speak your mind well in public, but also that you have a level of emotional empathy that enables you to listen to and appreciate – or at least respect – other points of view, even when they stand in direct contradiction with your own. Being involved in politics is also very useful for a job in economics, particularly policy-adjacent roles. 3. IT skills Students may have the opportunity to assist university staff and/or students with technical problems. Often, universities employ student workers in IT help roles as a first line of defense against tech issues, helping other students on campus resolve computer problems – and escalating to a more seasoned professional for non-routine fixes. These types of roles may also give you limited experience with coding, especially if your job includes performing functions for university webpages. Software proficiency is becoming increasingly important for economists, so demonstrating technical skill in this area is a bonus for most employers. Economists often need to use statistical software like R, SAS, Stata, and more for their work, and other tools like LaTeX will be useful in their careers. Showing employers that you have the skills needed to master new software tools quickly can be a big plus for your future job prospects. 4. Charity fundraising Volunteering can be a rewarding experience and can help you grow a lot as a person. It can also be good for your career prospects, even beyond just showing your strength of character. If you want to work in a non-profit after university, or conduct research, then the ability to bring in funding (either by typical fundraisers or by securing grants) is a big requirement of many jobs. Showing that you've already been successful at fundraising while you were at university can put you at the head of the pack. Moreover, charity fundraising can often give you the opportunity to travel. Plenty of charities work around the country and in other nations around the world. Travelling is one of the most rewarding things you can do, and employers like to see that their potential employees are well-rounded and have some life experience, which includes getting to know other cultures. Aside from this, charity work is simply a noble thing to do and can show that you're emotionally intelligent and tolerant, two essential skills to have in an ever more diverse workplace. And, you might even benefit from that “warm glow” that stodgy economists talk about when describing altruistic behavior. 5. Sports teams Sports teams are often a big part of university life, and most universities provide such a variety of sports clubs that almost everyone can find something that matches their interests and talents. These might offer the opportunity to travel around the country and occasionally the world, especially if you join something a little bit more niche like scuba diving. And of course, sports are a great way to meet new people who could become lifelong friends, improve your teamwork and social skills, and stay fit while doing it. Best of all, from a career point of view, if you are head of a team and organizing matches, you have already shown your ability to lead a group which is a great skill to demonstrate. 6. Student newspaper Student newspapers are great places to develop writing and editing skills, and to get used to a fast pace of work with tight deadlines. There are usually multiple areas of the newspaper you can work on, including design, editorial, and of course, writing and journalism. Many newspapers have local news, political reports, and comment sections that deal with more sensitive issues. Even if you just write a few times rather than having a set role at the paper, it means you'll slowly build your portfolio of written work (which can be useful if you’re asked for non-academic writing samples), have some interesting things to put on your CV – and of course, seeing your name in print is always a wonderful feeling. Some university papers may even pay for your work. Learning how to write well can be an essential skill if you're going to be communicating complicated economics ideas to non-economist audiences for whichever company or institute you're working for. Clear communication skills are an area that employers have already identified as important for economics graduates. Academic language is often impenetrable, so being able to show that you can present your ideas clearly and concisely outside of academic contexts is an invaluable skill. 7. Learning a language Learning a language is one of the most productive things you can do in life. With language skills, you can work in an international company and be an extremely valuable asset to them, or you could even move into specialized economist roles that require multiple languages such as international politics, working as Chief of Staff for an international development project, or conducting research with economists in other regions. It also means if you ever decide you want to live abroad, you have a head start; not only could you live, for example, in Germany, but many people report learning a third language easier once they have already learned a second. Reports have also come out that suggest learning a new language is one of the best favors you can do for your brain, with some studies suggesting it can even help prevent Alzheimer's. Many universities' language courses are of a high standard – as one would expect – and as they are generally diverse, multicultural environments, with plenty of opportunities to practice with other students. If you want to learn a language, adding a few courses to your schedule during your studies is an excellent way to get started. 8. Entrepreneurship For the really ambitious student, why not start your own business? It may not feel like it, but at university you'll be in an ideal environment with plenty of time and resources to develop your own ideas. That’s because adult life outside of uni is often much busier. Often, universities have entrepreneur challenges where students pit their ideas against one another in order to win a certain pool of money that might even help them get the idea off the ground. They also often offer advice and support for students who have business ideas, host entrepreneurship courses, and of course, you might have the opportunity to befriend a business professor to tutor you. Whether or not your business is successful, you'll learn a huge amount from trying to start a business before your peers have even got a foot into the workplace. Plus, it's a clear demonstration of your independence and self-motivation which employers will appreciate, especially if you plan to specialize in financial economics or wish to work in a policy analysis role related to business. 9. Chess Club or Go Club The age-old games of chess and Go both have massive followings, chess traditionally in the West and Russia, and Go more traditionally in East Asia – although both are now played worldwide. Aptitude in either game can be seen as a sign of strategic thinking, dedication, and intelligence. So, if you already enjoy chess or Go, joining a university club for the hobby or doing well in tournaments can be a perk on your future economics resume. Both chess and Go can develop your critical thinking and ability to improvise and adapt successfully, too. This idea extends to other strategic hobbies as well. Other strategy games likely help develop similar skills and show your acumen just like chess or Go can, but employers will likely only be impressed if they actually know what the game is. Header image credit: Lukas Prudil on Pixabay (published under pixabay content license)
Attending university can be a ton of fun, but it’s also supposed to prepare you for the next stage in your career. Normally, this involves a lot of studying. But breaks and hobbies are important to have, too.
Put simply, the multiplier effect is the macroeconomic phenomenon that causes the economy to grow (or shrink) by more than the amount of money that has been introduced into or taken away from it. This is possible because of a chain reaction caused by the fact that money can be used many times. The effect in action Let’s begin with an economic growth example, where the effect has a positive impact on the economy. Suppose that someone experiences an exogenous increase in wealth of $500, meaning that this $500 magically appears in the economy and is granted to one randomly-chosen person – let’s call him Frank. When Frank receives this magically generated $500, the total amount of money in the economy grows by $500 immediately. Thus, GDP (defined by the income method) has also grown by $500. But Frank hasn’t even done anything with the money yet! Let’s say he chooses to save $200 of it, and he spends the other $300 on a pair of limited-edition Air Jordan shoes from Nike. Now, although the amount of money in the economy hasn’t changed, the economy itself has actually grown by $800 (in total)! That’s because the $300 that Frank spent on Nike shoes just became new income for the owner of the Nike store. Now, suppose that the owner of the Nike store chooses to save $200 of Frank’s extra spending, and chooses to use the remaining $100 to have the store cleaned by Silva’s cleaning service. The $100 becomes income for Mr. Silva, the owner of the cleaning service. Now, the economy has grown by a total of 500 + 300 + 100 = $900, all from Frank’s magical $500. This process will continue, increasing GDP by much more than the original $500 that Frank acquired. Readers may wonder how this makes sense. Hasn’t the money just moved around, and Frank has become poorer? After all, once Frank spends $300, he only has $200 left. This question seems logical but is missing a key fact. Frank isn't poorer. Rather, he's just traded $300 in cash for $300 worth of goods (the Air Jordans), which theoretically increased his utility by at least $300 (since we assume he’s behaving rationally to maximize utility). Then, his $300 became income for another person, and the cycle continued. If the money changes hands faster, the economy grows faster; this is measured by the velocity of circulation. Mathematically-minded readers might realize at this point that there is technically no end to this ripple effect – just like an infinite series in math, the money will perpetually continue to circulate through and stimulate the economy. Of course, in economic terms, eventually the amount of money received is so negligible (fractions of cents) that we can ignore it. While most economics courses won’t test your calculus knowledge by asking you to solve a limit problem, it’s important to understand this concept as it filters through many layers of macroeconomic policy. Government spending, fractional reserve banking requirements, changes in national income, changes in consumer sentiment, and more can have massive ripple effects on the economy thanks to the multiplier effect. Multiplier Math From our example with Frank above, it’s clear that there are two factors controlling the size of the multiplier effect: the speed in which the money changes hands, and the amount of money that is saved by each person in this chain reaction. The former effect is determined by the velocity of circulation, and the latter by the marginal propensity to consume (MPC). The formula for the multiplier m is: m = 1 / (1 – MPC) where MPC is the marginal propensity to consume. To recap, the MPC is a proportion that determines how much money individuals will spend when they receive an amount of money. A high MPC means that there’s a lot of spending, but little saving. A high MPC also means that the multiplier m is high as well. The closer the MPC is to 1, the higher the multiplier m becomes. In other words, as people save less and less money, the multiplier effect causes the economy to grow more and more from an influx of new (exogenous) income. This is clear when considering our story with Frank earlier. The formula above accounts for the MPC, but we also mentioned that the velocity of money plays an important role. Although it doesn’t appear formally in the above equation, the velocity of money is partly determined by the MPC, and is proportional to m itself; when the velocity is high, m is high and MPC is also high. For a formal treatment on the derivation of the multiplier effect that also covers its mathematical relationship with velocity, see the Further Reading section. Implications for recessions and government spending The multiplier effect may also be referred to as the fiscal multiplier or the Keynesian Multiplier. The reason for this is simple: the multiplier effect was proposed by John Maynard Keynes, and is implied by his theories. In classical economics, individuals perfectly anticipate that an increase in government spending must be funded by taxes taken from them, and when they adjust their behavior to account for that, the economy is unaffected. For the rest of this section, we ignore the classical model and assume that the Keynesian model is correct. Recessions are one of the unfortunate realities of economic life. When a recession hits, people tend to cut back on their consumption spending (especially on things like luxury goods) and attempt to save as they seek to weather the economic storm. Unfortunately, this behavior can make recessions worse – and the multiplier effect shows how. Consider the case where Frank lost $500 instead of gaining it, perhaps because he had a $500 bill, but it was burned up on accident and ruined. This would reduce the money supply, and the future transactions with the Nike store and the cleaning company wouldn’t happen. In fact, because Frank is poorer now than he was before, Frank would cut back on his spending such that even fewer transactions happen in the economy than before he lost the money. This gives us a template for how recessions can occur and linger in the economy. An exogenous negative shock to the economy causes a reduction in income. Then, people tend to cut back on their spending, and because of the multiplier effect, even more people cut back on even more spending. The result is that the economy shrinks by much more than the original amount that was lost. Enter Keynesian economics. One of the tenets of Keynesian theory is that an increase in government spending (G in the aggregate demand formulation) can offset the downturn, and help the economy recover. The initial spending increase by the government first improves the economy by itself. Then, those who receive this spending as income will in turn save some and spend some – according to their marginal propensity to consume – and the multiplier effect will get to work, bolstering the economy by more than the initial amount of government spending. Good to Know Throughout this article, we have assumed that everyone has the same marginal propensity to consume. But, in the real world, people’s MPC varies greatly depending on many factors, like personality and how well-off they are. People with more money tend to have lower marginal propensities to consume. That’s partly because the proportion of money they need to spend on necessary items (like food and heating) is very low. Naturally, this also means that people with larger amounts of wealth tend to save more. This fact is one potential argument in favor of focusing government stimulus efforts – like giving out cash during a pandemic, or tax cuts – to poorer people rather than richer people. The former group is not only much more likely to spend their money in the local economy, but they also have higher marginal propensities to consume, bolstering the multiplier effect compared to a very wealthy person who would save more of that money. Further Reading For a formal derivation of the multiplier effect, along with an examination of its relationship with the velocity of circulation through the quantity theory of money equation (MV = PY), be sure to read Wang, Xu, and Liu’s “Keynesian multiplier versus velocity of money”, published in Physics Procedia, Volume 3, Issue 5 in 2010: https://doi.org/10.1016/j.phpro.2010.07.009.
Economic growth leads to higher income for everyone – at least in theory. This isn’t a surprising fact. What may be surprising, though, is that adding $500 to the economy can actually increase economic growth by more than $500. This is possible because of a phenomenon known in economics as the multiplier effect; let’s take a look at what the multiplier effect is and how it works.
Assumptions Mainstream economic theory is built upon a foundation of assumptions that are becoming increasingly outdated. For example, the way that businesses operate has changed drastically over the lifetime of the discipline, though many of the core assumptions of economics have remained unchanged. The shift towards the ‘knowledge economy’ and the idea of ‘economies of scale’ are proof of this business evolution. Both of these concepts have great appeal for capitalists – if companies get bigger, they benefit from cost savings. Bulk buying, advertising discounts, lower borrowing costs, and the ability to reduce fixed costs proportionally can all help bigger organisations reduce their average spend. Image credit: University of Bath. However, should companies get too large, ‘diseconomies of scale’ can set in. Perhaps production processes for different components can’t scale up at the same speed, communications get lost in translation, or workers start to feel less motivated. The theory implies that as businesses grow, they eventually hit limitations. This should mean that no company can grow large enough to corner the market. At least, that’s what we used to think. Grow – Continuously. While some companies still have scope for diseconomies of scale, in other cases, these forces can be offset by ‘increasing returns to scale’ which allow growing companies to reinforce their gains. Often described as ‘being ahead to get further ahead’, if a company grows by clever strategy – or even by chance – increasing returns can magnify this advantage. Therefore, the product, company, or technology can go on to lock in the market. In the new intangible economy, companies can grow – continuously. There are different sources of increasing returns, too. For example, the idea of ‘learning by doing’ (the more experience you have in doing something, the better you become) is one mechanism by which companies can experience increasing returns. Take the production of lithium-ion batteries for electric vehicles (EVs). According to Morgan Stanley researcher Michael Mauboussin, “cumulative output has moved Tesla down the cost curve faster than its competitors” for batteries and EV production. Morgan Stanley analysis finds that Tesla has benefited from lower battery costs and operates the most productive automobile plant in the US. Another example is ‘network effects’, when the value of a good or service increases as more people use it. Platform businesses are a good example of these. If a ride-share company such as Uber attracts more riders, they will find it easier to recruit more drivers, customers will be able to find rides faster, these effects will attract more customers, and so on. Image credit: University of Bath. The AI Catalyst: Accentuating Superstar Status The advent of artificial intelligence (AI) is poised to further entrench the position of larger companies, amplifying their growth in sales, employment, and market valuations. By leveraging the power of AI, these "superstar" companies could solidify their dominance and exacerbate existing power imbalances within the global economy. Counterbalancing Forces: Regulation and Complacency Despite their formidable advantages, the rise of knowledge companies is not unstoppable. Regulations and the threat of complacency could serve as counterbalancing forces, curbing their unchecked growth and dominance. Regulatory Oversight Regulatory bodies can intervene to prevent monopolistic practices and promote fair competition, as exemplified by the recent US antitrust lawsuit against Apple alleging "exclusionary, anticompetitive conduct." While tech giants often defend such actions as necessary for innovation, regulatory oversight remains a crucial check on their power. The Complacency Trap Success can also breed complacency, leading companies to become overly reliant on their "golden goose" and neglect innovation. As warned by experts, even technologies with powerful network effects, like the fax machine, can be superseded by better alternatives if companies fail to adapt and innovate. Embracing the Next Wave As the renowned economist W. Brian Arthur cautioned, "the ability to profit under increasing returns is only as good as the ability to see what's coming in the next cycle and to position oneself for it." While the current wave of technological advancements has enriched some companies to stardom and reshaped the global economy, their fortunes are not guaranteed. Complacency and a failure to anticipate the next disruptive innovation could render even the mightiest companies obsolete. As Arthur sagely advised, "Those who have made a killing on this cycle should not become complacent," for "technology comes in successive waves," and those who position themselves for the next wave may emerge victorious. Image credit: University of Bath. Fuel Your Mind. Transform Your Career. Packed with engaging, challenging, real-world content, you can further your understanding of the world of economics with the University of Bath’s Applied Economics (Banking and Financial Markets) online MSc. Find out how you can make strategic decisions that could impact the next wave of economic growth. Join the next student intake. INOMICS would like to thank the University of Bath for their support in the production of this article. Header image credit: University of Bath.
In today’s world, the discipline of economics finds itself at an inflection point. The mainstream orthodoxy, often criticised for being made up of half-truths, is starting to unravel. As a result, a transformative shift is happening.
In other words, information goods are non-rivalrous, i.e. one person consuming it does not affect another person’s ability to consume it, too. Further, as they can be freely shared, they’re considered non-excludable in “normal” circumstances, which means they can be accessed and consumed by people who have not paid for them. As such they can be considered a subset of public goods (since they’re both non-rival and non-excludable). Markets usually fail to produce the socially optimal level of public goods, since the incentives to produce them are very low compared to their benefits. This is one of the reasons why information goods are often patentable, subject to copyright, or considered intellectual property, which typically make them temporarily excludable for commercial use. These innovations in economic law allow markets to produce a healthy level of these goods – more on this later. For example, a book can be considered an information good. It contains knowledge, or simply a good story, that can be copyrighted and digitized for distribution, and it’s not depleted when consumers enjoy it. In the same way, movies, music, and video games can also be considered information goods. Many of these goods can take physical forms, too; books, CDs, and DVDs can be held, for example. But that doesn’t prevent them from being considered information goods, because what differentiates one book from another is the text printed into it. And, since that text can be digitized and distributed, it is an information good. There are many other examples: online courses, databases, software programs, algorithms like specific AI models, and even your private consumer data are all information goods. Information goods often have high fixed costs to develop, because someone must discover or invent the information that’s worth selling. Consider a pop song, for example. It takes years of training and many hours of hard work to write a high quality, record-breaking pop song. However, after development is complete, the variable cost to produce and distribute the song is almost zero (at least in modern times) – once recorded, it’s very easy and cheap to spread the music. These characteristics of information goods pose problems for the creators of the goods; recall that in a perfectly competitive market equilibrium, goods are sold where the price equals the marginal cost. But if that’s true, a seller of an information good might reasonably expect to make zero profit! How then can innovators be motivated to develop their products at all? Protections for information goods abound in modern society Because competitive markets usually have trouble reaching the socially optimal level of production for public goods like information goods, societies have constructed laws to allow innovators to make profit from them. These laws include copyright and intellectual property rights laws, among others. For simplification, let’s refer to all of these laws as simply a ‘protection’ for now. Governments may approve a protection immediately when a work is created, after a work or invention has been successfully proven to be unique and worthy of protection, or in other ways. These protections typically allow information goods to be legally excludable for a limited time (granting limited-time monopolies), thereby encouraging innovation. This solves many of the problems we’d normally expect from a market selling information goods, though it does create new problems. Monopolies are notoriously inefficient arrangements for markets, as they lower output to maximize profit. They also introduce the potential for price discrimination. The exact protections vary by the specific law and the country the information good is being traded in, but nevertheless offer similar benefits: the creator of the good is given the exclusive right to profit from their invention for a period of time. They may also allow others to profit from their work, for example by issuing licenses or collecting royalties, but they usually control the process of granting approval and dictate the terms of use. Despite the drawbacks of monopoly, these systems of protection are good for the economy, as they provide incentives for these public goods to be developed in the first place. Without them, innovation would be severely limited. Any company could steal proprietary code for a new software product, any pharmaceutical company could immediately and cheaply copy another’s discovery, etc. The high cost of development for low-to-zero payoff would incentivize individuals against developing these information-based innovations at all. In summary, without protections innovators and creators would be unable to profit from their creations efficiently and would have a much reduced incentive to innovate, which would drastically slow the pace of economic growth. Thus, having these protections in place encourages innovation without fully preventing society from reaping the benefits of widely shared information goods. Network effects and tipping points Information goods are often made better when many people experience the goods. That’s because they often create positive externalities, which are also famously under-provided by competitive markets. For instance, computer software products like Microsoft’s Windows operating system are often a better experience when more people use them (in other words, they have network effects). It’s easier to share files, troubleshoot, and develop applications when the majority of people are using the same system. Similarly, being a fan of a particular movie or TV series is more enjoyable for most people when their friends are also fans, and companies tend to produce more content for more popular series. Because of these positive externalities and network effects, buyers may decide that certain information goods aren’t worth purchasing unless there is a sufficient user base already. And, information goods with a higher number of users may attract more potential buyers simply because there’s already many people using them. In this way, the markets for information goods may feature a “tipping point” where all consumers suddenly want to be part of that ecosystem, and other products struggle to attract buyers. These tipping points can suddenly cause otherwise competitive markets to resemble monopolies or oligopolies – even without formal intervention. A classic example is the market for smartphones, which is dominated by Google’s Android (and also Apple’s iPhone in the United States). Other aspects of markets trading information goods But the markets for information goods pose other challenges for consumers. Some information goods can also be considered “experience goods”. This means that in order to know exactly what’s being sold, a potential customer must experience the information first – thereby eliminating their need to buy the good at all. Normally, it’s easy to inspect the product being sold. Buyers of pears, for instance, can easily tell if they’re in good condition, if they’re ripe enough, and how large they are before buying. It’s easy to tell if a pear is worth the price, even if you can’t bite it until you buy it. But experience goods don’t share this feature. For example, when looking to experience a movie or a novel, consumers won’t know the quality of the item at all until they buy it and have access to the full experience. This sounds highly problematic in theory, but in reality, markets have adapted quite well to this feature of information goods. Readers can likely already think of several market innovations that help to mitigate these aspects of experience goods. Movies and TV series frequently release trailers; books sometimes offer free previews, or can be rented from libraries; and sellers of software products (like video game companies) often provide demos for interested buyers. These previews allow consumers to get a taste of the good, and decide to purchase or not. “Shareware” is a similar concept, where developers release an information good for free, and ask consumers who enjoyed it to donate and support them. Further Reading For a more formal introduction to information goods, look no further than Dr. Michael Hutter’s Information Goods chapter published in the Handbook for Cultural Economics, https://doi.org/10.4337/9781788975803.00038.
Information goods are an important component of the modern economy. The definition of “information good” may vary, but it generally refers to goods that can be shared digitally (even if they haven’t been) and aren’t depleted when consumed.
It’s helpful to define the term “investment” in an economics sense before continuing. The word “investment” in finance and in everyday discourse usually refers to the buying and selling of assets like financial securities. However, in economics, investments are economic activities that have potential to grow the economy. They can be conducted by private firms, governments or other entities (like entrepreneurs) Examples include the building of a new university, the construction of a manufacturing facility, or the R&D expenses used to develop a new medication. When firms or other economic agents want to make an economic investment, they must typically take out a loan, usually with the help of a bank to act as an intermediary. The money comes from funds that economic agents have saved, which are then considered loanable funds since these are the funds banks can repackage and make available for borrowing as loans. So, the savings-investment identity holds true by necessity. The amount of money available for borrowing is equal to the amount of savings that economic agents have stored, because those savings are converted into loanable funds. Describing the identity mathematically We can show this identity mathematically by using the formula for GDP and making some assumptions. The relevant formula is: GDP = C + I + G + NX, where C stands for consumption, I stands for investment (defined just as we’ve discussed above), G is government spending, and NX represents net exports. As a side note, readers may notice that this is the same as the equation for aggregate demand (AD), and that’s because GDP is one measure of Y, or economic output. When the economy is in long-term macroeconomic equilibrium, Y as measured by GDP is equal to AD and both short-run and long-run aggregate supply. Returning to the equation, let’s assume that the economy under consideration does not trade with any others, so that the NX term is zero. Let’s also assume that aggregate demand and both short-run and long-run aggregate supply are in a stable long-term equilibrium, which means that GDP = AD = SRAS = LRAS = Y. These two assumptions allow us to replace GDP with economic output Y and ignore NX, transforming our equation to: Y = C + I + G. Now subtract the portions of GDP that account for spending activity, yielding: Y - C - G = I. This shows that economic output minus consumption and government spending is equal to investment. We can replace the term on the left-hand side with one “new” term: savings S. This gives us the savings-investment identity S = I. Macroeconomics courses may define Y - C - G = S straight away, but let’s walk through the logic behind this idea further. To see how S = Y - C - G, consider the following. When rational economic agents have money on hand, they must choose how to allocate that money among two basic options: spending it or saving it. Every use of money falls into one of these two basic categories. Money that is not spent must be saved, and vice versa, or else money is being irrationally lost or is going unused. While that is possible in the real world, it’s common and useful to assume that all money not used for consumption is put into savings, such that there is no money lost or “wasted”. (Even quite advanced economics courses typically assume this, since wasting money represents a Pareto inefficiency, and is an irrational “decision” facing no meaningful tradeoffs, making it economically irrelevant. It is always economically optimal to not waste money.) Considered from an economy-wide perspective, then, economic agents do not waste money and must choose between two basic options: save or spend the money they have. The total amount of money they have is Y (remember that GDP can be considered the sum of all income in the economy!). Then, the government, individuals (or households) and firms choose to spend some of their money on goods and services, increasing the spending categories C and G as they do. In this example, all spending falls into either C or G. Finally, any money that governments, firms or consumers have left over becomes savings, S, which is used in the loanable funds market to supply borrowers with loans. Then, these borrowers use those loans to invest in economic investment projects that will grow the economy. Thus, as long as money isn’t wasted or destroyed, S = I, and Y = C + I (or S) + G. See the diagram below for a depiction of this process. Incidentally, the proportion that consumers choose to save – which can change depending on people’s preferences and the state of the economy – is determined by the marginal propensity to consume. Readers interested in this effect should read the linked article. A note on taxes Taxes have been hidden in our analysis thus far, but it helps to include them formally. Before, we did not do so because in a closed economy without trade, all government spending G must be funded by taxes T taken from domestic consumers. So, in the previous section, G = T and Y is not affected by the level of taxes, since all taxes taken from consumers’ incomes (C and I) are used in G as the government’s income (of course, this assumes there is no deadweight loss from taxation). Another way to view the previous section’s equation, then, is: total national income Y equals consumption spending C plus savings S (aka investment) plus taxes T; Y = C + S + T. In other words, the total income for consumers Y is spent on either consumption, savings, or taxes. This corresponds to the income method of constructing GDP discussed in the linked GDP article. Now with trade: the identity in open vs. closed economies In this section, we consider “open economies” to be those that trade with other countries, while “closed economies” are those that are not open to any trade (they are autarkic). The above discussion is accurate for closed economies. The savings-investment identity works similarly as before for open economies, with one key difference: in open economies, foreign economic agents can invest in the domestic economy, and domestic agents can save in foreign economies. If the balance of these financial flows is not equal to zero, the NX term reappears in our equation: Y = C + I + G + NX. We can further break up NX into two terms, imports M and exports X, so that net exports NX = X – M. Now it’s clear to see that NX is negative when there are more imports than exports, decreasing Y. This means domestic agents are spending more money to acquire foreign goods (imports) than foreign agents are spending to buy domestic goods (exports). This lowers Y, and ceteris paribus means that there is less investment in the domestic economy. Instead, domestic agents are sending money abroad (by purchasing foreign goods). Conversely, if exports X are greater than imports M, NX is positive. This is the case when domestic agents are spending less abroad than foreign agents spend domestically. This grants the domestic economy more savings than it would have otherwise had, potentially increasing the amount of investment than would be possible with only domestic agents saving. Incidentally, the balance of imports and exports may be referred to as a trade balance. This also affects an economy’s capital accumulation. When X > M, it is said to be a trade surplus and it causes a “net capital inflow”, and when M < X it is a trade deficit and causes a “net capital outflow”. Mathematically, we must modify the closed economy version of the formula to account for these new possibilities. Now, our full equation is Y = C + I + G + X - M. Notice that if X = M (the case with an even trade balance), our analysis is exactly the same as before. And finally, before proceeding, note that S is now the total amount of savings in the domestic economy, from all sources. We have two equations for Y; the “aggregate demand” version just defined and the income equation Y = C + S + T. Setting these two equations equal yields C + S + T = C + I + G + X - M. Consumption spending cancels to yield: S + T = I + G + X - M. Subtract taxes to finally yield the savings equation in this open economy: S = I + G - T + X - M. Now, savings in the domestic economy equals savings by domestic agents I, plus government saving G - T, plus savings by foreign agents X - M. It’s also clear that if government income and spending are equal, and if the trade balance is perfectly even, savings equals investment as before. Readers may be confused by the above. How can the identity still hold, if the balance of trade isn’t even? To see this, recall that S in the above equation is total savings in the domestic economy. It’s possible for total savings in an open economy to be greater than the amount saved by domestic agents in a closed economy, if foreign agents save money in the domestic economy. This may seem like a violation of the identity. But, it isn’t, because foreign agents saving domestically represents income or investment for a domestic agent to utilize, growing the economy more than it could have on its own. In this article, we’ve assumed that foreign money only enters the domestic economy when foreign agents purchase domestic goods and services, increasing X. Yet in the real world, it’s possible (and quite common) to outright purchase foreign assets or save money in foreign economies. This doesn’t change our analysis, however; these activities can simply be considered a part of exports in our simplified model. Finally, note that the savings-investment identity must hold globally as well. If all savings and all investments in the world are summed, they will be equal. To see this, redefine the “domestic” economy as the entire world. In this case, there is no foreign trade, only trade among domestic agents. Then, the equation simplifies to the closed economy case above where I = S = Y - C - G. Further Reading The IS Curve is a concept that follows directly from this description of the savings-investment identity and the goods market. It describes in a single curve the equilibrium points for the goods market where investment equals savings, and is used as one of the main portions of the IS-LM model in macroeconomics. The liquidity preference model and the demand for money form the LM part of the IS-LM model.
The savings-investment identity in economics is a macroeconomic concept related to aggregate demand, the IS Curve and the market for loanable funds. This identity states that the amount of funds available for investment activities must be equal to the amount of money saved in the economy. It can also be thought of as an accounting identity, as it is true by definition.
This means that supply and demand are balanced. There is no excess demand, no supply surplus, and no problems: everyone can participate in the market transactions they want to. This is only possible if aggregate demand and aggregate supply are equal (AD = AS; we assume in this article that short and long-run aggregate supply are the same). This also happens to be the point where desired national savings and desired national investment are in equilibrium at a certain interest rate. Understanding how these concepts are intertwined is important for intermediate macroeconomics students, so let’s dive in. National savings and the goods market equilibrium condition The goods market equilibrium is often defined in economics textbooks as the point where “desired national savings” equals “desired national investment”, sometimes referencing the savings-investment identity, since the identity describes how investments must equal savings. Some authors or textbooks might introduce these concepts together. But this identity doesn’t seem to be at all related to product markets or the point where AD = AS, so let’s examine further. Goods market equilibrium emerges from a description of GDP that uses the same equation as that for aggregate demand: Y = C + I + G + NX. In short, one of the methods for calculating GDP is to sum up spending in the economy, including consumption spending C, investment spending I, government spending G, and – you guessed it – net spending on trade NX. By this logic, GDP can be thought of as the sum of all spending in the economy, since all money is either spent to acquire goods or is “spent” on savings, which fuels investment spending. The savings-investment identity in this construction of GDP describes that spending on investment is fueled by savings, and thus that savings really represents investment spending. Therefore calculating GDP by focusing on spending does not exclude savings. Let’s start by examining the market equilibrium using algebra. The goods market is in equilibrium when AD = AS. This is also the point where the economy is producing at its full employment potential output Y. The equation for Y is as follows: Y = C + I + G (we ignore trade and assume the economy is in autarky here, for simplification). For a full explanation on this equation, see the article on aggregate demand. We adjust this equation to the following to prove that at the goods market equilibrium, desired national saving is equal to desired national investment and the savings-investment identity holds. It becomes: Yd = Cd + Id + G. Here, the d superscript indicates the desired level of the variable, such that Yd is desired output, etc. As a simplification, government spending G is assumed to be exogenous. Now, just as with the savings-investment identity, subtract to yield: Yd - Cd - G = Id. To finish our analysis, we must realize that the left-hand side of this equation is simply desired national savings. That’s because all income must be spent in one of three ways: buying goods and services, saving, or taxes. Notice that Yd represents total output, which is the same as total income for all agents in the economy. Now that we’ve subtracted two of the three ways income can be spent from it on the left-hand side, we’re left with only savings as the last portion of income that wasn’t spent on taxes or consumption. Therefore, Sd = Yd - Cd - G = Id. This is the goods market equilibrium, and it shows that the savings-investment identity must hold. It also has an effect on interest rates in the economy. That’s because the amount of savings desired – which is another name for the demand for savings – has an effect on the interest rate. If more savings are desired, real interest rates will be pressured down, and vice versa. The goods market and interest rates Seeing the goods market equilibrium depicted graphically is very useful to see how it affects interest rates. Again, this equilibrium describes a situation where AD = AS and desired savings is equal to national investment. See Figure 1 below for a depiction. Figure 1: equilibrium in the goods market In Figure 1, QE shows the equilibrium point where the real interest rate balances out the quantity of savings and investments desired. Sd represents desired savings at every real interest rate, while Id represents desired investment at each real interest rate. As the interest rate rises, the quantity of savings desired increases while the quantity of investment desired decreases. Recall that the interest rate represents the cost of borrowing, and functions similarly to a “price” for taking on debt – in other words, the interest rate can be thought of as the cost of investing (naturally, this is a simplification and does not cover every usage or nuance of the relationship between the interest rate and the amount of economic investment. That’s fine for our learning purposes). It also represents the return to savings. When the interest rate rises above the equilibrium level, the cost of borrowing is increased, and so the demand decreases for borrowing in the market for loanable funds. Meanwhile, the return on saved money increases, which leads to an increase in the amount of desired savings. In this case, the market is in disequilibrium because there is an excess supply of savings ready to be lent out, and a lack of demand for borrowing those savings to fuel investment. Then, the interest rate will be pressured downward by market forces, as savers accept lower interest rates in order to actually secure a savings account, since banks facing excess demand for savings could lower interest rates and still find customers. Further, banks would be incentivized to lower the cost of borrowing to find borrowers and make loans, and would agree to lower interest rates to do so. These forces will pressure the interest rate down, until it eventually returns to equilibrium. In summary There are many moving pieces in this summary of the goods market. So, to recap: the goods market equilibrium describes the point where the demand for goods and services is equal to the supply of goods, in other words where AD = AS, which is influenced by the interest rate. This is also the point where desired national savings and desired national investment are equal, and where the loanable funds market is in equilibrium. Thus, in this state market forces have perfectly balanced the amount that economic agents want to buy, save, or invest. If the interest rate is too high, individuals will be incentivized to save more and therefore purchase less (AD is pressured downwards and there is an excess supply of loanable funds), while firms will be incentivized to borrow and invest less, and vice versa. This changes the equilibrium until market forces bring the interest rate at a point where it is in equilibrium again. Good to Know Because the goods market equilibrium is defined where AD = AS, it will change when shocks to aggregate demand or aggregate supply change the equilibrium in those markets. This can include things like a change in consumer preferences, sudden changes in wealth, changes in the velocity of circulation, government policy changes, natural disasters, etc.
The “goods market” is a vague-sounding (and rather poorly named) term in economics that is nevertheless an important macroeconomic concept. Goods market equilibrium refers to the idea that, in an economy, there is equilibrium between how many goods consumers want to buy and how many goods producers want to supply.
From Gambling to Economic Growth: how a Greek goddess inspired a new model for Italy’s local development
In the author’s own words, “Strange, perhaps, for a book that intends to deal with economic issues to bring Greek mythology into question.” He continues: “Certainly, it was not my intention to disturb the Gods of Olympus except that, absentmindedly reopening a booklet on Greek mythology, I once again came across the myth of Athena after about thirty years…The rereading of this myth and this very original Goddess made me reflect on the qualities and characteristics that every healthy society should possess to guarantee balanced and constant progress over time.” According to Giliberto, for some years now there has been debate in Italy about the need to undertake new models of territorial development. To that end, the book hypothesizes a desirable “cultural conversion”. By encouraging local citizens to invest even small sums of their money into local development rather than gambling with it, economic growth could be stimulated. Further, citizens would become more aware of the businesses and economic details of their region, increasing civic involvement. The Athena Model: regional development via local stock exchanges Giliberto notes that research has shown that at a certain point, increasing wealth no longer increases happiness. But that doesn’t mean that development isn’t a worthy goal, particularly in areas where the local economy has declined. And, Giliberto asserts that this model of development could serve two purposes: not only economic development, but also fostering cultural growth by better serving under-developed areas. He writes: “On the one hand, new theoretical approaches to well-being tend to demonstrate that it is necessary to review traditional models of development. In the case of my book, the intention is to reverse a cultural trend...Often, parts of the local population are abandoned to intellectual isolation, which also leads to forms of addiction [such as] gambling, alcohol and drugs...Perhaps the time has come to involve citizens in participating in the development and progress of local communities…not only from an economic point of view.” To facilitate such a transformation, the author proposes creating “a circuit of small local investment exchanges governed as ‘game firm’ systems…managed online”. This would involve the creation of small stock exchanges that local residents could invest in. But these wouldn’t be typical stock exchanges, nor would they be tied into existing larger-scale exchanges. Instead, these exchanges would be set up by regional government bodies and open to participation by local companies and residents. Local firms would release details of specific investment projects they’d like to undertake, rather than simply releasing ownership shares of their company. Local investors would then be choosing not only a company, but also betting on whichever investment projects seemed most promising. Image credit: DC Studio on Freepik. The author envisions providing key details about businesses’ operations, including classic financial report cards, to help local citizens place their “bets” into specific investment project details. The author also mentions creating simple information sheets with details about the businesses, their products created, the amount of workers they employ and their average turnover, and details on the planned investments that the companies would actually use the money for. “This information should be able to guide citizens in their virtuous bets…In fact, every local company that intends to make its own investment puts it up for auction for a share it deems appropriate, and on the basis of the information prepared on it by a local online rating, every citizen can decide to invest their money...The repayment plans would be on a quarterly, half-yearly or annual basis, depending on the size of the investment…[this] could generate a widespread system of territorial investments and an increase in business support infrastructure. Part of the shares invested in incentives will, in fact, flow into a dedicated fund for territorial infrastructure.” There’s some consumer behavior logic in this proposal; investing in stocks is quite similar to gambling in some respects. The investor puts in money to back a certain individual or event that they expect will perform well, accepting some risk. However, in this case, both the “gambler” and the business being “gambled” upon stand to directly benefit. That is, rather than a winner-take-all approach as with traditional gambling, investing in local firms instead can generate income that benefits both parties. Perhaps, then, there’s ample room to turn a penchant for traditional gambling into a healthier form, putting money towards productive uses. Giliberto dubs this the “Athena Model”, inspired by his reconnection with the goddess of wisdom’s philosophies. The author suggests that taxes would likely be needed to help set up and run the infrastructure, which don’t have to be large but nevertheless may impose some deadweight loss. Giliberto suggests, however, that citizens who partake in the system could even be incentivized through tax credits – which may help get around that particular issue: “Local administrations would also take care of increasing this local financial circuit by dedicating small percentages of local taxes to the financing of functional infrastructure works, which in turn may serve local businesses. This also guarantees small amounts of return from investments made through tax microcredits to citizens.” If such a system were to succeed in helping regions develop economically, the initial tax burden could even pay for itself in the medium-to-long run. As the region develops, and businesses thrive, more income would be generated – leading to higher future tax revenues for the local and national government. Challenges to success Of course, there are a number of challenges that could hinder such a system from paying off. Incentives and the information provided to local residents must be carefully chosen such that productivity is incentivized and rewarded, while “cooking the books” is heavily discouraged. Businesses must be held accountable; investment projects they receive funding for must be attempted, for example. Giliberto’s model also presumes that there is enough income (and businesses with ambition) in a given region to support this type of system in the first place. And, local residents must be willing to invest more time into this “quasi-gambling” than they normally would. After all, many gamblers simply rely on the knowledge they’ve gained through personal experience to place their bets. In a theoretical online stock exchange system, these same residents likely would at least need to learn about the other investment options before betting on their favorite local winery. And, if the primary draw of gambling for individuals is entertainment, not the chance to make money, the local exchanges may fail to draw enough interest in the first place – the harsh reality is that betting on a game of football is probably more entertaining to gamblers than betting on a cafe’s future success. However, even ignoring the possible side effect of shifting gambling tendencies from “wasteful” private operations into productive public investments, this Athena Model has potential. Overall, the effect of the citizen's investment behavior would support local businesses, hopefully increasing economic development and eventually creating new job opportunities and generating an increase in income and consumer spending. Giliberto concludes: “Is all this utopia?...the word utopia…literally means "no-place", a place that does not exist...it is necessary for our country to draw lessons from the past, establishing, as other European countries have done, mission task forces to ensure that the [Recovery] funds are used promptly and fully.” Such a model, well-constructed, could very well prove to be up to the task. What do you think? Feel free to discourse with us in the comments! References 1: https://www.statista.com/topics/4032/gambling-industry-in-italy/
Is it possible to reinvigorate under-developed regions by turning the public’s penchant for gambling into a force for economic growth? That is one of the questions asked by labor policy economist Luigino Giliberto in his debut book, Athena’s Reasons (currently offered in Italian). The book details a model of regional economic growth that aims to reinvigorate Italy’s less developed areas, inspired by the ancient Greek goddess Athena.
Mesoeconomics: Missing Link, or Needless Pedantry?
Microeconomics is generally concerned with the optimal decision-making of individual economic actors, while macroeconomics considers the behavior of economies and economic data from a bird’s-eye view. But what if these two labels aren’t sufficient to encompass all of economics? Are economists missing something by failing to think outside of these “big or small” labels? That’s the question asked and answered by the term “mesoeconomics”, which purports to be the crucially important in-between that the field of economics has been missing. This term has been around for some time (it was first coined in 1986 by economist Yew-Kwang Ng) but has yet to become very popular among mainstream economists. That may be because there hasn’t been enough attention on the term to produce a significant body of research for it yet. Or, it could be because it’s a distinction that is simply not necessary to have within the field of economics. This article will dive into both sides of the argument, helping you make your own informed opinion. Will mesoeconomics become the next exciting new sub-field, like game theory, behavioral economics, and others before them – or is it overly pedantic? Before discussing the potential pros and cons of popularizing this new label, let’s first define it. Defining mesoeconomics Mesoeconomics is often defined as “the intermediary between micro- and macro-economics”, but this definition is quite lacking, as it does not explain what, exactly, is in between. Where “micro” is concerned with an individual economic agent’s decision-making, and “macro” is concerned with larger-scale economic behavior, mesoeconomics studies how society’s institutions – made up of individuals – interact based on the incentives that they face. As such, two existing sub-fields of economics can already be considered mesoeconomic; regional economics (often considered macroeconomics) and industrial organization (often considered microeconomics). To learn more about mesoeconomics, let’s take a deeper look at some arguments for re-labeling these topics. Supporters of the mesoeconomics label would argue that the focus of regional economics is not the same as true macroeconomics. That’s partly because regional economics studies the regional policies and systems that shape a region’s economic performance. Meanwhile, macroeconomic studies typically study economic performance at large, and may not always consider the variations in regional policies making up the overall economic performance. “Mesoeconomists” would argue that regional economics tackles an “in-between” area, where systems are larger-scope than with individual decision-making (micro) but still more detailed than with studying larger economic phenomena which may not need to take into account the nuance of specific individual policies (macro). Industrial organization extends the “theory of the firm”, studying how firms interact and form markets. This is generally considered a microeconomics endeavor, because the basic unit of analysis is the individual firm. Mesoeconomists, however, would claim that industrial organization stretches into the study of an ecosystem of firms that create industries and form markets, and can treat markets or industries as their own entity within the context of such study. This takes it a level above microeconomics – but not quite at the massive, national or global economy-wide scale of macroeconomics. Besides these examples, one of the major focuses of mesoeconomics is economic policy. There are myriad policies – and nuances to how they’re implemented – that can cause large shifts in expected behavior in industries and markets. Therefore, understanding how industries operate and how they’re intertwined is crucial to designing effective policies! Mesoeconomics aims to draw attention to this (arguably) neglected area, raising the bar for economics as a whole. If this sounds like an excellent idea to you, you’re in good company. It’s time to discuss the pros of popularizing the mesoeconomics label. Pros of mesoeconomics Were mesoeconomics to become more “mainstream”, such that economics students began to take “Mesoeconomics 101” alongside their micro and macro courses, discourse about economics would undoubtedly shift. Arguably, this would be for the better. First, more explicit attention to the practical side of how economists’ recommendations actually play out in the real world is certainly a good thing. This increased attention to translatability could earn economists some credit in the post-financial crisis and post-COVID world, where the failures of professional macroeconomists to predict economic ails have been noted by the public. At best, this mesoeconomic focus could help economists study and identify future man-made crises in the first place (like the 2008 financial crisis, which precious few saw coming). And, it could drive more economics research towards practical applications of policy, perhaps leading to even better policy recommendations that get taken more seriously by politicians. Finally, if “meso” was seen as a third sibling to micro- and macroeconomics, universities and researchers would experience a rapid increase in attention being given to these practical concerns. This could serve to further legitimize the field of economics in the eyes of the public. And, it would likely lead economists further away from the “white room” theorizing problem that has been a consistent critique of the discipline. In writing, “white room syndrome” refers to a scene that lacks enough description to help readers picture the “reality” – an example is a string of dialogue without any references to the surroundings. Similarly, economic ideas are often criticized for resting on unrealistic assumptions that lack real-world grounding, many times even by the economist who came up with the idea! For instance, Alfred Marshall formalized many classic microeconomics concepts, but he recognized their limitations and encouraged his students to surpass his work. Maybe introducing mesoeconomics would make Marshall proud of his intellectual descendants – or maybe, he would simply argue that it doesn’t represent a new innovation so much as needless jargon. Cons of mesoeconomics One of the greatest arguments to make against the need for mesoeconomics is that it doesn’t actually do anything new. Attempting to further sub-divide the field of economics into more labels arguably does not produce new ideas, and may be overly pedantic. Further, this third label may simply confuse laypeople, policymakers, and new economics students without generating meaningfully new discussions. Even though mesoeconomics purports to study industries and the economy from a middle-level view, one might argue that economists already do this routinely throughout their work. For instance, policy recommendations are very often made after studying the local, regional, or national situation. And, middle-level institutions (like state governments) are perfectly capable of hiring economists to help them. Whether we call it mesoeconomics or not, the work is already being done. Further, even from a theoretical standpoint, one could argue that an increased focus on the “middle” between micro- and macroeconomics is both poorly defined and not necessary. At what point does something cease to be a microeconomics analysis, but not yet become a macroeconomics one? Micro- and macro-analyses aren’t neatly defined by the geographical area studied; rather, they use quite different mathematical and statistical tools to analyze data and answer specific questions. For example, microeconomic techniques can easily be used to study the behavior of international trade, if each country is viewed as an individual economic agent that must optimize its trade balance. Similarly, macroeconomic techniques can be applied to small areas to test macroeconomic theories. The geographical scale doesn’t define the discipline; the theories and analyses utilized do. So, to carve a well-defined space for itself, mesoeconomics must have a well-defined set of theories and techniques that are unique enough to be recognizably different. Finally, the label “mesoeconomics” was coined in 1986, nearly forty years ago at the time of this writing. But the term is still very niche – many economics students never hear the word during their entire Master’s or PhD programs, the news rarely if ever mentions it, and research papers seldom use the term. A quick search of the term “mesoeconomics” on RePEc’s EconPapers database returns only 241 results total, and only 10 that have been updated or published within the last year. This heavily suggests that economists have not needed to adopt the term, simply because it isn’t very useful. What do you think? Will mesoeconomics take off and become its own respected area of economics, or remain doomed to niche arguments in small corners of the field? Feel free to share your take in the comments below.
Everyone’s heard of micro- and macroeconomics. The two terms are so deeply ingrained in the world of economics that even lay people generally know what they refer to. Almost everything economists analyze can be arguably given one of these labels.
Economist Earnings by Job Title and Degree in 2023
We begin by examining the average earnings of economists by various job titles around the world. Figure 1: global average salaries by job title (global data, PPP-adjusted) Average salaries for economists follow a clear trend globally. Unsurprisingly, there is an increase in earnings as academic economists are promoted from Lecturer/Assistant Professor level to Associate Professor and finally full Professor status. Similarly, industry economists continue to earn more as they rise from Junior Level Positions to Middle Level Positions and finally Senior/Executive Level Positions. Consultant and Researcher/Analyst roles out-earn Middle Level Positions, and earn less than Senior/Executive positions. Note that these numbers are slightly different than what can be found in the INOMICS Salary Report’s Figure 12 (for example). This is because Figure 1 is a simple average rather than a cross-segment average, which the Salary Report utilizes. One surprising result from Figure 1 is that academic economists out-earn industry economists by a substantial margin. Regionally, however, this pattern does not always hold true; in the INOMICS Salary Report we find that academic economists typically earn less than industry economists until they are promoted to a full Professor of Economics, at which point they tend to earn as much as the highest-paid industry earners. This phenomenon can be seen in the Salary Report’s “Regional Analyses of Academic and Industry Economist Salaries by Job Title” subsection. Here, in Figure 1, the reason academic economists out-earn their industry counterparts is due to the geographic distribution of survey respondents in worldwide data; 45% of the survey respondents in academic roles are from the high-paying “Global West” region while only 30% of industry respondents are from this same region, skewing the results downward for industry roles compared to academic (the “Global West” region is defined below). Nevertheless, this global data paints an excellent first ballpark picture of what economists can expect from their earnings. One important consideration that aspiring economists will have to make is whether or not they ought to study for an economics PhD, as a pay increase is expected upon earning this highest level of degree. Let’s examine how Figure 1 changes when we consider economists who hold a PhD versus those with a Master’s degree. Figure 2: Global average salaries by job title and highest degree held (global data, PPP-adjusted) Figure 2 begins to paint a more nuanced picture of economist earnings by job title. In almost every case, holding a PhD has increased earnings by job title substantially. This is especially true for industry economist jobs globally, particularly for Middle Level and Senior/Executive positions. In both of these cases, earnings more than double for economists with a PhD compared to a Master’s. One interesting exception is for the full Professor category, where Master’s-degree-holding Professors out-earn PhD Professors. This does not appear to be a mistake. First, the sample size for Professors of Economics with a Master’s degree is dwarfed by the sample size of PhD Professors (only 5 Professors of Economics hold a Master’s degree compared to 103 PhD holders). This speaks to the fact that in order to pursue a full professorship, economists should expect to earn a PhD as a minimum job requirement in most cases. Further, the few Professors holding a Master’s degree and not a PhD have decades of experience in economics, which suggests that they are probably former industry economists who left industry after decades of work to become professors. These economists were likely earning high salaries in industry, and so command high salaries as Professors due to their bringing a high degree of industry expertise to their new roles as well. While this is not necessarily a typical career path, it’s interesting to note that this route into academia may exist for former industry economists, without a massive drop in salary. This raises another interesting point: economists with a PhD are probably older on average than those with a Master’s degree. Therefore, we examine years of experience to try and determine if holding a higher degree is truly a meaningful contributing factor to the increased salaries in Figure 2, or if years of work experience is more important for the salary increase. Job Title Avg. Years of Experience (PhD) Avg. Years of Experience (Master) Differential Professor 25.9 19.8 6.1 Associate Professor 17.6 9.3 8.3 Lecturer / Assistant Professor 9.5 8.1 1.4 Consultant 19.4 12.5 6.9 Researcher / Analyst 11.1 8.2 2.9 Senior / Executive Level Position 20.1 13.4 6.6 Middle Level Position 15.7 9.8 5.9 Lower Level Position 5.0 4.1 0.9 Figure 3: Work Experience differential in favor of PhD Economists by job title Figure 3 lists the number of years of work experience on average for each job title category between PhD holders and Master’s degree holders. Column 3 additionally calculates the differential in favor of PhD economists as a simple subtraction. Figure 3 shows that PhD holders do have more years of work experience on average in every category. However, the average differential is under 7 years of experience, which – while significant – is probably not enough to explain the large salary increases in Figure 2 on its own. Some of the large salary increases are likely due to the relatively higher experience level of PhD holders, but it also seems that earning a PhD greatly increases each type of economists’ earnings independently from experience. The takeaways, then, are clear: for economists who wish to work in any role, earning a PhD is clearly worth the investment. Industry economists seem to benefit more on average from earning a PhD than academic economists, even though the latter type of economist often must earn a PhD to attain full Professor status. But before deciding if doing a PhD is right for them, readers may be curious about how this data breaks down regionally. In the remainder of this article, we consider regions with similar levels of pay alongside each other; these are the “Global West” and the “Global South”. The former consists of North America, Western Europe & Scandinavia, and East Asia & Australasia. The latter consists of the Caribbean, South & Central America, Africa, South Asia, Central, Southern & Eastern Europe, and the Middle East, Central Asia & North Africa regions. Using two overarching regions for the following analyses is useful to grant us a high sample size when breaking job titles down further by category, but in the INOMICS Salary Report we consider each individual region on its own. See the Salary Report 2023 section “Regional Analyses of Academic and Industry Economist Salaries by Job Title” for more information on each specific region’s breakdown. Breakdown for the Global West Figure 4 repeats Figure 2 but considers only economist jobs in the relatively higher-earning “Global West” region. Figure 4: Global West average salaries by job title and highest degree held (PPP-adjusted) Average salaries in the Global West (Figure 4) closely follow the same pattern as worldwide average salaries (Figure 2), with a few notable differences. First, among respondents from these generally richer countries there were zero survey respondents who held a PhD and were working in a “Junior Level Position”, which is sensible. Second, the massive salary increases for certain categories – particularly Middle Level and Senior/Executive Level Positions – are somewhat less than the worldwide average, though these two categories still feature very substantial salary increases. Finally, the Professor category features a similar quirk where Master’s-degree-holding Professors out-earn PhD Professors. But again, this is likely due to industry economists who choose to become Professors later in their careers, as the sample size is quite small and the years of experience quite high (in this region, Professors with PhDs have on average about 25 years of experience compared with 38 years for Professors with Master’s degrees). Furthermore, industry economists in these world regions tend to out-earn academic economists, so an industry economist becoming a professor would likely demand a correspondingly high salary. Figure 5: Global South average salaries by job title and highest degree held (PPP-adjusted) The worldwide trends identified in Figure 2 remain largely true in the “Global South” countries (Figure 5) as well. In these lower-paying world regions, Master’s degree holders earn much more comparable salaries to PhD holders in most industry roles; however, in this region Consultant and Researcher/Analyst salaries increase dramatically for PhD holders. Meanwhile, Professor salaries are quite high for Master’s degree holders. In addition to the aforementioned reasons, in the Global South region it may not always be as strictly necessary for Professors of Economics to hold a PhD (although it is surely still a boon to one’s competitiveness). Which job titles value a PhD the most? Overall, then, this article has painted a clear picture: earning a PhD, regardless of job title, improves one’s earning potential significantly in most regions. This is especially true in industry roles, where employers offer a pay premium to compete for sought-after economics PhDs. Academic economists in many regions must earn a PhD in order to be competitive for the full Professor role, though a small portion become Professors after many years in industry. Excluding the anomalous Professor category, where the rare Master’s degree holders earn very highly, most economist jobs yield higher pay for economists with PhDs compared to those with Master’s degrees. Judging by Figure 2, it appears that Senior/Executive, Middle Level and Consultant roles feature the largest pay increases for PhD holders. Figure 6 below examines the pay differences from Figure 2 in more detail: Figure 6: Percentage increase in pay from earning a PhD by job title (worldwide) Figure 6 shows clearly that economists working in a Middle Level Position stand to benefit the most from earning a PhD compared to their colleagues with a master’s degree, followed by Senior / Executive Level Position economists. Although in Figure 2 Consultants appeared to face relatively high earnings increases, percentage-wise it represents a fairly typical increase among industry roles. Academic roles feature relatively low earnings increases from earning a PhD, but in order to advance, academic economists are expected to earn PhDs. Again, Professors actually earn less on average if they hold a PhD. But, this is due to the small amount of very high-earning Master’s degree economists who were likely given a professorship after decades of industry experience (as they have higher average years of experience than PhD Professors as well). Overall – and particularly in industry, where earning a PhD is more of a choice – economists stand to gain a significant amount by furthering their education. Earning 60% or more than their peers without an equivalent degree is a substantial benefit. In the higher-paying world regions, salary increases from earning a PhD are smaller percentage-wise but higher in absolute terms due to high base salaries. Meanwhile in lower-paying world regions, Master’s degree holders earn more comparable salaries to PhD holders in most industry roles (excepting Consultant and Researcher / Analyst roles), though earning a PhD still increases earnings. The results, then, are clear: in terms of potential salary, earning a PhD is a significant benefit for almost every economist regardless of job title. Of course, pay alone is not the only consideration to make when deciding to earn another degree, and some economists can find meaningful employment with a Master’s degree. But the benefits of a PhD show that aspiring economists should strongly consider planning to complete a PhD in economics at some point during their career, or have strong reasons for not doing so. Otherwise, significant earnings are being left on the table. For an aspiring economist, the choice of job title and level of education is likely influenced by myriad other factors beyond salary expectations – personal life goals and choices matter, too. And of course, the job titles examined here are overarching categories and not individually specific. However, this data-driven insight can certainly help inform those choices. For more detail about economist earnings by job title and region, see the INOMICS Salary Report, which is available freely for download. Header image credit: Freepik.com / Magnific (free license)
Aspiring economists may be curious to know: how much do economists earn in different types of jobs? The INOMICS Salary Report contains a wealth of data about economist pay by job title and region (among many other factors). This article takes Salary Report data on salaries by job title and analyzes it from a new angle, including highest degree earned, which will help younger economists to plan their career path.
This quote from the famous economist Keynes raises a number of areas that help us begin to answer the question of how to succeed as an economist. Reading the quote, an economics student may ask: in the modern age, what are the necessary skills one must possess in order to become a “successful” economist? The answer is, of course, hugely subjective. It may also fluctuate as one’s own career goals change. Here, we will identify some of the age-old must-haves – as well as some of the new skills economists ought to acquire in the age of climate change, globalization, and AI. Before we begin: the need for economists The present age is a remarkable time, probably among the most exciting and challenging times ever to enter the field. Many economic models and presumptions of the past are continually showing themselves to be outdated and in need of theoretical improvements. This has much to do with the new challenges facing our generation. Whether it’s in confronting climate deterioration, demographic change, the rise of AI and automation, wealth inequality, or even incorporating basic realism into textbooks, there is room for increasingly advanced economic models that can more accurately account for the complexities of real life. Beyond the need for improved economic models, though, is a societal and political need. In handling many of these emerging challenges – some of which were wrought by an inability to regulate our own activities – the ailing neoliberal orthodoxy has found itself ill equipped. To borrow the words of economist Howard Reed: “until we ditch the old textbook, we’ll never face up to the challenges of the modern world”. So far, there has been little sign of this happening any time soon; as Prospect editor-in-chief Tom Clark has observed of most Western governments, “out-dated frameworks still inform policy prescriptions”. In fact, searching for alternative solutions may partly explain why there’s been a resurgence of nationalist and even fascist sentiment across democracies in recent times – but those systems have been tried before, and surely do not hold the answers society needs. The responsibility, then, lies with the next generation of economists to combat this deficit of ideas. Optimistic, open-minded, and determined to make the world more livable for all, it is they that must provide the insight, innovation, and policy stewardship needed to guide our future path. Think you have what it takes to answer the call? Read on. What’s needed: the (quantitative) basics It should be no surprise at this point that a familiarity with mathematics and statistics is vital to any aspiring economist. Competence in these areas will allow one to analyze data using econometric techniques such as regression analysis, a necessary skill for nearly any career in economics. Beyond the bread-and-butter quantitative skills, familiarity with data science will help economists navigate popular economic software such as Matlab, R, Python, and STATA. Variants of these software programs will, through necessity, become your future friends; it’s probably best to make their acquaintance as soon as possible. In fact, the entire discipline of data science increasingly intersects with economics. This will only become more true over time as AI tools continue to percolate through the economy. As such, a familiarity with computer science, data science, and programming can only help you. Some recent economics graduates may not yet be comfortable with handling large numerical datasets, using statistical software programs, or building bulletproof economic models to interpret data. It’s easy to take coursework only in one’s specialty or interests during an economics Master’s degree, for example, and to have forgotten the more numerically-focused introductory courses. If you find yourself in this situation, fear not. Consider signing up for professional skills trainings and/or summer schools to fill in the gaps in your skillset, which will not only improve your career prospects, but help you to become an even more capable and well-rounded economist. It’s never a bad idea to explore options like these to keep you on top of your game. Regardless, in order to analyze economic data, learn, and deliver powerful insights that can change the world, competence with the quantitative elements of the field is key. Interdisciplinary knowledge Beyond mathematical and data proficiency, economists ought to be curious, independent thinkers able to reason soundly, and possess the humility to admit when the data has proven one’s own theory wrong. These are excellent qualities to have for an economist, allowing them to glean new truths with minimal bias. Great strides in economics have come from dispassionately examining why things are the way they are and using the resulting models to help prescribe how they can be made better. Economists also tend to benefit greatly from “thinking outside the box”, sometimes going beyond the strict parameters of economics for tools and answers. This is where familiarity with other social sciences becomes key. Learning about other disciplines, particularly those that relate to economics in some way, can help an economist to make breakthroughs. Clearly then, modern economists (and economic theory itself) can benefit from taking up an interdisciplinary approach to research. Dr. Olivier Blanchard, our 2024 Handbook interviewee, named this kind of creativity as an important quality that young economists must demonstrate in order to excel. Communication Skills Another crucial skill is communication, in a clear and concise form, both verbal and written. The complexities of economics can easily be lost on important stakeholders like clients, politicians, constituents, and community members who – we should remind ourselves – don’t have advanced degrees in economics. This is important; the fact that economic processes underpin so much of governmental policy means it’s imperative that decision makers and ultimately the public are up to speed on economic issues, prospective policies and the like. But not everyone can study for a degree in economics. Thus, a great economist will be able to convey complicated, data-backed economic theories through understandable, accessible language. This is quite the skill, and its absence from public discourse can be potentially very damaging. Few would argue, for instance, that the entire British electorate had all of the relevant facts at hand when deliberating withdrawal from the European Union. Further, politicians and the news media around the world often routinely misunderstand the nuances of economics. As Lord Thomas Macauley once stated, as an example of this: “Free trade, one of the greatest blessings which a government can confer on a people, is in almost every country unpopular”. The benefits of comparative advantage have been well documented, yet many modern voters around the world rally to the call of protectionist policies, not realizing that those policies will ultimately increase the costs of the goods they buy every day. This is one example to demonstrate the importance of clear economic communication. But of course, it isn’t just public-facing economists who should master communication skills. Business clients and other stakeholders alike should be presented economic facts and recommendations in understandable terms so that they can make properly informed decisions, too. Know this: history fuels continuous improvement in economics One of the many reasons economists were lambasted for their failure to predict the economic crash of 2008 was that it exposed some unrealistic assumptions that economists had grown accustomed to leaning on. This includes analyzing the decision-making of individuals as if everyone was perfectly rational at all times. Pre-2008 economic orthodoxy often assumed that people followed a very rational thought process when faced with a decision. First, list all possible outcomes of all possible options, attach a value to each, and assess potential risk. Next, perform a comprehensive analysis based on the expected returns of each option, and choose the optimal decision. Is this process rational? Certainly. Realistic? Well… Evidently, such purely rational thinking was absent in the lead up to 2008, where banks famously began to package subprime loans and sell them as financial securities that were overvalued. The systematic understatement of risk, fueled by moral hazard, represented a bet that cost the world dearly. Partly in response to such tragedies, economics since its inception has accepted criticisms of its models and failures, and used them to create more robust and realistic models of the economy. One major example of this is the advent of behavioral economics, which increasingly asks how real people behave towards decision-making and risks in ways that aren’t necessarily optimal. It incorporates psychological, cultural, social, and emotional factors into its theories, and is a prime example of how economics can benefit from other social sciences. Calling all future economists In summary, and though there is no strict formula, great economists typically have the statistics and math skills to work with data and derive meaningful insights. They often have a specialization in one or two areas, but benefit greatly from an understanding of others. They are able to emerge from the depths of analysis and communicate the high-level meaning to other important stakeholders who don’t have the same training. And, the absolute best of them possess a drive and motivation to do the right thing, to advance theory, and to make the world a better place. Now more than ever, economists are uniquely suited to help the world understand and navigate the potentially tumultuous future being presented by challenges like climate change and the explosive growth of AI tools. Perhaps you can take up the call and become an economist who will guide us all towards prosperity. The above article includes small sections that were originally written by William Pearse. Header image credit: Freepik.com / Magnific (Free license)
The following article first appeared in the INOMICS Handbook 2024. Download the INOMICS Handbook “The master-economist must possess a rare combination of gifts. He must reach a high standard in several different directions and must combine talents not often found together. He must be mathematician, historian, statesman, philosopher…He must study the present in the light of the past for the purposes of the future. No part of man's nature or his institutions must lie entirely outside his regard. He must be purposeful and disinterested in a simultaneous mood; as aloof and incorruptible as an artist, yet sometimes as near the earth as a politician.” – John Maynard Keynes
The INOMICS Questionnaire: Fratzscher vs Blanchard
Olivier Blanchard is the C. Fred Bergsten Senior Fellow at the Peterson Institute for International Economics and the Robert M. Solow Professor of Economics emeritus at the Massachusetts Institute of Technology (MIT). After obtaining his PhD in economics from MIT in 1977, he taught at Harvard University before returning to MIT in 1982. He was chair of the economics department from 1998 to 2003. In 2008, he took a leave of absence to serve as economic counselor and director of the research department at the International Monetary Fund, where he stayed until 2015. He then joined the Peterson Institute. Blanchard has worked on a wide set of macroeconomic issues, including the role of monetary and fiscal policy, speculative bubbles, the labor market and determinants of unemployment, economic transition in former communist countries, the nature of the Global Financial Crisis, and the recent burst of inflation. He is the author of many books and articles, including two textbooks on macroeconomics (one at the graduate level with Stanley Fischer and the other at the undergraduate level). He is a past editor of the Quarterly Journal of Economics and the NBER Macroeconomics Annual; he is also a founding editor of the American Economic Journal: Macroeconomics. He is a fellow and former Council member of the Econometric Society, a past president of the American Economic Association, and a member of the American Academy of Arts and Sciences. Marcel Fratscher: What is your favorite place on earth? Olivier Blanchard: The French island where I have spent most of my summers, and, with time, a longer and longer period of time each year. Zen, sea, and fortunately and unfortunately, zoom. MF: Outside of economics, what occupation would you choose if you could be absolutely anything? OB: Concert pianist (although there is zero evidence that I have the slightest gift in that particular direction). But music moves me more than nearly anything else. MF: What is your favorite piece of music? OB: Gymnopediés by Eric Satie. MF: What is the virtue you appreciate the most? OB: Straightforwardness, honesty. MF: Your all-time favourite figure in economics? OB: I shall choose close to home: my advisor, Bob Solow. I admire him for the importance and the beauty of his work, but also his human qualities. I admire, but am not sure I would have loved him, Keynes. MF: Your #1 economics blog? OB: I do not read economic blogs. Nothing personal. (I am more a short Twitter person). On general blogs, Ezra Klein. MF: Your ideal student? OB: Somebody from whom I learn. I have written papers with many of my students, learned a lot and always enormously enjoyed it. MF: What should be done to address a gender bias in research in economics? OB: I am proud of what we have done at the American Economic Association. I think the right institutions and rules are in place. (Some) male behavior unfortunately will take more time to adjust.* *Editor’s note: Aside from making policy changes to improve the environment for women in economics, the AEA launched the Committee on the Status of Women in the Economics Profession. An update on the Committee and the AEA’s work can be found in the 2023 CSWEP News Issue IV on the AEA’s website. MF: What is the most misguided research agenda in economics? OB: Let me avoid labeling it misguided, but Real Business Cycle theory and methodology is the quintessential example of a disrupting technology. 50 years after its inception, I am still not sure whether the benefits are offsetting the costs. It is definitely becoming more useful by incorporating more distortions and more heterogeneity, but it suffers from nearly genetic problems, such as the black box aspect. This is actually made worse by the increased complexity of modern DSGE versions. MF: What is the most promising current research field or issue in economics? OB: Quite clearly, all the fields that benefit from the increasing availability of large data sets. But, in general, looking for examples at the NBER working paper list each week or so, I am amazed at the richness and the scope of current research. They include forays in behavioral issues, use of experiments, forays at the border of sociology and psychology, and work on institutions. MF: Where does economic research have the most influence on policy-making? OB: In a lot of places, antitrust, macro, etc. But, and this is a plaidoyer pro domo, there have to be people with one foot in research, and one foot in the real world, to be able to translate the conclusions of research to specific policy recommendations. MF: On what issues should policy listen more to economists? OB: All the time…but especially when economists derive conclusions at odds with what would seem to be common sense. The paradox of saving, the incidence of taxes, the market for lemons, etc. MF: What is your career advice to a young economics researcher? OB: You need to demonstrate two things. Your analytical abilities, i.e. your ability to cleanly formalize an issue and derive implications. And more importantly, your creativity, i.e. thinking in a new way about an essential issue. The challenge: Balancing the two in your thesis. Start with a question to which you do not know, but would like to know, the answer (and one where you think the answer will be interesting to others too). Preferably not from an extension of another paper. References: The Peterson Institute for International Economics’s bio page for Dr. Olivier Blanchard was referenced when writing the introduction to this article. It can be found at the following address: https://www.piie.com/experts/senior-research-staff/olivier-blanchard Header Image: Composite. Photos kindly provided by Marcel Fratzscher and Olivier Blanchard.
The following article first appeared in the INOMICS Handbook 2024. Download the INOMICS Handbook Professor Marcel Fratzscher, esteemed macroeconomist and president of the DIW Berlin, once again asks questions about economics and life in general to a peer in the 2024 edition of the INOMICS Handbook Questionnaire. This time, he poses the questions to Dr. Olivier Blanchard, a prominent macroeconomist, who graciously took to the spotlight in this latest round. Thus, the back-and-forth has been dubbed Fratzscher vs. Blanchard, as is tradition. Dr. Blanchard offers us some interesting food for thought: the interview touches on the joy of conducting research with former students, the sometimes counterintuitive things we learn from economics, an analysis of Real Business Cycle Theory, and more.
You may be wondering how to make a strong resume for economics jobs that you’re interested in. Resume tips abound online, and many of them are quite good for your economics job application, too. In this article, we share some of the best ones, as well as economics-specific advice to help make your application stand out and ensure your resume gets noticed and read. Keep in mind that this article will focus on resume tips for an industry job application. If you’re more interested in applying for a PhD or academic jobs, check out our PhD application infographic or academic cover letter examples. You may also be interested in professional cover letters, or even highlighting your study abroad experience to your future employers. Now on with the tips! Formatting, formatting, formatting Realistically, the most important part of your resume is the formatting. That’s because the majority of recruiters and hiring managers will take only 6-7 seconds to “read” your resume (according to Indeed)! Applications submitted to job postings number in the hundreds on average (according to Zippia), and can be much higher. This incentivizes recruiters to spend as little time as possible skimming their massive stack of resumes to pick out potential leads. Although AI-assisted algorithms are increasingly being used to pick out the best applications for hiring managers, you need to ensure that your resume is formatted well so that when it is seen by a human, it isn’t tossed out immediately. So what makes for good formatting? Important information in bold (your name, job titles you’ve held, section headings, etc.) Use a clear, professional font, and use the same font throughout the entire document (like Arial, Cambria, or Times New Roman, etc.) Font size no smaller than 11pt Consistent margins, spacing, and font size Very little color; black-and-white should be sufficient Prioritizes readability and logical flow over creative design Clearly labeled, skimmable sections for Education and Professional Experience, and possibly Skills Limit your resume to one page only; if you’re running out of space, consider cutting experiences that are older or less relevant to the job Design and structure In general, a simple structure is better than a complicated one. Your resume should be easy to read and does not need to be creative to succeed in the economics job market; rather, it must be relevant and informative first. A header section towards the top with your name, contact information, and current location is a good start. Job seekers usually put their name in slightly larger text than the rest, so that it stands out and is easy to find among a stack of resumes. Keep in mind, too, that recruiters often read resumes using an “upside down L” shape; they’ll skim the top few lines and the left-hand side of the page, looking for key words and phrases. Only the absolutely most interesting resumes will get more attention than this. So, you should do your best to make sure the important keywords are to the left side of the page. Below are some further tips for the body of your economics resume: Don’t pack your resume to the brim, keep it concise and informative Consider using bullet points instead of paragraphs; avoid large blocks of text! Highlight your achievements as concisely as possible Emphasize experience that matches the job, and use keywords found in the job post Use numbers to quantify your successes if you can (i.e., reduced department overhead by 20%) Present information in reverse chronological order; your most recent experience should go first (unless you have earlier experience that is particularly relevant for the job) Double and triple-check your resume to correct any spelling or grammar errors Plenty of good, professional examples can be found online using a quick search. We recommend finding an example you like and making something that looks similar. Be specific Aside from common themes like communication skills, flexibility, and the ability to stick to deadlines, there will be economics-specific skills that employers mention in the job postings. In your resume, specificity will set you apart, and show that you’re qualified. When describing your experiences, avoid generic phrasing such as “analyzed voting patterns” or “researched fluctuations in international trade”. It’s much better to include specifics, for example “analyzed voting patterns using logit regressions” or “With a gravity model, described fluctuations in international trade”. This gives the employer a much clearer impression of your skills, showing that you have the specific economics knowledge to succeed in the role. Further, even if the employer has no need for those exact skills, being specific like this proves that you’re capable of learning and applying various quantitative (or qualitative) methods to a task. In fact, many economists opt to include a short “Skills” section that lists specific quantitative techniques and software skills. For recent graduates, a “Relevant Coursework” section is also acceptable and fulfills a similar purpose. But be careful – it’s not recommended to highlight prior coursework for too long after you graduate. If you’ve been out of university for more than 2-3 years, consider trimming down or cutting this section entirely and focusing only on your experience. Be concise When drafting your resume, you’ll need to be brief, often painfully so. Aim to describe only the most important points about your experiences (using specific language!). And, share these using the shortest sentences possible. For example, suppose you contributed to a research study that studied the link between capital accumulation and income inequality using historical data. The research aimed to prove that increasing capital accumulation would drive inequality by concentrating income in the hands of the few, who would then continue to accumulate capital – and wealth – at increasing rates. To do this, you used historical datasets from countries formerly occupied by the U.S.S.R. This involved months of work to find, clean, and use historical datasets from several different countries. With your research partners, you decided to use a two-way linear fixed effects regression model, tested for heteroskedasticity, ensured the residuals were approximately normal, justified your usage of certain control variables and proxies, and more. After months, you emerged from your trials, with a hypothesis definitively proved. Success! How should you summarize such a mighty task on your resume? Here’s a good example: Studied capital accumulation’s effect on inequality via two-way fixed effects regression using the methodology found in Bartels et. al. (2024)1. It’s challenging to summarize months of your life’s best work in a single sentence, but on a resume this is necessary. If you find that it’s not hard, chances are you need to make it even shorter! So how do you decide what to emphasize? A great question, answered by the next point… Go back and re-read the job description A job description is a gold mine of information. The description will describe the nature of the work and the skills the employer is looking for. You should add or re-write details to your resume to (truthfully) match as many of these as possible. If you’re applying for an industry position that requires economic research, for example, you should highlight the research experience you have as well as your thesis topic, especially if it is relevant. Or, if the job posting mentions the importance of presenting to company leadership, highlight your presentation experience at previous jobs, or in conferences or other roles. In short, look for specific quantitative or qualitative methods, responsibilities, topic areas, and software programs (like R, Stata, SQL, etc.) that are mentioned in the post. Then, include a bullet point to show your experience with each of these topics. It’s best to include these naturally as bullet points under the experiences where you used those skills, and how you used them (even if you also make a separate “Skills” section on your resume). Finally: Don’t Give Up! Looking for a job can be a difficult and discouraging process. But, don’t give up! With these tips and your economics degree in hand, you’ll be well on your way to a successful application. Remember, it only takes one successful application to land yourself an economics job, and economists are in high demand. Aside from polishing your resume, we also recommend networking to help you find a job. A business is much more likely to consider a candidate seriously if an employee knows them already. And, your network might be able to help you improve your resume, too, if you ask the right people. Just be sure to treat them to coffee or send them a thank-you to show your gratitude. Don’t forget, too, that you can always patch up holes in your economics skill set and strengthen your resume by taking professional training courses, summer school classes, or even deciding if doing a PhD is the right way to go for you. Whatever your choices, we wish you the best of luck and imminent success! References 1: Bartels, C., Kersting, F. and Wolf, N. (2024): "Testing Marx. Capital Accumulation, Income Inequality, and Socialism in Late Nineteenth-Century Germany", Review of Economics and Statistics (forthcoming), CEPR Discussion Paper 17925. Header image credit: Drazen Zigic on Freepik.com / Magnific (free license).
Completing an economics degree course is hard enough. But after you’ve earned your degree, you may very well begin to look for a job in economics, which is a whole new type of challenge!
Publish A Summary of Your Economics Research on INOMICS
We invite economists who are conducting or have conducted research to write a summary of their research and why it’s important, interesting, or unique in the field, and share that article with other economists via INOMICS. This “research summary” article can function as an extended abstract that will help other economists discover your work and learn more about your area of expertise. The tone can be similar to a relatively casual lunchtime conversation with colleagues who are trained in economics but unfamiliar with your work. Please note: We do not publish academic research. However, an article that describes your research and its importance to an audience of early-career economists and economics students is encouraged. Writing a research summary article on INOMICS can help your research reach a broader economist audience, inspire others’ research, broaden your network by reaching others in related areas, and add to your portfolio of written work. Our Goals for Your Submission: You are able to share your research topic and other factors related to it with economists on INOMICS. Economist readers of INOMICS can find interesting articles about recent or upcoming research in economics on the INOMICS Blog, in addition to what’s already been shared on the Blog. You are able to build your portfolio of written work, and develop your reputation among the thousands of readers who use INOMICS. You add to the library of interesting INOMICS content; readers benefit from learning about the interesting topic area. Less experienced readers additionally benefit from learning about your research, evaluation of economics issues, methodology or challenges overcome while researching, etc. Submission guidelines: Articles must be written in English Articles should be at least 1000 word and no more than 2500 words. Use a conversational but intelligent style - short introduction and conclusion, relatively short sentences, informal but intelligent tone (imagine you are speaking to a junior economist colleague or student at lunch hour). Additionally, please send a description of yourself and your academic and/or career credentials, no longer than 300 words, including a photo and a mention of your affiliated institution or your job title. Again, please note: We do not publish academic research. However, an article that describes your research and its importance to an audience of early-career economists and economics students is encouraged. Submission Process: Please send complete article drafts to: mailto:submissions@inomics.com. Articles that match these submission guidelines will be reviewed by a member of the INOMICS editorial board. If your article is of sufficient quality and adds to our content, we will contact you with initial edits, and begin the editing process with a member of our team. This may entail several rounds of edits. The final draft will be reviewed by another member of our editing team, and any last changes will be communicated with the author. Then, the article will be published on INOMICS, and you will be able to share it across your own channels as long as they are linked to the article’s “home” on INOMICS. Finally, contributors whose articles are published will receive a profile page on INOMICS and will have the opportunity to submit further articles for publication on INOMICS in the future. Contact: INOMICS Team submissions@inomics.com +49 30 2084712 50 Terms of Submission: By sending your submission, you guarantee that the submitted research summary article has not been published in part or in full elsewhere (note that this regards the summary written about the research, NOT the research itself). By sending your article submission you agree that INOMICS may publish your research summary article in-part or in-full, or publish an excerpt of your article in a larger content piece (for example a collection of opinions). If your research summary article is published in-full by INOMICS, you agree that in the event that you share or publish the article elsewhere, you will refer/link to INOMICS as the original location of publication for the research summary article (but NOT the research itself). You guarantee that you are the sole author(s) or that you have permission from your co-authors to publish this summary, and you confirm that you need no further permission from other co-authors, employers or funding bodies in order to grant copyright of the article to INOMICS.
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Indeed, Alfred Marshall is considered one of the founding thinkers of neoclassical economics. He was a mathematician and philosopher who later became a microeconomist. His work formalized foundational economic concepts and theories such as supply and demand, price elasticity of demand, consumer and producer surplus, marginal utility, and production costs to produce some of the earliest cohesive economic models. He was even instrumental in making economics its own separate subject for the very first time at Cambridge, where he taught for much of his career. The entire field of economics was greatly influenced by both Marshall and several of his pupils, including famous economists Arthur Pigou and John Maynard Keynes. Alfred Marshall’s life Marshall was born in 1842 in London, England. He was at one time considering a career in the clergy, but abandoned the idea after he demonstrated significant talent for mathematics. Thereafter, Marshall attended St. John’s College in Cambridge, earning accolades in math (such as “Second Wrangler” in the Cambridge Mathematical Tripos) and securing his future as an academic. At first, Marshall wasn’t an economist – few in his time were! Rather, he studied subjects like math, physics, philosophy, and ethics, like many other thinkers of his time. It was allegedly Marshall’s love for ethics that led him to eventually study economic decision-making, as he saw economics as a means of improving the human condition for the common man. This was an ideal he shared with Adam Smith, another (earlier) important British thinker in economics. Thus, Marshall lent his considerable intellect to economic pursuits. In 1865, he was elected to a fellowship at St. John’s College at Cambridge. He married in 1877, left St. John’s, and taught at the University of Bristol and then at Oxford for a period afterward. In 1885, he became the Professor of Political Economy at the University of Cambridge, where he remained until his retirement in 1908. During this time, Marshall turned the study of economics into its own, self-contained discipline, creating the Faculty of Economics and Politics and helping to launch the first formal economics degree program at Cambridge in 1903. Famously, Marshall taught economic giants Arthur C. Pigou and John Maynard Keynes, who each went on to make their own grand contributions to the field, and often had great things to say about Marshall’s influence and teaching. The book Principles of Economics was Alfred Marshall’s magnum opus. He worked on it from 1881 to 1890. It was rapidly recognized as a success and a great achievement in economics upon its publishing. Yet Marshall was unsatisfied with the limiting assumptions of classical economics (some of which he helped to popularize!), so his work shouldn’t be viewed as a definitive snapshot of his economic beliefs. Instead, Marshall was keen to have his students surpass him and replace his models with more accurate ones, such that he was known to gift them copies of his Principles of Economics with signed messages such as ‘To [name], in the hope that in due course [they] will render this treatise obsolete’. Alfred Marshall died in Cambridge in 1924, at the age of 81. Alfred Marshall’s contributions to economics Marshall’s contributions to economics are numerous. As a former mathematician, he formulated many concepts in the field with equations. This approach helped him formally define many of the concepts mentioned at the beginning of this article, which other economists of his time had not been able to do. Nevertheless, he also attempted to distill economic insights into language that was understandable by non-mathematicians, a crucial skill for successful economists even in today’s world. This is evidenced by his placing math equations and graphs only in the footnotes and appendices of his Principles of Economics, not the main text. Besides Principles of Economics, Marshall’s other economics works include the 1879 text The Economics of Industry, which he co-wrote with his wife Mary Paley (a former student of his, and one of the first-ever female economics students. She was denied a degree on the basis of being a woman, a discriminatory policy that her husband Alfred Marshall supported; but nevertheless she was a brilliant economist in her own right). Alfred Marshall was also a crucial figure in popularizing the idea of “thinking on the margin”. Marginal analysis today is a core and foundational concept in economics, where someone’s decision is based on the benefit that the next unit provides, not the sum total of all units. The so-called “Marginal Revolution” began with economists William Jevons, Carl Menger, and Léon Walras in the 1870s. Marshall is one of a “second wave” of economists who, seeing the brilliance of these marginal ideas, set about integrating them into economic models. John Keynes, his former student, said this of his work: “[William] Jevons saw the kettle boil and called out with the delighted voice of a child; Marshall too had seen the kettle boil and sat down silently to build an engine.” According to Keynes, Marshall’s writing also put an end to a debate over whether cost or demand determined the value of items in a market, positing convincingly that it was actually both. As such, Marshall is credited with developing the idea that the price and output supplied of a good are determined by the intersection of supply and demand. This approach is so foundational as to seem obvious to economists today, which speaks to the success of his idea! Marshall also introduced early ideas of the different “time horizons” that economists frequently reference. He pointed out that in the short run, changes in demand tend to have more effects on markets than costs, while in the long run supply-side facts like costs can significantly shape markets. According to Keynes, Marshall was also the first to provide an actual formula for price elasticity of demand – which earlier authors had mentioned, but not formalized. He did the same with consumer and producer surplus as well, which French engineer and later self-taught economist Jules Dupuit had originally described. Marshall’s works were broad, covering even more topics than these. His students Keynes and Pigou, and later economists like Joseph Schumpeter, have several recorded quotes about the thoroughness of Marshall’s Principles that are readily available online. These include the fact that Marshall’s models and formulae hidden in the footnotes of the Principles often provided solutions to problems that were only thought of later on. So, next time you’re studying economics – particularly microeconomics topics – don’t be surprised to hear Alfred Marshall being given the credit! References 1 https://www.econlib.org/library/Enc/bios/Marshall.html 2 https://carleton.ca/keirarmstrong/learning-resources/selected-biographies/marshall-alfred-1842-1924/ 3 https://hope.econ.duke.edu/sites/hope.econ.duke.edu/files/documents/caldwell_2004_ALFRED%20MARSHALL%20and%20the%20CAMBRIDGE%20SCHOOL_0.pdf Header image credit: wikimedia / public domain.
Alfred Marshall is a famous economist who made great contributions to the field when it was still relatively new towards the end of the 19th century. Yet, students often learn about important figures in economics only briefly and in passing, although the content taught in economics courses often comes from brilliant economists such as Marshall.
Recruiting Economists for Your Professional Training Courses
Economics is a large field with many sub-disciplines, and it’s impossible to master the whole lot from just one Master’s degree or even a PhD. A single economist doesn’t have to master the entire field, but taking time to deepen important skills can be very helpful for an economist’s career. So, proactive economists will seek opportunities to further their skills beyond graduation, especially as they encounter situations in the workplace that demand more technical or subject-specific skills. Professional development courses or skills training are one great method for them to do so, and institutions can develop and advertise them with this in mind. Who, what, and where: the basics of skills trainings for economists Professional training courses for economists may be offered by universities or by other organizations, including private companies and even multinational organizations like the IMF. Usually for a modest tuition fee, applicants can take a class that lasts anywhere from a single day to a few weeks. Some of these economics trainings are only offered in person and on-site, but many course providers are increasingly offering online courses so that anyone around the world can join in. These training courses are usually focused around a particular topic, and are designed to give either an introduction to a specific area of economics (for example, macroeconomic forecasting), a useful tool for economists (such as R or Python), or a related field (like data science). Economists looking to develop their skills will often search the Internet to look at online courses offered by their alma mater, another school they know of, or a reputable international organization. Online course platforms like Coursera are also a common place to search, but economists will typically still want to know which university is actually behind the course. And of course, to develop or host such a course, one must have an appropriate expert to help develop and deliver the course. This is one of the main reasons why universities and well-known international organizations tend to be the ones hosting economics trainings – they already have access to experienced economists willing to teach, as well as access to a community of (young) economists who might be interested in taking them. Common topic areas of professional development for economists There are a number of in-demand areas in which economists (particularly fresh Master’s or PhD graduates) seek to further hone their skillset. Below we list major topic areas institutions should consider promoting specifically to economics graduates and professionals: Econometrics and statistics: This is an important area containing many critical skills for economists, and as such these courses tend to be very popular – but that doesn’t necessarily mean they’re the easiest to recruit for, since there’s also lots of competition for these courses. Additional coursework in econometrics or statistics can be massively helpful in a young economist’s career, offering a deeper understanding of the math and methods that power economic analysis. This can include topics on statistics, time series analysis, managing panel data, niche or advanced regression models (like gravity models), etc. Courses on quantitative topics such as these are both difficult to learn and widely applicable across a variety of economics subfields, which lends to their popularity. It’s usually necessary for professional economists to develop their skills in a few useful quantitative methods at some point in their careers. If your institution is attempting to design and launch more professional training courses for economists, consider starting with courses in these areas first. Software tools: R, Stata, Python, SAS, SPSS, Eviews and dozens more: the statistical software tool options for economists are as myriad as they are complex. It’s likely that economists will need to learn at least one of these tools well in order to conduct data analysis. While many institutions offer introductory courses on these tools during economics degrees, professional economists often need a deeper expertise that schools usually cannot provide during the already-demanding economics degree program. So, many economists find themselves lacking advanced proficiency with software tools that they’ll need in the workplace. Courses in this area can help patch up those deficiencies. Data Science topics: Data science is a distinct field from economics or the econometric software that they use. Nevertheless, economists increasingly find many topics in data science interesting and helpful for their research and career. That’s because understanding data science can help economists work more effectively and conscientiously with their large economic datasets. Data science courses can also help prepare economists for the cutting-edge technology and research methods that will impact how economics is researched in the future. For example, economists and data scientists are already using machine learning algorithms to make forecasts, and may increasingly be using large-language models (LLMs) to analyze economic data. Other elements of data science (such as bootstrapping and decision tree models) have already made their way into the field of economics, so it can be helpful for economists to become familiar with these tools. Advanced micro- or macroeconomics: Although every economics degree comes with micro- and macroeconomics coursework, advanced topics within these broad categories may need refreshing after a graduate has taken the first steps into their economics career. Advanced microeconomic or macroeconomic courses help take the fundamentals closer to real-world application, and can even inspire research by reminding graduates how macroeconomists (for example) tackle some problems that microeconomics-focused specialists don’t think about as often. Niche topics within these categories may be helpful for economists in a new role, too; perhaps a labor economist could benefit from reviewing the latest behavioral economics models, for example. And finally, some courses could delve deep into newly emerging research methods, or explain niche economic models that semester courses didn’t have time to introduce. Advertising your course When advertising your training courses, it’s important to emphasize the specific professional development skills that each course aims to provide, and offer a clear look at the course curriculum. These factors are usually the bare minimum for an economist to consider the course. For example, if they want to develop their Stata skills, they’ll look for a course that is all about Stata and contains specific topics they’re struggling with. Therefore, in your communications about the course – via advertisements, emails, or other messaging – be sure to clearly state the course’s topic areas of focus. Any accolades earned by the economics department or professor overseeing the course should be mentioned as well. Similarly, It’s also important to design an informative title for the training course. This involves understanding the reasons why an economist might search for the course. Designing the name of the course to clearly communicate the skills economists will learn is key to driving recruitment and engagement. For example, “Advanced Macroeconomic Analysis” is a fine name for a required course during a degree program. But for a professional training course, it falls flat. That’s because it’s unclear what the course is actually about, other than ‘macroeconomics’. A better title clearly lists the specifics, so that a prospective learner can quickly determine if the course will help them with what they need. For example, titles like “DSGE Models for Macroeconomic Analysis”, “Advanced Stata Tools for Time Series Analysis”, and “Analyzing Business Cycle Theory with Panel Data Tools” are much more eye catching to students looking to develop in those areas, and help a prospective student get excited about the course content before they even click on the link. Announce your course on INOMICS For most economists, the first place to search for professional development training courses is online. Therefore, finding a useful hub for economists where your course can be listed is very helpful. Generic course-catalog sites like Coursera can serve this purpose, for a fee to the institution. Other options include economics-specific sites where you’re likely to find a very high concentration of your target audience, like INOMICS. INOMICS helps put your Professional Training Announcement in front of potential candidates in economics across the web, email and social media, increasing your chances of reaching interested candidates and making your course a success. To really expand the number of candidates seeing your announcement, we have advanced promotion options and tools like Multi-Channel Promotion to try. This gives recruiters a tailor-made blend of content marketing, social media and email advertising to target the listing among our audience of economics professionals and students. Be sure to speak to our Sales Team at info@inomics.com to customize the right package for your institution, or check out our publish page for our latest pricing. INOMICS’ mission is to help institutions raise their profile and reputation and effectively recruit the best candidates in economics. Whether you are promoting a study program, postdoc, professor job, industry position, economics conference, scholarship, professional training course, or institution, our packages can be tailored to your needs to produce the best results. Header Image Credit: Robert Kneschke via Shutterstock (Licensed image - copyright)
This article overviews different types of economics skills training courses and discusses how course organizers and recruiters can make sure their programs get seen and attract the right talent. If you’re looking to better serve the economics alumni from your degree programs, build a pipeline of potential PhD candidates, or just attract more attention to the professional training courses you offer, keep reading for more.
In the labor market, employees sell their labor (the service being sold) to employers for a wage (the price at which employers can purchase the service we call labor). Since labor is a very important factor of production, the labor market is classified as a factor market. As with the market for any normal good or service, demand for labor tends to increase as the wage (or, the price of labor) falls, while the supply of labor tends to increase as the wage rises and it becomes more attractive for people to work. This is the same general relationship that can be observed in most product markets. However, the market for labor has a few unique characteristics that other markets don’t have. For example, as wages increase beyond a certain hourly wage level, the labor supply will start to decrease. This happens because when wages become high enough, employees become satisfied with their total income and begin to want more leisure rather than more income. This causes them to substitute work time for leisure. Due to this desire for work-life balance, the labor supply curve is “backward-bending”, unlike most product or service markets. In other words, an increasingly high wage will eventually incentivize people to work less, since they can afford to take a large amount of time off and still enjoy a high income. Figure 1 shows a typical labor market with downward-sloping employer demand for labor D and upward-sloping employee supply of labor S. The market is in equilibrium at an hourly wage of w* for h* hours of labor per week. The supply of labor is backward-bending beyond a "high enough" wage level of w', where further increases in wages will only incentivize workers to take more time off. That is, if quantity demanded for labor in this market increased such that employers were willing to pay more than w' per hour (for example due to a surge in demand for a product that requires specialist skilled labor), employees in the market would not supply hours of labor beyond h' per week as they would prefer to have more leisure time instead. The labor market would then be said to be “tight” and/or a “sellers’ market”. Since employees sell their labor to employers, the employees would have more power than employers in this situation. Figure 1: Labor supply as hours and wages increase Labor Economics Labor economics is the sub-field of economics that studies the labor market and the labor force. Labor markets, job markets, the movement of workers, labor force participation rates, and more can be studied at different levels of the economy. And, these can all be studied for different types of employment, from the perspective of different types of workers, by gender, by level of education, across borders, and much more. No wonder labor economics is one of the largest subfields of economics! It is common to sort employment in an economy by region, industry, occupation and the educational qualifications of employees. In practice, the process by which wages are determined also varies according to industry, education level, and occupation – and sometimes, even by factors such as ethnicity or gender (even though determining wages based on these factors can constitute illegal discrimination in many cases). In some sectors, free bargaining over wages takes place between employers and employees. This bargaining is heavily affected by the relative market power that employers and laborers hold. In situations where employers have more power (i.e., labor supply exceeds demand), negotiations will be tilted in favor of the employers, and vice versa. Another common type of wage determination involves trade unions, which negotiate wages with employers on behalf of employees. In these cases, individuals don’t negotiate for their wages; representatives for the employees do. Negotiating failures in these circumstances can often lead to widely-publicized strikes, where employees refuse to work until employers make concessions in wage negotiations. Meanwhile, in the public sector, wages may be subject to strict regulation such that its labor market is not really in free-market equilibrium. Furthermore, governments often set minimum wages for the economy as a whole (which function as a price floor in the market for labor). Labor markets differ from the markets for other items in that the labor being exchanged is inherently human; labor is not a simple commodity. Indeed, the conceptualization of the market for employment as hours worked in direct exchange for a wage is overly simplistic. The notion that people only go to work for the money is misplaced. There are many other motivations for seeking employment such as the desire to make a contribution to society, as well as one’s personal and social esteem associated with a job. There are benefits to holding a job in addition to the direct monetary compensation, typically including access to health and other social insurance, accommodation during the working day and opportunities to access wider professional and social networks. The fact that people volunteer their labor for no wage at all in some sectors of the economy is evidence of these other motivations. Nevertheless, the basic tools of microeconomics can still be used to quantify labor supply and demand in more complex labor markets: people’s valuation of a job in excess of the visible wage can be estimated by observing their working behavior over time. Labor Economics is a very rich and interesting area of study for economists precisely because of its more human aspects. Further reading The US Bureau of Labor Statistics offers a vast range of information and statistics on the American labor market on its website, and it is an excellent starting place to gain an overview of important and current topics for the sub-discipline of Labor Economics. For the more theoretically-minded reader, Chung-cheng Lin provides a plausible alternative explanation for backward-bending labor supply curves in his article, “A backward-bending labor supply curve without an income effect” (Oxford Economic Papers, 2003). Good to know In recent years, much has been made of the emergence of a “gig economy” in which firms hire workers on a short-term basis via contracts that offer little or no job security (just as musicians and other artists have traditionally been hired for gigs). People then no longer work as employees for an employer but rather as contractors paid by the hour or, more commonly, based on some specified output as gig workers (such as number of rides given for an Uber driver). While the pros and cons of such set-ups like gig work are certainly debatable, it is very possible that the future world of work will be more gig-like. In fact, when the labels of “employee” and “employer” are dropped for participants in the market, a gig economy comes closer to a "pure" labor market and it is thus easier for economists to study, understand and predict than employment markets that are regulated with high degrees of social protection for employees.
Employment is a major topic within macroeconomics, so much that labor economics is a massive field of research on its own. The market for employment, while unique, can be thought of just like the market for a physical good or service. So, what is the labor market?
A producer is typically a seller in the market for a final good or service (supply SG in the graph below). Simultaneously, these producers are also buyers in the markets for the factors of production (demand DF below) that they use in their production processes. For example, a paper manufacturer is a seller in the market for paper while being a buyer in the market for wood pulp. Figure 1: Illustration of factor markets for a firm producing final good G Figure 1 depicts how markets are often interlinked with one another. For example, the market for cars depends on the markets for raw materials such as steel, rubber and glass. It also hinges on labor markets for people to design and assemble the cars. That’s because these factors are all inputs to production for car producers, who depend on the markets for steel, rubber, glass, laborers, etc. to help them build and sell cars. Therefore, what is happening in one market can have a “ripple effect” on surrounding markets. If the price of steel increases, car producers face higher costs to produce the same products. This will cause them either to reduce the supply of cars, or to increase their price. Similarly, if the price of fuel increases, demand for cars will fall due to cross elasticity of demand. This will result in declining demand for steel, rubber, and other inputs by car producers, as they produce fewer cars in response to the lowered demand for cars. When deciding how much of a production factor to employ, producers weigh its marginal cost (MC) against its marginal revenue product (MRP). MC is derived from prices in the factor market. MRP depends on the market for the final product. As long as the last unit of input adds more to revenue than it does to cost (MRP > MC), it still makes economic sense to use it. If there were perfect competition in all markets, then the effects of a supply or demand shock from one market onto another’s prices would be relatively easy to calculate. However, in reality, most markets exist in some state of imperfect competition. This means that power is not equally balanced between buyers and sellers. For example, the labor market is a factor market where prices (i.e. wages) are often affected by collective bargaining through trade unions. It could also be influenced by a government’s decision to implement a minimum wage or some other regulation. Producers can then find themselves squeezed between a high degree of competition in the markets for their final products and high or inflexible costs in their factor markets. Interdependencies between factor and product markets sometimes provide good reason for producers to buy out their input suppliers, merging along the supply chain (so-called vertical integration). For instance, if a car manufacturer purchases the firm they buy steel from, they would be vertically integrating. In effect, sales contracts are then replaced by employment contracts and free, internal transactions between departments. This helps a business reduce transaction costs when acquiring inputs, and gain a higher degree of control over the production process. While such changes in ownership structure can help producers to control risk and increase efficiency, they also tend to reduce competition. This can lead to market failure and issues of antitrust. The major factors of production in an economy So far in this article, we’ve discussed factors from the perspective of firms selling final goods. But, there are a few other major factors of production to discuss: land, labor, capital, and entrepreneurship. These four factors of production aren’t always bought and sold like typical factor inputs, yet they are all considered inputs to production. Land as a factor is bought and sold much the same way as other factors, but it is unique in that there is a finite amount of land to share between everyone. Labor has already been alluded to. The labor market is the factor market for labor, where skilled workers vie for employment as a valuable input for an employer’s business. Labor is usually accounted for in the basic Cobb-Douglas model of production by the variable L. Capital itself is also a factor of production. Capital as a factor includes inputs such as manufacturing machines and other tools and equipment. It also includes financial capital that businesses use to operate, and human capital, a very important input that is developed by education and on-the-job training. Capital is represented in the basic Cobb-Douglas model of production by the variable K. Entrepreneurship is not always pointed out as a factor of production, but some economists mention it because it is the ingenuity that helps foster economic growth. Entrepreneurs combine inputs in new ways, develop more efficient and productive economic processes, and launch entirely new ventures that can disrupt industries and lead to creative destruction. Further reading John Dunlop and Benjamin Higgins discuss how different forms of competition in factor markets can affect wages and prices across the economy. They use a general-equilibrium approach in their early paper, “‘Bargaining Power’ and Market Structures” (Journal of Political Economy, 1942). Good to know A sound understanding of factor markets is imperative for making successful investments in the stock market. When assessing a firm’s future potential it is important not just to consider direct competition in its final product market but also to look at the trends in its factor markets and their effects on its future performance. For example, if the price of jet fuel rises, ceteris paribus one would expect airlines' financial performances to decline. Generally speaking, the higher the degree of competition in factor markets and the lower the degree of competition in the final-product market, the higher the value of a final producer.
Factor markets (or resource markets) are markets that help connect buyers and sellers of the inputs used to produce goods and services. “Factors”, then, are inputs used in production, often natural resources or intermediary products that are needed to make more complex goods, like nails or computer chips.
Austrian Economics: Historical Contributions and Modern Warnings
Although these “schools” are separately defined, many modern economists probably consider themselves to fall into an ideological mix of several, and theories from a school can be useful even if an economist considers themselves a “member” of another. This article focuses on the latter of these schools of thought, which happens to be set apart from the others in a unique way. Austrian economics is considered “heterodox”, or not mainstream. The Austrian school of economics may not even be considered legitimate economics by some modern economists. This article provides a brief history of the school, its contributions to economic theory and the reasons it’s generally no longer considered orthodox. Finally, there is a gentle warning about how the label may be misused in modern discourse. Defining Austrian economics To an Austrian economist, economics is about individual people making choices based on their preferences – in other words, human behavior (or “praxeology”, as Austrian school thinkers like to reference). Austrian economists are often also concerned with the unintended consequences of these individual choices, which have lasting effects on economic activity. Due to this concept of unintended consequences, Austrian economists tend to purport the idea that economic institutions form in unintentional and inefficient ways, as the result of individual agents’ own decisions and actions. In this view, it’s no one person who designs the economic systems we put in place – rather, they result as a by-product of the self-interested actions that individuals take. Then, because these systems are not purposefully designed, and because it’s impossible to know the preferences and utilities of every individual, Austrian economists tend to believe that government activity is usually harmful. In this way, they agree with classical economists who believe that government intervention is neutral at best. However, Austrian school economists disagree with the classical economists on other key ideas; the classicals believe that money is neutral, while the Austrians assert that money is not neutral at all (similar to the monetarists). In the present day, there are two major camps of Austrian thinkers, with two historical figures acting as their guide. One camp functions as stated already, being staunchly against government intervention and rejecting much of neoclassical economic theory. They follow the philosophies of Ludwig von Mises and Murray Rothbard. The other camp is more lax about these concepts and may not always be against intervention, though they certainly don’t promote it as (neo-)Keynesians would. These Austrians accept more of neoclassical economics than the others, and follow the thinking of Friedrich Hayek, who won the Nobel Prize in 1974 for his contributions to “the theory of money and economic fluctuations” (alongside Gunnar Myrdal). Austrian economists believe that economic truths can be learned by conducting “thought experiments” that don’t have to rely on data. This involves using logic and reasoning to postulate their theories. Austrian economists therefore tend to downplay (or altogether reject) the role of econometrics and data in economics – as many of them believe that human behavior cannot be modeled effectively in mathematics as conveniently as many orthodox economic theories attempt to. In the modern age, this stands in stark contrast to mainstream, orthodox economics, where empirical evidence and quantitative skills are considered critically important to support or discredit economic theories and models. Modern academic research prizes falsifiable hypotheses and quantitative analysis to support theories, so these skills remain crucial for economists hoping to publish in top journals. This is, of course, a relatively recent development; economists began to favor econometric methods more heavily in the mid-twentieth century. Until then, most economists’ methods were much more similar to those of Austrian economists. Yet, more recently Austrian economists have tended to reject some economic theories and concepts that are widely accepted by those in the mainstream, further separating them ideologically. For example, many Austrian thinkers would reject the idea that the free market can be inefficient, while the majority of mainstream economists would agree that externalities, asymmetric information, and more can make markets inefficient (though of course, they may disagree about the best interventions to solve the problem, if any!). The vast majority of professional economists today consider themselves non-Austrian, and would consider Austrian economics at its best to be misguided. Economist Leland Yeager wrote that he opposed Austrian economists’ “...ultra-subjectivism in value theory and particularly in interest-rate theory, their insistence on unidirectional causality rather than general interdependence, and their fondness for methodological brooding, pointless profundities, and verbal gymnastics"1. Similarly, economist Paul A. Samuelson wrote that “...the exaggerated claims that used to be made in economics for the power of deduction and a priori reasoning…Fortunately, we have left that behind us.”2 However, this ideological divide was not always so stark. The beginnings of Austrian economics Austrian economics is widely considered to have begun upon the completion of Carl Menger’s Principles of Economics, which was published in 1871. This work put forth the idea that the logic of individual choices, even when those choices are uniquely human and not “economically rational”, should form the basis of economic analysis. Nevertheless, although he is considered the “father” of the Austrian school, Menger himself wasn’t necessarily opposed to or opposed by mainstream economists of his time. He dedicated his seminal work to a prominent German economist (William Roscher), who at the time belonged to a philosophical camp that touted historical evidence as key to learning economic truths and proving theories. This camp became a major force opposing the emergence of Austrian economics, which argued that historical facts were merely illustrative of human behavior, but that theory alone should be relied upon. In fact, it was these German “historical school” economists who labeled Menger’s ideas as “Austrian economics” in the first place. The term was meant to be derogatory, but it was later adopted by Austrian economists, who began using it to label themselves. Contributions of Austrian economists Economists used to be quite limited in their ability to conduct quantitative analysis, when calculators and computers weren’t widely available. Conducting procedures like regression analysis by hand can be extraordinarily tedious, and being forced to research economic data by finding historical records in libraries was much more time-consuming than downloading an economic dataset from the Internet. It should be no surprise, then, that Austrian theories and methods – that don’t always rely on empirical evidence – were quite relevant and more accepted by economists in the past, as they reflected mainstream approaches of the time. In fact, Austrian economists have contributed to theories and ideas that support what is very much considered orthodox today. For example, Austrian ideas are credited with influencing the “Marginal Revolution” in economics, which occurred in the late 1800s and introduced the now-mainstream idea of “thinking on the margin” or “marginal analysis” to economics. For example, the “father of Austrian economics” himself, Carl Menger, is partially credited – alongside famous economists such as Léon Walras – with developing the idea of marginal analysis. The “Marginal Revolution” (or marginalist revolution) introduced concepts like the theory of marginal utility for the first time. These ideas showed that economic agents make decisions based on their consumption of the “next unit”, as they weigh the costs and benefits of each action they take. Core economics concepts such as diminishing marginal returns sprang from this period, and continue to be widely acknowledged and taught in mainstream economics today. Opportunity cost is another example of an economic theory first introduced by an Austrian economist, as it’s attributed to Friedrich von Wieser, an Austrian economist who formulated the idea around the same time, in the late 19th century. Therefore, it’s undeniable that Austrian economists in the past have contributed to the development of the field of economics today. And, Friedrich Hayek winning the Nobel Prize in Economic Sciences in 1974 gave a brief resurgence of legitimacy to the Austrian school. But even by that point, Austrian economics was widely considered heterodox by most professional economists. As time went on, and as math, statistics and econometrics became increasingly important in economics, the majority of economists came to believe that quantitative analysis of empirical data is a key tool to furthering our understanding of the economy. As a result, Austrian economics is now considered heterodox in large part due to what other economists would call a lack of empirical rigor (of course, some Austrian economists may actually use empirical methods and so argue this point, but the school overall remains less committed to empirical evidence than many modern economists are comfortable with). The accusations run in both directions; Austrian economists have levied critiques against mainstream economists, as well. According to some Austrian economists, orthodox schools of thought fail to account for the unintended consequences of economic policy or individual choice. Others would claim that an over-dependence on quantitative rigor has led modern economics astray. While it’s not correct to “throw the baby out with the bath water” with regards to quantitative methods in economics, there may be some merit to this latter claim. Occasionally, mainstream economics is criticized by other actors as well for failing to see the “big picture” from among the strings of equations and data. One example of this is the 2008 financial crisis that precipitated the Great Recession. Very few economists correctly predicted the crisis or warned about the weaknesses in the global financial system. Arguably, a lack of “big picture” thinking partly led to the failure of economics to prevent catastrophe. This illustrates how economists should be careful not to get caught fully up in data or empiricism so they can still see the whole picture – though of course, data and empirical analysis are key tools when used properly. Finally, other factors (like corporate greed and lax legislation) were arguably much more to blame for the crisis than economists' failure to raise the alarm about the economy, although that task certainly does belong in the economics wheelhouse. The intertwining of the far right and Austrian economics Regardless of ideological differences, readers ought to consider the economic theories and evidence critically when encountering a self-described Austrian economist in the present day. Unfortunately, Austrian economics’ fondness for thought experiments, de-emphasis of quantitative rigor, and the label “economics” itself has caused the school of thought to be an attractive ideological tool for disingenuous actors in contemporary times. Because these facets of the school lower the barrier to entry for individuals who haven’t studied economics (at least to feel that they are competent economists), they have allowed unsavory groups, including far-right ideologues, to flock to “Austrian economics” as a means of disguising hateful ideologies as “economic theories”. Austrian economic theories heavily favor unregulated free markets, and are against almost every form of government intervention. These facts, too, tend to attract political actors who fall into libertarian, anarchist, or right-wing camps, who then tout the theories of Austrian economics as a priori fact and use them to push their own policy agendas without much factual backing. Further, this lower barrier to entry required by Austrian views encourages the development of “armchair economists”. This is in line with the general decline in trust of experts that has plagued society in the 21st century. It’s easier for an individual with a moderate view to read the writings of extreme “Austrian economist” conservatives touting these a priori theories as fact, than it is for them to work through a detailed economic paper using quantitative methods that provide a sound empirical basis, let alone study a degree in economics and learn about the vast depth of nuance that characterizes modern economic research on topics that might seem obvious at first – like the effects of a minimum wage. These actors may then very well consider themselves on par with professional economists, and even write “economics” opinion pieces without any sort of formal training, and repeat ideas that far-right actors have pushed as economic truth. For example, racist individuals can point to Austrian school style non-interventionism to push the idea that affirmative action, or any sort of policy that benefits minority interests, are destructive and should never be implemented for any reason. Similarly, any government redistribution programs – such as those to alleviate poverty, support retired veterans, etc. – are considered wasteful and a net loss for society. These views easily lend themselves to the types of far right-wing ideas that quickly spiral into anti-immigrant, racist, or other ultra-conservative positions. For example, far-right ideologues can take the anti-affirmative action or anti-redistribution stance, and go a direct step of (bad) logic further to state that these policies are really just discrimination against white people, decry them as morally wrong, and stoke the flames of racist anger – while hiding behind the guise of analyzing society as an unbiased “economist”. Sometimes, these actors may use Austrian positions to denounce the work of professional economists, central banks, and governments. And, a proportion of “armchair” Austrian economists may completely disregard the findings of economics professionals. Be wary of such discourse, and be sure to look to the evidence, research, or teachings backing any self-described Austrian positions, to determine what lines of reasoning are based on legitimate economic theorizing, and which are not. Be aware of bad-faith critiques of professional economists Whether connected to political agendas or not, there are modern-day Austrian economists who disparage the field of economics at large. The label “economics” has given a sense of legitimacy to these actors, emboldened by the writings of so-called Austrian economists who may have an agenda. Some of these writings come from self-described Austrian think tanks or other ideologically-focused organizations. One clear example is Jonathan Newman’s writing for the Mises Institute. In a March 2024 article, “Economics Needs a New Methodenstreit Based on Austrian Methodology”, Newman sets about criticizing mainstream economics (“Even a cursory look at what passes for economic scholarship in mainstream journals today shows that the methodological errors that were exploded by Menger and Mises persist”). One of the underlying assumptions in Newman’s writing is that state intervention is always undesirable – such that it is a foregone conclusion that the American Economic Review articles he shares must be biased because they conclude that state intervention or government programs led to positive results in some cases. His article also notably demonstrates the disdain for econometric methods common in modern Austrian economics discourse. Newman’s third and fourth examples of poorly-done economics research are simply an abstract about econometric methodology and a screenshot showing several equations. These are apparently evidence of those papers’ lack of usefulness. As another, more in-depth example, Henry Hazlitt’s 1946 book Economics in One Lesson3 is a popular and acclaimed read among contemporary Austrian economists. Unfortunately, the book contains a large amount of disingenuous language that seeks to discredit professional economists, and proposes the Austrian model of thinking as the obviously superior alternative. The following quotes offer examples taken from the book. “…the whole of economics can be reduced to a single lesson, and that lesson can be reduced to a single sentence. The art of economics consists in looking not merely at the immediate but at the longer effects of any act or policy; it consists in tracing the consequences of that policy not merely for one group but for all groups…Nine-tenths of the economic fallacies that are working such dreadful harm in the world today are the result of ignoring this lesson.” (page 5) Here, Hazlitt attempts to reduce the entirety of economics to one sentence, and in the same breath claims implicitly that economists routinely fail to consider longer-term effects of their policy suggestions. “But comparatively few people today make this error; and those few consist mainly of professional economists. The most frequent fallacy by far today, the fallacy that emerges again and again in nearly every conversation that touches on economic affairs…the central sophism of the “new” economics, is to concentrate on the short-run effects of policies on special groups and to ignore or belittle the long-run effects on the community as a whole” (page 5) This quote more blatantly targets “professional economists” as people who fail to consider long-run effects of their policy recommendations, a fallacy that other people would not make. “An elementary fallacy. Anybody, one would think, would be able to avoid it after a few moments’ thought. Yet the broken-window fallacy, under a hundred disguises, is the most persistent in the history of economics…It is solemnly reaffirmed every day by great captains of industry…by learned statisticians using the most refined techniques, by professors of economics in our best universities. In their various ways they all dilate upon the advantages of destruction…they see almost endless benefits in enormous acts of destruction. They tell us how much better off economically we all are in war than in peace.” (page 13) This quote from Hazlitt stands out as a neat summary of a chapter that disingenuously presents economists as professionals that celebrate destruction. Hazlitt correctly identifies that destruction is not good, and in fact that it’s wasteful when the money that would have gone towards other things must go towards rebuilding instead. However, he asserts that professional economists do not make this connection. “The analysis of our illustrations has taught us another incidental lesson. This is that, when we study the effects of various proposals…the conclusions we arrive at usually correspond with those of unsophisticated common sense.” (page 177) This quote from Hazlitt’s book asserts the idea that correct economic conclusions “usually correspond with those of unsophisticated common sense”. This is, clearly, a minimization and denunciation of the field of economics at large. The above direct quotes are filled with bold claims about the ineptitude of professional economists. This type of charged language is a red flag signifying that the written work itself has not been written with a full understanding of economics, its aims, and role in decision making. Nor, clearly, has it been written in good faith, or without bias. It should be clear that these types of emotionally-charged critiques of mainstream economics often contain dishonest assertions and sweeping generalizations about how economists think, advise, and research. To believe that the scores of professional economists working around the globe are unwilling or unable to consider the consequences of the policies they research, support, or criticize, is to think that all economists are short-sighted at the very best – and is a blanket insult to the profession. Yet they come from a self-described Austrian economist who did not study economics. The author of the book, Henry Hazlitt, was a journalist who wrote for the business and finance sections of several publications. However, his writing is often cited by present-day “Austrian economists” and touted as fact. In summary: the legacy and pitfalls of Austrian economics In summary, then, readers should take care when encountering self-described Austrian economists. In the past, such economists did contribute to economic theory and helped to advance the field. Today, however, Austrian economics has remained rooted in the past such that it is no longer considered mainstream, preferring to remain with thought experiments and eschew the empirical research that economics at large has embraced. Further, the label “Austrian economics” is often applied to harmful or disingenuous political positions, to grant them an air of legitimacy that the average member of the public may not be informed enough to think twice about. The best legacy of Austrian economics is the serious theorizing that gave rise to concepts like marginal analysis and opportunity cost, and Friedrich Hayek’s Nobel Prize-winning study of money and economic fluctuations. But unfortunately, readers must be wary of ultra-conservative, anti-expert pundits and self-described economists who take the label to further their own, sometimes problematic and politically-charged ideas without substantial evidence to back them. References 1: Yeager, Leland B. (1997). "Austrian Economics, Neoclassicism, and the Market Test". Journal of Economic Perspectives. 11 (4): 153–165. 2: Samuelson, Paul A. (September 1964). "Theory and Realism: A Reply". The American Economic Review. American Economic Association: 736–739. 3: Hazlitt, H. (1946). Economics in One Lesson. Harper & Brothers Publishers. First edition reprint accessed at https://www.liberalstudies.ca/wp-content/uploads/2014/11/Economics-in-One-Lesson_2.pdf. Header image credit: Mises Institute - Fair use image of Friedrich Hayek retrieved from Wikipedia at https://en.wikipedia.org/wiki/File:Friedrich_Hayek_portrait.jpg.
There are many schools of thought in economics. Each rallies around one or more different theories about how the world works, and builds models to support those theories and explain the economy. These schools include the (neo)classical, (neo)Keynesian, monetarist, and Chicago schools. Readers may have heard about the Austrian school of thought as well.
After high school, you got the economics degree. At great emotional and financial cost, you got it. Three years of diligent work, complete. Never to be repeated, either; your liver feels permanently weakened, you continually explain to people that your degree had nothing to do with the stock market, and you’ll never hear the word “incentive” quite the same way. You then finished the internship. Though it was lengthy, unpaid, and involved minimal compensation, it was likely worthwhile because everyone strongly encouraged you to do it, and you complied. It served one important purpose at least. Brought up-to-date, with the font size adjusted to 24, your CV finally ran to a full page of A4, now ready for new job opportunities. Emboldened, you began the job search. 14 months later, self-esteem long gone, your persistence paid off, the application process, the long-awaited interview, vindication. You remained calm under pressure, outperformed tough competitors through four rounds of interview questions, and impressed your hiring managers with your commitment to working weekends. Contract signed, you now sit at the computer, nervously, waiting for adulthood to begin in this first step into the working world. <11an>limit:3;categories:Postdoc;disciplines:Economics</11an> Now, don’t get fired! And the nerves are there for a reason. Work is no walk in the park. Indeed, resting on your laurels now would be unwise. The 9-to-5 can be a cruel master, ruling with an iron fist, and is particularly prone to nepotism and other office politics. To survive its tumult and built-in bias, one must be smart, savvy and alert - things they don't teach at college, yet things you’ll need asap. Complacency on any of these fronts and, well, expect disappointing results. But let’s remain positive! You can prepare. Follow these tips to reduce the risk of floundering and increase your chances of experiencing success. Together, they make up the INOMICS guide to surviving your first entry level job. Get to know the office culture, quickly An appreciation of office culture will be critical to your longevity. As a general rule you should respect it (unless, of course, it’s toxic), particularly at the start. That includes the parts that seem silly, too. For inevitably - and this is fine - there will be aspects of it you don't like. Wearing a tie in 35 degree heat, for instance, is gross, and there’s nothing professional about sweaty, red faces. But as a newbie in an entry level position, save the protest and keep your neck below the parapet. Try to gauge the work culture before you go about dismantling it (great advice to remember when you are inevitably promoted to a manager position, too!). It developed in your absence and will reflect both the history and values of the company, which, unsurprisingly, many will hold dear. Don’t go about offending on day one. And not offending should be easy, you’re a considerate person after all. But presumably you’ll have loftier aspirations; you’ll want to impress. One of the best ways to do so - besides routinely leaving cookies in the staff kitchen, which can be expensive - is to ask questions. Not to just anyone, though. Find a sympathetic colleague, someone with years of experience within the company, and get the office low down. Do people leave as the clock strikes 5? Are hour-long lunch breaks standard, or looked down upon? Does the boss have any unusual quirks you may need to tip-toe around? And how formal is office etiquette? Not only will getting a grip of these practices help you settle, it will move you out of the firing line and push you towards your dream job. And certainly, if you can afford it, don't forget to bring cookies. Bribery works. Signpost your humility and willingness to learn It may sound desperately obvious, but you’d be surprised how many people fail at their first job for not showing enough eagerness to learn. Don’t be one of them. Learn from your mistakes quickly, ideally while remaining dignified. And be open about what you don’t yet understand. Asking for instruction when unsure on something is preferable to charging ahead, effectively blind, and hoping for the best. The results of this wrecking-ball approach are time-consuming, discomfiting and potentially even job-losing. Avoid it. In fact, you ought to consider surveying your workload and your colleagues in your first few weeks. What skills do others have that you might need, or be expected to learn? What parts of your job make you feel the least qualified? Especially in economics, it pays to review areas of study that you may need more intensely in the office than in school, or topics that you might be unfamiliar with but need in this role. Companies often hire economists for their proven ability to learn and analyze data, not just their expertise in labor movements across borders (for instance). Bosses also admire humility in their employees. Its practice facilitates honest, efficient communication, and demonstrates both maturity and confidence. Remember, you’re only entry-level. No one is expecting perfection, so there’s no need to pretend you offer it. Be cool with what you do know. It did, after all, get you hired. However, keep in mind that excessive humility is to be avoided. You don’t want your colleagues to think you’re incapable. Be honest when you’re in over your head and ask for help; gracefully accept the praises given to you, and earnestly consider the feedback (positive and negative) you receive. Now to the signposting. A practical way of doing this is establishing an open dialogue with your superiors. Not all companies will automatically schedule performance reviews, and oftentimes when they do, they’re sporadic. Not so helpful for a newb. If this is your experience, be proactive (signposting in action) and request one. It doesn't need to be too formal. It is just a way to check your progress and identify areas for improvement. Consider bringing specific topics or questions for feedback, to tighten the scope of such meetings. Also, a bit of one-on-one time with your seniors is always handy for making - or hopefully consolidating - a good first impression and to build relationships. Be sensible, though: sycophancy is an unattractive trait. Limit any excessive flattery, customize it to suit your boss's ego in a subtle way. Over stretching is bad And easily done. It's normal to want to make promises to everyone, especially in the first few weeks when you may still be nervous. We all know the desperate desire to impress, to be seen as competent, independent, and unfazed. Abstractly these inclinations are positive, they show you to be a well-intentioned person, willing to pull your weight, and more. So on that front, well done. However, you must have them under control. Unfettered enthusiasm can get you into all kinds of trouble. Don't make big promises you can't keep. It can upset important people who have control over your job and could fire you. Ward against this. It’s fine to say no to doing yet another ‘favor’, and sometimes necessary. As the famous saying goes: it’s better to do one thing well than three things catastrophically. Don’t undersell yourself, just be realistic with what you can manage. If you’re nervous about refusing a favor outright, consider asking if it can be delayed, and mention that your work time is dedicated to other important, time-sensitive projects. Don't be afraid to take the initiative While keeping the above in mind, you should take the initiative. And if possible, try and do so when people - the more senior the better - are watching: make it visible. This will make you look accomplished, show leadership, and when promotions are in the offing, help you stand out. Taking initiative can be achieved in a number of ways. The most obvious is doing more than is expected of you. At the beginning, your task will be clearly defined and not too difficult. Try to do more than expected, but be careful not to do too much as advised above. This does not mean taking out the bins, although that’s a nice gesture and a chore many avoid. It means sharing your ideas, skill sets and expertise in topics you are interested in, even if no one has requested them. It also means thinking critically about the tasks you’ve been handed, and trying to find new, innovative ways to accomplish them. Modern institutions know well the need to innovate to stay relevant. Try to become part of this innovation. For if you do, you’ll find your career path, safe from the next round of cuts. Final words Okay, back to you, sitting there at your computer, tense. You can take a breath, we’ve covered the basics. It is now for you to remember them. Print them out, recite them and make sure you follow them. The imposter syndrome will subside if you do; and what a feeling that would be. Seriously though, things, in all likelihood, will be fine. With a good attitude and the ability you (surely) have, it won't be long before you gain the confidence to look away from your computer screen to the room and colleagues around you. In that beautiful moment you’ll realize you deserve the position you’re in. You’ve worked hard, and in reality, you are ready for this job. You may also notice that actually most of your work is pretty well received. You feel a bit less stressed, and you’re even getting invited to after work drinks now and again. The bliss... Now, to ask for a pay raise. Image Credit: fizkes / Shutterstock (Licensed Image - Copyright)
It’s your first day at work and you’re nervous, naturally. You decide to quickly remember the journey that brought you to the computer screen you are now looking at. Many INOMICS readers will relate to this journey.