The Top Economics Blogs to Follow in 2025
At INOMICS, we believe economics blogs offer a treasure trove of interesting, informative, and often unique perspectives. That’s why we’ve curated this list of our favorite blogs and podcasts to follow in 2025. Whether you're looking for real-time economic insights or a deep dive into economic theory, this list covers it all. Check out our top picks below and explore them for yourself! Staying informed and gaining new perspectives is important. It can give valuable insights into current economic trends, policy talks, and new research. Economic bloggers come in many types. 1. Marginal Revolution Written by George Mason University professors Tyler Cowen and Alex Tabarrok, Marginal Revolution is a top source for interesting ideas about economics. This covers policy discussions and cultural insights, making it essential for those interested in current economic topics. Their ability to connect economic theory to real-world applications makes this blog a crucial resource. 2. The Grumpy Economist John H. Cochrane is a Senior Fellow at the Hoover Institution. He provides clear and smart insights on economics, finance, and public policy. This blog is known for detailed data analysis and valuable discussions about financial and economic policies. He challenges conventional wisdom and encourages critical thinking. His clear, accessible writing style makes complex economic concepts coherent to a broad audience. 3. Calculated Risk Bill McBride’s "Calculated Risk" is a trusted source for understanding real estate, housing trends, and the economy. His detailed and data-focused approach helps readers, professionals, and academics grasp the complexities of the economy. This makes it a valuable resource for anyone interested in real estate economics. 4. Econ Log EconLog, run by the Library of Economics and Liberty, includes various contributors sharing ideas on economic theory, public policy, and classical liberal views. This blog offers a place for lively debate and different opinions. 5. VoxEU The Columns section on VoxEU is part of the Centre for Economic Policy Research which offers concise, research-based commentary on pressing economic issues. It features articles written by economists and researchers, covering a wide range of topics such as macroeconomics, finance, trade, labor markets, and policy debates. The columns distill academic research into accessible insights, helping readers, including policymakers, academics, and the general public, stay informed about the latest economic trends and evidence-based policy discussions. 6. Noahpinion Noah Smith’s "Noahpinion" offers engaging commentary on economic trends, technology, and policy. Smith has a background in finance and economics. He offers clear and helpful insights into current events and economic theory. He often looks at how technology is changing the economy. He also explores how these areas affect one another. His approachable style and ability to explain technical concepts make his blog a favourite among both novices and experts. 7. Bruegel Commentaries The Bruegel Commentaries, managed by the Bruegel think tank, is a great resource. It offers detailed insights into European and global economic policy. It includes input from various experts. They give clear comments on topics like EU economic rules, the digital economy, and global trade. The blog focuses on policy issues and has top contributors. This makes it an important resource for both policymakers and scholars. 8. The Undercover Economist Tim Harford’s "The Undercover Economist" continues to demystify economics for the everyday reader. Harford explains complex economic ideas with relatable stories. People enjoy seeing how these concepts apply to everyday life. 9. The Conversable Economist Timothy Taylor, author of "The Conversable Economist," offers comprehensive and accessible discussions on economic trends and policy. Taylor can explain difficult topics in simple ways. This makes his blog helpful for both experienced economists and new readers. 10. Econbrowser Econbrowser, managed by James Hamilton and Menzie Chinn, provides a detailed examination of macroeconomic and international economic issues. They focus on data and current economic trends. This makes it a useful resource. It helps anyone who wants to understand the complexities of the global economy. 11. Digitopoly Digitopoly studies how the digital world affects economics, covering innovation, competition, and technology's influence on markets. Joshua Gans and his co-authors provide expert insights into how the digital economy is reshaping traditional economic paradigms. 12. The Global Economy and Development Blog The "Research and Commentary" section covers global development issues and provides in-depth policy evaluations. Experts share views and research-driven reports on economic growth, poverty reduction, and global policy. This makes it a helpful resource for understanding global economic issues. 13. Naked Capitalism Naked Capitalism often provides critical analysis and commentary focusing on the flaws in mainstream economic thinking and corporate influence. It offers original articles and curated news links that discuss financial markets, banking, economic policy, inequality, and corporate governance. If you’re looking for alternative viewpoints on economic and political matters this blog is for you. 14. Enlightenment Economics Diane Coyle an economist, provides thoughtful commentary and analysis on economics, focusing on the intersection of economics, technology, and public policy. It includes reviews of economics books, reflections on economic theory, and insights on current economic issues, with an emphasis on how technological change is shaping the economy. 15. Focus Economics News The News section of FocusEconomics provides readers with up-to-date economic news and analysis, covering global economic trends, country-specific data, and key indicators like GDP, inflation, trade, and financial markets. It delivers concise reports on the latest economic developments from various regions, offering insights for businesses, investors, and policymakers. The section is valuable for tracking macroeconomic trends and forecasts across countries and industries. 16. INOMICS Blog Finally a shameless plug for our own blog, with a focus on economics careers and economics education, as well as insights into interesting areas of economics research that can guide and inspire economics students and young economics researchers. But then you are already here, so you already knew that! Conclusion We selected these top economics blogs for their expertise, quality content, and relevance to today's economic topics. Following them will keep you informed about the latest trends, debates, and research in the field of economics. These blogs provide useful information for students, teachers, and workers. They can help you understand the economy better. Each blog has its niche or specialty that it focuses on; use this to your advantage, and find the right blog for you! Keep being curious and explore these resources to learn more and stay updated in the changing world of economics.
Staying informed on economic trends, policies, and research is key to gaining valuable insights into the ever-changing global economy. Whether you're an economics student, educator, or enthusiast, exploring different viewpoints is essential. Economics bloggers and podcasters come in all forms—some are academics like Gregory Mankiw and Paul Krugman, while others are insightful thought leaders like John Cochrane and Tyler Cowen. Their expertise spans from real estate to public policy and macroeconomic trends.
How to better engage economics students in work placements
A typical work placement can be embedded within a degree programme either as an additional year (typically, the third year of a four-year course), or as a module within a year of study, where students get practical training and work experience in an organisation (e.g. a consultancy firm or a government institution). Work placement experiences can be crucial experiences for economics graduates. Even though economics degrees equip students with many skills that are desirable by employers – like data analysis and problem-solving skills – a shortage of certain skills and wider technological challenges have still been observed among graduates. In this article, we discuss why and how to encourage economics students to participate in work placement programmes. Work placements help students develop transferable skills There is a broad spectrum of benefits associated with the ‘real-world’ experience that students gain through placements. By being immersed in a professional environment, students develop valuable transferable skills across different broad areas, like communication, taking initiative, planning and organisation, and professionalism. Further, students develop and enhance subject-specific skills and knowledge during placements. For instance, they gain data analysis skills by working on ‘real’ data, using them to produce charts and statistics, and critically analysing them. Industry knowledge is important not only in economics-oriented sectors like consultancy or banking, but also in those that require expertise from other disciplines, like energy or telecommunications. The industry knowledge that economics students acquire during their placements in these sectors can offer a strong advantage for certain careers and graduate schemes, like the graduate development programme at Ofgem, Britain’s independent energy regulator. Image credit: Pixabay. Another notable benefit of work placements, perhaps one of the most important, is that students tend to gain confidence in their skills. This includes improving their understanding of their skills, how academic knowledge from their studies is applied to real world settings, and confidence in articulating those skills. For example, at university, students usually learn econometric methods and use economic modelling in the first and second year of their studies. These skills can then be applied in research-oriented roles, like those offered by the Bank of England or consultancy companies that carry out forecasting and risk analysis. What’s more, the placement year offers students the opportunity to apply economic theories to real-life situations in different sectors. For instance, students might use core economic concepts to understand international markets and the economic performance of a country and draw insights from macroeconomic indicators, such as inflation and economic growth. Other benefits of work placements Networking is another important benefit of placements. Students meet and interact with new and different people, including peers from other universities, colleagues and managers. Students not only gain knowledge and experience from their placement work, but they also create contacts with line managers and other employees, who can share their insights into careers and support students’ applications for future job openings. Further, placements can be a useful way for employers to identify graduate talent. There are potential monetary benefits of placements too. Most economics placements are paid, typically offering annual salaries of around £20,000, but there are occasions that these may exceed £30,000 and even reach £40,000 (for more details see Arsenis and Flores, 2020). Furthermore, graduates can reap monetary benefits by securing graduate jobs with their placement employers. These earnings can alleviate students’ debt or help them to save. Obviously, such earnings need to be considered in conjunction with the costs associated with the work placement (including the reduced tuition fee for the placement year, and the delayed entry to the graduate labour market), which vary depending on individual circumstances. Overall, economics placements can be an important first step in career progression. They provide students with the opportunity to trial the world of work, gain valuable skills, and discover potential career pathways. Our recent study shows that graduates who have undertaken a placement are more likely to find graduate jobs that are aligned with their careers than those who did not have such an experience. Engaging economics students Students often need to be aware of placement opportunities early in their degree, or even before they begin their studies, as these opportunities are often competitive. Students’ first-year performance matters for securing a placement, while prior school performance, particularly in economics and maths, does not seem to matter. This creates the additional spillover effect that students are incentivised to engage more with the first year of their undergraduate studies. In UK universities, this year often does not count towards their final degree classification, even though it provides key, foundational training that is built on throughout their degree. Universities and economics departments can improve student engagement in different ways. First-year induction sessions could cover basic features of the available placement programmes and highlight their benefits as well as challenges (for example, the time-consuming process of applying for jobs while attending classes and sitting assessments). Career fairs and employability sessions could also be organised during the year to further motivate students and show them ways to improve their employability. In addition to the general employability sessions that careers services typically offer to students (including careers information and advice on skills development), economics departments can provide a more tailored learning experience that addresses economics graduates’ career paths and aspirations. To this end, inviting alumni to share their ‘success’ stories and advice with the current cohort is a great way to raise students’ interest in improving their own employability. Economics graduates tend to be employed in a wide spectrum of job roles; thus, it is important that invited alumni reflect that diversity. For example, economics graduates working in technology, media, and pharmaceutical companies can be invited along with graduates that have followed more traditional pathways, like banking and wealth management. Covering both private and public sector opportunities is important too. Indeed, there are lots of public sector roles available for economics graduates, such as those in the Treasury or the Government Economic Service. Crucially, students would need a dedicated point of contact - staff who can advise and direct them to the appropriate resources and services. Ideally, this person should be economics staff with a relevant role, like an employability or placement director, who also regularly liaises with the university’s employability and careers service to organise and advertise relevant events and resources. Image credit: Pixabay. Academic support for placement success Academic support can be crucial for students’ success in securing placements. One type of support is the role of placement tutor. Placement tutors typically visit students on placement (or meet them online), keep track of their progress, advise them on tasks they need to perform to complete the placement year, and assess students’ performance on related assessments. The placement tutor also fosters links between the university and employer, and keeps track of skills that are necessary in the graduate labour market. That part of the placement tutor’s role is important as it can also help to shape curricula. These days, a diverse set of skills is expected of economics graduates, including knowledge of data analysis and visualisation, coding, even machine learning. By creating syllabi and assessments that help students develop these skills, not only are students better prepared for the graduate labour market, but they also have better chances of securing a placement (and eventually a job) too. Academic support is a crucial element of work placement degrees, where a supportive learning environment can be enhanced by the contribution of placement tutors. Indeed, there is evidence suggesting that student access to academic support throughout the placement is an important aspect of the design of such programmes. The placement tutor can also contribute to a smooth transition from university to the graduate labour market. Challenges While adopting these approaches may go a long way towards engaging students with placements, it may not always be enough. Nowadays, a rising number of students in higher education come from different socio-economic backgrounds and face different challenges. But unfortunately, it is noteworthy that the economics discipline performs particularly poorly in terms of inclusivity. For example, it has a remarkably low share of students from low socio-economic backgrounds and from neighbourhoods with low participation in higher education (relative to the average student). Economics educators should be concerned about these challenges, as university degrees have arguably become increasingly necessary to be competitive in the labour market. It is crucial to first acknowledge these challenges, and to take appropriate action. Acknowledging the issue suggests that economics departments should not present the option of placements as the only path to developing employability while studying. Instead, alternative pathways should be promoted, like paid internships, which require less time to complete and usually take place outside of term times. But importantly, they still offer some of the benefits of work placements, such as creating new professional contacts and gaining insights into careers. Another way to encourage employability is by designing a curriculum that explicitly addresses it; for instance, by introducing modules or changing existing ones to involve opportunities for self-reflection on skills that students developed while working on assignments. Taking appropriate action involves supporting students who may want to go on placement but face financial constraints. For example, bursaries can be offered to students who come from low-participation neighbourhoods or low-income families. Clear widening participation criteria should be set and advertised to promote inclusivity, and to encourage students from different backgrounds to apply for placements. Summary In this article, we have set out the benefits of work placements and showed ways to engage students with them. Economics departments should be actively involved in this process and tailor their information to economics students. Economics educators should also be aware of the challenges that many students face and adjust their engagement strategies and support accordingly.
Employability is a key concern for students, educators and employers in the UK. Indeed, many students want to see employability playing a bigger role in their courses. One way in which universities can foster graduate employability is through work-based learning (WBL) programmes, such as work placements.
The Economics of Pokémon: Development, Pricing, and Wealth
The world that Pokémon presents has won over the hearts of kids and adults alike for decades. Trading cards, video games, movies and TV shows, collectible plushies, action figures, and much, much more have been commissioned from the franchise, earning it an impressive (estimated) $98.8 billion since its inception in 19961. The way this fictional world functions has some interesting implications for the economics of the society living there. Let’s assume that the internal logic of the world – people and Pokémon living in harmony in a seemingly modern world, where Pokémon can battle but do no lasting harm – is reasonable, and examine the implications for the economy. Domestication and industrialization in the Pokémon world The clear place to begin is by examining the economic implications of the Pokémon themselves. The Pokémon world features an absolute abundance of these essentially magical creatures, and they’re both unquestionably friendly to humans and easy to domesticate. The existence of Pokémon should lead to a massive boost in economic productivity compared to a world without these creatures, leading to rapid industrialization with a fraction of the human population. In our world, domesticating creatures like oxen, horses, cows, and camels led to massive changes in our quality of life, allowing humans to cultivate consistent sources of wool, meat, and muscle power. Both livestock and work animals were major factors helping early humans build their societies and grow – in fact, according to Jared Diamond’s Guns, Germs and Steel and other research, having animals nearby that were domesticable and useful was a major factor in determining how rich societies would be centuries later. Now, just picture an ox that can control the weather in addition to pulling your plow, and you’ll have a good idea of why early Pokémon-world societies would have skyrocketed past our own in development. Many Pokémon have powers relating to one of the nineteen elements identified by the franchise. One of the most obviously beneficial to an economy is the Electric type. In numerous episodes and video games, it’s been shown that a small number of Electric Pokémon can produce a massive amount of power. In Pokémon Gold and Silver, for instance, a single Pokémon powers the lighthouse for the port city Olivine, and it was (evidently) so reliable that when it gets sick, the lighthouse shuts down. The city didn’t have any contingency plan for this single-Pokémon power generator, presumably because it hadn’t ever needed to worry about it. Energy is crucial to the function of the economy, and developing electrical systems that could efficiently power our society took hundreds of years of innovation. To this day, producing power cheaply and efficiently is a major concern for nations around the world, and the prices of energy are a major concern for consumers. If easily-domesticated, electricity-generating Pokémon were readily available, power would (very likely) be incredibly cheap across the board, and Pokémon society probably would have advanced to utilizing electrical energy with incredible speed compared to our own. Perhaps the Industrial Revolution would have skipped the usage of coal and other fossil fuels entirely, producing electricity by sustainably harnessing the friendly lightning monsters (though it’s worth noting that there is a rock-and-fire Pokémon made of coal that could have spurred the Industrial Revolution as we know it on its own, so they could have gone that route too). This may even explain why the human population in Pokémon appears to be pretty low compared to our world. In Pokémon, there are relatively few major cities spread wide across various continents, each populated with thousands of people (to give a generous estimate). But if it was far easier for people to industrialize – especially as Pokémon can help provide labor to actually build things – it’s feasible that a much smaller human population was able to modernize extremely fast, before exponential population growth was able to produce as many people as we have in our world today. In the Pokémon world, Thomas Malthus may even have been an optimist. Infrastructure and the environment Electricity isn’t the only benefit these creatures provide to their human counterparts, though. Other Pokémon have been shown to be consistently useful and reliable throughout the franchise’s history, providing services such as labor (helping with construction projects and moving services), helping with gardening, ferrying across water, digging, delivering mail, assisting with cooking, and much more. For example, flying Pokémon have been used to taxi people around entire nations free of charge, ensuring rapid travel (for example, the Corviknight taxis shown in Pokémon Sword and Shield). Although a bird probably can’t fly as fast as an airplane, having an accessible and free taxi service would be immensely useful as a supplement for riding the subway or driving. In fact, very few cars and roads are shown in the Pokémon world, probably because of the existence of these free taxis, and the fact that individuals can simply train their own flying Pokémon to take them around. But that’s not to say that the Pokémon world is bereft of infrastructure. Paved and unpaved roads, highways, and especially ferry, train and subway systems abound. There’s even a space station and a naval base housing research submarines in Pokémon Ruby and Sapphire. It just so happens that personal automobiles are relatively rare throughout the series, most likely because of the ease of transit that flying Pokémon willingly provide. This lack of cars and fossil fuels contributes to another factor that Pokémon seem to have helped with – environmental friendliness. The usage of Pokémon in many capacities such as power generation and travel has allowed the societies in the Pokémon world to become extraordinarily sustainable by our standards. Nature is abundant in almost every single Pokémon setting that’s been shown, and pollution is nearly unheard of. This is consistent in a world where neighborhood animals can be domesticated and harnessed to perform such a wide variety of useful economic functions. There are even poison-type Pokémon that eat trash as part of their diet, making cleanup even easier! As we’ve discussed on our blog before, nature is incredibly valuable to our societies, but is also very fragile. If Pokémon had existed in our world and helped us develop with such high levels of sustainability throughout history, it’s likely that global warming – one of the major challenges currently facing our generation – would be very mild or even nonexistent. While our world is still struggling to transition to green energy, the world of Pokémon was able to leverage domestic creatures to produce green energy from the start. And, the abundance of energy likely means that energy prices are very cheap. But certain goods in the Pokémon world are anything but… Interpreting Pokémon’s Odd Prices For Consumer Goods Clearly, the Pokémon world gained a myriad of benefits from the titular “pocket monsters” themselves that allowed society to flourish. One would expect the Pokémon economy to be doing quite well, then. But the prices seen throughout the world (especially via the games) often vary greatly compared to our own, and seem to make no sense on first glance. For example, in the original Pokémon games, a single bike costs one million “dollars”! The bike is completely unpurchasable, as the character can only hold up to $999,999 (the English translations call the currency “Pokémon dollars”, but the Japanese originals use yen – here we simply refer to dollars, and use the $ symbol). Other prices seem nonsensical too. Vitamins such as iron, zinc, and calcium are widely available for purchase, but often cost around $10,000. Meanwhile, many other valuable items are priced far cheaper than mundane objects like bikes. For instance, Pokéballs – the items used to catch and house friendly Pokémon – typically cost only $100, and valuables like a “big nugget” of gold typically sell for $10,000, while a high-quality pearl goes for $3,750. But, rather than throw this evidence away as the unrealistic manifestations of a kid’s fantasy world, if we assume that Pokémon prices are rational, we can learn why the Pokémon economy may have reached such a wildly different equilibrium than ours. There are some explanations for why these prices seem so odd, but could be legitimate. First, as cars are rare and Pokémon themselves often available for transport, bicycles may actually be a premium transportation option. Why buy a bike when you can just catch a small bird Pokémon for $100 that can fly you across the city, protect you from wild animals, and also be your favorite pet? Vitamins may be expensive for a different, very important reason: feeding your Pokémon vitamins makes them stronger. In a world where Pokémon are so ubiquitous and useful, items that can make them stronger are likely in high demand, especially because Pokémon themselves are so easy to domesticate. This would massively increase the demand for supplements like vitamins compared to our own world. And, as Econ 101 has taught us, high demand for a limited supply of goods will increase the price. Meanwhile, the ‘low’ prices for what we consider valuables like gold and pearls (only thousands of dollars compared to vitamins’ tens of thousands) can be explained by Pokémon, too. The cat-like Meowth wears a gold coin on its forehead, and has been depicted throwing a seemingly limitless supply of gold coins around. It even learns a battle move called Pay Day, which showers the participants in actual money that can be picked up by the Pokémon trainers, and spent (though this may be a herald of hyperinflation to come…). Similarly, Gholdengo is a Pokémon made of gold that also slings coins around with reckless abandon. What about pearls? Clamperl is a very common bivalve Pokémon that makes one pearl during its lifetime. But in our world, natural pearls are rare – occurring in only one in every 10,000 mollusks naturally. By comparison, the Pokémon world would have a massive supply of natural pearls, since there is a 100% chance for any random clam to supply a pearl at least once (compared to the paltry 0.01% chance in our world). Naturally, this would reduce the price of a high-quality natural pearl compared to our world, and relative to other goods in the Pokémon economy. More money, less problems These conclusions also imply that being rich is a huge advantage in the world of Pokémon; rich people can afford to travel to catch rare Pokémon across the world, perhaps Pokémon like Gholdengo or Meowth who can simply create gold for them whenever they want. And, rich trainers would be able to afford a pharmacy’s worth of supplements to make their Pokémon grow more powerful faster than an average Pokémon trainer would be able to. To that end, it’s worth noting that most of the professional Pokémon trainers shown throughout the series, like gym leaders and Elite Four members, often have no other job than to battle Pokémon and win tournaments. Meanwhile, most “regular” trainers that players in the Pokémon games encounter do have normal jobs – as janitors, chefs, daycare workers, actors, scientists, radio show hosts, and many more. This supports the idea that being rich allows someone the resources and time to “be the very best, like no one ever was”. Despite this advantage, wealth inequality in Pokémon doesn’t appear to be a big issue. This, too, is sensible. In real life, sustaining oneself requires a large expenditure of effort to farm and maintain a home (or, to hunt and gather). In modern society, participating in the labor force by working is necessary to sustain oneself – few people have the expertise needed to leave society, move to the wilderness, and survive on their own (if there was even land available for them to legally do so). But in the Pokémon world, the readily available aid of friendly creatures with (essentially) magical powers makes it much easier for individuals to support themselves. People could easily make a living with their Pokémon helping to support them, and protect them from wild animals. Further, the availability of widespread and free veterinary healthcare (in the form of Pokémon Centers) makes this even easier. Even tiny towns in Pokémon often have free Pokémon Centers. Therefore, wealth itself seems to be less important for Pokémon people than it is for us. In fact, everyone in the Pokémon world – average people, the greatest trainers of all, even schoolchildren – consistently fork over real money to the winner of a Pokémon battle. This is an unspoken norm, and seemingly never a problem for anyone – people simply pay what they can to the winner. This cultural norm can be likened to a form of friendly, low-stakes, buy-in poker. In our world, friends sometimes come together, put a small sum of money into a “pot”, and let the winner take all for a fun game night. But this practice or norm rarely extends beyond a group of trusted friends. The unspoken agreement to have a friendly wager in the Pokémon world for every battle, even between complete strangers, suggests both widespread trust and that wealth itself is simply less valuable for these people than it is for us. Few people seem bothered about losing some cash for the sake of a Pokémon battle, which seems very much like a sport for them. Pokémon Sword and Shield especially depicts Pokémon battles as a nationwide sport, and combatants are always depicted as friendly challengers – certainly more friendly than boxers in a ring. In the Pokémon world, people already have freely accessible transportation, booming economies, easily domesticable magical creatures, and more – so why worry about a bit of loose change? In summary Human society in the Pokémon world benefited greatly from its titular creatures. Their domestication spurred far-reaching and rapid economic growth, developing society to a modern-like level of technology, seemingly without a negative impact on the environment or even a difficult transition period to using green energy. The Pokémon’s abundance and friendliness further led to a prosperous society where people seem to have few needs, and where the creatures themselves – understandably – are a central feature of the culture. While we don’t have Pokémon in our world, we do have domestic animals, many of which are dearly beloved – and many of which carried our early societies on their backs. Remember, we owe a great debt to nature and to our livestock, even if they might not be able to summon rain or fly you to the supermarket. References 1: Highest-grossing media franchises on Wikipedia Header image credit: toxmendoza via Pixabay (Free for use under the Pixabay Content License)
Almost everyone has heard of Pokémon: it’s the highest-grossing media franchise in the world1. The core concept is also familiar to most people – in the Pokémon world, quasi-magical creatures live alongside people in idyllic, family-friendly harmony.
This means that individuals’ inflation expectations changing causes the nominal interest rate to fluctuate in parallel, keeping the real interest rate the same. Roughly speaking, a typical nominal interest rate, for example the interest rate offered by a bank for a loan, will reflect the real interest rate (the cost of borrowing the money), plus any expected changes in inflation. This is because the bank will want to compensate for the anticipated loss in spending power (inflation) of the money it is lending out, when it receives payment back a year later. Alternatively, the Fisher Effect can be stated in terms of actual inflation. In this case, nominal interest rates change to match the real level of inflation. This again means that real interest rates are stable. This case rests on slightly different assumptions, but students may encounter either version and the takeaways are largely the same. The effect is named after American economist Irving Fisher, who first proposed it. The idea of the Fisher Effect is similar to the economic theory of monetary neutrality in that real economic outcomes are said to be unaffected by “nominal” variables (like, in this case, the nominal interest rate). Defining the Fisher Effect again, with math! It’s important to understand the difference between nominal and real interest rates in order to study the Fisher Effect. For more on this difference, see the article on interest rates. The Fisher Effect states that the nominal interest rate is approximately equal to the real interest rate plus the expected future inflation rate. It can be easily described mathematically as follows: i ≈ r + 𝜋e, where i is the nominal interest rate, r is the real interest rate, and 𝜋e is the expected rate of future inflation. It’s important to keep in mind that this equation is only approximate. From this equation, it’s clear to see one of the core concepts of the Fisher Effect: that inflation expectations can change nominal interest rates. This makes sense. If rational economic agents expect high inflation, they will adjust the terms of their financial agreements. For example, a bank will set the conditions for loans while taking into account the (expected) decreased purchasing power of money by the time of repayment. Alternatively, the effect can be expressed as r ≈ i – 𝜋e. This is the same equation rearranged, showing more clearly that the real interest rate is defined by the nominal interest rate and the expected rate of inflation. There is another version of the Fisher Effect that you may encounter that uses inflation directly instead of inflation expectations. To acquire this formula, simply replace 𝜋e from above with 𝜋. In this version of the Fisher Effect, agents in the economy are able to perfectly adjust the nominal interest rate at the same time as inflation changes to achieve the desired real interest rate. Students may come across another, even more advanced formulation of the Fisher Effect as well (this equation is considered more accurate, however it is still an approximation): (1+i) ≈ (1+r) * (1+𝜋) In this formula, the real interest rate r is typically held constant by assumption. This leads to the same result as above, where changes in inflation (𝜋) are mirrored by changes in nominal interest rates (i) to keep the real interest rate (r) steady. Regardless of the specific equation used, the conclusions and implications of the Fisher Effect are the same. The main difference is that the assumptions powering the Fisher Effect are slightly different depending on whether actual or expected inflation is used. Specifically, in order for the Fisher Effect to be true, economic agents must be rational and have enough information to accurately predict (or measure) the rate of inflation. Further, financial markets must be efficient. These assumptions allow the nominal interest rate to mirror the (expected) inflation rate, preventing the real rate of interest from changing. But, if financial markets are inefficient or if economic agents lack information, the resulting frictions will cause the real interest rate to differ from the Fisher Effect equation. Implications of the Fisher Effect There are some important implications of the Effect to explore. First, if people expect a positive rate of inflation, then nominal interest rates will be higher than real interest rates. This means that the cost of borrowing money (which is the real interest rate) will be lower than what’s laid out in contracts (the nominal interest rate), and the benefit from saving or lending money will be lower as well. To see this, consider a scenario where a borrower takes out a $250 loan and must repay $20 one year after taking out the loan (i is 8%), while inflation is 5% over the course of that year. Since the purchasing power of money decreases by 5% over the year, $20 at the beginning of the year can only buy $19 worth of goods by the end of the year, since prices increased. Thus, although the nominal inflation rate (i) was 8%, the real interest rate (r) was only about 3%. You can verify this with the more precise version of the Fisher Effect equation above to find that r is roughly 2.89%. Conversely, if people expect deflation, nominal interest rates will be lower than real rates. This causes the cost of borrowing money to be higher than what’s laid out in contracts, and the benefit from saving or lending to be higher than what’s written as well – if inflation behaves as expected. Keep in mind that these are merely expectations of inflation. Actual “winners” and “losers” don’t emerge until inflation actually occurs. If inflation is higher than expected, the purchasing power of money declines more than expected over the period. This means that borrowers have to pay back less than expected in real terms and they are “winners”, while savers and lenders experience lower returns than expected and are “losers”. Meanwhile, if inflation is lower than expected, the opposite is true. To return to our example above, if the borrower spent their $250 immediately, but six months later there is an unexpected period of intense inflation, such that prices have doubled by the end of the year, the $20 owed would now be worth only $10 in “old money”. In this scenario, the borrower would “win”. The bank would “lose” because the $20 they receive back would be worth less than the $19 they expected and had calculated into the nominal interest rate. For more on winners and losers when inflation differs from expectations, the article on interest rates offers a more involved discussion. The Fisher Effect has important implications for monetary policy, as well. Central banks play a crucial role in setting interest rates through their monetary policies (though they can’t directly control interest rates across the entire economy). The Fisher Effect suggests that central banks must consider inflation’s effect when setting nominal interest rates to target the desired real interest rate. For example, suppose the central bank wishes the real interest rate target to be 5%, and inflation (or inflation expectations) is 2%. Then, the appropriate nominal interest rate to set according to the Fisher Effect equation is about 7%. But, if inflation is -10% (a case of deflation), the appropriate nominal interest rate is actually roughly -5%! Clearly, it seems economically irrational for someone to accept a financial agreement with a negative rate of interest: why should a lender pay a borrower to borrow their money? This illustrates the “zero lower bound” problem that central banks may face when attempting to implement very low interest rates. Evidence for the Fisher Effect in real life If the Fisher Effect held (approximately) true at all times, then central banks could easily manage inflation by changing nominal interest rates. A lower nominal rate would lower inflation, and vice versa. Unfortunately, the Fisher Effect does not always appear to hold in the real world. Over the years, economists have found mixed evidence for the existence of the Fisher Effect. Fredric Mishkin found that the Fisher Effect existed in the long term, but in the short term was negligible1,2. In 2018, Martín Uribe found that the Fisher Effect held true for temporary changes in the nominal interest rate, but when the nominal rate changed permanently, it actually led to inflation; the author dubbed this the “neo-Fisher Effect”3. The fact that there is some limited evidence makes sense. It’s likely that the Fisher Effect mechanism is taken into account by rational economic agents – since they must account for inflation as they make financial agreements. But, we’ve also seen in history how central banks cannot completely control inflation with their monetary policy tools, which include nominal interest rate adjustments – just look at the financial market crash of 2008 that prompted the Great Recession. The mixed evidence for the existence of the Fisher Effect suggests that policymakers should take the effect into account when designing policy, but should not be beholden to it, nor should they expect the economy to always behave as the Fisher Effect equation would predict. Good to Know The Fisher Effect has implications for the market for loanable funds; equilibrium in that market is determined partially by interest rates, after all. According to the Fisher Effect, when inflation expectations rise, the nominal interest rate will rise with it just enough to perfectly offset any effect on real interest rates. Since equilibrium in the loanable funds market is dependent on the real interest rate, if the Fisher Effect holds, changes in inflation expectations and the nominal interest rate have no effect on the market for loanable funds. But if the Fisher Effect does not hold, a change in inflation expectations can affect the market for loanable funds. Suppose that consumers expect inflation to increase in the future, but the nominal interest rate does not adjust to these new expectations quickly. This will cause more people to seek borrowing in the short term, before the expected increase happens, and fewer people to save, despite no change (yet) in the interest rate. That’s because they expect the purchasing power of money to diminish in the future, and can take advantage of this by borrowing money and paying lower-than-expected repayments (in real terms). This causes a rightward shift (increase) in the demand for loanable funds, and disequilibrium in the loanable funds market. Suddenly there is an excess demand for loanable funds, but a lack of supply to give out those funds (since borrowing became less expensive and lenders would reap a lower return). To restore equilibrium, the real interest rate must rise. References 1: Mishkin, F. (1991). Is the Fisher Effect for Real? A Reexamination of the Relationship between Inflation and Interest Rates. https://doi.org/10.3386/w3632 2: Mishkin, F., & Simon, J. (1995). An Empirical Examination of the Fisher Effect in Australia. https://doi.org/10.3386/w5080 3: Uribe, M. (2018). The Neo-Fisher Effect: Econometric Evidence from Empirical and Optimizing Models. https://doi.org/10.3386/w25089
The Fisher Effect in economics refers to the idea that inflation and expected inflation affect nominal interest rates, for example those offered by banks for savers or borrowers. Importantly, it implies that consumers’ inflation expectations are reflected in the nominal interest rate, which prevents the real interest rate from changing.
Macroeconomics and Monetary Economics (JEL E)
Money can take several different forms, both digital and physical. People can decide that any object is a form of money; societies in the past have used stones, seashells, and other objects for this purpose, though nowadays it’s most often paper, metal, or a combination of both. Digital money is becoming increasingly common, too. It’s tracked and stored in computers, accessible via plastic cards or smartphones, and is increasingly becoming preferred over physical money. It’s useful to understand what makes certain choices of money – seashells, for example – better or worse than other options. There are six characteristics that economists have identified that help make a certain material better or worse for use as money. Durability First, money should be durable. It should be easy to preserve and relatively difficult to destroy, or else having money for an extended period of time would be difficult. For this reason, items like ice cream or glass tokens would make for very poor forms of money, because they’re highly likely to be lost or ruined in a relatively short amount of time. Conversely, items like paper, stone, or digital currencies are much more durable and can be safely stored for long periods of time. Portability The primary use of money is to exchange it for goods and services. Therefore, it’s important that money can actually be carried around! Portability is thus important; items like paper and plastic cards are highly portable and make good forms of money. Meanwhile, items like stones or livestock make poor forms of money, since they’re very hard to transport (even though they may be durable or valuable in other ways). Uniformity Money ought to be uniform, that is, units of money (that are the same value) should be the same so that their value is not brought into question. To see this, picture a scenario where it’s agreed that stones are money. It would be hard to determine how much each rock was worth, since they vary greatly in size, shape, and composition. Conversely, paper bills and metal coins of the same value are the same size and shape, so there is no argument about their relative worth. Divisibility It’s helpful to be able to break money down into smaller components to make change. This allows agents in the economy to exchange goods and services for very precise amounts, and reduces transaction costs. Paper and coin money do this well – it’s easy to pay for something that costs exactly $3.47 with these types of money. But if something like stones or seashells were money, it would be very hard to determine where $3.47 worth of a stone was, and even harder to split the rock in just the right way to actually hand the other person $3.47 worth of the stone. Acceptability Money should be widely acceptable so that all economic agents are able to make use of it. This characteristic blends into some of the others, but is worth mentioning on its own. Again, paper and coin money do this quite well. But if peanuts were considered legal tender, some people would be unable to hold onto it or accept it due to their allergic reaction. Similarly, objects that are cumbersome may not be widely acceptable enough to become currency. If camels or shards of broken glass were money, many people may reject them and attempt to find easier forms of money to carry around. Supply-limited It’s important that money has a limited supply in order for it to function properly. If money was infinitely available – say, if blades of grass were considered money – then one unit of money would represent a tiny amount of work, and it would be very difficult to use money to pay workers a fair wage. Consequently, people would have to carry around massive quantities of the stuff in order to conduct even simple transactions – making even blades of grass essentially un-portable. Further, having a limited supply means that people can’t simply grant themselves an unfair bounty of money when they feel like it. The central bank (such as the Federal Reserve in the USA) often manages the money supply to ensure these problems are kept at bay. See the related article Money and the Money Supply for more. Further Reading The reason we use money is simple: it makes conducting transactions in the economy far more convenient, and it can allow us to save. This is aided by three core qualities of money, which directly follow from the six characteristics above. First, money is a convenient store of value. Because it is durable and portable, it’s easy to save. Second, money is a unit of account. Because it is uniform and divisible, it’s easy to tell exactly how much money is in a given amount, and how much exactly a certain item will cost. Finally, all six characteristics mean that money is an effective medium of exchange: it’s easy for people to carry around money and use it for transactions. These three qualities of money, and details on how the money supply works, are discussed further in the article Money and the Money Supply.
Money is both a key concept in economics and something that we use every day. We earn money by performing our jobs, and we use money to buy goods and services and to save for the future. In the modern world, it’s quite difficult to survive without using money.
Corruption Uniquely Alters How Institutions Promote Economic Growth
Welcome to the world of my research, where I explore this intricate relationship between institutional quality and economic growth. My work dives into how institutions shape economic dynamics, focusing on issues like corruption, the impact of the euro, and the role of institutional frameworks in economic convergence. Discovering Corruption’s Effect on Economic Growth When we think about the factors that drive or hinder economic growth, corruption often surfaces as a prime suspect. But how exactly does corruption influence the economic trajectory of a nation? Our recent study (Beyaert, García-Solanes and Lopez-Gomez, 2023) takes a fresh approach to answering this question, using innovative regression tree analysis and advanced econometric techniques to explore the nuanced effects of corruption on growth across 103 countries over the period from 1996 to 2017. Traditional economic growth models, like those developed by Barro and Sala-i-Martin (1992) and Mankiw et al. (1992), have typically treated corruption as a direct drag on growth. However, this study challenges that assumption by suggesting that corruption's impact is more indirect—and complex—than previously thought. Rather than applying a one-size-fits-all model, the researchers utilized regression tree methodology, which allowed them to segment countries into different subgroups based on specific characteristics (or "split variables") and then estimate distinct growth models for each group. The regression tree algorithm was allowed to determine endogenously whether the group divisions should be based on corruption, “Rule of Law”, or a combination of both. In particular, the analysis showed that separating countries into just two primary groups was best: those with high levels of corruption and those with low levels of corruption. This segmentation is crucial as it reveals how the impact of traditional growth factors—like capital accumulation and population growth—varies significantly across these groups. In nations with higher levels of corruption, these traditional growth determinants play a more significant role compared to countries with lower corruption levels. Essentially, corruption seems to exacerbate the influence of these factors, making them more critical in determining economic outcomes. Data for the study were sourced from authoritative references such as the International Country Risk Guide (ICRG) and the World Bank's Worldwide Governance Indicators. These sources provided key variables, including levels of corruption and the quality of the Rule of Law, which are essential for understanding the institutional landscape of each country. To enhance accuracy, we employed the GUIDE (Generalized Unbiased Interaction Detection and Estimation) methodology, which addresses the selection bias issues common in other analytical methods like the CART algorithm. The GUIDE method facilitated a more precise identification of split variables, leading to more reliable and nuanced results. It resulted in two groups, as detailed in Table 1. Table 1. Countries Grouped by Corruption Levels Detected by Regression Tree High Corruption Group Low Corruption Group Algeria, Angola, Argentina, Albania, Armenia, Belarus, Bangladesh, Bolivia, Burkina Faso, Cameroon, China, Rep. Congo, Cote d’Ivoire, Dominican Republic, Egypt, Gabon, Ghana, Guatemala, Guinea-Bissau, Honduras, Indonesia, India, Jamaica, Kenya, Latvia, Mali, Malawi, Mexico, Mozambique, Niger, Nigeria, Pakistan, Papua New Guinea, Panama, Paraguay, Philippines, Russia, Sierra Leone, Togo, Thailand, Tunisia, Turkey, Uganda, Ukrania, Zimbabwe Australia, Austria, Bahrain, Belgium, Botswana, Brazil, Bulgaria, Canada, Chile, Colombia, Costa Rica, Croatia, Czech Republic, Denmark, Estonia, Ecuador, El Salvador, Finland, France, Gambia, Germany, Greece, Hong Kong, Hungary, Iceland, Ireland, Israel, Italy, Japan, Jordan, Korea, Rep., Kuwait, Lithuania, Luxembourg, Malaysia, Madagascar, Morocco, Namibia, Netherlands, Nicaragua, New Zealand, Norway, Peru, Poland, Portugal, Romania, Singapore, Senegal, Slovak Republic, Slovenia, Spain, Sri Lanka, Sweden, Switzerland, United Kingdom, United States, Uruguay, Zambia Source: https://doi.org/10.1108/AEA-11-2021-0297. Copyright © 2022, Arielle Beyaert, José García-Solanes and Laura Lopez-Gomez. Published in Applied Economic Analysis. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Subsequently, after dividing the sample into these two subgroups, a traditional cross-sectional Solow model was estimated, incorporating standard drivers such as investment, initial GDP per capita, and population growth. To ensure the robustness of these findings, the researchers utilized instrumental variable estimations, drawing on the methodology of Gründler and Potrafke (2019) to refine and enhance the instruments employed. This advanced econometric technique addresses the issue of endogeneity—a common challenge in growth studies—by ensuring that the identified relationships are truly causal rather than merely correlational. By improving the instruments and applying them within each identified subgroup, the study provides a more reliable estimation of the growth models. One of the study's key revelations is that corruption does not have a statistically significant direct effect on economic growth in either the most corrupt or least corrupt countries. Instead, its influence is more subtle, indirectly altering how traditional growth determinants operate; the algorithm revealed growth parameter differences between countries, showing that those with higher levels of corruption were farther away from reaching an economic steady state. These findings resonate with the work of Durlauf et al. (2001), which identifies parameter heterogeneity in the Solow model, suggesting that corruption contributes significantly to this variability. The evidence points to a clear pattern: the more corrupt a country, the more pronounced the effect of growth determinants. This means that corrupt countries are generally further from their economic steady state, and thus, experience a stronger impact from factors like investment. Interestingly, the study also highlights a developmental divide: more developed nations typically exhibit lower corruption levels, while less developed countries struggle with higher corruption. This finding emphasizes the dual challenge facing developing nations—not only must they fight corruption, but they must also focus on enhancing investment and managing population growth effectively. Geographically, the analysis identifies three major regions: Europe and North America, with low corruption; Africa and Latin America, characterized by higher corruption levels often linked to their colonial histories; and Asia, marked by significant corruption variability. Notably, China and Russia, despite both being part of the high corruption group, exhibit divergent growth trajectories. Russia’s corruption has been a drag on its growth, while China has managed to sustain rapid growth rates despite similar corruption levels. The difference is attributed to the more organized nature of corruption in China compared to Russia. In conclusion, this study urges policymakers and economists to reconsider how they model and address the effects of corruption on economic growth. It’s important for policymakers to recognize that improving institutional quality can help lower corruption. By recognizing that corruption's impact is largely indirect and varies significantly across different contexts, and by employing more sophisticated econometric techniques like improved instrumental variables, more tailored and effective strategies can be developed to foster economic development, especially in countries where corruption remains a significant hurdle. Regional Case Study: How the Eurozone Navigates Corruption and Institutional Quality While global discussions often focus on the broad impacts of economic integration, it’s essential to zoom in on specific regions to truly understand these effects. Shifting the lens to the Eurozone, my research delves into the influence of the euro on corruption control within this unique economic area. Using a counterfactual analysis based on the methodology of Abadie, Diamond, and Hainmüller (2015) and conducted by Beyaert, García-Solanes, and Lopez-Gomez (2023), we explored the hypothetical scenario of a Eurozone without the euro. Surprisingly, the findings suggest that the introduction of the euro has not worsened corruption control in southern Eurozone countries. Instead, economic integration and standardized practices seem to have a stabilizing effect on corruption levels. Still, the Eurozone has not achieved institutional convergence, as highlighted by Beyaert, García-Solanes, and Lopez-Gomez (2019) and García-Solanes, Beyaert, and Lopez-Gomez (2021). There are notable asymmetries in institutional quality among member states, creating macroeconomic imbalances, economic frictions, and inefficiencies, which potentially reduce the Eurozone's overall GDP (García-Solanes et al., 2023). This underscores the need for more uniform institutional standards to address these disparities. My research delves further into this economic convergence within the Eurozone. Using Phillips and Sul (2007, 2009) tests and a logit model, my findings suggest that successful economic convergence heavily depends on strong normative and judicial frameworks (Lopez-Gomez, forthcoming 2024). Countries with robust governance and legal systems tend to converge more effectively, while those with weaker institutions face persistent economic gaps. Finally, an analysis of income per capita and corruption control using panel Granger causality and cointegration tests (Lopez-Gomez, 2023) reveals no bidirectional causal relationship between economic growth and improved corruption control. The Great Recession further weakened this relationship, especially post-2008, with notable exceptions in Eastern Eurozone countries. Taken as a whole, the results of my research indicate that anti-corruption measures need to be tailored to the specific institutional contexts of each country, as a one-size-fits-all approach is unlikely to be effective. The Broader Implications Looking at the broader picture, my research consistently highlights one key theme: institutions are more than just background structures, they are pivotal in shaping economic behavior and outcomes. It’s a complex but crucial relationship, and unraveling how institutions interact with broader economic dynamics is essential for crafting effective solutions. Understanding these interconnections is key to developing policies that not only address immediate issues but also foster long-term stability and growth. So, where does this leave us? The future of economic growth and development hinges on our ability to enhance institutional quality. This means not just fighting corruption or reforming legal systems, but fostering environments where effective governance can flourish. The journey ahead is filled with challenges, but also immense opportunities. As we continue to piece together the puzzle of economic growth, one thing is clear: the role of institutions cannot be overstated. They are the hidden gears that drive economic performance. Thanks for joining me on this exploration of how institutions and economic growth intersect. It’s a journey through models, data, and analysis, driven by a passion for understanding and improving our economic systems. Here’s to the ongoing quest to piecing together the puzzle of economic growth! References Abadie, A., Diamond, A., and Hainmueller, J. (2015). Comparative politics and the synthetic control method. American Journal of Political Science, 59(2), 495-510. Beyaert A., García-Solanes J., Lopez-Gomez L. (2019). Do institutions of the euro area converge?, Economic Systems, 43(3-4), 100720. Beyaert A., García-Solanes J., Lopez-Gomez L. (2023). Corruption, quality of institutions and growth. Applied Economic Analysis. https://doi.org/10.1108/AEA-11-2021-0297 Beyaert A., García-Solanes J., Lopez-Gomez L. (2023). Did the euro really increase corruption in the eurozone?, Hacienda Pública Española-Review of Publics Economics, 3-36. García-Solanes. J, Beyaert, A and Lopez-Gomez, L. (2021). Clubes de convergencia en la zona del Euro, Papeles de Economía Española. García-Solanes. J, Beyaert, A and Lopez-Gomez, L. (2023).Convergence in Formal and Informal Institutions and Long-Run Economic Performance in the Euro Area. The Routledge Handbook of Comparative Economics Systems, 256. Lopez-Gomez, L. (2023). On the relationship between income and control of corruption in the Eurozone. The European Journal of Comparative Economics, 20 (1), 3-37. http://dx.doi.org/10.25428/1824-2979/020 Lopez-Gomez, L. (2024). The role of political institutions on the economic convergence process. Journal of institutional economics. Forthcoming. Phillips, P. C., and Sul, D. (2007). Transition modeling and econometric convergence tests. Econometrica, 75(6), 1771-1855. Phillips, P. C., and Sul, D. (2009). Economic transition and growth. Journal of applied econometrics, 24(7), 1153-1185. Header image credit: Aideon via Pixabay (Free for use under the Pixabay Content License)
Imagine this: you're trying to solve a complex puzzle where every piece represents a different facet of economic performance. Now, imagine that the shape of some of these pieces are influenced by the quality of the institutions in place—things like governance, legal frameworks, and anti-corruption measures. As it turns out, the fit of these pieces can make or break the overall picture of economic growth. Institutions, in this sense, are not just background players; they are fundamental to how the economic puzzle comes together.
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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