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Patrick Rooney

I found this article extremely interesting, particularly, because Krugman ridiculed the analysis and thought processes of huge names in the Developmental Economics field. I’m not sure if this perspective just comes from the ignorance of an undergraduate economics major, but I’ve always perceived economists who publish literature as extremely smart and possessing valuable conclusions from their own research. It was surprising for me to see that PhD economists are fallible like the rest of us. I thought Krugman was very persuasive when he spoke on going back to the roots of why models are made in the first place, and how developmental economists lost this idea of the elementary usage of models. Krugman emphasizes that models are untrue simplifications used to provide insight on a vastly more complex system or problem. In physical sciences, models with this objective are lauded such as Fultz with his dishpan full of water to examine weather patterns, but in social sciences, like economics, this is far less common. This paper is unique as it criticizes economists for overthinking and doing too much, when often in economics classes it feels like there is always one more variable or a more sophisticated model that will help us solve the problem at hand. It’s fascinating that for the progression of an entire discipline of economics, it was necessary to move backwards to more rudimentary ideas to better understand a more complex problem. Moving forward, I am interested in the following questions: What has been the natural progression of ideas and models in other economic disciplines (surely no discipline is linear in its progression)? How have the lessons from this rise and fall of developmental economics influenced research in other social sciences?

El Ellenz

Krugman makes some valuable points about how models can help us to understand pieces of an infinitely more complex world. This paper certainly made me reflect on my own views about the models we use in our theory courses, which have often tended toward the dismissive once I understood the assumptions you had to make when using them. One line that I returned to after finishing the article was when Krugman argued that certain people dislike models because their “convictions are essentially driven by values rather than analysis.” It took me a little while to realize what had made that sentence stand out to me: the separation of values from analysis, as if the two are discrete entities that never touch. As if analysis itself doesn’t proceed from the values of the analyzer and the analyzer’s society, as if scholarship (particularly economic scholarship) can really be value free. Krugman appears to frame the creation and use of models as objective, which doesn’t quite make sense to me. The creation of a model, even the choice among existing models, seems to me a task that interacts with the values of the analyzer as they chose which factors to include, which to leave out, which simplifying assumptions are acceptable and which are not. None of this is to say that I don’t think Krugman is absolutely right when he argues that formalized models can make valuable contributions to our understanding, but I do think he may be too quick to present the formalized economic model as an objective and value free tool of analysis as opposed to his portrayal of less formalized and/or more interdisciplinary approaches as "an intellectual dead end."

Eric Bazile

A friend and I recently discussed whether economics should be considered a part of STEM. After reading this article, I feel more supportive of economics being considered in STEM.

I feel that a big component of economics not being considered science is that people do not know what economics is. However, economics is a multifaceted subject that can be looked at from many perspectives just as any other science can be. Many people outside of economics generalize it to simply money and where it ends up. However, numerous economists debunk this. Amartya Sen, a very prestigious economist (I have read his work in numerous classes), argues that economics is about autonomy, capabilities, and functions.

Many people associate science with experiments. And in a lot of cases, it is unethical to conduct an economic experiment, especially in lower-income countries. However, another way phenomena are analyzed is through observational studies. Instead of controlling variables as one would do in an experiment, an observational study requires researchers to observe natural phenomena and compare them. This method is mainly used when studying economic development. Countries like South Korea were not given advantages so observers could experiment, but developed naturally through policy advancements, and researchers notice this and speculate whether this could work for other countries.

Another reason that economics is often not looked upon as science is that people in the sciences are pretentious. Science to some STEM folk is required to be difficult for some reason. The term “STEM” carries weight in society, with many feeling that all intelligent people are concentrated in the traditional STEM fields. This is problematic because economics shares many characteristics with any other sciences, as proven by this article. However, many people still in disagreeing whether it should be considered science.

If you are convinced to see economics as a science, then I would also like to convince you to regard economics, specifically development economics, as the most important science, simply because people matter. Wealth gaps in countries are diverging and individuals are being denied access to not only necessities but also a consideration as a human with dignity. Poverty is a pandemic plaguing the whole world, and the cure is not as simple as a vaccine created by a biologist in a lab. The remedy requires an advanced balance of intellect which the most astute scientists must collaborate upon.

Sarah Wittpenn

I thought that this articles exploration of the fall and rise of development economics throughout history along with the changing thought processes around modernization was really interesting. In my mind, it makes sense that economists struggled with getting their ideas heard and considered seriously as a result of their inability to express the ideas in such tightly specified models. Despite this, I could imagine strong, breakthrough ideas frequently being overlooked and tossed aside prematurely because of economists inability to model. I think that while this is problem and unfortunate for economists and anyone with strong ideas, our world is completely based on evidence and data. People struggle to see truth and reality in ideas and statements without concrete evidence. While modeling may have been considered "mainstream" economics, I do think that it is necessary to back up ideas. I also thinks it helps people understand and see the whole idea instead of just comprehending a part of it. Though it could be viewed as a constraint, based on people's resources and available techniques, I think that models help succeed in "rationalizing some of what you see in the world in a way that you might not have expected."

Another part of the article I found interesting was the discussion of ignorance and simplification with models. As I mentioned earlier, I don't think there are alternatives to models. However, when economists understand how to simplify their models to express their ideas, they can get the system down to something manageable. As long as there is understanding and self awareness about the simplification, they can be used and shared. I agree with Krugman about how "it is important not to let ideas slip by just because they haven't been formulated your way." I think this temporary ignorance is necessary if economists ever want there to be progress and is important to avoid dismissing ideas that could be transformative and revolutionary but just can't be perfectly modeled.

I also thought the idea that people did not want to confront new areas and new ideas as they developed interesting. I see this with myself and in the status quo bias, but I wonder if other fields encounter the same issues of resistance around technological breakthroughs or modernization.

Tyler Waldman

Upon reading this article, I kept coming back to the same question: how does the movement of economics in a formalized, mathematical direction affect potential economists that are not inclined toward math? I agree with the author that formalization may be the best strategy to develop the field of economics in the long run. The ability to predict the effects of various actions is the key contribution of economics in many fields. However, the “high development theory” that Krugman says will lead toward professional exile may be the key to solving some of the world’s greatest issues. When we aren’t thinking about the world in an innovative way, formal models won’t lead in the best direction. The key issue with this line of this is directly voiced by Krugman in the paper. He asks those with lofty goals and a lack of motivation to formalize their ideas if “... you [are] sure that you really have such deep insights that you are better off turning your back on the cumulative discourse among generally intelligent people that is modern economics?” My response to that question would be those with those deep insights may have already left the field due to its heavy focus on formalization. There is balance in every discipline, and the field of economics is incredible because of its unique place between hard sciences and humanities. I think that straying too far one way will always have advantages and disadvantages, and weighing them is crucial for the future of the field.

Will Kistler

I thoroughly enjoyed reading Krugman’s paper on the fall and rise of development economics and the utility of formal modeling. The introduction of high development theory to the intellectual world was nothing short of a tragedy–not to mention greatly ironic. This slump in the history of economics goes to show the fallacies in human thinking among even some of the greatest intellectual minds of their time. In reading Krugman’s statements on the true value of models I was very impressed. Being that people often generalize economics as the circulation of money or other resources in simple models that display their scarcity, it was fascinating to hear Krugman pull apart the actual applications of formal models. As stated by Krugman, “The sophisticated thing to do is not to pretend to stop, but to be self-conscious -- to be aware that your models are maps rather than reality.” This idea of models functioning as more of a roadmap or oversimplification of a complex system is one that I believe is often disregarded.

In the end, economic modeling is not the end-all answer to a real-world issue, but rather “an improved insight into why the vastly more complex real system behaves the way it does”. The lessons that can be taken from the decay of development theory are plentiful. Obviously, there is almost no problem in the world that can be boiled down to a simple model of supply and demand; however, these same foolishly oversimplified models can help economists gain tremendous insight into complex issues. I believe that economists should be wary as to not make the same mistake twice in letting a radically impactful economic theory sit on the shelf for decades without any implication.

Sherman Golden

I found this paper quite interesting because I find the concept of linkages fascinating. I took Professor Alvarez's Latin American Economics course last year, and we focused on linkages in the context of institutions, commodities, and industry within many Latin American economies. I feel that I have a fairly firm grasp on backward linkages, for example, if a firm that produces mostly commodities (agriculture) is able to do so efficiently enough to produce a surplus, it will rely on downstream firms to process its products, and transport or export the final goods. This makes sense, from a tory telling sort of perspective and is fairly easy to follow. On the other hand, forward linkages have never made sense to me. When I read the section regarding linkages, I gained vary little clarity. I think this says something about the greater story of developmental economics. Theories are great, but what's the point if they aren't understandable or practical? Should the field be more focused on producing theories or measuring the actual outcomes in the real world? How realistic is the current trajectory of developmental economics?

Will Fearey

I find the most intriguing portion of Krugman’s article to be the discussion about how simplified models can be a critical tool in helping us understand complex concepts. His examples of Fultz’s dish-pan and folk cloud wisdom made me realize that I have been studying many simplified models for my entire life. For example, in analyzing the various creeks and rivers that ran through my high school, I was not learning about one body of water, but many. Studying what animals and sediments exist in these habitats taught me not necessarily what is in others, but what there may be and what to expect in separate locations. A more relevant example is that of the supply and demand graphs that were taught both in my high school and college economics related courses. If it were not for these simplified models, my understanding of how the economy actually reacts to external forces would be far worse. While the graphs do not perfectly predict how markets perform, they help us tremendously in making predictions as to how they might. The idea that simple models, while they may not be able to show the full picture, can still have a practical use and give us information about basic concepts is integral to our understanding of how the world functions. In addition, the article discusses how some people do not like relying upon models for social sciences. My thought here is that since people rely upon economics for their daily finances, it is understandable why they do not want their livelihoods to rely upon approximations. However, I still believe that these models benefit us more than they hurt us in these areas of social sciences since they enable us to take action based upon educated predictions and past model examples.

Jack Lewis

I enjoyed reading this article and particularly seeing the different stages of economic development such as the big push being discussed. Additionally, I enjoyed the section where the author discusses economic models. When choosing economics to be my major I really tried to think about what exactly is economics and what am I studying? Yes, graphs, analysis, and numbers are involved, but there is another aspect that the article touches on that makes economics unique. The theoretical part of the subject is seen everywhere, such as economists theorizing about what can explain greater flooding in a nearby city and so much more. Economists try to explain association through models, but how can we know how good a model is? The article has a great quote in it stating "It will never be right in the way that quantum electrodynamics is right. At a certain point you may be good enough at predicting that your results can be put to repeated practical use, like the giant weather-forecasting models that run on today's supercomputers; in that case predictive success can be measured in terms of dollars and cents, and the improvement of models becomes a quantifiable matter." Repetition for accuracy of a model is likely the best strategy for testing but it will never be as clear-cut as math, or physics. As we advance in the class and in the field of economics, I will be intrigued to see if there will be development in how models are judged to be good.

Natalie McCaffery

I found this article a bit frustrating because I prefer there to be a 'right' answer in modeling and science. This mathematical approach gives me, alike many others, certainty and platforms to build off of. Nevertheless, I understand Krugman's argument that a model is just what we see as important about a concept at a time in the most simplified manner. This made me think about the convergence of economics and psychology and how if leaders are able to influence what is deemed important at a time, they can base models for growth off of that importance. This highlights the ignorance engrained in human nature, proving the inability to ever be 100% accurate in a model reliant on people. This goes back to the 'if' statements we spoke of in class, where capital was to be distributed back to the state earned, jobs are 100% guaranteed, and there is 0 opportunity loss. IF constants are held, we can develop models. Thinking about health and food access, hypothetically, the model could be derived backwards so that the 'ifs' necessary to build it out are met by the population before the model is introduced. What might be the 'ifs' of the UN's SDGs? Have they been met?

Ian Kinney

I thought that Krugman raised a number of interesting points in the article about the path development economics has taken over the last number of decades. I particularly liked his aside about the way European maps of Africa changed over time, noting that as standards grew more stringent, much that used to be included on maps was left off. This made me wonder about whether similar phenomena occur in other fields, or even elsewhere within economics.

Krugman writes of development economics spending a period of time out in the wilderness before being drawn back into the mainstream. I wonder, as economics has moved in the direction of mathematical models, how much knowledge has been lost that is yet to make such a return. Even if a theory lacks a model, it may have some value it can offer to those of us seeking to better understand economics. That being said, I agree with Krugman’s approach; he clearly has respect for Hirschman and those who agreed with him, while noting that it is worth sacrificing some complexity if it means developing models that can keep ideas of development economics from being marginalized.

Ryan Messick

What stood out to me about this article was the line, ’Broad insights that are not expressed in model form may temporarily attract attention and even win converts, but they do not endure unless codified in a reproducible -- and teachable -- form’. We tend to categorize and model successes and failures to ascertain a subjective truth about any given state of the world with hopes that it will help justifiably prove or disprove any given entities beliefs and actions, and we build models assuming that communities will behave in a way that aligns with whatever model we have built. As a result, developed countries will try to reciprocate their own successes using these models (whether explicitly or implicitly) and will oftentimes find shortcomings in success. I think this is a testament to Krugman’s later argument about how people claim to transcend the limitations of models to little success, as people tend to neglect the true reason why models fail: people do not base their decisions off of a classified behavior, but rather on an individual basis that can be influenced if convinced. Therefore, while models can serve as a basis for ideas, conceiving ideas for bettering the livelihoods of underdeveloped communities requires a much more specific and open-minded approach.

Josh Fingerhut

I think this is sage advice. Basic models often assume certain truths about humanity. Many assume homo economicus, that humans are rational, economic decision makers. In turning to psychology, economists can see how instead, humans have somewhat predictable biases. Furthermore, while it isn’t necessarily the job of the economist to prescribe and implement policy, insights from the study of government/politics might allow economists insight into what will be done with their research. As economics is really a way of understanding the world, I agree with Krugman that it is crucial to reach outside of the formal field for insight. Still, economists should not shy away from simplicity within their own field, as a basic model can always be expanded to power more complex situations.

Josh Fingerhut

*Sorry my whole post did not copy above

While this article is definitely relevant to the history and content of our course, my main takeaway from the article is a core paradox of the field of economics. The field of economics seeks to explain decision making in a scarce world. Our world is infinitely complex, yet many of the most powerful tools in economics turn out to be incredibly simple. In many cases, these simple models prove far more powerful than more complex theories that may have come before them. This is the story that Krugman paints with development economics. Favor for rich and complex theories precluded academics from stopping and considering simple models such as "the big push". Krugman urges those who want to turn their backs to simple models to stop and think. But his advice doesn’t end there. Krugman also encourages those inclined to use basic models to look for insight in other areas outside of economics.

I think this is sage advice. Basic models often assume certain truths about humanity. Many assume homo economicus, that humans are rational, economic decision makers. In turning to psychology, economists can see how instead, humans have somewhat predictable biases. Furthermore, while it isn’t necessarily the job of the economist to prescribe and implement policy, insights from the study of government/politics might allow economists insight into what will be done with their research. As economics is really a way of understanding the world, I agree with Krugman that it is crucial to reach outside of the formal field for insight. Still, economists should not shy away from simplicity within their own field, as a basic model can always be expanded to power more complex situations.

Gabe Miller

Krugman's justification of models and brief history about how models were created in the development economics space both explained the importance of models and gave me questions about what information we might actually be losing by purely relying on modeling in economics. Models allow economists to justify and develop scientific theories which explain phenomena, predict future outcomes, and assist policy makers. Krugman went into detail about the importance of different assumptions in models; particularly, how accurate development models could not be created for some time because economists were unsure how to model economies which were neither assumed to be perfectly competitive or perfect monopolies. Krugman also explained that while models provide value, there is loss as well. His example is how mapping Africa led many to view the continent as barren and empty.

Modeling is essential in economics, but I think it is still important for policy makers and others to also rely on what Krugman calls discursive analysis. When it comes to applying economic theory in the real world, it is important for a policy maker to understand how the people of their country will react to a given economic policy- that effect is not necessarily represented by any model or the economic assumption of rational behavior. A non-economic example of irrational behavior is militiamen in Africa attacking doctors trying to treat patients with Ebola. Another example is the tendency of some people to spend significant portions of their income on tobacco or alcohol. The success of an economic policy is as contingent on local culture and customs- discursive data- as numerical data.

An example of an economic policy which factored human behavior into its equation is China's economic revitalization, which has been discussed in class. China adopted a policy based off of the Lewis 2 Sector model, and enforced it through strictly controlling the migration habits of farmers and others. Chinas strict control of its citizens enforced rational behavior- the Chinese government knew exactly how people would react to their policies because the policies forced people to act in a certain way. I would hope there are other ways to factor in human behavior to a policy that don't involve so much government control. Nonetheless, China is a great example of a government accounting for human behavior when drafting policy.

Trip Wright

To no surprise, Krugman is an eloquent and smart writer——the man has his own opinion column in the New York Times. While reading this piece, I could help but feel a sense of frustration towards what could've been mainstream "high development theory" today. To think that the economics profession digressed from pursuing an emergent——and extremely important——field of economics due to an "unwillingness to confront those areas the new technical rigor could not yet reach" is absurd! Fortunately, the discipline has not continued to trend this way, otherwise, we may be still trying to figure out the opportunity cost between "guns" and "butter." I kid. Nonetheless, it is "tragic," as Krugman puts it, to witness Hirschman's methodology not emerge as a leading sub-discipline within economics due to the assumption of economies of scale proving "too complex" for Samuelson's neo-Keynesian economics.

I am not criticizing the "model," and I believe Krugman does a sound job of explaining the many benefits it serves within economics (and all sciences) today. In fact, much good came out of neo-Keynesianism like the modern "Principles of Economics" textbook that serves to teach thousands of students annually; however, its time for a bit of an update to such texts——Samuelson would agree——but that's a discussion for later. Models help make the complex world we live in more approachable and digestible while serving as the building blocks by which each of us began to understand the disciple of economics. Yet, it is disheartening to discover today that the focus on formal, simple models led to the demise of a promising field. Had "high development theory" been lauded for its complexity——like so many new economic theories today——the growth and development of nations on Earth could have had more promising outcomes. This is all to say that "might" have occurred: or "it depends," Dr. Casey's greatest and truly most appropriate answer. At the end of the day, a model is only good "if it succeeds in explaining or rationalizing some of what you see in the world" in an unexpected way. Let's not make the same mistake with the next theory from left-field.

Kit Lombard

This article was very interesting in revealing an almost secret theory of economics that was overlooked because the theorist, Hirschman, did not make a model or equation. I was stumped in two ways, at first I wondered if it was justified to disregard Hirschman's theory because of his lack of models, but then also, I questioned why he did not come up with them. After all, Hirschman was a gifted individual and I would imagine he could have had other economists or students work with him to create a model or mathematical representation of his theory.

Models are useful to break down a theory, but this article poses the question of whether their existence is necessary for a theory’s existence to be justified. Even a model itself can be utilized in multiple ways to fit the agenda of the user. For example, in Social Issues with Professor Goldsmith, Professor Goldsmith noted the Federal Reserve’s push to reduce inflation through interest rates and his personal opinion feeling this is not the best route. Both the head of the Federal Reserve and Professor Goldsmith are experts in the field of economics and although there are graphs about inflation and interest rates, they have two opposing views. When this article states the impact Hirschman’s high development theory could have on economics, it makes me question the requirement for economic theory to always have a theory, at that exact moment. The theory could still have been brought up in discussions and then over time a model and equation could have been naturally formulated. This article just brings up the question again as to who gets to decide the theories and rules being played out in a field of study. Is it anyone passionate in the field or those who want to remain in power? Are there other theories that had the potential to contribute to the field but were overlooked due to a graph?

Kyle Lutz

Much of what I want to say about this article is in line with what Ian and Josh have already said. I enjoyed reading about the history of high development economics and I find it fascinating that it was pushed out of mainstream economics because it could not yet be defined as a formal model. I must say, a lot of this article I found confusing and took me a good bit of time to process a lot of it. Specifically, the idea of forward and backward linkages, I hope we can discuss in class tomorrow. With that aside, I do find the ideas of "development is a virtuous cycle driven by external economies," "modernization breeds modernization," and the fact that massive amounts of investment are needed for economic development in opposition to the "balanced growth school" very persuasive and concepts I would like to dive into deeper.

Jack Calihan

I felt this reading highlighted the limitation of modeling in economics. During the 1940s and 1950s, ‘high development theory’ flourished. The concept emphasized that large scale modernization can be self-sustaining, but it is also easy for countries to get caught in a low level trap. It argues that certain policies, along with the ability to bring workers from unemployment/low level agricultural employment into factory jobs, can help prevent the low-level trap. However, the leaders of the ‘high development’ movement clashed with their economic colleagues pushing for more ‘teachable’ mathematical/economic modeling. As a result, the field of ‘high development economics’ grew stagnant for decades until Murphy et. al presented the Big Push idea, rooted in a sensible and simple model.

One question I had regarding this reading pertained to the description of backward and forward linkages. I hope that we can discuss these concepts further in class.

Cal Christianson

To me, the biggest takeaway from this piece comes from the conclusion. Krugman states that “ Good ideas were left to gather dust in the economics attic for more than a generation”. This seems like a very apt description, not just for the field of development economics, but for all disciplines. It is very hard for new ideas to break into the mainstream. Too often the established theories of the time hold little room for new ideas. In this specific instance, it is almost sad to imagine where the world could be if new ideas had been adopted in a timely manner. Would the world have needed the Millennium Development Goals? Would we need the SDGs? Or would the world be the same as it is now? Unfortunately, we will never know. I did like how Krugman admitted that while no one knows whether a model heavy approach or a metaphor heavy approach will produce better results, the answer lies somewhere in the middle. Nothing but continuous trial and error and free flow of ideas will allow progress in the field. It is important not to discredit an idea just based off of the methods used.

Chadrack Bantange

This paper on the fall and rise of economic development is among the most interesting economic articles I have read so far. It gives good insights into why economics relies on assumptions to come up with models that somehow explain what happens in real-life situations. Most importantly, I learned that economics models are not meant to capture all variables that might influence an outcome we are interested in, but rather a simplified way to understand what happens in reality. What I would have liked to get out of the article was how the difficulties involved in coming up with a "perfect" economic model tie back to the idea of development. For example, policy A might be successful at alleviating poverty in country B while it does not have the same effects in country C. So if this is the case, does it suggest that economic theories should not be a set of generalized principles that are true all around the world or they should be country-specific?

Andrew Arnold

I think this article is really interesting for a couple of reasons. For one reason, I think the logic of the argument can be applied to economics as a whole. When these models are created, they are very simplified versions of complicated realities. From humans acting in different ways, to global interaction, I feel like development economics is even more complicated to model because of how large the international economy is. I think anyone could poke holes in a given model because they always have to be simple. All this just to say that I do think it is important to keep our minds grounded in reality when we use these models and theories. It feels like to me that there has to be a balance between practicality and theory.

Another reason I think this article is interesting is because development economics is individualized to a given country with a different situation. I think it's really hard to make a one sized fits all model for low income countries. For instance, the industry of a land locked country would be entirely different than a coastal country. I think this article is really grounding as we go through this semester and attempt to analyze case studies with data and models.

Renan Silva

I thought it was very interesting the comparison the author makes between the map-making development in the African continent and economics. It was shocking to learn how over the decades important details of Africa’s landscape were removed from maps for being considered as non-valid data. This analogy is very helpful in order to understand the fall of high development theory over time.

The topic of methodology and its implications on the development of economics also caught my attention. Economists like Albert Hirschman and Paul Rosenstein-Rodan tackled the complexity of the unknown when coming up with these theories, and successfully presenting them to the public was nowhere near an easy task. The paper concisely explains factors on the decay of high development theory in the mid-20th century, and raises questions at the end that I also thought of as I read the paper: what could development economics be nowadays if the high development theory was given more attention at the time of its origin?

Chris Ruiz

I found this paper to be a bit of a bore, a whole lot of words only to arrive at the conclusion that it is important to embrace silliness. I do think that is a great message though. One of my economics professors here implored to our class that economics is a perfect science, and he has a PhD in the subject so I will not disagree with him. However, I do think it is of note that economists create these simple, perfect models to represent very complex and seemingly imperfect things and processes (i.e. humans and the societies we have created). Obviously it would be tremendously difficult to model to 100% accuracy with all the nuance and unexpected possibilities that could disrupt the exactitude of a concept or process explained by a model. As such, it is important to recognize and correctly perceive the significance of models in the field of economics. Models make complicated ideas easier to understand through the employment of a visual aid and mathematical formulas. Beyond this, another point in this paper that I thought was valuable was the importance of reconsidering things that we may initially dismiss. The ability to admit that we are wrong and opening our minds to different, perhaps better ways of looking at and understanding things. As for what other people are saying in this thread, I do not know if I would categorize economics under the STEM umbrella. While it certainly contains elements of science and math, people and governments and businesses are at the core of what economics deals with. It is definitely not a natural science, so unless we want to qualify all social sciences as STEM subjects, I think it is okay to stick with the separate social science identity tied to economics and refrain from advocating for it as a part of STEM.

Tyler Smith

This article gives really good insight into the history of development economics and the role of models within the discipline. To begin, the analogy to African mapmaking struck me as being an underappreciated aspect of economic theory. The article mentions that as technology and general mapping abilities improved over the course of a few centuries, the details that were considered important to include on the map of Africa evolved. Coastline details such as general geography, rivers, and cities were mapped with extreme accuracy, but at the expense of the internal mapping of the continent. Because the internal mapping details were provided by unreliable informants, the space became empty, which actually led to a decreased understanding of the area. In the same manner, as we raise our standards of what is considered "valid" information and technique in economic theory, we also reevaluate previous assumptions and theories that were previously considered true, which can lead to periods of reduced knowledge or understanding until we are able to fully comprehend the nuance. Although important, I find this to be frustrating. The article mentions that increases in the standards of rigor led to an "unwillingness to confront those new areas the new technical rigor could not reach." Of course, it is easy for me to sit as an undergrad student and demand further exploration into complicated economic theory, but at the same time I feel like these theories are a lot more essential and/or accessible than 18th century map making.

I also particularly enjoyed the article's discussion about models. Indeed models can be an economist's best and most loyal companion, but most models are also a drastic oversimplification of an overwhelmingly complex social issue. The question, "how do I know if my model is a good one?" is a key distinction and yet remains, for the most part, completely unanswerable. Perhaps this is why development economics was pushed out of mainstream economics. The inability to formalize development economics into a stable, simplified model is unlike other economic disciplines. I do find the wording of economists reaching into their "bag of tricks" to make models to be somewhat comical, but it also makes me question again why there was such a long delay in the development of development theory. If such basic assumptions could be made in order to create a rigorous development theory model, why could we not create a model decades ago?

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