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Andrew Harris

I am intrigued by the idea that models are meant to be so simple that they leave out many commonly held or seemingly obvious beliefs, but that eventually the models will become so studied and rigorous that they will come back to those same ideas. The author defends this point well with a few examples. While the model of the Big Push is almost too simple in that it only focuses on labor, it provides a convincing basis for the overall idea. It is impressive that the model that the author provides could be taught in a middle school classroom but was created by someone with a PhD. Expressing complex ideas so simply and so bare bones is difficult. I am curious if any progress has been made on modeling the complex ideas behind economies of scale. I would be more convinced by a model that can incorporate capital at the very least, but at the time of writing an accepted model was clearly not available to the author. I wonder if world leaders and others responsible for economic policy are only satisfied by models or are satisfied by the intuition behind the Big Push and other economic theory. I am basically wondering if models are only effective persuasion tools for economists and students and are therefore given too much weight in the field.

Claire Kallen

I found this article extremely interesting. Reading about different views of modeling- from finding them too simple to finding them too complex and complicated- was very captivating because we spend so much time in economics courses modeling so I enjoyed reading about others’ opinions. The point I want to discuss is the idea that some had, “trouble expressing their ideas in the kind of highly specified models”. I found this quote to be especially interesting because I have learned that you are able to model almost anything with two variables/ factors. This approach to modeling began to unravel the high development theory in the 1950s. The words that stuck out the most to me in describing the high development theory were “persuasive” and “influential”. It is hard for me to believe that something that important was able to become “incomprehensible”.
About 30 years later, coming back to it with a “fresh-eye” it was decided that the high development theory really does make a lot of sense. One of the major themes of confusion with the high development theory was that it was hard to get it to fit into a specific simple model. This is where the theme of the differencing views of modeling come into play. As I stated earlier, I believe you can model most relationships between two variables, that is something we have proven in econ courses, so I think there is a way to model the high development theory it is just a bit more complicated, as is later stated in the reading.
Overall, I found this article to be captivating and it helped explain a lot of the confusion around the high development theory and the eventual return to it that occurred in the 1980s. I feel much more confident now in my understanding about the relationships between models and the real world. I also enjoyed learning that economics is constantly changing and that even though something may have been written off in the past doesn’t mean it won’t resurface in the future. Sometimes it is best to leave and come back to it with an open mind to find a new way to make it work.

Claire Jenkins

This paper by Krugman helped me to gain a better understanding of high development theory and the evolution of development economics. It also provided great insights into economic models and their use. Models are used constantly in economics to provide insight into why a complex system behaves the way it does. We make oversimplifications and assumptions about reality that allow us to better understand economic behavior. I found the comparison to maps very insightful. Krugman states, "Models are maps rather than reality." Economic models are merely just the simplest starting points of understanding a much more complex story. It is important for us to keep in mind that the models don’t accurately reflect reality. Understanding models, but also understanding their greater implications and the stories behind them, are essential for creating policies to do things like combat inequality.

Krugman effectively explains the use of modeling in economics and how it fits into the history of development economics, and especially how the big push model relates to both. I found the evolution of development economics particularly interesting, especially as it relates to the speculation that Krugman brings up about if real world economic policy would have been significantly better if development economics hadn't decayed as it did. Beginning in the 1950s, mainstream economics became more and more formal in regards to modelling, and it proved difficult for development economists to model development theory in this formal way. As a result, high development theory faded out as there were no formal models backing it up. It was in the 1980s that more sophisticated modeling techniques were able to make room for high development theory. Krugman only touched slightly on the implications that this might have had for the real world and I think it would be interesting to see if one could dive deeper into that. It would be troubling to find that if this fall in development theory hadn't occurred, real world economic policy would have been better over the years and developing nations would have seen greater success, and success much sooner than many of them now. However, this would likely be hard to study.

Ella Hall

What stood out to me most in this reading was the discussion around the importance of using models despite the possibility of blind spots. Hirschman, Marshall, and their high development economist colleagues framed their decision to not include models within their findings as an intentional choice to not oversimplify a complex issue. In other classes, we have discussed how in a business setting not getting too caught up in the aspects of the business that can be quantified and including qualitative aspects that are equally important can help the business avoid overlooking something. Krugman’s emphasis on the importance of modeling in economics first brought my thoughts back to these conversations. Of course, then, he pointed out exactly what I was thinking by acknowledging that some might question if this would cause blind spots. I think the point that Krugman is trying to make to people who have the same thought as I did is that models are supposed to be simple. They are supposed to create a narrow framework for understanding the phenomenon taking place that can then be expanded as the limitations are overcome. The concern should not be does modeling oversimplify the issue, but rather how can we work to overcome limitations in the modeling to create an even better model. I do think models offer a meaningful way of understanding economics, as difficult as some might be to understand. But looking at them as a simplified version to facilitate understanding, rather than full explanations of every aspect of an issue, as Krugman explains, makes them appear even more useful in my opinion.

Valerie Sokolow

One of the main concepts Krugman emphasizes throughout the article is how formalizing and modeling concepts tends to leave out important information. In economics classes, we’ve always discussed that models are used to simplify real-world things to more clearly understand the interactions between variables. Krugman illustrates several cases where the blind spots created in simplifying/formalizing thoughts have been left virtually untouched and disregarded in such a blatant way. Reading the examples about Africa and storms, I could almost understand why previous thoughts and beliefs were written off as merely folklore or myths, but it was more difficult for me to read that essentially the same thing had happened in economics. While I agree that it is important in economics to present arguments and theories in a more rigorous and formalized way using models and equations, it is interesting that such a large part of development economics was ignored for so long. Krugman addresses this by explaining that it may not have been possible for economists at the time to address the role of increasing returns and circular causation because of their attraction to the possibilities of perfect competition and constant returns. Still, I wondered why these topics were essentially abandoned for the sake of such powerful assumptions.

Ben Barbour

Krugman creates many amazing points in his paper that I think should be highly valued; however, the section on “The Evolution of Ignorance” really caught my attention. Krugmans connection of cartographers making maps of Africa and going from including the inside to becoming ignorant of the inside was something that I had not heard of before. In addition, when it is related to economics having a period of ignorance between the 1940s and 1970s, I was amazed to find out that a model such as development economics went unexplored after being discovered. Krugmans smaller point in this section about being able to previously argue a point verbally was allowed, but after the 1960s it would have resulted in a ton of ridicule. It is a bit weird that such a short period would lead to such drastically changing ideas of authenticity in the same field. This smaller section on ignorance made me think a lot about how economics and economists can have trouble proving their theories, and how development economics was one of those hard to explain fields.

Besides the section of the paper on ignorance, I thought the overall paper was well written and not terribly hard to understand. The use of metaphors and discovering something that is already known seemed to me like an idea that is very prevalent in what we have learned so far in class. I like to think this is like what we spoke about in class with the “Deworming the World” initiative, where something, like nutrition affecting the effectiveness of education, seems so obvious and known can be found again in research. This idea is also constantly throughout Krugmans paper, especially when he talks about the Big Push. The Big Push, as said by Krugman, is both a simple and very sophisticated model. I think that the Big Push model is interesting in its ideas of resources, using only labor and a premium wage is unlike models you see in economics. But, I mostly understand the model and why Krugman relates to representing the world in a dish pan. Overall, I thought that this paper was good for explaining development economics and the sort of troubles that it overcame in the past, as well as how it is becoming important and how attempts can be made to try and “make sense of the worlds complexity.”

A Facebook User

I think the most interesting part of the paper is the Big Push model. The author details how in economics people tend to pigeon hole themselves in these ideas of perfect competition and constant returns when in reality that doesn't always happen! Why do models have to be exceedingly simplified when the world itself is not simple. The introduction to technology and the "modern sector" is important in development economics and in achieving a high development society

Jacob Thompson

I think it’s fascinating to think about economics beyond the scope of just models and theories, and really enjoyed the way I was challenged in reading this article. I had never before considered an alternate approach to economics beyond using models to explain why certain things happen the way they do, as it’s all I’ve learned up to this point. After reading about how Hirschman strayed from tradition in his approach to development economics, I can’t help but think if an approach like this could work in other aspects of economics as well. In my opinion, approaching an economic topic without using a formal model could provide for a very interesting discussion, as it allows us to step outside of all the assumptions that normally have to be made and truly try to tackle the topic at hand. While I acknowledge the severe importance of models to economics as a whole and recognize their necessity, I found this piece by Krugman to be refreshing in that it made me realize that economics does not always have to be so formal and by the book.

Max Thomas

Reading this article, Krugman argues for a balance between empiricism and narrative in economic research. In Krugman’s view, both empiricism (in the form of modelling) and narrative (in the form of metaphor and theory) play important roles depending on the audience and purpose of their respective projects. In arguing his claim, Krugman describes the “fall and rise” of high development theory. Because of initial difficulties in modelling high development theory, its assertions were disregarded for decades.

Given Krugman’s claims, I wonder how advances in data science and supercomputer capabilities will shape the future of economic modelling. I worry that, as researchers gain more access to data, emerging theories with limited advanced modelling will be disregarded. Regardless of computing power, researchers will never be capable of creating a completely accurate model; there will always be omitted variables and flawed data points. Accepting the fallibility of models will be critical for advancing research. To echo Krugman’s point, rather than striving for perfection, researchers ought to look for pragmatic explanations for their theories.

Brad Stephenson

In “The Fall and Rise of Development Economics,” the author dives into the confusion caused by “purely verbal exposition” compared to formal models. While I do feel that formal models do, on the whole, communicate their assumptions effectively, I believe that they also mislead individuals. Because the model is formalized and accepted by the economic community, someone may be more carried away by its findings than “verbal exposition.” As the author states in the reading, many intellectuals bypass important economic ideas because they are not formally modeled. This shows that “verbal exposition” is often ignored as it is seen as inferior to formal modeling. I would argue that formal models, even though they state their assumptions, can be equally if not more misleading than “verbal exposition” because models largely have a reputation for being more reliable.

Sally Ennis

I think that the comparison and use of the "dish-pan" model is a great example of how almost everything can be applied to a model or theory. For this reason, I agree with the article that it is surprising that something as simple as the high development theory could not be transformed into a model that would then be more widely accepted and supported at the time. The article pushes our understanding of models and highlights that although models provide an oversimplified way of understand complex concepts, it neglects crucial information that may influence economic decisions. This reminds me of the use of ceteris paribus and how it is particularly useful in modeling and theories, but relatively unlikely to happen in the real world as one can't hold certain variables constant while manipulating others outside of a model. I really enjoyed the backstory and history behind the map making in Europe of African countries because it shows that the development of ideas ebbs and flows as new information is being processed. It does raise the question of what else has been left out or disregarded because it hasn't followed the traditional format for displaying information? In a field that is still developing and is relatively new, I wonder if there are other concepts that have fallen through the cracks.

Teddy Bentley

This paper by Krugman was especially interesting because of his candid and frank message about basing economics on models. It was very interesting how he detailed how there can be very simple and very complex models that may not even be making the right assumptions. I think Krugman did an amazing job using metaphors to describe the complexity of the economy. The metaphor of predicting weather patterns resonated well with me as an example of how to predict economic development. When Krugman said, “In the early stages of a complex science, however, the criterion for a good model is more subjective: it is a good model if it succeeds in explaining or rationalizing some of what you see in the world in a way that you might not have expected.” I feel that the models in the past have explained more general assumptions and are not projecting events that one might not expect. In economic development, this has been a major issue, as Krugman explains, for economists using assumptions of perfectly competitive economies. Another metaphor, explaining how “folk wisdom” in weather prediction was widely ignored until it was actually looked back on and found to be correct. This is a great metaphor for the way economists have looked at development economics. Economists have ignored what seems to be obvious changes in assumptions concerning economies of scale and while Krugman argues that it is a fault of the economic development in the past few decades, I think it is just the evolution of theory that has to take place. I believe in any type of theory creation there are bad judgements and approaches to solving the problem. Here, is the example of economists going down the wrong paths and over simplifying situations for the sake of being able to teach these theories in the right way. However, going down the wrong path is one of the ways to finding the correct path and Krugman mentions that at the end of the paper. In conclusion, Krugman is very insightful in his theories and uses metaphors very well to help the reader understand his message. While economists have made some wrong turns, it has led to the advancement of economic development overall.

Chaz Cunningham

Krugman's article pointed out to me that there's this dilemma between accepting a model for what it is and theorizing off what is given or choosing to stagnate our understanding of economic development due to "blind spots" in our ability to formally model. This article caused to me think furthermore about my macroeconomic class, where we are reviewing the Mundell-Fleming Model on a macroeconomic scale. The final effect always contains some ambiguity because the model accounts for direction and "linkage" and not so much the precision of some shift. So although we do not have the exact inputs for the change in Monetary or Fiscal Policy, we still choose to follow the model because it can still be broken down for us to understand further "insight into why the vastly more complex real system behaves the way it does" as Krugman states.

On the other hand, it is also shocking to me how long the abandonment of such modeling implications lasted, given how fundamentally crucial it (economies of scale, increasing returns) was to economic development. I thought Krugman's point about Lewis' model was fascinating yet alarming at the same time. The absence of economies of scale in Lewis' work allowed economic theorists to model his work so well. This seems to directly associate to Krugman's concluding point that maybe "temporary ignorance is the price of progress".

Jacob McCabe

I found the fact that the high development theory began as a conceptual idea with no modeling or mathematical background a testament to the intuition of Hirschman and co. The way that the rigid structures of economics in the 70s brought forth important developments in how we approach economic analysis today suffocated the growth of abstract and creative thought, but it also set the foundation for applying those kinds of theories as the structures expanded for more variation in inputs and interpretations. While Hirschman may have been way ahead of his time, I believe that the high development theory played a role in forcing the invisible hand to apply more of this structure to the field, after which it could fit more abstract concepts within. While the early pioneers of this theory were ousted from the traditional schools of economic thought, I appreciated how Krugman recognized Hirschman not as the villain of the subject, but as the tragic hero who had to wait decades for his legacy and contribution to be fully accepted.

Mary Wilson Grist

I really liked the quote “Models should provide insight into why the vastly more complex real system behaves the way it does”. I think this is a helpful way to understand why there is so much emphasis on models in economics. In terms of the High Development Theory, it is interesting that it got disregarded due to the lack of ability to formally model the theory. However, I also agree with the argument that putting too much emphasis on models does take away from some important complexities that need to be analyzed. It is important to have an equal balance between simplistic models and the discussions of complexities.


I found it very interesting how economists chose to be so ignorant about loose ends when building their models from the 40s to the mid 70s, specifically pertaining to their inability to model economies with imperfect competition. I was surprised that they could continue producing models and publishing them despite these loose ends. Concepts like economies to scale and increasing returns to scale are so vital to one’s understanding of economics that I was shocked to see that they were dismissed although they had been speculated about at this time. It was really refreshing to see that, like in Fultz’s dishpan, thinking in terms of more simplified models consisting of assumptions is what is actually necessary in understanding the world, and that the main issue with economists throughout history was their inability to accept these simplifications and to look at the world through any lens other than that of perfect competition and constant returns. Overall, I found this article to be very intriguing and helpful in understanding the history of economic thinking.

Gavron Campbell

Models have always been my favorite aspect of Economics, possibly because I’m a visual learner but also because models help me look at complex circumstances at a wider perspective. Economics, especially development economics, has several intertwining factors that one can easily get lost in the weeds. One metaphor that clicked most with me is Krugman’s take on “the evolution of ignorance.” Due to the legitimacy standards rising, several pieces of information were discarded in the economics world. One those discarded areas were found once again, economists researched them in a nonmathematical method, which Marshall was a proponent for. Theories were then illustrated in a collection of models that indeed may oversimplify a complex situation, but at least attempted to explain certain phenomena. It was interesting reading about the path of development economics, and especially how different intellectuals approached problems in different ways. Lastly, I loved Krugman’s quote “it is a good model if it succeeds in explaining or rationalizing some of what you see in the world in a way that you may not have expected.”

Kaylann Adler

I found this paper interesting because of Krugman's discussion about both the strengths and shortcomings of the use of models in economics. I don't know if I've ever even considered the study of economics without models. I also liked the metaphors used in this article, especially the evolution, devolution, and subsequent evolution of maps in Africa. This whole section also has me wondering what concepts/ideas are in some economists' heads right now that have been dismissed or haven't yet been presented because of a lack of information or technology that isn't quite advanced enough yet. Finally, I think this paper is just a testament to how impressive it was for Hirschman and other similar economists to think through the concepts of high development theory without actually mathematically showing it through models. Personally, I love looking at models to help me learn and process economic concepts, and it's wild to me that those economists were able to think through the concepts without yet having the models that would allow them to show high development economics but were still shown to be correct decades later when the technology caught up to their theories.

Kevin Thole

I found Krugman's thoughts about the supremacy of models in economics compelling. The analogy he made to European ignorance of Africa painted a good picture of how discussions of developmental economics evolved from the early 20th century to the late 20th century. High development theory suffered during the model craze of the 1960s because it couldn't accurately be presented in a model. I always felt that that models in economics are restrictive because they leave out many variables and phenomena that could potentially affect outcomes. However, as long as the relationships represented in these models are accurate, the exclusion of other variables can be forgiven as long as those variables are taken into consideration in the creation of public policy. I also think that the obsession with models diminishes economic concepts that are more normative and are better described in writing. I found Krugman's ideas surrounding what gets left out of models interesting. His ideas highlight how some thoughts may not be wrong just because they can't be illustrated in a model. The assumptions required in many economic models don't hold up in the real world which creates problems for these models. This is why Krugman is enamored with Fultz's dishpan and other very simple models which don't rely on a whole lot of complexity. As long as the model explains a truth of the world around us, it is a good model.


I really enjoyed Krugman's analysis of modelling as both informative and necessary. It reminded me a lot of Catherine Z. Elgin's 'felicitous falsehoods' in her essay "True Enough". She too argues that models, while epistemically valuable, if not necessary, certainly cannot be counted as 'true'. Krugman seems to believe the same. There are certainly not strictly two types of economies, traditional and modern, but analyzing them separately and considering tradeoffs between them can create some extraordinarily valuable insights. 'The Big Push' also harkens back to microeconomics where consumers' preferences are assumed to be complete, reflexive, and transitive (not to mention monotonic and convex). I was surprised by the idea that all explanations are essentially models, and was even wondering if this extends to all language in general. Is 'tree' not just a model from which to identify a tree. I also appreciated that Krugman evaluated the other side of the argument as well saying with his African coast example. We really can gain valuable insights by limiting out some of the richness and complexity of the real world. I ultimately agree that models are good when combined with the recognition that the assumption made are really just that, ASSUMPTIONS.

Grace Owens

As several others have mentioned, I also found it surprising how much of a drawn out process creating this rather simple and basic economic model was. It interested me to hear about how that process compared to the Europeans mapping Africa, but made perfect sense too. I had never realized that the development of economic models could essentially regress and become less developed however, the process of that became much more apparent when it was compared to the mapping of Africa in the sense that technology and capabilities increased, but the standards of accuracy and expectations became higher. I wonder if the process of forming the economic development theories had been more linear if or how the end result would have differed, or if it would have even come to fruition. However, as was stated, “The cycle of knowledge lost before it can be regained seems to be an inevitable part of formal model-building,” so perhaps everything works out the way it does for a reason.
Another notable point was that economists tend to emphasize what they can formally model versus what they might not be able to. This, too, makes perfect sense and I certainly understand it, as I am not very comfortable with modeling myself. However, I expected economists first to have a better ability to model and second, there to be less inherent bias because it seems like a very obvious thing to do.

Matt Condon

While this reading poses some interesting points about the evolution of development economics, many of the author’s main points have relevance in the broader scope of studying economics in general. The author spends a great deal of time discussing models and the role that they play in our study of economics, and I think that his argument here is one of the more critical takeaways from this reading. Hirschman is presented at one extreme on the spectrum of modeling – he refused to try to formalize his idea through a mathematical or graphical model. On the other hand, the author also mentions individuals in the field who give far too much credence to models. The vast majority of economic models require massive concessions about what is or is not true in the form of assumptions in order for us to be able to poise the situation in a more understandable way. I think the author’s point of using models as metaphors hits the nail right on the head about the role models should play. They are a helpful way of representing market functions and other economic phenomena, but they are helpful only as long as one remembers that they are just a tool to make the phenomena more easily explainable. Usually, the systems that we attempt to understand are far more complicated than we could graphically or mathematically represent. This internal controversy around modeling in economics reminds me of a speech by political strategist George Kennan I read for another class, “The truth is sometimes a poor competitor in the market place of ideas – complicated, unsatisfying, full of dilemmas, always vulnerable to misinterpretation and abuse.” While the original context of this quote had nothing to do with economic modeling, I think it applies here. It would be far easier to either accept the models we use as fact or to reject them outright due to the unrealistic assumptions they call for, but neither of these gets us closest to the truth. These models are a valuable asset in the field of economics, but only as long as they are taken with a grain of salt.


The most fascinating part of this article in my opinion revolves around the how Hirschman took a different approach to development economics. Generally, most of the information we learn in economics is shown around different graphs and models with a variety of explanations for shifts and constants in the drawings. This makes good use for learning because it shows students visually what is going on. Hirschman turned away from models during his work in development economics and focused on the topic from a new point of view. This change in approach allows for him to throw all assumptions aside and just focus on his own work. If we were to carry this approach into our economics class would we struggle or have success? This question is up in the air but it is interesting to see work done from a perspective without graphs and models. I definitely think models are crucial but it was nice to see someone look at a topic from this alternative perspective.

Matt DiTondo

I founds Krugman's point about the loss of knowledge in pursuit of more rigorous models to be very interesting. There is an almost tragic sort of irony in the story of some piece of traditionally-held wisdom that is tossed out by a model, only to be later reaffirmed by the very same (only more matured) model that had cast it aside. The idea of how we always seem to throw the baby out with the bathwater certainly has wide-ranging implications, well beyond the field of economics, and it actually reminded me of a story I had read about a similar thing that occurred in a field sprung from economics: baseball analytics. We, for the most part, know of the sort of baseball analytics that were popularized by the book and movie Moneyball. We might not know the specifics metrics, but we have a gerneral idea that teams began to use advanced statistics and modeling to build better baseball teams. But we tend to think of this mostly as a singular discovery and not one that is continually evolving. And what has evolved over the last two decades as it relates to the position of Catcher is a textbook example of the effect Krugman describes. This evolution pertains specifically to one skill pitchers require, called "pitch framing". In essence this is the ability to catch a ball in such a way that, to the umpire, a ball appears as a strike. Up until the application of analytic models, it was unquestioned that this was one of the most important skills for a catcher to posses-- until it wasn't. For over a decade, all the smartest guys in the room thought nothing of this skill. Why? Because they lacked the data to quantify it. Their data showed only showed where a pitch had ended up and what the umpires call was, and with this data their (limited) models evaluated pitcher performance, and they determined pitch framing to be of dubious value. It wasn't until their data collection became more advance, specifically in technology that tracked the exact flightpath of every pitch, did they realize their error. With this newfound data, they reevaluated their models, and in the end reaffirmed that the age old wisdom had been correct: that this skill was one of the most important things for a pitcher to posses. While this story doesn't relate specifically to economics, it is representative of how this sort of failure of imagination and wisdom plagues more than just our study of Development Economics.

Alexandra Lindsay

This paper gave some really interesting insights on the value of models in not only economics, but models used in every field. The idea that we make false assumptions in order to get our models to something that we can handle is something that many of us don't think about when making models. The author also brought up the point that, similar to the process of mapping Africa, making these simple models produces gains and losses. Yet, we put so much faith in our models. Because of this, among other factors, I can understand the frustrations and troubles that economists had through out the 20th century when developing theories, like the high development theory. Interestingly, however, the world has made so many policies, conclusions, etc, with these somewhat incomplete models. Also, I was surprised by the level of dispute in theories and models throughout the 20th century, because I’ve always been under the impression that the models are right with no questions asked. This paper pushed me to be more curious and ask more questions regarding theories, specifically in economics.

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