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In Krugman's article titled "THE FALL AND RISE OF DEVELOPMENT ECONOMICS", he details the unfortunate waste of great economic minds resulting from the lack of technical ability to produce models in the field of high development theory, while the rest of the economic research scene had rapidly implemented rigorous models into their research. The author theorizes that the lack of satisfying modeling techniques lead to many great economists of the high development theory field to reject modeling due to fear of losing too much clarity when discussing their theories. Thus, such a model may predict an entirely false outcome and could be a detriment to the field than an advancement.
While Krugman does state that he dislikes the assumption that all social fields must try to be like physics with rigorous models that are correct to 5 standard deviations and that those types of models are pure. While such modeling is possible in fields where there is a great amount of observable data (i.e. the petabytes of data generated every run at the Large Hadron Collider), it is essentially impossible to make such models in economics, since the cost of obtaining the same degree of observations would be too large for such a model to be economical. Furthermore, some components of the economy can be difficult to objectively measure, since they are inherently subjective in themselves. For example, measuring confidence in the economy to grow by investors is subjective and can be influenced by many factors. Furthermore, this sentiment can change at a moment's notice or by a single tweet. That can make surveys taken just minutes before inaccurate. This adds a dimension of difficulty to the job of an economist that a physicist is unlikely to ever experience; the laws of the universe are in a constant state of flux.
However, I do think that there is room to make a comparison between physics and high development theory. While high development theory was held back by the lack of technical knowledge of how to model phenomena, physics is generally held back by the machines and techniques used to run experiments and generate data. Before the Large Hadron Collider was completed there was a great amount of theoretical work published on potential explanations of the inner workings of the universe. However, these predictions could not be tested until the infrastructure to make observations was completed. This is comparable to what high development theorists experienced early on; they did not have the correct tools, in this case modeling techniques, to show if their theories had merit.
Recently, there has been a lot of speculation of whether a leaked document stating that Google has reached quantum supremacy with its quantum computers is true or not. If this is true then quantum computers could potentially open the gate for even more rigorous economic models than current models, since it could offer vastly more cost effective computing and solve simulations that would have taken centuries for the fastest supercomputers to do in minutes.

Colby Boudreau

High development theory provides a potential solution towards helping countries escape their poverty traps, which is a topic that many have tried to tackle before. The core of the theory says that modernization breeds modernization, and that countries need to be committed to self investing and building and diversifying their market size. Upgrading to more modern means of production achieves greater productivity and margins, but also requires labor wages to rise so the new modern workers can be compensated better relatively to the traditional ones, as their new jobs may require more time, skills, etc. But this is where the first step of creating the circle is crucial, because an essential part of the high development theory is reaching a sustainable level of economies of scale combined with a large and/or growing market. However, this is difficult, since the transition from traditional production and techniques to modernization may be costly and naturally will cause the market to take its time developing and growing to the optimal size.Thats why paying the workers higher wages and empowering them to be a part of the modernization process is as important as the transition itself. As workers get paid higher wages, they will in turn become important members of that market that they are creating, and will lead them to be much more active participants in the market than their traditional counterparts. This then harkens back to what we were discussing last week, about how many developing countries find themselves stuck in a poverty trap, especially in scenarios where much of their economy is based off of agriculture. I think that “modernizing” an industry or workforce can be looked at two seperate ways. On one hand, it is easy to picture this process that they talk about is centered around simply taking current production areas and improving them, for example, taking a factory that produces cars and making it more modern, efficient, productive, and innovative. That begins the process of improving the economy and the lives of the employees, but I also think that modernizing a country’s economy on a large scale involve expanding and developing the industries with a more modern approach. We’ve already seen how societies that rely on agriculture are the ones that face difficult odds to escape the traps that they are in, so a logical approach would be to improve and diversify these economies, which inherently require workers of higher skills and higher wages. Only if we use the high development theory to address the issue at the root of where the trouble stems from, will we be able to begin seeing some sort of progress in these communities.

Alecsander Horne

I think this article fits well with the paper given to us last week on the issue of the poverty trap with developing countries. Countries which have been left behind have struggled to move from an agricultural-based economy to a manufacturing economy. However, even if they were able to make this transition, I still see developing countries lagging behind. As discussed in class on Tuesday, September 24th, the advancement of robots in the manufacturing industry is changing the game once again. This advancement known as the 4th Industrial Revolution will lead to higher wages and higher economic development in the countries which can employ the practice but will ultimately lead to a greater divide between the upper class and those on the bottom of the totem pole. If developed countries move to this practice, they will obviously be more efficient with producing goods and services in dark factories. That being said, workers will need to develop a new set of skills in order to continue working in factories which implement robots.

If agricultural societies were able to move to manufacturing, this would clearly help bolster their economies from their available workforces. Even so, these countries would still lag behind developed nations increased efficiency with robots in the manufacturing industry. This poses the question: if deemed profitable for entrepreneurs, is it possible for agricultural societies to jump from their current state to a manufacturing society with robots? The most important component for developing countries would be education. They would have to be able to learn the skills necessary in order to be a part of the workforce that implemented dark factories in their region. Sadly, I see it as an extremely difficult transition given the failure for many agricultural societies to transition to the manufacturing industry during the first wave of development. Even so, something must be done in order to combat the problem and maybe the implementation of education and automation in developing nations can help solve the issue.

Anne Riter

In Krugman's article, "The Fall and Rise of Development Economics," he points out how strange the history of development economics truly is. Typically, all things that rise must fall, but in the history of development economics, it had to first fall in order for it to rise.
I think Krugman's various analogies such as the Norwegian's and their folk tales about cloud shapes or the map of Africa becoming empty accurately describe the history of economics as a whole, not just the history of development economics. Before any of the math had been ironed out, economics relied on basic theories and graphs to describe phenomena economists observed. It also relied on a series of assumptions that attempted to boil down human action into "bite-sized" pieces. As the rigor increased and the techniques became more difficult, economists started to omit the information they couldn't explain away nicely. I find it sad and a little disheartening that so much in terms of development economics could have been achieved between the 1940s and the 1970s had people been willing to leave a few things left unexplained. Perhaps a lot of good could have been done to aid those developing countries stuck in the loop or the countries lagging behind (as the article last week described) had those economists not been worried about tying all the loose ends.
What is also similar to the article last week is the high development theory itself. It's described as very cyclical, where one action begets another which begets another and in the end, the final action improves the original situation, which then starts the cycle all over again. The cycle doesn't have to be positive, either. Economies can be stuck in a "low-level trap" which reminds me of the developmental laggard countries described in the article from last week.
Although it is possible for countries to escape the low-level trap, I think it is extremely difficult, and since development economics has only really recently (since the 1980s) developed itself, I think we have a little longer to go before people start to understand the difficulties poor countries face when trying to go from a primarily agrarian society to a manufacturing one. Probably the easiest way for this to be done is through technology, and if Google really did achieve quantum supremacy, then perhaps that technology can be used to improve the models put forth by Hirschman, or even to help the farmers in those lagging countries improve their situations.

Margot McConnell

In Krugman’s article, “The Fall and Rise of Development Economics,” he discusses how economic development took a down turn due to ignorance. He explains that from the 1940s to 1970s, there was a rise in understanding of certain economic principles and events, but there was also a lack of confrontation about areas that were less understood.
Part of Krugman’s Segway into his main argument about “the big push” is the idea that most of science is very similar in that one will have to make models that simply situations, and therefore, the analysis will never be fully complete. This is why models are used—in order to simplify situations so that we can better understand them. He goes on to say that creating a model is essentially the same for all disciplines because you have to start with some assumptions. Even though the assumptions might be unrealistic, it helps us be able to draw ideas about the relationship between variables, especially those that have to do with economic development. Krugman’s connection between economic modeling and the big push idea helps to tie in the idea that while models are not always realistic, they allow us to have a better understanding of the world. Therefore, one can use that information in order to understand why certain countries might be underdeveloped and what possible policies might lend a helping hand to fixing the development issue.
As Krugman analyzes the big push idea/model, he argues that one cannot conclude from the high development idea that countries are trapped in the low-income cycle. However, it can be concluded that self-reinforcing growth is possible. This was an important point he makes because a lot of developing countries end up caught in the cycle of poverty. This shows that while the big push model does not allow us to draw a conclusion about the low-income cycle, this could be one of the flaws within the model. The low-income cycle helps to explain why changes must be made in order to help improve living standards and the lives of those in developing countries.
When I was doing medical service work in Jamaica last December, it made me truly understand the low-income cycle. The people there are generally poor. They have very limited access to health care. I worked in a public hospital, which is funded through the state. In order to get treated at a private hospital, which is much cleaner, has more qualified doctors, and very little wait times, an individual has to pay a large amount of money. The average Jamaican cannot afford that. Therefore, in these regions where I was doing medical work that are rural, we had to travel over an hour in the mountains in order to reach these people. Most of these people lived in cement-like homes that were very open, lacking windows and sometimes had dirt floors. Some of them had plumbing and running water, but most of the time, the water had to be pumped from a well at a place far away. Additionally, many of the younger children had to take care of their parents who were ill, which caused them to miss days from school. One of the main takeaways I found from my experience was that the lack of access to quality health care either because it is too far away or it takes too long to wait in line at the emergency room caused a lot of other issues within the household. These people were able to work less because they were disabled or sick. Their children could not go to school. Their children were the ones that had to go fetch the water or buy the food that they were going to eat that night. Lack of education and lack of work are two things that can trap people in this cycle of poverty. In addition, the lack of treatment for even the simplest of treatments because of lack of accessing the right medicine or getting quality care shows that improvements have to be made in certain areas within the country in order to help these countries break out of this cycle. Development economics and its models are what helps to explain these issues and helps to characterize how to best solve these issues.

Lucas Flood

In the context of the “Big Push”, I find it interesting that Krugman is supportive of the Rosenstein-Rodan strategy of bold policy intervention. While government intervention may be a method of achieving the Big Push, the example of China discussed on Tuesday was certainly not something that should be followed completely. China was successful in creating massive economic growth by controlling the flow of its population between rural and urban areas. From a prescriptive policy perspective, following the example of China would more than likely create growth in an economy. However, under the Amartya Sen framework of increasing human freedom, the cost of China’s economic policy is significant. It is easy to think of China as a success from the perspective of increased life-expectancy, continued economic growth, and education. In the end, the anti-democratic policies of the Chinese government are the primary reason Hong Kong continues to experience violent protests. In light of widespread population control policies in China, I would argue China fails to uphold the human capability factor in Sen’s analysis. With China’s anti-democratic and controlling policies in mind, I would imagine a democratic government would have to adopt a vastly different approach to successfully implement the Big Push.


Krugman provides a thorough reflection on the history of development economics. He carefully meditates on the methods of important development economists—specifically the work of Albert Hirschman, Rosenstein Rodan, Myrdal, Lewis, and others. He ponders the reasons why development economics saw particularly slow momentum until the later-half of the century, hypothesizing that they were too caught up in finding—or avoiding limiting themselves to—appropriate economic models. Krugman specifically warns against Hirschman’s methods, claiming that he rejects the benefits models offer because of his deep sense of intuition and obsession with complexities in a fear that more will be lost than gained.

Something exceptionally interesting in the paper is the inevitable ignorance associated with designing a model. Krugman explains how a “loss of knowledge” is necessary in order to understand larger concepts and create more insights. Krugman’s “evolution of ignorance” is valid for being productive in fields of knowledge and understanding. Leaving out the complexities of reality allows for economists to move forward and solidify concepts into a bigger, more comprehensible, picture. Without models and metaphors, it would be extremely difficult to convey most economic ideas. There is currently a strong push to make progress and formulate effective policies in the field of development economics. However, without the ability to move forward and accept the flaws and assumptions of a model, economists will slow progress and allow time for more issues to surface.


While reading this article I could not help but to keep thinking about the article we had to read last week about the poverty trapped countries. This article touched on making the switch from an agriculture based economy to manufacturing based economy. Almost all the lag behind countries rely on an agriculture based economy but even if they switched to a manufacturing based economy would they still be trapped? First I do not know how long it would take to completely change a countries main export and economic system but even if they did they are still competing with countless number of other on the rise countries. The trap is like a never ending circle and I think the way out lies way deeper than changing a countries main export.

Krugman states, "The truth is, I fear, that there's not much that can be done about the kind of apparent intellectual waste that took place during the fall and rise of development economics. A temporary evolution of ignorance may be the price of progress, an inevitable part of what happens when we try to make sense of the world's complexity". What really can be done now to make up for what happened? He also states, "the advice is not to let important ideas slip by just because they haven't been formulated your way". I think this is a big thing in our development worldwide because people ignorance is always setting us back. We as humans believe our thinking is the right way to think but maybe the key to actual sustainable development is with the help of some of these models plus the ideas that may seem crazy at first but when we really dig deep into them can lead to big change.

Maisie Strawn

Krugman’s argument for the importance -even necessity- of models in economics is powerful and fairly irrefutable. It is hard to imagine explaining almost any economic concepts without graphs and equations. Further validating his argument, he acknowledges that modeling has limitations. Models must be understood as simplifications of very complex systems constrained by an economist’s resources, which include the knowledge that they have at the time. For example, “high development” theorists were limited in their ability to produce models because they did not know how to model economies of scale. Unfortunately, this led to the neglect of their theories by economists who were able to present their own ideas in more formal models. Eventually, their ideas would come back into the mainstream as modeling techniques became more advanced. However, the lag in their adoption was significant, and there may have been truly beneficial economic policies lost during their period of neglect. To conclude, Krugman advises one, “not to let important ideas slip by just because they haven't been formulated your way.” This is I believe is the most important part of Krugman’s paper when it comes to development economics, and unfortunately the least likely to be heeded. When it comes to development economics, it seems to me that there is a lot we cannot yet model. Especially when thinking in a Senian framework--how can we fully model the importance of various freedoms and capabilities in a mathematical framework? I am sure that our ability to do so is getting better with each year and with increased access to data. However, just like with the original theories of “high development” there will be a lag in our ability to create models that take into consideration such factors. It is vital that we learn from the past and keep in consideration these things that are intuitively important even if they cannot yet be modeled. As Krugman argues, models are important for allowing us to understand complicated interactions and systems, but they are not everything. They must be constantly adjusted with new information and understandings, and they cannot be the sole basis for policy because they are simplifications and significantly limited.


Throughout his analysis of the “strange history” and methodology behind high development theory, Krugman effectively demonstrates the functionality of models by actually incorporating various clever metaphors/models into his argument. Krugman supports the idea that even though models are limited, they still help explain how systems around us behave in a way that is easier to understand. As long as one acknowledges that the scope of the model is limited, one is ultimately better off with the insight that models provide than not bothering to give thought to a model in the first place.

Krugman’s first metaphor/model was his comparison of Hirschman to a “tragic hero,” which helped me to better understand Hirschman’s role in development economics. In trying to do what he thought was best (abandoning models and the technical side of economics), he limited the reach and perhaps the legitimacy of his findings. The critical assumption of economies of scale that high development theory depended on had never been modeled, so Hirschman decided to ignore models all together.

Another model/metaphor that Krugman used was the comparison between the African mapping dilemma and the loss of information in the field of economics in what he referred to as “the evolution of ignorance.” I found this topic very interesting because in both scenarios, improved technique led to a loss in knowledge for a while. The “dark regions” that could not be explained in technical terms were discredited, even though they weren’t necessarily incorrect. Krugman later uses the metaphor of the Norwegian cloud “folklore” to model the reemergence of high development theory in the economic world. Both concepts were discredited because they could not be proved, but later were found to fit with the technical models. High development theory’s popularity essentially came full circle.

Lastly, Krugman refers to Rosenstein Rodan’s Big Push story as “the essential high development model.” Rosenstein Rodan simplifies the economic model by creating a set of assumptions for resources, technology, demand, and market structure. Obviously labor isn’t the only resource in an economy, however by simplifying the system in this manner, one is able to understand its impacts in a “traditional” sector along with a “modern sector.” Ultimately, Krugman’s “The Fall and Rise of Development Economics” makes the important point that even though models leave out certain variables, models stick overtime and help us to understand a complex system. By using various “models/metaphors” throughout his article, Krugman inherently strengthens his claim.

Prakriti Panthi

In the article, Kruger highlights the importance of building a model in economics, while at the same time acknowledging that there are limitations to modeling. There are so many factors that play a role in an economics phenomenon and models tend reduce the complexity, that is society, to a math equation, or graph, that cannot always capture what is happening. But at the same time, modeling is a place to start understanding the social world, because we do not always have the deep insights we need. I remember reading in this week’s reading something along the lines of ‘something being necessary doesn’t mean that it is sufficient’, and I think that Krugman in this article is alluding this in some ways. A model that we create based on unrealistic simplifications is necessary but not sufficient to understand the complexity that is our world. From what I understand, Krugman is stating that although models are not the true reality, they are necessary, but not sufficient to make a conclusion about what is. But this raises the question: how do we determine how far this ‘metaphor’ is from the true reality? How do we calculate the worth of an economic analysis then? If we simplify too much, then don’t we run into the problem of external validity?

Caroline Florence

In “The Fall and Rise of Development Economics,” Krugman details the history of the development economics field. I think that Krugman makes a really important point in this article; while past theories of development started a conversation about development and are useful under some assumptions, they must be viewed in a more holistic framework. Models cannot, and should not tell the whole story, but that does not mean they are useless. I especially liked the example of Fultz’s dish pan weather model to illustrate this point. Obviously, the earth is not flat and air is not water, but the model was able to show aspects of weather patterns. It is easy to agree that scientific models cannot explain the entire systems but instead show parts, but why can’t we agree on the same for social science models? Models, though not perfectly predictive of the real world, are extremely useful tools for economists. Unfortunately, many discredit models based on their assumptions, particularly if a model does not support one’s political agenda. Though we certainly should pay attention to the limitations of models, we should not dismiss them simply because they contain underlying assumptions that are not always true in the real world.

I also agree that it is unfortunate that the “slump” in high development theory may have led to bad economic policy. Though we do not know the outcome that would have occurred if high development theory had not declined, one has to wonder if lives in developing countries could have been improved.

Lauren Paolano

In Krugman's article, "The Fall and Rise of Development Economics" in the Evolution of Ignorance section, there is a question of "why high development theory didn't get expressed in formal models?" Hirschman made significant contribution to the formal theory of devaluation in the 1940s and during this time, the development field itself was generating mathematical planning models (Harrod-Domar type growth models).

The explicit problem for the previous question is because of the market structure at the time. Until 1975, Economists knew how to model only a perfectly competitive economy, one which take prices as given rather than actively trying to affect them. I found interesting how there is a standard theory of the behavior of an individual monopolist who faces no competition, however, there remains to be no general theory of how oligopolists will set prices and output.

In my Business Ethics class this semester, we have been currently reading a lot of Marx and Adam Smith's pieces which correlate well to this paper especially. According to Smith, a society is not happy of which the greater part suffers, the goal of the economic system is the unhappiness of society because the economic system leads to the wealthiest condition. Furthermore, from the political economist's viewpoint, labor is the sole unchanging price of things, there is nothing more fortuitous than the price of labor. In "Estranged Labor", Karl Marx makes the claim that the whole society must fall into two classes: property owners and propertyless workers. The wheels for which political economy sets in motion are greed and the wars amongst the greedy (competition). In Krugman's article, economists didn't being to break through this barrier of completely understanding the regulations of competition and formulating the ideas into formal models until the mid 1970s.

Christopher Watt

In his paper “The Fall and Rise of Developmental Economics,” Krugman gives very valuable insights into both the ideas of modeling and the field of economic development as a whole. In describing Hirschman’s Big Push and high developmental theory’s inadequacies for a series of decades following the 50’s, he reveals the failure and shortcoming of high development theory to be applied to any real world situations and therefore have applicable and usable revelations. One of my main takeaways from his critique of Hirschman’s high complexity theories is the real objective use of models: to be used to better understand some aspect of the real world and therefore be able to address an issue or respond through policy to a given relationship. By overcomplicating modeling, it became impossible to understand economies of scale or the supply chain of a traditional laborers to “modern” laborers. If a theory cannot be modeled and applied, it cannot serve as a tool for creating strategies that promote human well-being or improve on current systems. Yet, at the same time, the idea of not capturing the richness of reality—or seeing all of the different formations of the clouds—is a bit upsetting to me as the issues developmental economists seek to understand and solve involve such highly complex systems and processes that I can see why a simple model would be ineffective. However, only through such simplification can essential relationships and systems be understood in a way that makes doing something about them possible. The Clouds ultimately can tell a story, and, building off of Krugman’s metaphor, each individual cloud can be seen for its own complexity and understood, allowing the whole process of the sky and greater meteorological system to be broken down and understood. It also educates that some of the stories of high development may be able to be boiled down to a single factor, such as in the example model. Though it’s just a theory, it can lead to further data collection and testing and ultimately applied to real systems. That is exciting and brings optimism for some of the problems developmental economics tries to address!
Lastly, this history reveals that though certain issues and systems seem to complex to be understood or simplified, with time and sophistication in analytical/modeling techniques, some of the confusing issues we face may be resolved. The "slumps" in development are disheartening; however, they may eventually be overcome.

Kenza Amine Benabdallah

In “The Fall and Rise of Development Economics”, Krugman offers a very interesting analysis of two different themes. First of all, he gives an overview of the bizarre history of development economics. He depicts the ideas and discussion about development from 1949 to the 1990s. I thought that was very interesting to see that, while it was highly questioned for a long period of time, in the 1990s economists were “able took at high development theory with a fresh eye” and they could finally understand that it made a lot of sense. He also describes the “problem of method” in the social sciences. I was surprised to know that high development theorists were always having a hard time expressing their ideas in the specified models that were becoming the language of discourse of economic analysis.
I also found it very interesting to read about the disputes over the nature of the policies that might be required to break a country out of the poverty trap. I thought it was related to the article we read last week on institutional barriers. I was not convinced by Hirschman’s theory that a policy promoting a few strong of the economy is key to development. I agreed more with the idea that Rosenstein and others argue saying that coordinated, broadly based investment program would be required for development. My evidence for this would certainly be the paper we have read last week. The paper also argues that the modern methods of production are potentially more productive than traditional ones, but their productivity edge is large enough to compensate for the necessity of paying higher wages only if the market is large enough, which I also thought was a strong and valid argument.

William Chapman

In the article, Krugman speaks about the downsides of requiring formal models and how this requirement pushed out high development when the ideas may have actually been beneficial to the field. Krugman puts forward a couple of examples from the past where correct ideas were pushed out before finally being proven correct. He mentions maps of the interior of Africa and using clouds to predict weather patterns. This argument seems flawed as there have been many times where traditional or unproven knowledge turned out to be completely wrong. There have been many superstitions over the years, such as magic or divine creation, that have been shown to be to be plain wrong. I believe it sets a dangerous precedent to say that in some cases it is not important to meet the rigors of a particular field. This is not to say I agree that these high development economists should have been exiled from the field. Instead, they should have continued focusing their efforts on finding ways to create models to represent their ideas or scaling their ideas to a more manageable position that could be more easily backed up and then built from there. Ideas should not be immediately dismissed in economics because they cannot be modeled but they should also not be automatically accepted without being put through the same rigors as other theories.

Olivia Luzzio

In his article The Fall and Rise of Development Economics, Krugman makes a compelling case for the importance of simplicity in developing theories about multi-faceted and widespread economic phenomena. Specifically, he discusses the importance of relying on assumptions to break down “high development theory” to a more basic level. I agree with this proposition because in order to test a theory in a variety of situations (such as across different countries and societies) it should first be tested in isolation from other variables, which is the role of economic models. However, I disagree with his reasoning that a half-century lag in economic development theory because of researchers’ unwillingness to use models was a setback. I believe the “fall” of economic development theory gave researcher’s the opportunity to expand and fine-tune their modeling techniques, which allowed development economists like Krugman to take advantage of them long-term.
A drawback to the modernization theories and models advocated by Krugman and other development economists like Solow is that they depend heavily on stable institutions. For modernization theory to succeed, industrialization and investments in human capital (such as healthcare and education) must also occur. This introduces exogenous factors which, while not included in the models above for simplicity’s sake, may be beneficial to model alongside mainstream development theories to increase their real-world applications. The “Big Push” story may be true, but we cannot be sure until we apply it to individual scenarios. As the role of institutions in economic development throughout the world becomes more apparent, I am interested to see if economists further build upon current models to demonstrate their effects, or if economic development heads into another fifty-year lag.

Adrian Lam

Krugman’s paper “The Fall and Rise of Development Economics” was especially relevant to me because I have some personal experience with modeling. I spent my last two years and summers modeling for my research position. My job uses mathematical in silico modeling to describe the circadian rhythms in spiders, so I agreed with many of the points Krugman made in his paper.

For example, I believe that all models are to a certain degree falsifications, but some are useful at explaining phenomena. In addition, I understand how difficult it is to balance between the simplicity and accuracy of a model. Since a model is only as good as its assumptions, you want to get all the essential assumptions into your model without overcomplicating it. This is why I believe Murphy’s model of Rosentein-Rodan’s Big Push was so effective. By only using several equations, it demonstrated that the decision to industrialize or stay in the traditional sector depends on other firms.

There were some parts of the reading where I did not fully agree with Krugman because I believe he overexaggerated the importance and impact of modeling. He argues that there are no alternatives to models, claiming that the “influence of ideas that have not been embalmed in models soon decays.” Although I certainly recognize the benefit and importance of models, I think they are only half of the puzzle. The inability to formally model economies of scales was probably only one of many reasons that caused high development economics to be bypassed.

In addition, I personally believe that the field of development economics today has gotten closer and closer to the consensus that every country requires its own unique analysis and strategy for development. We have so many different models today that attribute underdevelopment to different causes and propose varying solutions. Although simple models are useful, it seems like now is the time more than ever to go beyond modeling and figure out the complicated intricacies underlying poverty traps in different regions.

Going back to my modeling experience from my job, the model I worked with only got us so far. Without any data, the model was not very meaningful. Thereafter, it was incredibly important to go in the field to conduct an actual in vivo experiment with real spiders. Then, we used the differences between what the model predicted and what actually occurred to revise the model. Likewise, I think we should be wary not to diminish the importance of those ideas and observations that cannot be formulated through a model because these same observations can get us closer to the truth.

Danh Nguyen

“The Fall and Rise of Development Economics” by Krugman tells the story of the progress and debate relating to the field of development economics, particularly the development economics models. I completely understand people’s demand for a perfect economic model that takes into account exogenous factors and explanations for social phenomenon because these economic theories are taken into account when the government makes a decision. However, just like in physical science, it takes a very long time to make a good economic model, let alone a perfect one, and since countries vary so widely from one another, it is impossible to have a model that is representative of every economy. However, simplified models can further be elaborated by individual country to form applicable policies.
The biggest takeaway from the article in terms of development economics for me is how wage level is directly involved in the theory proposed by Hirschman. When wage is low, countries have more incentive to industrialize because people are paid at a premium when work in urban areas. When wage is high, there is no need for people to leave their homes and find a job somewhere else because they are already satisfied with their current state. People assume that wage is low in development countries, but I think one piece of the puzzle that plays a big role in this is how high the wage level is also depends on each country since the exchange rate vastly differs across countries. Right now, the GDP is adjusted to fit with the inflation rate and also the prices for baskets of goods. However, in the 1950s, this was hardly considered. Southeast Asian countries at the time had wage levels though lower than many developed countries but they could afford more compared to the same person with the same wage level in a developed country. They also failed to account for how some cultures were so deeply ingrained in agriculture, and the opportunity cost to leave their farm and family members behind was simply too much compared to the wage level offered in industrialized areas. The Big Push Theory is also a very risky one. It is said that the Big Push Theory might push a country into a virtuous cycle of positive economic development. However, debt budgeting is always a big decision for countries to make. Wrong decisions can lead to a push towards a virtuous cycle of lagging behind as the interest piles up and no money is reinvested into the economy. The answer to almost every economic and their applications is almost always “It depends.” So much more novel ideas are needed in the field of development economics, but as the article has proven, a lot of trials and errors are needed to test such novel ideas to see if they are applicable to a nation’s economy.

Sofia G. Cuadra

In "The Fall and Rise of Development Economics," Krugman offers important insight that, to me, harkened back to our first day of class. Krugman attributes the fall and rise in the acceptance of high development theory directly to the growing use of mathematical, economic models that occurred throughout the latter half of the 20th century. Essentially, the theory disappeared from mainstream economics because the theory failed to mathematically incorporate economies of scale into a simplified model. Krugman goes on to explain the limits of modeling and how they fail to capture the entirety of reality, but regardless of this fact, economic modeling should not be dismissed as it still can provide us a roadmap of reality, a more digestible way of looking at and explaining phenomena. His advice then leads to the recommendation that economists, at the same time, should not forget the main idea of one explanation just because the idea cannot be formalized. He is not recommending that we lower the standards of what classifies as strong, economic analysis but rather to strike a balance in understanding the potential value in all ideas.

To me, his recommendation liberates the approach to economics and makes it more accessible to a wide range of people, beyond experts. I believe it is important to remember that in developing countries, it is critical that the local population/experts have a chance to share their ideas of what could help growth or their opinion on a policy that implements a specific economic development theory. After all, they are the one's on the ground experiencing daily hardships. Just because their ideas cannot be formalized, does not mean their ideas lack value. Of course, models should be used whenever possible to justify economic theories of growth, but they are not the end all be all to sustainable development. Together, valuing both models and unformalized ideas can allow us to ask the right questions for effective policy, even more so than if we solely relied on economic theories that fit the mainstream.


In “The Fall and Rise of Development Economics,” Krugman described the history of the discouragement and re-establishment of the high development theory. While the theory contained much value, it was rejected as a valid theory of economics because the economists supporting it could not, due to a lack of modeling technique, produce a model to prove it. Through this essay, Krugman encourages economists to bravely use simplified models that omitted much complexity of reality since such models can deliver the results needed.
While I value the encouragement Krugman delivers in this article, I hesitate to agree with the Big Push model because it controlled so many variables that I do not imagine a real society to resemble the one presented in the model. Without resemblance, the model would lose its value in explaining how society works. The model assumes the modern sector to produce the same product as the traditional sector. With better technology in the modern sector, I think the modern sector would necessarily produce products of better quality. In this case, the companies have a fair reason to raise their price, which would help them earn profit even while giving workers premium wages. Even if we abide completely by the assumptions and assume modern sector companies only deliver products identical to those of the traditional sector, increasing marginal returns should enable the company to reduce in production cost, which allow companies to profit while paying works premium wages. Therefore, I believe people from the traditional sector would be incentivized to move to the modern sector.
What’s more, the Big Push model fails to account for many externalities that can happen in reality. The desire to explore a big city, for example, can drive people to enter the modern sector even without the guarantee that they would survive there. In that situation, premium wages are no longer necessary since the there would be a surplus in the supply of labor.


As I plan to major in a natural science, chemistry, I found this article very fascinating as it discussed both social science and material science. Krugman talks about models and their inherent nature to focus on a specific detail or factor while subsequently leaving something out of the picture. As we try to model and hypothesize very complex problems, it is necessary to break into more manageable parts; when we do this decisions and assumptions need to be made. When we think of the social science of economics, more and more assumptions are made to bring a model to simpler and broader terms. You can play with these factors, but any one model is limiting in its own right. This makes me think that economics, as much as it tries to be, is not as much of an objective science but perhaps more of a subjective one. Every scenario, depending on its specific exogenous and endogenous factors, is worthy of its own manipulation of a broader model. So in my opinion, how one uses a certain model is foundational to the model itself.
Dr. Uffelman always talks about good scientific models both describe how something works but also can predict accurately how a system will act in the future. When I think of some of the economic models that have been accepted and used and the ones that have been denied, my mind goes to Harrod-Domar model and its usage. It was a great model for post World War 2 Europe but it was not an effective model for other developing countries in different scenarios. It was used for quite some time with these other scenarios. It is not so much that this model was wrong, it is just that some of the assumptions made were for only post WW2 countries and not for other scenarios. There was a disconnect between the actual model and the application of it. Factors need to be checked and altered according to different situations. Models are great ways to describe and predict but they can naturally only take you so far, especially when they are not used entirely

Alice Chen

As I read this article, two points stuck out to me. First was the slump of high development theory. High development theory was interesting to read because it ties directly into what we covered in class. Krugman points out that "modernisation breeds modernisation" and poor countries remain poor because they haven't found a way out of this trap yet. Governments should intervene at this point, but corruption and even improper economic advice can keep these countries stuck in the poverty trap. Additionally, most poorer nations are mainly agricultural. Without the "modern" tools to develop, how can these countries overcome the poverty trap?
Additionally, Krugman heavily discusses the shortcomings of models. It's safe to say that we largely rely on models to analyse economic phenomenon, and Krugman describes a good model as one that "succeeds in explaining or rationalising some of what you see in the world in a way that you might not have expected". However, he points out that these models also rely heavily on assumptions. In class, we've discussed how the Lewis two-sector model has 4 key assumptions that we have to keep in mind, which is why it hasn't been extremely useful to describe many developing nations except for China. Other models, even physical ones like the dishpan, assume certain conditions as well. However, Krugman ends on the note that there are no alternatives to models. In fact, we all think using models and the only thing we can do is be aware that they are maps instead of reality.

Kristina Lozinskaya

I feel like “The Fall and Rise of Development Economics” by the Nobel laureate Paul Krugman serves as a nice continuation of the discussion of the history of development economics that we started in class this Tuesday which allowed me to see a bigger picture of the evolution of ideas and concepts in economics back then. In the paper, Krugman in a provocative and sometimes funny manner explores what he believes to be a “methodological” crisis of the high development theory of the 1950s. He illustrates this methodological crisis as the conflict between mainstream economic theory and the new kinds of ideas that were present in high development theory. By these ideas, Krugman specifically means the fact that economists had to make a certain set of simplifying assumptions (like, for example, the 4 Big Assumptions of the Lewis’s two-sector model that are not always empirically strong) to build their models – the assumptions to which mainstream economists were becoming gradually more hostile since mainstream economics was moving in the direction of more formal and careful modeling. Krugman argues that this hostility resulted in the fact that the high development theory was simply bypassed because nobody back in the day, due to the limited knowledge, could really create a model that would not rely too heavily on the oversimplifying assumptions which led to an even worse outcome: long slump in the development theory that entailed with it the loss of knowledge.
The paper thus really makes you appreciate those life-saving assumptions without which economic analysis becomes incredibly complex. Indeed, economics is an extremely multi-faceted type of science that relies on assuming that human decisions that guide economics are rational. And, funny story, one of my friends once gave me a weird look when I told him that I was going to study Economics. “Why would you want to major in such an unrealistic field that assumes that humans always act rationally when in fact they don’t?” (oh yeah, I guess it is now obvious that he is an Anthropology major). At the moment, I thought, well, it is precisely how we learn to make sense of the complex stuff – by starting with things being simple. And this paper resonated with this idea in that it is essentially a call to dare to be silly (my friend did have some truth in his argument, of course) like Murphy was when formalizing the Rosenstein-Rodan Big Push model. Murphy and colleagues “opted out of the mainstream,” “exploited the bag of tricks,” and for that Krugman praises their work. It’s actually astonishing how we just take the rationality of the models that we see for granted, not recognizing how much work and brain-wrecking went into their development (like the Solow growth model the applicability of which just blew my mind in class). When, in fact, the clue, it seems, is to simplify, to make a world in a dish-pan.

EC Myers

Questions! I have many!

Perhaps I am confused on the definitions of "market size" and "economies of scale" because prior to this paper, I thought they were the same thing. I'm now realizing they are not!

I'm very fascinated by the idea of forward linkages and backward linkages. I'd be interested to see which economists support Hirschman's definitions of these terms and how they have supported this with data. Have backward linkages proven to occur more often and more successfully than forwards linkages? Or is it vice versa? OR do we not have enough evidence that either work at all?

I'm also puzzled by the statement that "economies of scale were very difficult to introduce into the increasingly formal models of mainstream economic theory" because this seems like the opposite of what I know about economic theory, which granted is not all that much. I would have thought that economies of scale would be what mainstream economic theory is based around, both formal and informal. Is this the case but perhaps its just that it is difficult to introduce them into models if the models were not built based on economies of scale? While the author does discuss this a bit more in the section mentioning Ricardo, it is still somewhat unclear to me as to what kind of models were used to describe non-economies of scale and how they were not more difficult to incorporate in comparison to economies of scale.

I was very frustrated by the author's negativity towards other economists until he finally acknowledged that economic models cannot include every single aspect, just like the weather pan experimental model. This was the first part of the paper that I didn't feel like I had to question, which was nice. I found the history of questioning social sciences very interesting, too. Its a very good point that people would prefer to attack the assumptions of an analysis rather than question what their personal beliefs are based upon.

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