In "The Fall and Rise of Development Economics" I started looking at the models that I've continually been shown since my high school economics class with a new perspective. I've looked at the information and answers that come from the standard models in econ as a very defined set of solutions that are always correct and as eternal as gravity. But looking back on the answers that some of the models have presented it is now obvious that some of them are based on a decent amount of simple assumptions that might not always be right. This doesn't inherently make them wrong or make them lose their credibility but instead highlights that "if the model is a good one, it is an improved insight into why the vastly more complex real system behaves the way it does". In a world that is so infinitely complex and hard to understand, these models can give a lot of us solace as well a basic understanding of how to approach many problems. Thanks to Krugman's insights in the article I can also understand why certain people like Hirschman would refuse to use these simplistic models to get a basic understanding. In Krugman's words "model-building, especially in its early stages, involves the evolution of ignorance as well as knowledge; and someone with powerful intuition, with a deep sense of the complexities of reality, may well feel that from his point of view more is lost than is gained." For some people, these models and their short scope of accuracy might not be worth the depth that is lost by using them but in my eyes, the gained insight is entirely more useful than long-winded metaphors. In general, the article really made me think more about why we use models and what exactly is their cost and benefit.
Krugman has backed me into a corner. The Rise and Fall of Development Economics stirred in me an uncertainty that’s not particularly comfortable, but that ignited a series of deeper economic thoughts to which I had not given much consideration. Models are both the villain and the hero in my study of economics so far – I am a right-brained person with little skill in mathematics, but a model always clarifies my studies far better than reading and rereading definitions can. I feel woefully uncomfortable when faced with a statistics or econometrics problem, but visualizing curves, lines and intersections provides me with a deeper understanding of what’s in front of me. Krugman’s mention of Alfred Marshall and his tendency to tuck away difficult or confusing math and models in favor of parables and metaphors at first sounded like my kind of study. But later in the paper, Krugman talked through the Big Push with words. I was lost, and I scrolled to the bottom of the article for clarification in none other than a graphical model. So how do I, as a student of economics, deal with complexity? It appears I utilize both metaphorical, value-laden words and clean, crisp economic models. With that, I fall in line with Krugman. There is an intersection between the two that can provide those of us with an inclination for the written word a pathway to better understanding through visualization and analysis. In microeconomics, I read about supply, demand, perfect competition – but the multi-colored model Professor Kaiser drew on the blackboard is permanently engrained in my mind. I could reproduce it in my sleep – though I could never repeat the words I read. My personal dichotomy translates into the broader study of development economics in that parables can provide a framework for study or a simpler version of economic theory for those unable to understand graphical or numerical renderings. But models provide a more visual understanding of how development economics can be translated into policy. Neither option is perfect – the words are over simplified and the models are perfect in an imperfect world – but the two paired together are unbeatable.
This paper brings to light the interesting debate of simplification. In all of the Econ classes I have taken we have always looked to simplify the issue into only a few variables, often making huge assumptions such as everything else remaining the same (ceteris paribus), or that there is a perfect market where labor and goods are always perfectly traded. And these simplifications are always encouraged and taught to better explain the issue.
After reading the article and seeing the slump of over simplification in the history of development economics makes me question the assumptions we make to simplify the problems in all of our Econ classed. The simple models do help explain some economic ideas and support different theories, but are they applicable to the real world and should w be using them to defend policy change? By making assumptions in the models and leaving out variables to simplify them, we change everything and could come to solutions that couldn't be further from the truth.
I thought one of the most salient points of “The Fall and Rise of Development Economics” was the inherent variability of the data, and what constitutes an effective development policy, based on the country or region being observed. Hard data definitely serves its purpose, but as Krugman states “the pressures to produce button-down, mathematically consistent analyses” needs to be resisted “and adopt instead a muscular pragmatism in grappling with the problem of development.”
We are learning about a similar problem in my econometrics class this term – a regression equation can never account for every variable that influences the explanatory variable, yet the statisticians do their best to incorporate any foreseen and measureable variable in addition to an error term to try and statistically explain the relationship between two or more variables. And yet, despite this careful math, when the social and anthropology qualities are taken into account (even of the same variable) the explanation for the equation becomes unique to the population being analyzed. Simply, the numbers are not sufficient.
Krugman touches on this point when he highlights the importance of economies of scale to high development theory. However, these models “were very difficult to introduce into the increasingly formal models of mainstream economic theory” and so for a time were ignored. I think an essential aspect of development economics is to separate from traditional economics. Yes, while the basic studies are similar – a focus on markets, representative pricing, full information, utility maximization – the applications are totally different. Often, traditional economic models deal with theoretical situations while development economics attempt to quantify extremely tangible circumstances for the world’s poor.
Ultimately, I think the most noteworthy point of this article is that development economists must adhere to a “discursive, non-mathematical style.” I would add, however, that the use of statistical analysis as a means of quantifying data sets is a useful tool in the field. However, once again, these computations must be analyzed through a lens that takes into account the circumstances under which the data was taken, the culture of the population, as well as potentially extraneous, but important, variables that are not included in the regression. Numbers are not enough, but numbers combined with informed decision makers sets the stage for effective and targeted aid and change.
Upon reading “The Fall and Rise of Development Economics” and thinking about Kruger’s model, I found one particular scenario especially interesting -- that which occurs under the condition of very low wage premiums. If wage premium is low, this means workers are receiving a meager compensation for what seems to be much more strenuous modern sector jobs. Of course, the low cost of labor allows for business to grow quickly and, consequently, for the economy to balloon. What I am envisioning as a modern sector job in a developing country might be described as hundreds of underfed and sleep deprived workers, routinely assembling their product, packed into a massive yet grimy factory. Additionally, working this type of job in a developing country would probably entail extremely bleak living conditions in a hurriedly industrialized area (most likely lacking sufficient sanitation or quality air). Whether or not this portrayal is accurate, I am not totally sure. However, it seems likely that standard of living will suffer for workers as the wage premium declines. Is this story similar to the unprecedented modernization of China? As an additional aside, it seems likely that this trade-off would decrease the incentive one might have to leave a traditional sector job to take a modern sector job. Was this considered in the model and could it serve as an impediment to development? What are some ways by which this wage premium is variable? Is Krugman suggesting that the government of a country effectively kick start the modern sector so that less would be needed for common profitability?
While reading “The Rise and Fall of Development Economics,” I very much enjoyed Krugman’s insights on the use of modeling in economics. Since taking introductory microeconomics I have been fairly cynical of the effectiveness of economic models due to the number of assumptions that they make; however, I thought Fultz’s dish-pan experiment was a powerful analogy to include to illuminate how extremely simple models can be effective. Even quantum mechanics—the author’s example of a completely describable field, and (I believe) the most fundamental of scientific endeavors—is non-deterministic, with inherent uncertainty in measuring a particle’s location and momentum at any given time, but it is still highly valuable in making predictions about the world. Moreover, in defense of the trend towards models over metaphors, it seems as though because economics is so inextricably bound to politics, it makes sense for economists to demand quantified, formalized ideas in order to avoid obfuscation by the researchers’ biases and ideologies.
In addition to formulating these thoughts on metaphors and models, I also noted that one assumption, made by Rosenstein-Rodan in his model of transferring those with 0 marginal product of labor in agricultural or rural jobs to the modern sector, reminded me of the article we read for the first week of class, “The Economic Lives of the Poor.” In the “Economic Lives of the Poor” we saw that many people living in developing countries make what economics would deem inefficient decisions, such as buying sugar even though it lacks nutrients, simply because they want to, and don’t necessarily think about optimizing their long-term outcomes. It seems like something similar could occur in transferring workers from the agricultural to the modern sector: even though these workers might earn a higher wage in the modern sector, there are non-monetary costs associated with moving, and I think cultural influences, family obligations, resistance to change, etc. would deter many from making this switch, thus compromising one of the main assumptions of the Big Push model. Like I said, though, I am definitely sold on the models.
In the beginning of the paper Krugman mentioned Hirschman’s strategy to reject “buttoned-down, mathematically consistent analyses” and replace that with “muscular pragmatism” in the field of development economics. This means, to me, that economists should not automatically narrow their minds and make their mission to solely ‘prove’ something with a model. Instead, they should work to use some degree of an interdisciplinary approach when tackling their research, and think of the many complexities of humanity. This does not mean that there is no place for models in economics, or that we should be making them more complicated. I appreciate Krugman’s assertion to be aware of the simplicities when reading models, because they are still very useful in explaining and giving some substance to a theory, but the reader must remember a model has its limits. This leads me to our discussion of Kremer and his paper on the deworming children in order to increase educational outcomes, which all started with the simple logic that investments in education must be creating benefits. Sometimes, you have to be able to back up from the economics of the situation and realize the models are not always perfect. In Krugman’s conclusion, however, he asks us if we are sure we really have the insights that can reverse the modern economics community, so the main point I have gained from this piece is to simply be aware of the complicated process that creates the simple models we see in our textbooks and to understand their strengths and weaknesses.
Paul Krugman points out one of the biggest shortcomings of economic theory, the use of simple models to explain the complexities of the world. I personally believe economists rely too heavily on assumptions in their models causing them to be too simplistic and, therefore, inapplicable for real world considerations. However, I understand that many real-world factors are impossible to fit into a model. To use Krugman’s example, economies of scale are crucial to high development theory and should not be ignored when studying developing countries.
When considering economists’ struggle to accurately fit economies of scale into their models, I couldn’t help but think of the current struggle capture the effects of global climate change into models. The threat of global warming has serious implication for developing countries and no modern development theory should ignore this. In Environmental Economics, we learned the effects of climate change are measured in negative externalities but this doesn’t capture the true costs. While this is another example of the shortcomings of simplified economic models, the complete effects of climate change would be impossible to boil down into a single model.
This paper creates a dynamic discussion on the role of models in economic theory. While I think Krugman’s conclusion 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” is pretty harsh, it was interesting to get Krugman’s opinion on the different stages of development economic theory and how the subject has evolved over time. The main takeaway I have from this paper is that models are essential to economics because they allow us to make valuable estimations about the real world. As long as people utilize them with the caveat that they do not capture all aspects of reality, I think they should remain a part of the evolution of economic theory.
This paper covers a lot of ground and provides a good overview of the history of Development Economics. However, I would like to focus my thoughts on the degree to which research impacts policy.
Krugman said that high development theory was dismissed for a time because it lacked formal modeling. The theory challenged standard assumptions, including the existence of a perfectly competitive market and constant returns to scale, which rarely hold in practice. But in the absence of equations and graphs, the theory simply lacked the persuasiveness to gain widespread approval. As a result, Krugman added that the traditional “constant-returns, perfect-competition view of reality took over the development literature, and eventually via the World Bank and other institutions much of real-world development policy as well.”
I found this reality interesting in light of my experience last summer, when I interned for a political consulting firm in Washington, DC. Our bipartisan firm specialized in education and workforce issues, and frequently advised organizations on how to respond to new legislation. As such, one of my responsibilities was to attend congressional hearings and brief my supervisor on what was accomplished.
What I observed frustrated me, and often did not resemble the manner in which I imagine the high development was dismissed by policy institutions like the World Bank. I often listened to congressmen propose legislation about a certain issue without seemingly any data to support their stance. In an effort to get out in front of a potential conflict or change the status quo, politicians seemed fine with abandoning old policies and instituting new, untested ones.
All this is to say, that Krugman’s paper got me thinking about the history of development economics and led me to believe that the high development theory would have impacted public policy sooner had the political climate in the mid-1900s resembled that of today.
While reading "The Rise and fall of Development Economics" I appreciated his use siting different papers to help get his main ideas across. The paper I thought was very helpful was "The evolution of European ignorance about Africa," (pg. 3). This paper describes the changes in European maps of Africa from the 15th to 19th centuries. In the 15th century these maps were relatively inaccurate about coastlines and distances among other things, This was a result of the fact that the information being used to create the maps typically was second hand from travelers. By the 18th century the coastline had become more accurate on these maps, but the interior emptied out, the real cities and rivers had disappeared from the maps (pg. 4). Finally by the 19th century the maps of Africa were accurate. After reading about this paper, I found it significantly easier to understand what happened to development economics between the 1940s and 1970s. In addition it also helped me further understand his argument about models. Maps are obvious models, and easy ones to understand. Like a model they are over simplified to help you view an area. For example if you look at the map of Africa again you will notice that on the right there is the Indian Ocean and on the left there is the Atlantic Ocean. It can also tell you that Africa is south of Europe and that Madagascar is off the right coast. Just like a model it is oversimplified to help people understand where Africa is in the world, where the countries with in Africa are, and how some of the basic terrain is. What maps cannot tell you about Africa is the culture of each country, the animals that inhabit each area, the different languages spoken, and so much more. Just like economic models, in order to understand where countries are in the world you must simplify the country down to just it's basic location. You may be able to draw minimal conclusions about a place you've never been from a map, but until you've been there you won't understand much about that place. This is similar to a model that you may be able to draw some conclusions from it, but what happens in reality might not match up with the models predictions. Finally I also really enjoyed Krugman's closing remarks, "nd for those, like me, who basically try to understand the world through the metaphors provided by models, the advice is not to let important ideas slip by just because they haven't been formulated your way. Look for the folk wisdom on clouds -- ideas that come from people who do not write formal models but may have rich insights. There may be some very interesting things out there. Strangely, though, I can't think of any," (pg. 12-13).
The main theme I drew out from Krugman's "The Fall and Rise of Development Economics" was the idea of simplicity. His belief is that Development Economics did not make significant strides between 1940 and 1970 because they were not able to break down their ideas into more straightforward easily understood models. They could not "dumb down" their knowledge, and became too lost in the details inhibiting them from seeing the bigger picture. Economists such as Albert Hirschman were not wrong, however they didn't portray their knowledge in an efficient manner, "We can now see that high development theory made perfectly good sense after all. But in order to see that, we need to adopt exactly the intellectual attitude Hirschman rejected: a willingness to do violence to the richness and complexity of the real world in order to produce controlled, silly models that illustrate key concepts." Krugman seems to be saying to these economists - We know you're incredibly intelligent , but swallow your pride and produce a more simplistic model without getting lost in the complexities of the problem.
Breaking concepts down into their more elementary elements (such as outlining textbook chapters) is something we do as humans everyday - it is how we learn. Reading Kinsey's comment above rang true to me. It is quite common to feel your brain spinning when first reading dense material on a new subject, but when a simplistic model is drawn on the board - such as a supply and demand curve - it gives a base in understanding the material then allowing for pursuance of more complicated knowledge on the subject. It also makes that once dense reading more likely to make sense. Much like Krugman it is hard for me to understand why these economists could not simplify their models. If they did maybe we would be further along in Development Economics than we currently are today.
The mistakes in economics, in particular to ignore high development theory for several decades only to return to the thought, reveals several lessons to me. Thought is often going to be ahead of modeling, as it should be. Great thoughts may arise, but often times the numerical support to "prove" the thought may not be present. Thus, I believe that too much emphasis is often placed on models over thought. The prediction that complex models reveals can often dictate political policy that is used in practice, but these predictions are not always correct. Sometimes, we must step back and examine things in a logical manner of reasoning. In reference to the high development theory, I think the idea that "modernization breeds modernization" simply makes sense. Even though it took several decades for a model to be generated, the idea should not have been completely ignored until the model was formulated. By examining this idea in nature, maybe the concept can be displayed more clear, but by ignoring the thought entirely, it was a loss to the expansion of the discipline of development economics. With this being said, ideas cannot be examined with such a narrow-minded perspective. Examining surrounding factors can often illuminate some such trait that would make this inconceivable idea conceivable. Thus, often times the best perspective to take may be the simplest one. When you think of traditional ways to increase development, GDP/capita stands out, yet a number of complex factors go into this equation with the fact that markets are not entirely perfect. Here, one is able to draw comparisons to Sen. To say that development should focus on capabilities is quite simplistic, yet it took many years of complex models failing to provide an adequate solution. In today's world we can see that improving capabilities in turn does an amazing job in alleviating the problems of developing countries. Thus, from this realization shows complex phenomena can often be solved through simplistic manners. Examining something with from a complex perspective makes economics more difficult than it needs to be.
I found Krugman's article very insightful, because I for one tend to have a hard time relating to some of the models we have looked at over the years. I remember the frustration of sitting through Prof. Guse's microeconomic theory class as we poured over model after model that would hold true "given certain assumptions." These assumptions seemed impossible to hold true in reality and I found myself frustrated with trying to study something that may not be able to ever play out in the real world.
That's why I found myself so interested in behavioral economics and the electives offered in economics. There we got to see how the real world actually operated and how to approach the real issues that affect us in an economically real sense. I do however, recognize the necessity of the models. Even policy proposals we developed in class were based not on metaphors and anecdotes, but rather models that were developed. That is why I found myself at a crossroads after reading this paper. This paper I feel addresses the intersection between behavioral economics and economic theory; The necessity to keep developing models, while also gaining insight from how things are playing out in real life.
This paper brings to our attention a couple simple words that are learned in any introductory economics classes: ceteris paribus. I remember my freshman year introduction to microeconomics class in which people constantly asked “but what if you changed this or that” or “how could you assume that would be true”? At first it seemed odd and unrealistic to be using these graphs with only two products or only two sectors to explain our entire world economy, but the more economics classes I took, the more I became comfortable with this idea of assuming away any complication. However, Krugman brings back up that initial discomfort that many of us freshman exhibited when we questioned the validity and applicability of such a limited model to the real world. Now, in my microeconomic theory class, I am slowly being made aware of all the short comings that the introductory microeconomic models had. In order for us to gain any understanding at all it was necessary to at first make simple assumptions, however now that we have gotten to higher level classes it is assumed that we should be able to think critically about the assumptions being made, and further have a better understanding of what may happen if one of these assumptions were to be violated. Professor Goldsmith’s favorite “game” is ceteris paribus violation in which he forces us to think and question how some of these models may change if one of the assumptions were to not be true. While Professor Goldsmith makes a point of the model’s limitations, there are countless paper’s that I’ve read for other classes, which tend to forget that ceteris paribus violations do occur in the real world and this is what Krugman criticizes most. It seems to me that the best economists would combine the models and math with sound reasoning in plain English to explain economic phenomenon so that we can not only understand how the model should work in the real world, but also further question what may happen if certain assumptions are violated. I found this paper thought provoking as it caused me to reflect on how the models I have been taught have been expanded and changed over the 3 short years I’ve been studying economics and how much those classical models may change for economists who are on the cutting edge of research in new fields for example.
This paper touches on a lot of the struggles I have wrestled with in Economics. I am an Econ major, but was always bothered by the oversimplification of models. I loved learned about perfect competition and running through the logical steps or price changes and changes in elasticity in my head. It was fun, made sense, and helped to explain a lot of the decisions consumers make in the world. It was all fun until it didn’t actually work in the real world. If you look closer, what the models predict and the actual decisions people make are often not the same. People aren’t rational, trying to maximize totally benefit, and working in a perfectly competitive market. So I wondered, as I walked out of my Econ 101 class, how you actually try to make economic change in the seemingly complicated and irrational world we live in. It seems like development theory went through this same process. They made models and then abandoned them because they didn’t know how to apply them in policy. From there, they turned to metaphors and logic to explain phenomena, only to discover that you really do need models if you want to have a large and lasting impact on development theory. Krugman notes that theories, “do not endure unless codified in a reproducible -- and teachable form,” aka, a model. To me, it is understandable that many thinkers in those “lost years” turned away from models. Sometimes they don’t work, and they wanted to try a different approach. However, as the author points out, there is not other option except for models. It is not a matter of turning to a different medium for explaining the economy, but working on the actual models. You have to be creative and try and make different models to isolate different variables, helping you understand another piece of the puzzle. You also have to understand the limits of models. They are not a panacea, but just a useful way to understand some past experiences and try to predict what might happen in the future, given a set of conditions. Reading this article has really helped me come around to the idea of models again. They really aren’t these hypothetical situations that I can just forget about, but real tools that should be used in the right situations.
There are several points I find really interesting about this article. First of all, I think it is frustrating to think about the amount of years of knowledge that were lost because of the mere fact that some thoughts were not able to be written or presented in models. I honestly did not know of the relevance of development economics until some days ago. Development, as Todaro and Smith describe, is a “multidimensional process involving the reorganization and reorientation of entire economic and social systems” with the purpose of searching for models and forms of implementing solutions to increase people’s living standards and freedom. Knowing this, I think it is really disappointing to think about the time that was lost and the fact that a field as important as this one could have suffered such a “long slump”.
The other aspect, I believe, was interesting and we have gone through it in class, is how models of almost every system are “to some degree a falsification,” as they leave aside many aspects of reality and they involve an amount of assumptions that many times do not apply to real life. I think it is interesting how representing the world in simple models is important to get an essential point or several key points about our society.
As I was reading the article, I was thinking how, in the same way economies of scale represented a problem (as economist did not know how to incorporate this important concept to the existing models), freedom as presented by Sen, is also an extremely important concept in development, which is hard to introduce to models. Freedom is not a quantitative variable; however, according to Sen, it is not only the main end of development, but also the means to achieving that main end. In my opinion, it is shocking to think that Sen’s idea would have “decay” due to the fact that it would “have not been embalmed in models.”
The “Rise and Fall of Development Economics” addresses some of the issues that I have had with economics classes in the past. While I have only take intro to micro and macroeconomics, I could not fully understand the application of the models. It seemed very theoretical and couldn’t be applied to the real world. But as economics classes become more advanced, one has the opportunity to put more thought into the models. As a freshman, I was only trying to learn the models and understand them, but not apply them. The application aspect is important when getting closer and closer to entering the work place and leaving behind college. I now look for answers. The paper discusses the need for explanation behind these models and how there are so many different factors that are involved in them. Even a religion can deter a model from being correct. One’s set of beliefs can throw them off. Each model must be applied a little differently to situations. My whole life, I have related school and other things to sports. To me, this seems as if a coach comes up with a strategy, but refuses to change despite the other team making changes. Even if the other team has figured you out, you stick with what you are doing instead of making a few adjustments that would allow you to win the game. This is the way that I was able to understand the paper more fully.
Before reading “The Fall and Rise of Development Economics”, I had never really given much thought into the development and history of economic thought. One aspect of the article that I found particularly interesting was Krugman's explanations of the role of economic modeling. In the Econ classes that I have taken in the past (macro and micro), we were taught a number of different models. But while we were learning these models, I never really questioned where they came from or how accurate they were. This article really made me consider the evolution of economic modeling, and how it is important to remember what key assumptions are being made to form these models. I think this ties in nicely with our class discussion on foreign policy and decision-making. It is crucial to remember that while these models can be useful, they are built upon a number of important assumptions that are not always true in the real world.
I also found it interesting how the author related economic modeling to other types of scientific modeling (such as meteorology and physics). It was an interesting way to think about economic modeling, and reminds us again that models only work under a certain set of assumptions and conditions that are not always true in the real world. I also thought it was interesting to learn more about how economic models were become less mathematical. This makes me consider the accuracy of these models. They are often simplified and only make sense under a specific set of assumptions that are often unrealistic in the real world economy. This makes me wonder what other components we might consider in order to make our modeling more accurate and realistic when studying trends in the economy.
Being someone who always looks at models in economics and thinks “but what if…” it was very refreshing to read an article that didn’t stress the necessity of a model in order to come to a conclusion that could be correct. In fact, it is as if Krugman taught us a life lesson in the article: that if something isn’t there the first time you think of something, don’t give up on it altogether. In a way, Krugman’s article reminded us that economics is a social science and must be treated as such. There is almost never a single correct answer, and there are always different ways to come to any conclusion. Krugman also teaches that any conclusion must be backed with sufficient evidence or a strong argument. It is not acceptable to say this is what I think and everybody must accept it; there must be an explanation as to why you think this and what evidence there is to back it up. This is true of any of the social science disciplines, including economics. In Krugman’s view, it was important for a model on Hirschman’s High Development theory to be created in order to provide evidence for Hirschman’s original theory. This article both teaches a piece of the history of development economics and a life lesson: never give up on an idea just because it cannot be proven at a given time.
I agree with many of the individuals who commented before me. The increase in the complexities of the models is quite staggering. However, one typically believes that a more simplistic approach to an economics model would allow it to be more easily understood; yet it appears that the move towards complex models is not quite as helpful, though it is accurate. It is in this manner that the simplistic approaches maybe better due to the fact that they are all encompassing. Consequently, this defines economics as a social science rather than a mathematical equation. This article validates the fact that it is dealing with individuals whose decision cannot always be calculated. Thus it is in this manner that you cannot predict every one or everything’s actions but rather can predict what the massive body will choose to do. Thus, it is the natural assumptions that tend to corrupt the economic models that we use.
In "The Fall and Rise of Development Economics", Krugman highlights the "high economic theory" and illustrates why it unraveled even though it made a lot of sense.
As an economics major, I tend to sit through many classes in anger at the simplicity of models that are attempting to describe or "map out" our economy. I understand that the economy is too complex to truly map out in a model, but I always wonder if the conclusions we draw from these models can be leading us in the wrong direction when we assume, for example, perfect competition, closed economies, etc. I also wonder to myself when a model makes sense, whether there are outside factors that we might be overlooking that affect the model, which usually turns out to be true.
I believe this article is important as Krugman points out that while models are very useful in describing how the economy works, the bottom line is that the economy is too complex to ever map out on one simple model; therefore, Krugman urges not to get too caught up in models, and overlook important insights or concepts simply because it is not laid out or "formulated" in a model.
Development Economics as complex as it may seem should definitely not be seen as inferior to mainstream economics first and foremost and is one of the points Krugman emphasizes in this article. It was also mentioned that mainstream economics even began to acknowledge the usefulness of development theory and modeling techniques. Models are great ways to bring ideas to life and in the development perspective, it is important to understand that models should also not be limited to basic ideas such as constant returns as was done in the past. With the dish-pan analogy, it was easy to understand how models bring great ideas and theories to life through visual representation. While reading this, I tried to look inward to see how this whole verbal versus visual factors played a role in my own life and I recognized the need for an interaction of both and this is precisely what Krugman is hammering at. I think the decaying of high development theory historically gave room for a better and more nuanced understanding of development economics and the importance of models in policy making decisions. By looking from this perspective, it is therefore imperative to understand that despite the seemingly complexity of development economics, much can be done with the interaction between metaphors and models in a way that helps construct simple, effective, and long-term policies in the development field.
Kruger’s analogy to the map of Africa resonated with me and reminded me a lot of our discussion in class last week. Uncertainty bred ignorance when cartographers refused to consider or incorporate information that may not have been entirely accurate or easily represented. This in turn gave way to passivity and the interior of Africa remained blank until there was complete confidence in cartography technology. The notion that a failure to produce a perfect model of something would discourage or discredit efforts to engage with or understand ideas is incredibly concerning to me, particularly in the context of development.
Similar to what we discussed in class the other day, just because we cannot always determine definitive casual relationships between phenomena does not mean we should shy away from alleviating the suffering. Ultimately the models are not the primary concern and should never preclude us from doing something poverty. Of course models are often incredibly useful. However, just because we struggle to craft the perfect model, does not mean we should shy away from or delegitimize the underlying theories or ideas. In accordance with Sen’s freedoms-based approach, poverty-related issues can rarely be reduced to numbers and statistics. Oftentimes the complexities of poverty make it difficult to model and understand but that does not mean we should not try.
Paul Krugman presents a compelling case for the use of simplified models in economic study, one that I wholeheartedly support. An excerpt I found exceptionally eloquent and succinct was, “You make a set of clearly untrue simplifications to get the system down to something you can handle; those simplifications are dictated partly by guesses about what is important, partly by the modeling techniques available. And the end result, if the model is a good one, is an improved insight into why the vastly more complex real system behaves the way it does.”
This sentence brought several connections to mind. The first, though not pertinent to economics, is an interesting point to speak to Krugman’s overarching thesis that modeling is essential, and arguably inherent to human nature. Aldous Huxley, author of popular high school English unit “Brave New World”, once wrote that the human brain essentially spends all its time performing an analogue to modeling, in order to present us with a version of the world with can function in and interact with. He claimed our brains and nervous systems are designed to block out information and stimuli that needlessly complicate the situation at hand, much as economic models do.
Another drew me back to a class with Professor Eastwood, in a course called Neighborhoods, Culture and Poverty. During discussion about the complications of addressing persistent, multi-generational poverty, the class began to despair at the web of interconnected variables that affect a child’s economic outcomes. Everything from the neighborhood the child grows up in, to the education of her parents, their proximity to community centers and the area’s capacity for collective action plays a role, and untangling the complexity seems insurmountable. Krugman and Professor Eastwood make similar points regarding this challenge, in that simplification is a necessary step, despite the outcry that may come of willfully making untrue assumptions or detaching oneself from the “deep complexities of reality”. Instead of turning away from models because they cannot represent accurately our reality, it is useful to apply them as the best alternative to glean as much information as we can, until our tools become advanced enough to “transcend those limitations”.
One of my favorite lines from Krugman's Fall and Rise of Development Economics is his defense of simplistic models in complex systems- they give insight into why the "vastly more complex real system behaves the way it does". I find Krugman’s embrace of the unsophisticated to be both refreshing and essential to studying economics. His insight that these basic models challenge us to go out and measure instead of us giving us a false sense of understanding is especially pertinent to development economics. Yes, it is important to intellectually understand the economic struggles of developing countries. However, it is the resulting action that makes the impact.
Reading through this article, I find it easy to see why this is one of Professor Casey’s favorite pieces. An emphasis on models with an ‘it depends’ disclaimer- what more could you ask for?
In "The Fall and Rise of Development Economics" I started looking at the models that I've continually been shown since my high school economics class with a new perspective. I've looked at the information and answers that come from the standard models in econ as a very defined set of solutions that are always correct and as eternal as gravity. But looking back on the answers that some of the models have presented it is now obvious that some of them are based on a decent amount of simple assumptions that might not always be right. This doesn't inherently make them wrong or make them lose their credibility but instead highlights that "if the model is a good one, it is an improved insight into why the vastly more complex real system behaves the way it does". In a world that is so infinitely complex and hard to understand, these models can give a lot of us solace as well a basic understanding of how to approach many problems. Thanks to Krugman's insights in the article I can also understand why certain people like Hirschman would refuse to use these simplistic models to get a basic understanding. In Krugman's words "model-building, especially in its early stages, involves the evolution of ignorance as well as knowledge; and someone with powerful intuition, with a deep sense of the complexities of reality, may well feel that from his point of view more is lost than is gained." For some people, these models and their short scope of accuracy might not be worth the depth that is lost by using them but in my eyes, the gained insight is entirely more useful than long-winded metaphors. In general, the article really made me think more about why we use models and what exactly is their cost and benefit.
Posted by: JohnKeithGreen | 09/27/2016 at 04:04 PM
Krugman has backed me into a corner. The Rise and Fall of Development Economics stirred in me an uncertainty that’s not particularly comfortable, but that ignited a series of deeper economic thoughts to which I had not given much consideration. Models are both the villain and the hero in my study of economics so far – I am a right-brained person with little skill in mathematics, but a model always clarifies my studies far better than reading and rereading definitions can. I feel woefully uncomfortable when faced with a statistics or econometrics problem, but visualizing curves, lines and intersections provides me with a deeper understanding of what’s in front of me. Krugman’s mention of Alfred Marshall and his tendency to tuck away difficult or confusing math and models in favor of parables and metaphors at first sounded like my kind of study. But later in the paper, Krugman talked through the Big Push with words. I was lost, and I scrolled to the bottom of the article for clarification in none other than a graphical model. So how do I, as a student of economics, deal with complexity? It appears I utilize both metaphorical, value-laden words and clean, crisp economic models. With that, I fall in line with Krugman. There is an intersection between the two that can provide those of us with an inclination for the written word a pathway to better understanding through visualization and analysis. In microeconomics, I read about supply, demand, perfect competition – but the multi-colored model Professor Kaiser drew on the blackboard is permanently engrained in my mind. I could reproduce it in my sleep – though I could never repeat the words I read. My personal dichotomy translates into the broader study of development economics in that parables can provide a framework for study or a simpler version of economic theory for those unable to understand graphical or numerical renderings. But models provide a more visual understanding of how development economics can be translated into policy. Neither option is perfect – the words are over simplified and the models are perfect in an imperfect world – but the two paired together are unbeatable.
Posted by: Kinsey_Grant | 09/27/2016 at 05:57 PM
This paper brings to light the interesting debate of simplification. In all of the Econ classes I have taken we have always looked to simplify the issue into only a few variables, often making huge assumptions such as everything else remaining the same (ceteris paribus), or that there is a perfect market where labor and goods are always perfectly traded. And these simplifications are always encouraged and taught to better explain the issue.
After reading the article and seeing the slump of over simplification in the history of development economics makes me question the assumptions we make to simplify the problems in all of our Econ classed. The simple models do help explain some economic ideas and support different theories, but are they applicable to the real world and should w be using them to defend policy change? By making assumptions in the models and leaving out variables to simplify them, we change everything and could come to solutions that couldn't be further from the truth.
Posted by: Walker Tiller | 09/27/2016 at 08:06 PM
Blog Post _ Sept 28
I thought one of the most salient points of “The Fall and Rise of Development Economics” was the inherent variability of the data, and what constitutes an effective development policy, based on the country or region being observed. Hard data definitely serves its purpose, but as Krugman states “the pressures to produce button-down, mathematically consistent analyses” needs to be resisted “and adopt instead a muscular pragmatism in grappling with the problem of development.”
We are learning about a similar problem in my econometrics class this term – a regression equation can never account for every variable that influences the explanatory variable, yet the statisticians do their best to incorporate any foreseen and measureable variable in addition to an error term to try and statistically explain the relationship between two or more variables. And yet, despite this careful math, when the social and anthropology qualities are taken into account (even of the same variable) the explanation for the equation becomes unique to the population being analyzed. Simply, the numbers are not sufficient.
Krugman touches on this point when he highlights the importance of economies of scale to high development theory. However, these models “were very difficult to introduce into the increasingly formal models of mainstream economic theory” and so for a time were ignored. I think an essential aspect of development economics is to separate from traditional economics. Yes, while the basic studies are similar – a focus on markets, representative pricing, full information, utility maximization – the applications are totally different. Often, traditional economic models deal with theoretical situations while development economics attempt to quantify extremely tangible circumstances for the world’s poor.
Ultimately, I think the most noteworthy point of this article is that development economists must adhere to a “discursive, non-mathematical style.” I would add, however, that the use of statistical analysis as a means of quantifying data sets is a useful tool in the field. However, once again, these computations must be analyzed through a lens that takes into account the circumstances under which the data was taken, the culture of the population, as well as potentially extraneous, but important, variables that are not included in the regression. Numbers are not enough, but numbers combined with informed decision makers sets the stage for effective and targeted aid and change.
Posted by: Elizabeth Wolf | 09/27/2016 at 08:10 PM
Upon reading “The Fall and Rise of Development Economics” and thinking about Kruger’s model, I found one particular scenario especially interesting -- that which occurs under the condition of very low wage premiums. If wage premium is low, this means workers are receiving a meager compensation for what seems to be much more strenuous modern sector jobs. Of course, the low cost of labor allows for business to grow quickly and, consequently, for the economy to balloon. What I am envisioning as a modern sector job in a developing country might be described as hundreds of underfed and sleep deprived workers, routinely assembling their product, packed into a massive yet grimy factory. Additionally, working this type of job in a developing country would probably entail extremely bleak living conditions in a hurriedly industrialized area (most likely lacking sufficient sanitation or quality air). Whether or not this portrayal is accurate, I am not totally sure. However, it seems likely that standard of living will suffer for workers as the wage premium declines. Is this story similar to the unprecedented modernization of China? As an additional aside, it seems likely that this trade-off would decrease the incentive one might have to leave a traditional sector job to take a modern sector job. Was this considered in the model and could it serve as an impediment to development? What are some ways by which this wage premium is variable? Is Krugman suggesting that the government of a country effectively kick start the modern sector so that less would be needed for common profitability?
Posted by: David Cohen | 09/27/2016 at 10:30 PM
While reading “The Rise and Fall of Development Economics,” I very much enjoyed Krugman’s insights on the use of modeling in economics. Since taking introductory microeconomics I have been fairly cynical of the effectiveness of economic models due to the number of assumptions that they make; however, I thought Fultz’s dish-pan experiment was a powerful analogy to include to illuminate how extremely simple models can be effective. Even quantum mechanics—the author’s example of a completely describable field, and (I believe) the most fundamental of scientific endeavors—is non-deterministic, with inherent uncertainty in measuring a particle’s location and momentum at any given time, but it is still highly valuable in making predictions about the world. Moreover, in defense of the trend towards models over metaphors, it seems as though because economics is so inextricably bound to politics, it makes sense for economists to demand quantified, formalized ideas in order to avoid obfuscation by the researchers’ biases and ideologies.
In addition to formulating these thoughts on metaphors and models, I also noted that one assumption, made by Rosenstein-Rodan in his model of transferring those with 0 marginal product of labor in agricultural or rural jobs to the modern sector, reminded me of the article we read for the first week of class, “The Economic Lives of the Poor.” In the “Economic Lives of the Poor” we saw that many people living in developing countries make what economics would deem inefficient decisions, such as buying sugar even though it lacks nutrients, simply because they want to, and don’t necessarily think about optimizing their long-term outcomes. It seems like something similar could occur in transferring workers from the agricultural to the modern sector: even though these workers might earn a higher wage in the modern sector, there are non-monetary costs associated with moving, and I think cultural influences, family obligations, resistance to change, etc. would deter many from making this switch, thus compromising one of the main assumptions of the Big Push model. Like I said, though, I am definitely sold on the models.
Posted by: Clark_Mabey | 09/27/2016 at 10:48 PM
In the beginning of the paper Krugman mentioned Hirschman’s strategy to reject “buttoned-down, mathematically consistent analyses” and replace that with “muscular pragmatism” in the field of development economics. This means, to me, that economists should not automatically narrow their minds and make their mission to solely ‘prove’ something with a model. Instead, they should work to use some degree of an interdisciplinary approach when tackling their research, and think of the many complexities of humanity. This does not mean that there is no place for models in economics, or that we should be making them more complicated. I appreciate Krugman’s assertion to be aware of the simplicities when reading models, because they are still very useful in explaining and giving some substance to a theory, but the reader must remember a model has its limits. This leads me to our discussion of Kremer and his paper on the deworming children in order to increase educational outcomes, which all started with the simple logic that investments in education must be creating benefits. Sometimes, you have to be able to back up from the economics of the situation and realize the models are not always perfect. In Krugman’s conclusion, however, he asks us if we are sure we really have the insights that can reverse the modern economics community, so the main point I have gained from this piece is to simply be aware of the complicated process that creates the simple models we see in our textbooks and to understand their strengths and weaknesses.
Posted by: Corey_connelly | 09/28/2016 at 09:41 AM
Paul Krugman points out one of the biggest shortcomings of economic theory, the use of simple models to explain the complexities of the world. I personally believe economists rely too heavily on assumptions in their models causing them to be too simplistic and, therefore, inapplicable for real world considerations. However, I understand that many real-world factors are impossible to fit into a model. To use Krugman’s example, economies of scale are crucial to high development theory and should not be ignored when studying developing countries.
When considering economists’ struggle to accurately fit economies of scale into their models, I couldn’t help but think of the current struggle capture the effects of global climate change into models. The threat of global warming has serious implication for developing countries and no modern development theory should ignore this. In Environmental Economics, we learned the effects of climate change are measured in negative externalities but this doesn’t capture the true costs. While this is another example of the shortcomings of simplified economic models, the complete effects of climate change would be impossible to boil down into a single model.
This paper creates a dynamic discussion on the role of models in economic theory. While I think Krugman’s conclusion 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” is pretty harsh, it was interesting to get Krugman’s opinion on the different stages of development economic theory and how the subject has evolved over time. The main takeaway I have from this paper is that models are essential to economics because they allow us to make valuable estimations about the real world. As long as people utilize them with the caveat that they do not capture all aspects of reality, I think they should remain a part of the evolution of economic theory.
Posted by: Cara Hayes | 09/28/2016 at 10:43 AM
This paper covers a lot of ground and provides a good overview of the history of Development Economics. However, I would like to focus my thoughts on the degree to which research impacts policy.
Krugman said that high development theory was dismissed for a time because it lacked formal modeling. The theory challenged standard assumptions, including the existence of a perfectly competitive market and constant returns to scale, which rarely hold in practice. But in the absence of equations and graphs, the theory simply lacked the persuasiveness to gain widespread approval. As a result, Krugman added that the traditional “constant-returns, perfect-competition view of reality took over the development literature, and eventually via the World Bank and other institutions much of real-world development policy as well.”
I found this reality interesting in light of my experience last summer, when I interned for a political consulting firm in Washington, DC. Our bipartisan firm specialized in education and workforce issues, and frequently advised organizations on how to respond to new legislation. As such, one of my responsibilities was to attend congressional hearings and brief my supervisor on what was accomplished.
What I observed frustrated me, and often did not resemble the manner in which I imagine the high development was dismissed by policy institutions like the World Bank. I often listened to congressmen propose legislation about a certain issue without seemingly any data to support their stance. In an effort to get out in front of a potential conflict or change the status quo, politicians seemed fine with abandoning old policies and instituting new, untested ones.
All this is to say, that Krugman’s paper got me thinking about the history of development economics and led me to believe that the high development theory would have impacted public policy sooner had the political climate in the mid-1900s resembled that of today.
Posted by: Spencer Payne | 09/28/2016 at 10:53 AM
While reading "The Rise and fall of Development Economics" I appreciated his use siting different papers to help get his main ideas across. The paper I thought was very helpful was "The evolution of European ignorance about Africa," (pg. 3). This paper describes the changes in European maps of Africa from the 15th to 19th centuries. In the 15th century these maps were relatively inaccurate about coastlines and distances among other things, This was a result of the fact that the information being used to create the maps typically was second hand from travelers. By the 18th century the coastline had become more accurate on these maps, but the interior emptied out, the real cities and rivers had disappeared from the maps (pg. 4). Finally by the 19th century the maps of Africa were accurate. After reading about this paper, I found it significantly easier to understand what happened to development economics between the 1940s and 1970s. In addition it also helped me further understand his argument about models. Maps are obvious models, and easy ones to understand. Like a model they are over simplified to help you view an area. For example if you look at the map of Africa again you will notice that on the right there is the Indian Ocean and on the left there is the Atlantic Ocean. It can also tell you that Africa is south of Europe and that Madagascar is off the right coast. Just like a model it is oversimplified to help people understand where Africa is in the world, where the countries with in Africa are, and how some of the basic terrain is. What maps cannot tell you about Africa is the culture of each country, the animals that inhabit each area, the different languages spoken, and so much more. Just like economic models, in order to understand where countries are in the world you must simplify the country down to just it's basic location. You may be able to draw minimal conclusions about a place you've never been from a map, but until you've been there you won't understand much about that place. This is similar to a model that you may be able to draw some conclusions from it, but what happens in reality might not match up with the models predictions. Finally I also really enjoyed Krugman's closing remarks, "nd for those, like me, who basically try to understand the world through the metaphors provided by models, the advice is not to let important ideas slip by just because they haven't been formulated your way. Look for the folk wisdom on clouds -- ideas that come from people who do not write formal models but may have rich insights. There may be some very interesting things out there. Strangely, though, I can't think of any," (pg. 12-13).
Posted by: Jillian Leigh | 09/28/2016 at 12:35 PM
The main theme I drew out from Krugman's "The Fall and Rise of Development Economics" was the idea of simplicity. His belief is that Development Economics did not make significant strides between 1940 and 1970 because they were not able to break down their ideas into more straightforward easily understood models. They could not "dumb down" their knowledge, and became too lost in the details inhibiting them from seeing the bigger picture. Economists such as Albert Hirschman were not wrong, however they didn't portray their knowledge in an efficient manner, "We can now see that high development theory made perfectly good sense after all. But in order to see that, we need to adopt exactly the intellectual attitude Hirschman rejected: a willingness to do violence to the richness and complexity of the real world in order to produce controlled, silly models that illustrate key concepts." Krugman seems to be saying to these economists - We know you're incredibly intelligent , but swallow your pride and produce a more simplistic model without getting lost in the complexities of the problem.
Breaking concepts down into their more elementary elements (such as outlining textbook chapters) is something we do as humans everyday - it is how we learn. Reading Kinsey's comment above rang true to me. It is quite common to feel your brain spinning when first reading dense material on a new subject, but when a simplistic model is drawn on the board - such as a supply and demand curve - it gives a base in understanding the material then allowing for pursuance of more complicated knowledge on the subject. It also makes that once dense reading more likely to make sense. Much like Krugman it is hard for me to understand why these economists could not simplify their models. If they did maybe we would be further along in Development Economics than we currently are today.
Posted by: Matthew Sgro | 09/28/2016 at 01:15 PM
The mistakes in economics, in particular to ignore high development theory for several decades only to return to the thought, reveals several lessons to me. Thought is often going to be ahead of modeling, as it should be. Great thoughts may arise, but often times the numerical support to "prove" the thought may not be present. Thus, I believe that too much emphasis is often placed on models over thought. The prediction that complex models reveals can often dictate political policy that is used in practice, but these predictions are not always correct. Sometimes, we must step back and examine things in a logical manner of reasoning. In reference to the high development theory, I think the idea that "modernization breeds modernization" simply makes sense. Even though it took several decades for a model to be generated, the idea should not have been completely ignored until the model was formulated. By examining this idea in nature, maybe the concept can be displayed more clear, but by ignoring the thought entirely, it was a loss to the expansion of the discipline of development economics. With this being said, ideas cannot be examined with such a narrow-minded perspective. Examining surrounding factors can often illuminate some such trait that would make this inconceivable idea conceivable. Thus, often times the best perspective to take may be the simplest one. When you think of traditional ways to increase development, GDP/capita stands out, yet a number of complex factors go into this equation with the fact that markets are not entirely perfect. Here, one is able to draw comparisons to Sen. To say that development should focus on capabilities is quite simplistic, yet it took many years of complex models failing to provide an adequate solution. In today's world we can see that improving capabilities in turn does an amazing job in alleviating the problems of developing countries. Thus, from this realization shows complex phenomena can often be solved through simplistic manners. Examining something with from a complex perspective makes economics more difficult than it needs to be.
Posted by: Matthew Jones | 09/28/2016 at 01:24 PM
I found Krugman's article very insightful, because I for one tend to have a hard time relating to some of the models we have looked at over the years. I remember the frustration of sitting through Prof. Guse's microeconomic theory class as we poured over model after model that would hold true "given certain assumptions." These assumptions seemed impossible to hold true in reality and I found myself frustrated with trying to study something that may not be able to ever play out in the real world.
That's why I found myself so interested in behavioral economics and the electives offered in economics. There we got to see how the real world actually operated and how to approach the real issues that affect us in an economically real sense. I do however, recognize the necessity of the models. Even policy proposals we developed in class were based not on metaphors and anecdotes, but rather models that were developed. That is why I found myself at a crossroads after reading this paper. This paper I feel addresses the intersection between behavioral economics and economic theory; The necessity to keep developing models, while also gaining insight from how things are playing out in real life.
Posted by: Matt Parker | 09/28/2016 at 01:29 PM
This paper brings to our attention a couple simple words that are learned in any introductory economics classes: ceteris paribus. I remember my freshman year introduction to microeconomics class in which people constantly asked “but what if you changed this or that” or “how could you assume that would be true”? At first it seemed odd and unrealistic to be using these graphs with only two products or only two sectors to explain our entire world economy, but the more economics classes I took, the more I became comfortable with this idea of assuming away any complication. However, Krugman brings back up that initial discomfort that many of us freshman exhibited when we questioned the validity and applicability of such a limited model to the real world. Now, in my microeconomic theory class, I am slowly being made aware of all the short comings that the introductory microeconomic models had. In order for us to gain any understanding at all it was necessary to at first make simple assumptions, however now that we have gotten to higher level classes it is assumed that we should be able to think critically about the assumptions being made, and further have a better understanding of what may happen if one of these assumptions were to be violated. Professor Goldsmith’s favorite “game” is ceteris paribus violation in which he forces us to think and question how some of these models may change if one of the assumptions were to not be true. While Professor Goldsmith makes a point of the model’s limitations, there are countless paper’s that I’ve read for other classes, which tend to forget that ceteris paribus violations do occur in the real world and this is what Krugman criticizes most. It seems to me that the best economists would combine the models and math with sound reasoning in plain English to explain economic phenomenon so that we can not only understand how the model should work in the real world, but also further question what may happen if certain assumptions are violated. I found this paper thought provoking as it caused me to reflect on how the models I have been taught have been expanded and changed over the 3 short years I’ve been studying economics and how much those classical models may change for economists who are on the cutting edge of research in new fields for example.
Posted by: Allie Barry | 09/28/2016 at 01:31 PM
This paper touches on a lot of the struggles I have wrestled with in Economics. I am an Econ major, but was always bothered by the oversimplification of models. I loved learned about perfect competition and running through the logical steps or price changes and changes in elasticity in my head. It was fun, made sense, and helped to explain a lot of the decisions consumers make in the world. It was all fun until it didn’t actually work in the real world. If you look closer, what the models predict and the actual decisions people make are often not the same. People aren’t rational, trying to maximize totally benefit, and working in a perfectly competitive market. So I wondered, as I walked out of my Econ 101 class, how you actually try to make economic change in the seemingly complicated and irrational world we live in. It seems like development theory went through this same process. They made models and then abandoned them because they didn’t know how to apply them in policy. From there, they turned to metaphors and logic to explain phenomena, only to discover that you really do need models if you want to have a large and lasting impact on development theory. Krugman notes that theories, “do not endure unless codified in a reproducible -- and teachable form,” aka, a model. To me, it is understandable that many thinkers in those “lost years” turned away from models. Sometimes they don’t work, and they wanted to try a different approach. However, as the author points out, there is not other option except for models. It is not a matter of turning to a different medium for explaining the economy, but working on the actual models. You have to be creative and try and make different models to isolate different variables, helping you understand another piece of the puzzle. You also have to understand the limits of models. They are not a panacea, but just a useful way to understand some past experiences and try to predict what might happen in the future, given a set of conditions. Reading this article has really helped me come around to the idea of models again. They really aren’t these hypothetical situations that I can just forget about, but real tools that should be used in the right situations.
Posted by: Ella Rose | 09/28/2016 at 01:34 PM
There are several points I find really interesting about this article. First of all, I think it is frustrating to think about the amount of years of knowledge that were lost because of the mere fact that some thoughts were not able to be written or presented in models. I honestly did not know of the relevance of development economics until some days ago. Development, as Todaro and Smith describe, is a “multidimensional process involving the reorganization and reorientation of entire economic and social systems” with the purpose of searching for models and forms of implementing solutions to increase people’s living standards and freedom. Knowing this, I think it is really disappointing to think about the time that was lost and the fact that a field as important as this one could have suffered such a “long slump”.
The other aspect, I believe, was interesting and we have gone through it in class, is how models of almost every system are “to some degree a falsification,” as they leave aside many aspects of reality and they involve an amount of assumptions that many times do not apply to real life. I think it is interesting how representing the world in simple models is important to get an essential point or several key points about our society.
As I was reading the article, I was thinking how, in the same way economies of scale represented a problem (as economist did not know how to incorporate this important concept to the existing models), freedom as presented by Sen, is also an extremely important concept in development, which is hard to introduce to models. Freedom is not a quantitative variable; however, according to Sen, it is not only the main end of development, but also the means to achieving that main end. In my opinion, it is shocking to think that Sen’s idea would have “decay” due to the fact that it would “have not been embalmed in models.”
Posted by: Julia Mayol | 09/28/2016 at 01:41 PM
The “Rise and Fall of Development Economics” addresses some of the issues that I have had with economics classes in the past. While I have only take intro to micro and macroeconomics, I could not fully understand the application of the models. It seemed very theoretical and couldn’t be applied to the real world. But as economics classes become more advanced, one has the opportunity to put more thought into the models. As a freshman, I was only trying to learn the models and understand them, but not apply them. The application aspect is important when getting closer and closer to entering the work place and leaving behind college. I now look for answers. The paper discusses the need for explanation behind these models and how there are so many different factors that are involved in them. Even a religion can deter a model from being correct. One’s set of beliefs can throw them off. Each model must be applied a little differently to situations. My whole life, I have related school and other things to sports. To me, this seems as if a coach comes up with a strategy, but refuses to change despite the other team making changes. Even if the other team has figured you out, you stick with what you are doing instead of making a few adjustments that would allow you to win the game. This is the way that I was able to understand the paper more fully.
Posted by: Andy Kleinlein | 09/28/2016 at 01:56 PM
Before reading “The Fall and Rise of Development Economics”, I had never really given much thought into the development and history of economic thought. One aspect of the article that I found particularly interesting was Krugman's explanations of the role of economic modeling. In the Econ classes that I have taken in the past (macro and micro), we were taught a number of different models. But while we were learning these models, I never really questioned where they came from or how accurate they were. This article really made me consider the evolution of economic modeling, and how it is important to remember what key assumptions are being made to form these models. I think this ties in nicely with our class discussion on foreign policy and decision-making. It is crucial to remember that while these models can be useful, they are built upon a number of important assumptions that are not always true in the real world.
I also found it interesting how the author related economic modeling to other types of scientific modeling (such as meteorology and physics). It was an interesting way to think about economic modeling, and reminds us again that models only work under a certain set of assumptions and conditions that are not always true in the real world. I also thought it was interesting to learn more about how economic models were become less mathematical. This makes me consider the accuracy of these models. They are often simplified and only make sense under a specific set of assumptions that are often unrealistic in the real world economy. This makes me wonder what other components we might consider in order to make our modeling more accurate and realistic when studying trends in the economy.
Posted by: Rachel Baer | 09/28/2016 at 04:11 PM
Being someone who always looks at models in economics and thinks “but what if…” it was very refreshing to read an article that didn’t stress the necessity of a model in order to come to a conclusion that could be correct. In fact, it is as if Krugman taught us a life lesson in the article: that if something isn’t there the first time you think of something, don’t give up on it altogether. In a way, Krugman’s article reminded us that economics is a social science and must be treated as such. There is almost never a single correct answer, and there are always different ways to come to any conclusion. Krugman also teaches that any conclusion must be backed with sufficient evidence or a strong argument. It is not acceptable to say this is what I think and everybody must accept it; there must be an explanation as to why you think this and what evidence there is to back it up. This is true of any of the social science disciplines, including economics. In Krugman’s view, it was important for a model on Hirschman’s High Development theory to be created in order to provide evidence for Hirschman’s original theory. This article both teaches a piece of the history of development economics and a life lesson: never give up on an idea just because it cannot be proven at a given time.
Posted by: Alex Shields | 09/28/2016 at 04:33 PM
I agree with many of the individuals who commented before me. The increase in the complexities of the models is quite staggering. However, one typically believes that a more simplistic approach to an economics model would allow it to be more easily understood; yet it appears that the move towards complex models is not quite as helpful, though it is accurate. It is in this manner that the simplistic approaches maybe better due to the fact that they are all encompassing. Consequently, this defines economics as a social science rather than a mathematical equation. This article validates the fact that it is dealing with individuals whose decision cannot always be calculated. Thus it is in this manner that you cannot predict every one or everything’s actions but rather can predict what the massive body will choose to do. Thus, it is the natural assumptions that tend to corrupt the economic models that we use.
Posted by: Thomas Thagard | 09/28/2016 at 04:49 PM
In "The Fall and Rise of Development Economics", Krugman highlights the "high economic theory" and illustrates why it unraveled even though it made a lot of sense.
As an economics major, I tend to sit through many classes in anger at the simplicity of models that are attempting to describe or "map out" our economy. I understand that the economy is too complex to truly map out in a model, but I always wonder if the conclusions we draw from these models can be leading us in the wrong direction when we assume, for example, perfect competition, closed economies, etc. I also wonder to myself when a model makes sense, whether there are outside factors that we might be overlooking that affect the model, which usually turns out to be true.
I believe this article is important as Krugman points out that while models are very useful in describing how the economy works, the bottom line is that the economy is too complex to ever map out on one simple model; therefore, Krugman urges not to get too caught up in models, and overlook important insights or concepts simply because it is not laid out or "formulated" in a model.
Posted by: Crosby Ellinger | 09/28/2016 at 05:26 PM
Development Economics as complex as it may seem should definitely not be seen as inferior to mainstream economics first and foremost and is one of the points Krugman emphasizes in this article. It was also mentioned that mainstream economics even began to acknowledge the usefulness of development theory and modeling techniques. Models are great ways to bring ideas to life and in the development perspective, it is important to understand that models should also not be limited to basic ideas such as constant returns as was done in the past. With the dish-pan analogy, it was easy to understand how models bring great ideas and theories to life through visual representation. While reading this, I tried to look inward to see how this whole verbal versus visual factors played a role in my own life and I recognized the need for an interaction of both and this is precisely what Krugman is hammering at. I think the decaying of high development theory historically gave room for a better and more nuanced understanding of development economics and the importance of models in policy making decisions. By looking from this perspective, it is therefore imperative to understand that despite the seemingly complexity of development economics, much can be done with the interaction between metaphors and models in a way that helps construct simple, effective, and long-term policies in the development field.
Posted by: Ololade Rachel Oguntola | 09/28/2016 at 05:37 PM
Kruger’s analogy to the map of Africa resonated with me and reminded me a lot of our discussion in class last week. Uncertainty bred ignorance when cartographers refused to consider or incorporate information that may not have been entirely accurate or easily represented. This in turn gave way to passivity and the interior of Africa remained blank until there was complete confidence in cartography technology. The notion that a failure to produce a perfect model of something would discourage or discredit efforts to engage with or understand ideas is incredibly concerning to me, particularly in the context of development.
Similar to what we discussed in class the other day, just because we cannot always determine definitive casual relationships between phenomena does not mean we should shy away from alleviating the suffering. Ultimately the models are not the primary concern and should never preclude us from doing something poverty. Of course models are often incredibly useful. However, just because we struggle to craft the perfect model, does not mean we should shy away from or delegitimize the underlying theories or ideas. In accordance with Sen’s freedoms-based approach, poverty-related issues can rarely be reduced to numbers and statistics. Oftentimes the complexities of poverty make it difficult to model and understand but that does not mean we should not try.
Posted by: Charlotte Braverman | 09/28/2016 at 06:56 PM
Paul Krugman presents a compelling case for the use of simplified models in economic study, one that I wholeheartedly support. An excerpt I found exceptionally eloquent and succinct was, “You make a set of clearly untrue simplifications to get the system down to something you can handle; those simplifications are dictated partly by guesses about what is important, partly by the modeling techniques available. And the end result, if the model is a good one, is an improved insight into why the vastly more complex real system behaves the way it does.”
This sentence brought several connections to mind. The first, though not pertinent to economics, is an interesting point to speak to Krugman’s overarching thesis that modeling is essential, and arguably inherent to human nature. Aldous Huxley, author of popular high school English unit “Brave New World”, once wrote that the human brain essentially spends all its time performing an analogue to modeling, in order to present us with a version of the world with can function in and interact with. He claimed our brains and nervous systems are designed to block out information and stimuli that needlessly complicate the situation at hand, much as economic models do.
Another drew me back to a class with Professor Eastwood, in a course called Neighborhoods, Culture and Poverty. During discussion about the complications of addressing persistent, multi-generational poverty, the class began to despair at the web of interconnected variables that affect a child’s economic outcomes. Everything from the neighborhood the child grows up in, to the education of her parents, their proximity to community centers and the area’s capacity for collective action plays a role, and untangling the complexity seems insurmountable. Krugman and Professor Eastwood make similar points regarding this challenge, in that simplification is a necessary step, despite the outcry that may come of willfully making untrue assumptions or detaching oneself from the “deep complexities of reality”. Instead of turning away from models because they cannot represent accurately our reality, it is useful to apply them as the best alternative to glean as much information as we can, until our tools become advanced enough to “transcend those limitations”.
Posted by: Corey Guen | 09/28/2016 at 06:59 PM
One of my favorite lines from Krugman's Fall and Rise of Development Economics is his defense of simplistic models in complex systems- they give insight into why the "vastly more complex real system behaves the way it does". I find Krugman’s embrace of the unsophisticated to be both refreshing and essential to studying economics. His insight that these basic models challenge us to go out and measure instead of us giving us a false sense of understanding is especially pertinent to development economics. Yes, it is important to intellectually understand the economic struggles of developing countries. However, it is the resulting action that makes the impact.
Reading through this article, I find it easy to see why this is one of Professor Casey’s favorite pieces. An emphasis on models with an ‘it depends’ disclaimer- what more could you ask for?
Posted by: Tony Du | 09/28/2016 at 07:13 PM