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09/26/2016

Comments

Lilly Grella

Oftentimes in economics courses, professors will stress the idea that the models are purely a simplistic representation of the world. Despite the untrue assumptions associated with modeling, they are extremely important to the field of economics. Krugman spends a lot of this article being his standard cheeky, bold self as he speaks on the progression of economics and the influence models have on it. He criticizes Hirschman for his lack of acknowledging the importance of empirical proof and modeling, but he applauds the concepts. His problem is mainly with the methodology. As a thesis he sets the paper up to address this issue of methodology within development economics (and economics as a wider field).

Krugman combines what he believes is to be two drastically different but similarly lacking methods of modeling. I find it extremely easy to agree that this is a successful compromise. On one side, there are the models from around the 1950s, which are too focused on formalities (thus many things are overlooked). He uses the Africa mapmaking as a metaphor for the lost knowledge that comes from the strict modeling. Hirschman’s method, on the other side, surrounds a lack of modeling and involves too much of a focus on abstract ideas. The solution is to create “silly models that illustrate key concepts”. Krugman recognizes that models are just that: models. Too much complexity and it makes understanding and further knowledge difficult. Lack of models turns something with academic and research practicality to a solely verbal argument. This loses some of its standing in the field. Thus, the middle ground seems to be a solution to each problem.

Ultimately, I think Krugman acknowledges the importance of understanding economics as a field that is dynamic and adaptable to the times. Models have the ability to show advancement, as they are open to change themselves. He ends his paper recognizing that in efforts to make sense of the world, there will be times where we overlook important facts or remain ignorant to key information. It is important to remember that this is all related to the ebb and flow of economics.

Pearce Embrey

I thought that Krugman made some very interesting points in his paper "The Rise and Fall of Development Economics." It is obvious to the modern college student that modeling is an incredibly important tool in economics. Models are able to give us a glimpse into some sort of economic reality. But that is just it-they are glimpses. Economic models are not meant to account for everything under the sun. In Professor Guse's microeconomic theory class, the models we examine are almost always in what he calls "Pizza and Beer World," where the consumer is making decisions with pizza and beer being the only two goods available. Of course we know that this is overly simplistic, but we use the model to get a general idea of an economic concept. The world is way too complex and difficult to understand just looking at economic models. For Pete's sake, in these economic classes we always assume that individuals are rational thinkers, but now there is even evidence that calls that into question. Economics is a discipline that evolves over time. I think that Krugman is wrong to sort of crucify Hirschman for not taking the time to model his high growth theory. Maybe modeling didn't make sense to Hirschman at the time, but today, we still could learn a lot from his ideas of high growth theory, with or without the formal modeling.

Michael Hegar

"The Fall and Rise of Development Economics" brings some interesting points to light. I've only scratched the surface of economics in my academic career and I never really thought about what life was like before the models were made. Simplifying complex ideas into manageable models is incredible useful. It can also be incredible difficult.

I liked Krugman analogy about the Norwegian scientists discovering what folk wisdom told them all along. As economists we must be careful not to let our view narrow so much. Focusing in on an important part of development is not bad. But when we get caught up with the process of making a model and only focus on certain variables, we can miss the big picture.

For me I think of things in terms of sports. Krugman's concluding remarks remind me of my dad. He never played basketball but he has an understanding of how the game works. In high school he would often point out things that I might have missed on the court. "Look for the folk wisdom on clouds -- ideas that come from people who do not write formal models but may have rich insights." In sports and in economics we cannot have a narrow focus solely on what we do. We need someone in a different field (or a coach) to help us see the big picture sometimes.

Tanpreet Hunjan

This paper turned the concept of models upside down for me and made me see modelling for ‘’maps instead of reality’’. Studying economics at high school, models were extensively dictated to me and there was little discussion of economics in the real world- where models often don’t fit verbatim. It reality several exogenous variables come into play and this concept was not brought to the forefront. Krugman’s mention of Alfred Marshals preference to metaphors as opposed to confusing math’s and models therefore surprised me. It was also interesting to read models as an unusual mechanism used in social science due to their prevalence in physical sciences. Krugman’s mention of high development theory losing creditability due to lacking formal modelling also perplexed me. A theory that challenged standard economic assumptions for me should not be glanced over because of its inability to theorize and test in formal measures.
On a broader scale reading this article made me question the broad generalizations we make in class when learning about fundamental models. The word ceteris paribus is used excessively and is used to dismiss what is happening in reality and real life. Often at times there is never one variable to test by itself which makes social and physical sciences so complex. Although models give us an insight into shaping public policy among other things, it stops short at telling us about the bigger picture.

Ddevereux9

I applaud Krugman for his opening to this paper. Stating how he is not an expert on the works of Hirschman is a classy move and lets the reader appreciate how much he actually knows. The main concept Krugman brings up that caught my eye was the simplistic model argument. While it is true that a simple model is much too small and simplified down to be representative of an actual economy, it still does its job. Its job is to simplify an economy down small enough to be in a model. It helps economists analyze data that is too large in scale with too many different variables. Assuming some variables are held constant is the only way they would be able to even draw any conclusions.

Jim Grant

The article “the rise and fall of development economics” by Krugman, brought forward some interesting insight about the use of models. Krugman makes an interesting point that models, while they may be considered oversimplifications, are necessary for economists and there’s no avoiding the “narrowing affect” as Krugman calls it. Krugman starts with the comparison to the cartography of Africa. At first I failed to see the relevance of the anecdote, but as I continued it became more apparent. It described poignantly how lack of knowledge and technology can limit our perceptions and constrain our information. True intelligence is realizing what you don’t know, and as our knowledge of economics has developed it’s become apparent that the models we use don’t provide all the answers. In the case of the maps of Africa, cartographers realized they had made mistakes with their models. Similar to that economists realized the models they used were not sufficient to account for the variables that weren’t accounted for initially. Krugman’s article was an interesting read and I enjoyed his conversational tone. Admittedly it was hard to follow at times since a lot of his explanations and evidence was more theoretical and analytical, but I found his work very interesting and look forward to reading more.

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