The basic job of an economic theorist is to write papers, usually with at most one or two co-authors, that develop new models of some phenomenon of interest. A reasonably successful theorist writes about one such paper per year. Each paper contains a brand-new model, which while often similar to other models that have come before, has to be built up from scratch. The fact that you have to build up a new model with each paper, combined with the fact that you have to write lots of papers, means that the models can’t be too complicated, or at least can’t be complicated in ways other than the specific ways that you want them to be. They have to be tricked out in just such a way as to allow you to get at the question of interest, while leaving a whole bunch of other (important) stuff out.
Sorry, to be clear, I'm referring to microeconomic models like Arrow-Debreu equilibrium or game theory; e.g. the sort of stuff that appears in http://econtheory.org/ . Looks like the other commenters have macro models in mind.
Making big complex models sounds like a great idea if you can fit them to real data (or attempt to do so). But theoretical economics is so theoretical, the models are related to reality only though analogies. Thus the only value you can get out of them is to explore their mathematical properties and hope those properties are analogous to properties in the real world. Since it's easier to explore mathematical properties of simpler models, simple models are better for pure-theoretical modeling.
Now, of course, that doesn't address the value of the entire enterprise of theoretical modeling... I still like it, but I admit that's more due to aesthetics than a conviction it's good for the advancement of scientific understanding. (I confess to having written both an honors and master's thesis that were purely theoretical...)
Arnold Kling has some good insights into large, complicated models, both of the macroeconomic and climate change variety.
Basically his contention is that the data used in economic analysis doesn't allow big models to be calibrated. Small models work with the data that is available.
Seeing as how climate science uses huge models (in fact, the fastest computers in the world are being built just for this field) I don't think that your thesis that academia itself drives model size is correct. Presumably, climate scientists are under the same academic pressure as economists.
Robin, You are right that individual researchers have a strong incentive not to do stuff that they consider fun but that the powers that be in their field don't like. But the powers that be in economic theory research are themselves economic theorists, so tastes that are common across economic theorists will be the ones that prevail.
Eric, It seems like you are saying two different things. The first is that most worthwhile economic theory insights really do come from playing around with relatively simple models, so it's a good thing that this is what most theorists do. As I mentioned in the post, I have sympathy for this view, but I still suspect that too little of the complicated stuff is done. The second is that people should be doing more complicated stuff, but they don't not because it's not fun, but because it's too risky to tie your whole life's work to one huge project, even if it has a high expected payoff. You may well be right about this.
eric: I think you are commenting on a false understanding of the original post. I am working incrementally if I publish a paper that takes as its point of departure a complex model that has already survived contact with data from the real world and peer review and makes a single simple modification or enhancement to that model.
How would you have liked to be one of these 60 year old economists who 35 years ago thought they were going to really capture the whole frickin' macroeconomy, only to find out it was a dead end. Ack! My life has been a great big snark hunt! Prudent incrementalism involves introducing new&true&important ideas one at a time, rather than trying to work them into an ubermodel on your own for 10 years and presenting it to the public. It's easiest to fool yourself, you need more objective criticism than that. I can't think of a successful economic theory that isn't rather pithy in its essence, can you?
I doubt you can explain very much of the variance of academic methods or topics by what seems "fun." Academia is a very competitive field, where most people fail, so a high price is paid for pursing your own fun. There are many fun topics, like alien intelligence, that academics have avoided exactly because they seem too fun.
Sorry, to be clear, I'm referring to microeconomic models like Arrow-Debreu equilibrium or game theory; e.g. the sort of stuff that appears in http://econtheory.org/ . Looks like the other commenters have macro models in mind.
Making big complex models sounds like a great idea if you can fit them to real data (or attempt to do so). But theoretical economics is so theoretical, the models are related to reality only though analogies. Thus the only value you can get out of them is to explore their mathematical properties and hope those properties are analogous to properties in the real world. Since it's easier to explore mathematical properties of simpler models, simple models are better for pure-theoretical modeling.
Now, of course, that doesn't address the value of the entire enterprise of theoretical modeling... I still like it, but I admit that's more due to aesthetics than a conviction it's good for the advancement of scientific understanding. (I confess to having written both an honors and master's thesis that were purely theoretical...)
Arnold Kling has some good insights into large, complicated models, both of the macroeconomic and climate change variety.
Basically his contention is that the data used in economic analysis doesn't allow big models to be calibrated. Small models work with the data that is available.
Seeing as how climate science uses huge models (in fact, the fastest computers in the world are being built just for this field) I don't think that your thesis that academia itself drives model size is correct. Presumably, climate scientists are under the same academic pressure as economists.
Robin, You are right that individual researchers have a strong incentive not to do stuff that they consider fun but that the powers that be in their field don't like. But the powers that be in economic theory research are themselves economic theorists, so tastes that are common across economic theorists will be the ones that prevail.
Eric, It seems like you are saying two different things. The first is that most worthwhile economic theory insights really do come from playing around with relatively simple models, so it's a good thing that this is what most theorists do. As I mentioned in the post, I have sympathy for this view, but I still suspect that too little of the complicated stuff is done. The second is that people should be doing more complicated stuff, but they don't not because it's not fun, but because it's too risky to tie your whole life's work to one huge project, even if it has a high expected payoff. You may well be right about this.
eric: I think you are commenting on a false understanding of the original post. I am working incrementally if I publish a paper that takes as its point of departure a complex model that has already survived contact with data from the real world and peer review and makes a single simple modification or enhancement to that model.
How would you have liked to be one of these 60 year old economists who 35 years ago thought they were going to really capture the whole frickin' macroeconomy, only to find out it was a dead end. Ack! My life has been a great big snark hunt! Prudent incrementalism involves introducing new&true&important ideas one at a time, rather than trying to work them into an ubermodel on your own for 10 years and presenting it to the public. It's easiest to fool yourself, you need more objective criticism than that. I can't think of a successful economic theory that isn't rather pithy in its essence, can you?
I doubt you can explain very much of the variance of academic methods or topics by what seems "fun." Academia is a very competitive field, where most people fail, so a high price is paid for pursing your own fun. There are many fun topics, like alien intelligence, that academics have avoided exactly because they seem too fun.
Sorry, to be clear, I'm referring to microeconomic models like Arrow-Debreu equilibrium or game theory; e.g. the sort of stuff that appears in http://econtheory.org/ . Looks like the other commenters have macro models in mind.
Making big complex models sounds like a great idea if you can fit them to real data (or attempt to do so). But theoretical economics is so theoretical, the models are related to reality only though analogies. Thus the only value you can get out of them is to explore their mathematical properties and hope those properties are analogous to properties in the real world. Since it's easier to explore mathematical properties of simpler models, simple models are better for pure-theoretical modeling.
Now, of course, that doesn't address the value of the entire enterprise of theoretical modeling... I still like it, but I admit that's more due to aesthetics than a conviction it's good for the advancement of scientific understanding. (I confess to having written both an honors and master's thesis that were purely theoretical...)
Arnold Kling has some good insights into large, complicated models, both of the macroeconomic and climate change variety.
Basically his contention is that the data used in economic analysis doesn't allow big models to be calibrated. Small models work with the data that is available.
Seeing as how climate science uses huge models (in fact, the fastest computers in the world are being built just for this field) I don't think that your thesis that academia itself drives model size is correct. Presumably, climate scientists are under the same academic pressure as economists.
Robin, You are right that individual researchers have a strong incentive not to do stuff that they consider fun but that the powers that be in their field don't like. But the powers that be in economic theory research are themselves economic theorists, so tastes that are common across economic theorists will be the ones that prevail.
Eric, It seems like you are saying two different things. The first is that most worthwhile economic theory insights really do come from playing around with relatively simple models, so it's a good thing that this is what most theorists do. As I mentioned in the post, I have sympathy for this view, but I still suspect that too little of the complicated stuff is done. The second is that people should be doing more complicated stuff, but they don't not because it's not fun, but because it's too risky to tie your whole life's work to one huge project, even if it has a high expected payoff. You may well be right about this.
eric: I think you are commenting on a false understanding of the original post. I am working incrementally if I publish a paper that takes as its point of departure a complex model that has already survived contact with data from the real world and peer review and makes a single simple modification or enhancement to that model.
How would you have liked to be one of these 60 year old economists who 35 years ago thought they were going to really capture the whole frickin' macroeconomy, only to find out it was a dead end. Ack! My life has been a great big snark hunt! Prudent incrementalism involves introducing new&true&important ideas one at a time, rather than trying to work them into an ubermodel on your own for 10 years and presenting it to the public. It's easiest to fool yourself, you need more objective criticism than that. I can't think of a successful economic theory that isn't rather pithy in its essence, can you?
I doubt you can explain very much of the variance of academic methods or topics by what seems "fun." Academia is a very competitive field, where most people fail, so a high price is paid for pursing your own fun. There are many fun topics, like alien intelligence, that academics have avoided exactly because they seem too fun.
Sorry, to be clear, I'm referring to microeconomic models like Arrow-Debreu equilibrium or game theory; e.g. the sort of stuff that appears in http://econtheory.org/ . Looks like the other commenters have macro models in mind.
Making big complex models sounds like a great idea if you can fit them to real data (or attempt to do so). But theoretical economics is so theoretical, the models are related to reality only though analogies. Thus the only value you can get out of them is to explore their mathematical properties and hope those properties are analogous to properties in the real world. Since it's easier to explore mathematical properties of simpler models, simple models are better for pure-theoretical modeling.
Now, of course, that doesn't address the value of the entire enterprise of theoretical modeling... I still like it, but I admit that's more due to aesthetics than a conviction it's good for the advancement of scientific understanding. (I confess to having written both an honors and master's thesis that were purely theoretical...)
Arnold Kling has some good insights into large, complicated models, both of the macroeconomic and climate change variety.
Basically his contention is that the data used in economic analysis doesn't allow big models to be calibrated. Small models work with the data that is available.
Seeing as how climate science uses huge models (in fact, the fastest computers in the world are being built just for this field) I don't think that your thesis that academia itself drives model size is correct. Presumably, climate scientists are under the same academic pressure as economists.
Robin, You are right that individual researchers have a strong incentive not to do stuff that they consider fun but that the powers that be in their field don't like. But the powers that be in economic theory research are themselves economic theorists, so tastes that are common across economic theorists will be the ones that prevail.
Eric, It seems like you are saying two different things. The first is that most worthwhile economic theory insights really do come from playing around with relatively simple models, so it's a good thing that this is what most theorists do. As I mentioned in the post, I have sympathy for this view, but I still suspect that too little of the complicated stuff is done. The second is that people should be doing more complicated stuff, but they don't not because it's not fun, but because it's too risky to tie your whole life's work to one huge project, even if it has a high expected payoff. You may well be right about this.
eric: I think you are commenting on a false understanding of the original post. I am working incrementally if I publish a paper that takes as its point of departure a complex model that has already survived contact with data from the real world and peer review and makes a single simple modification or enhancement to that model.
How would you have liked to be one of these 60 year old economists who 35 years ago thought they were going to really capture the whole frickin' macroeconomy, only to find out it was a dead end. Ack! My life has been a great big snark hunt! Prudent incrementalism involves introducing new&true&important ideas one at a time, rather than trying to work them into an ubermodel on your own for 10 years and presenting it to the public. It's easiest to fool yourself, you need more objective criticism than that. I can't think of a successful economic theory that isn't rather pithy in its essence, can you?
I doubt you can explain very much of the variance of academic methods or topics by what seems "fun." Academia is a very competitive field, where most people fail, so a high price is paid for pursing your own fun. There are many fun topics, like alien intelligence, that academics have avoided exactly because they seem too fun.