aecon641

Charness, Oprea, Friedman (2012)- Continuous Time and Communication in a Public-Goods ExperimentContinuous Time and Communication in a Public-goods Experiment [eScholarship] You might also check out their lab's website (Learning and Experimental Economics Project of Santa Cruz: "LEEPS"). They have a free software that runs economic games in continuous times (unlike Z-tree which does discrete time).

If you study contract theory you will become an expert in using esoteric mathematical concepts to describe highly abstract models about equilibrium interactions that can never be tested empirically. If you study behavioral economics you will learn about the labor supply habits of New York city cab drivers and about how college undergrads exhibit loss-aversion and altruism while participating in laboratory experiments. Does it sound like these things will help you as a consultant? Now I'm sort of joking with my response, but not really. My point is that the topics you dedicate yourself to in a PhD program are highly academic, and therefore it only makes sense to learn them if you want to be an academic. If you want to sharpen your skills in the consulting world, join a Masters program and take every empirical class that you possibly can (anything that involves econometrics and gives you a chance to develop some software/programming skills). If you want to learn about contract theory and behavioral economics for your own enjoyment and edification, go for it-- just be aware that this is not going to improve your ability as a consultant.

I almost went there for undergrad. Overall I think it is a fine school, although I know nothing about the econ program. It is in my hometown so I can tell you that the school is located in a pretty rough area of philly. On the bright side, you wouldn't be too far from a good cheesesteak.

It is also important to consider selection effects when discussing this topic. People tend to overemphasize the added value effect of going to a top program while ignoring the fact that many students at top programs place really well on the job market simply because top programs try to admit only the most talented and hard working candidates. I think if someone is talented and dedicated enough to publish in the AER within 6 years after graduating, they are probably capable of publishing in the AER regardless of where they earned their PhD-- although attending a very low-ranked program might delay success (see John List).

I agree with some of the the other posters regarding the difficulty of completing a PhD transfer successfully. I think that doing this is probably not worthwhile in most cases. The only situation where I would advocate transferring is if your current program does not have faculty to advise you on the topic that you hope to research. If, for instance, you wan't to do research in labor econ and your current school doesn't have a faculty adviser who is an active labor economist, then you should definitively consider transferring. Moreover, your current professors will likely be more understanding of your desire to transfer if you explain that this is your circumstance. On the other hand, if you have an adviser who can effectively guide you through your dissertation, there is no reason, in my opinion, to think about transferring. A PhD is only as good as the work you do to earn it; so focus more on your research and your relationship with your adviser rather than worrying about how impressive the name of your school sounds when you mention it at dinner parties. Focus on publishing, not prestige.

You will learn about all that stuff in the class. However, since the class goes through the material so fast, you'll benefit a lot from having at least some experience with games of asymmetric information, such as principal-agent problems. If you don't have time to read all the papers, don't worry about it. It's not required, but certainly encouraged. If you can get through a dense theory paper in one day and understand everything in it, that is pretty good. It is common to have difficulty getting through theory papers; you will improve through practice, but I'm not sure it ever gets easy. You can take both courses if you are dedicated and ready to work your tail off. Also, you mentioned wanting to take contract-theory to learn something that is more "useful". If your goal is to learn something that is useful in an applied sense, I would suggest taking an empirical IO course over contract theory. While contract theory is a very interesting and important sub-field, it's often very abstruse and may not relate well to your research interests unless you want to be a theorist.

I took this course with Simon Board (so much for concealing identifying information). Is he teaching it again this year? If so, check out his webpage; he posts plenty of course material and past exams/assignments that will give you an idea of what you're getting into. This is a very difficult class. Many of the students in my year were unable to answer the problems he assigned on problem sets. You will probably need more preparation than MWG as the course is more game-theoretic whereas MWG is mostly focused on individual decision-making. If you are serious about the course, I'd recommend you start reading Bolton & Dewatripont's "Contract Theory" if you have time. Many of Board's lectures on moral-hazard and auctions overlap with the lessons in this textbook.

I couldn't tell you about Berkeley specifically, although I do have experience taking grad courses at another UC school. I can give you general advice. Go for the grad micro. The curriculum for grad macro varies widely from school to school, whereas grad micro does not. If you are interested in checking out the field courses (IO, international, ect.), keep in mind that this will be a very different experience from taking core micro or macro. On the one hand, field courses will be more difficult because the professor will assume that you are already familiar with the concepts taught in the core grad econ sequence, and assignments might require you to use advanced techniques and tools that you haven't seen before. However, it may actually be easier to earn an A in one of these field courses; professors are sometimes more lenient in grading field courses since most of the students attending a field course have already passed prelims and are just trying to prepare for doing research-- i.e. grades are meaningless at this point. That being said, you will probably get more out of a core course, since much of the material taught in the field course will probably be over your head (even if you are very smart).

I learned MATLAB for econometrics using John C. Frain's guide: http://www.tcd.ie/Economics/assets/pdf/TEP0110.pdf You can also download the LeSage toolbox for econometrics, in which case you can use the following guide: http://fmwww.bc.edu/ec-p/software/matlab/mbook.pdf Not sure this is what you were looking for, but these guides helped me a lot. Also, I don't know anything about mathematica but I'd recommend MATLAB. Its debugging features are great and it offers a great balance between offering an intuitive and technical interface.

MOOC is just another medium for selling educational content. If they are successful, I think it should help academics by lowering costs for academic consumers (students), thereby increasing demand. Think of what online sales of airline tickets did for demand in the airline industry. Of course there might be some organizational changes brought about by MOOCS-- e.g less reliance on tenured professors. But it is unfair to to speculate on possible deleterious effects without considering the countervailing benefits of new technologies and freedoms. For instance, being able to teach online certainly makes academic labor (professors) more mobile, so that a professor/lecturer who would otherwise be confined to a limited job market (say, the area where his wife works and kids go to school), would be able to apply for jobs that serve students all around the world.

Also look at Caltech and UC San Diego (I think UCSD has Vincent Crawford but I'm not sure). Keep in mind that both of these schools, along with the ones you mentioned, are highly ranked and therefore have very competitive admissions standards. Even if you have an excellent profile, you should still apply to some mid-lower ranked programs with strong behavioral departments. Although I can't name any off the top of my head, I am sure there are plenty of programs that fall under this category.

Statistics and econometrics (along with ability to use statistical software) are the most useful things you can study. Take as many of these types of courses as you can-- even take graduate coursework if it is available. No matter what you decide to do with your career (academic, industry, gov.), or what field in economics you choose to research, being really good at statistics will make you stand out. I think this is especially important because there is a good chance that your interests will change over time and ideally you want the things your studying now to help with what you do in the future. Also, don't discount the value of a liberal arts education. Being able to write well and articulate an argument is one of the most important skills an economist can have (for support of this, see Andrew Oswald's advice to young researchers: http://www.andrewoswald.com/docs/Young-faculty-researchers-PhDs-talk-Oswaldapril2013.pdf).

I'm assuming your referring to Friedman, Milton, "The Methodology of Positive Economics", Essays In Positive Economics (Chicago: Univ. of Chicago Press, 1966), pp. 3-16, 30-43. His argument isn't that the theoretical premises of economics don't matter-- that would be a pretty foolish thing to say. He simply argues that investigating the truth of these premises is a waste of time because if they are false then they will produce bad predictions. In other words, he thinks that the quality of the predictions is a sufficient test for soundness of the premises, which should otherwise be taken at face value. In my opinion he overstates this point a 'bit. There is still something to be said for having premises that don't completely violate common sense. Moreover many theoretical models are difficult to falsify by empirical test (see macro). Read my first post and you will see there is nothing inflammatory. I basically just said that doing quality research (regardless of field) is more difficult than doing math problems. The rest is a tangential set of responses to Insti.

Truths about what? As with logic, all mathematical truths boil down to tautology. Hence math itself doesn't say anything about the real world (although this is sometimes debated by philosophers-- see Frege and Russell for instance). Even if we were to accept the claim that mathematical truths are objective truths, then this does not imply that any field that uses mathematical proof produces objective truths. It merely comes down the the difference between validity and soundness: proofs guarantee the validity of an argument but not the soundness. Validity is necessary but not sufficient for establishing truth. Since economics is an empirical science, the truths of economic propositions isn't guaranteed merely by mathematical validity. I'm sorry for that. Try checking out a book on sentencial logic at your school's library. Take a look at Rudin and tell me the ratio of words to mathematical symbols used. So are you arguing for the objectivity of a proof based mathematical approach or an empirical approach? Or perhaps both? Please be more clear. If the data referred to by an argument is noncontroversial (the sky is blue) and does not make any statement about measure (quantity), then there is no need for data or mathematics. Why would philosophers use math to address issues in, say, epistemology? Different questions warrant different approaches. I don't know where you're getting this from. And yes, drawing up an unflattering an ill-informed caricature of a discipline counts as belittling it.

The point of my post was to make a general claim, using philosophy an example. Your response reflects an immature attitude. Have you ever read an academic journal article on the topic of philosophy? Probably not. Yet you feel qualified to critique the entire discipline. What are these objective truths you speak of? Just because something is mathematically expressed doesn't make it an objective truth. Mathematics is an analytic tool that produces solutions to problems requiring complex deductive reasoning. These are theoretical solutions, not "objective truths". Economics is an inductive science that uses mathematics to extract conclusions from a set of theoretical premises; and these conclusions are then tested against empirical data. Although mathematics assures the validity of an argument, it does nothing to assure the soundness of the premises (and let me tell you, every economic proposition, even at the most basic theoretical level, is riddled with simplifying and identifying assumptions). So give me a break with the math = objective argument; that is the type of thing one typically hears from naive undergrads who know nothing about how the field works. As for philosophy, I don't see how not using mathematics invalidates a line of inquiry. The standard in philosophy is to present a logical argument; sentencial logic is taught at the beginning of any philosophy graduate sequence. Logic precedes mathematics in that the rules of mathematics are derived from axioms established by logicians. Philosophers tend not to use math because the substance of their arguments is usually not quantitative, so there is no need to use math as an analytic tool. However, this is not always the case-- some philosophers do use math (in fact, many of history's most famous philosophers were also prominent mathematicians). I never said that math is easy. I'm not sure where that knee-jerk response comes from when I simply said that other fields are rigorous and challenging despite their not being mathematical. The fact that developing original insight is much more difficult that solving problem sets will become self-evident when you enter the dissertation phase of your PhD (but hopefully you will realize this sooner).