APJ

Yes, It is amply clear that there is trade off when you choose academic career as against corporate career. The terms of trade off include independence vs designated job, research motivated by passion about the question or subject vs research motivated by money making objective, opportunity to work on the topics of own interest vs at least at initial stages predefined job, leaisurly life style vs hectic life style (some say active), enough money vs rich. What is needed is that one thinks carefully before he decided anything. Its certainly not easy to give 5 years to a PhD program if you do not have passion for research. But I also add that certain jobs in corporates require hight level skills in finance/economics/mathematics and these are generally possesed only by PhD people. So even after doing PhD, you can certainly be well employed in Industry in a fruitful job. MAny of the corporates do give some space to write own reserch and even publish it. So not all is lost if one joins in corporats

thanks guys, links were really helpful

Dear all, I am working through SLP for dynamic programming. I am doing fine with it, but I am getting a feeling that I need to read something more intuitive as well at this stage. May be a worked example or simple explantion of bellman equation etc. Can anyone suggest me some resources on that? Thanks

Mathematical Methods and Models for Economists by Angel de la Fuente and Real Analysis with Economic Applications by Efe are good, accessible texsts.

Science moves ahead if scientist convert even obvious looking things in to scientific model. Though it is obvious that poor food intake will affect work productivity, mathematical model may lay the foundations for empirical analysis of questions of the form such as what is the extent of this relatioship between food intake and productivity etc. The fact that why economics could convert itself from mere collection of rules of thumbs to a science is the fact that economists have always tried to build models. Some of these might be ridiculous, but great discoveries have always come through solid theoretical models, which might have based on some seemingly unrealistic assumptions. The fact that economic studies now can not be dismissed simply by argument, but only by other scientific study is a great achievemnt of the field and I think this approach to abstarct from the real world has to do with it. In philosophy, any study will be refuted by a mere statement. This is not an ideal environment in which any field can blossom. Once convinced that this approach which economic sciences has adopted is correct, we can ask next question whether this approach has delivered any results? No one can deny that some of the magnificiant insights about how economy works have come through theoretical models: Information economics, asset pricing, labour markets have all been developed using same apporach which has enriched our understanding of the world to a great exent, even when models in isolation might have looked bit unrealistic.

It does not offer scholarship for economics. I was going through the fields of study which are eligible for scholarship.

Ecotrix + Measure theory. (In ideal world all three, but given constarint, this is optimum in my opinion) For two reasns: 1) Trix will be interesting to know before you start with graduate level trix 2) FA comes after Measure 3) Measure theory will be useful in its own right

I am from Asian University too. I did not have any research experience and my maths grades were poor in MA eco (Barely managed to pass). To compensate that I did another 9 months masters in mathematical finance and did well (fortunately) on that (Topped the program and thesis) I do not think lack of Research experience might have killed you. As fas as my college is concerned, none of the previous candidates had research exp. but still guys with good grades and letters managed to crack in to Princeton, NYU, columbia and at least 5-7 guys get through Maryland, Boston, Indiana, Pennstate each year. A very good RE might improve your chances but lack of it can not kill you. MAny of the candidates from my college who did RA with professors, J-PAL etc could not compensate for lower grades and got shut out. Of course, you have to be competitive in other aspects of your profile. For Asian Universities, they look for straong grades and some LOR's from the professors they have come to know over the years. Like, in my college a sprofessor writes letters only for bright guys. He is not well know (hardly has any publications) but the candidates he recommanded did extremely well in the program. So his letter will be valued a lot even when he is not famous. So for Asian Universities, these aspects might be more important than research work.

Yes, MWG is tough, but it is the most precise and elegent of all in my opinion. But you can refer to various sources topic wise. For example, Varian/jehle also are good for consumer theory and production theory as results are srandard. For industrial organization, you can refer to Tirole and for GE, Jehle might look more compact. Else you can look directly in Theory of Value for that matter. For moral hazard problems and related stuff, Kreps give you excellent intution and after that reading, you can go through MWG/Laffont-Tirole/Jehle. But MWG presents all in one and it is not like Green's textbook on econometrics (with no theme and uselsess notation). On the other hand, i find MWG intutive and precise.

As per email by Aude some time back, they offered 6 scholarships under TSE/JJ Loffont fund. 3 students were in waitlists including me. But since I am not going, someone lese might have got on the waitlist. This implies that they will/may not extend anymore funded positions.

I might pitch for marks improvement more than field experience. (If there is provision for retaking exams). If your grades aren't great/good, probably J-PAL may not help much to subside the impact of lower grades. You need good LOR's to crack in to Phd programs. I am not sure, if J -PAL job would give you imporved LOR's. A systematic RA under some professor might help more than J - PAL in my view, if retaing exams or additional course work is not possible.

I feel BU MA is more solid than UCSB. four reaons: 1) There coursework at least contains micro, macro and econometrics at a reasonably rigorous level (though not as rigorous as Msc in LSE or UCL is concerned). 2) There is some trend of students applying to PhD programs from BU MA. 3) There Ma job placements are better than UCSB. 4) You can always take audit courses in BU or BC or MIT etc, which is a great opportunity

hey thanks, thats useful

Dear all, I was just going through convex analysis and wanted the proof of Farkas Lemma. I came across couple of places where it is given, but they are not exhaustive proofs in the sense they assume some major result and Farkas Lemma comes out as a corollary. Proof given in Kim Border also does not give proof of it and Efe requires reading complete chapter on convex analysis to understand the proof he has given. Where can I get a clean proof of Farkas Lemma? Preferably from Linear algebra point of view. Thanks

Thanks asquare for such a detailed and very informative post. and thanks to you eigenman as well. So the sense I am getting is that your advisor is not going to help you out with each and every equation you write, but may guide your general direction of research and looking at the big picture of your model etc. Also seems to be lot of work from 3rd years onward. But one thing seems to be good that I can write on two linked but seperate issues as a part of my dissertation.

Hi guys, First couple of years in the program will be devoted mostly to coursework and research seminars. The real research work would start from 3rd year onwards. Though all of us have some idea about how these years will span, I was curious to know more. How often do you meet your advisor and when do you know that you have a publishable idea with you? Does a candiate keep on developing his model/theory all the three years or he kind of churn many publishable papers during the PhD itself? Also how would be the work load? Do we get seperate room or cubicle to work with? I know it is not a very informative/intelligent collection of questions, but I was curious to know. Thanks

Are you really sure? When whole batch of MBA's from a good college (around 100 students) get average offers of 100K - 120K, PhD's should earn at least that much. I was in London for a year and Phd guys from college get around 80K -100K pounds on an average, even when my college was not higly ranked like LSE. Top guy from Ohio state (Fisher business school) got a million dolloar job in some private sector outfit (of course his profile was great and his research was excellent and all, but that is what we mean by a top guy). I doubt if a top guy would get only 100-200K range salary. They should be able to claim more. The problem is PhD guys may not be wanted by some corporates at all because there is no specific work which require such a high level of research output. In that case premium will be low of course. (Just to support my point, A friend of mine, who passed out from MIT as a PhD in chemical engineering got the offer of 300K for 6 months consulting with Mckinsey and this was 5 years back.) For economics/finance, you got to expect more if you have valuable research/strategies really useful for corporates.

I agree. But I quated just in case. Hogg and Craig is a better text

I do not know much about MS programs in USA. For Europe, I guess, PSE, Toulouse, LSE, Oxford Mphil, Tinbergen Mphil, Barcelona GSE, Vienna are all good and can place you in good programs. But I guess, U Toronto, British Columbia, Boston University, NYU also has good MA programs. But I have heard skeptical views about their abilities to plce students in top PhD programs. But on this, I agree with dreck, that you can be placed in top ranked institute, if you perform well even if you come from not so highly ranked UG program. (My college in home country which is not even a top 500 college in World, places at least 3 students in top programs each year). But buidling maths/stats in one more year of UG 9as suggetsed by dreck) is better than doing MS from delware

Micro: MWG (Great introduction to Game theory as well, but not sufficient obviously. The clearest presentation of basic game theoretic concepts I have evenr found at a rigorous level. Gibbons is a good starting point, but less rigorous) Kreps gives good intuiion to the ideas/model (especially moral hazard models) but its not rigorous enough or even adequate. J- R is a standard text with good and clear language, neat proofs (But MWG is impeccable and most elegent) Macro: Many sources, Slp, Sargent, romer, Barro-Martin will do I guess Econometrics: I hate Green. Read chapter 8 from Hamilton. wonderful introduction to OLS, far better than Green's. Hamilton is of course preferred choice for time series. Hamilton is extremly good for GMM as well (Though Hayashi is a good text for this too). Davidson is a general reference, not very useful for 1st year I guess. Hayashi/amemiya can be good (good reference for mathematical statistics is hogg anf Craig, Rice or Feller) Mathematical Economics: I do not know if there is specialised course in mathematical economics in 1st year Phd, but I am ardent supporter of Efe Oke.

I guess, PhD is a different product from employer's perspective. There has to be a suitable role for phD in the organization. I do not think that PhD would be offered far higher a premium over Msc people if he is doing more or less same work as a masters candidate. In trading, PhD would work in developing new startegies and a trainee or starting trader would try to implement startegies closely. Nature of work and increased complexity or it, inability of a mere master's candidate to deal with the work would create a good opportunity for a PhD guy in a corporate world. Salary premium naturally follows.

I disagree with assumptions part. One economists (I am foregetting the name, but he is a nobel prize winner) said that you can classify assumptions in to two sets: critical and non critical. critical assumptions are those which if altered would alter basic conclusions of the research. Non critical assumpitons if changed may at the most make it difficult to prove the same results. These are generally made for mathematical convinience. Hence, counterarguing these assumptions does not invalidate the theory. Also, if certain result is achieved under specific distributional assumptions or linearity etc, research always almost tries to generalise the assumptions. (For example, see how the asset pricing field tries to make a point in general settings). It is not always possible to achieve desired results under fully realistic set of assumption in one go. It is a process: called research. If one is not comfortable with this (which I feel is a right process, albeit slow) process, then probably research is not the optimum field for him to work in. Again, the real test of the theory is not the quality of its assumptions, but if theory works in practice. Inability to understand DGP (data generating process) may lead economists to work with what may look like unrealistic assumptions. But if theory fits in practice, there is no mechanism to throw the assumption in garbage box on the plea of being unrealistic, simply because there is no mechanism to verify if the assumption is false. Also, in certain cases, even when it is amply clear that assumptions are unrealistic, even then there is no need to throw the theory out the literature. Simply because, theory may make a point which is unobservable otherewise. Theory might not be intened to work in practice immediately or may just introduce new tool of mathematics/econometrics to the science of economics (Like GMM by Hansen), or it might simply try to characterise phenomenon in toy world. It thus sets responsibility on ohter researcher to convert the toy equilibrium/findings to real wolrd equilibrium etc. (I always find example of finite state pricing by Arrow - Debreue compelling to make this point. The logic is, though everyone knows that world is not characterised by finite states and probability space might be dynamic through time, the first step to price security in infinite state space is to price it in finite and stationalry state space. Hence, though assumption of finite state may look unrealistic, it paved the way for great research to foster in coming decades.)

Well said Gecko ! But surely I agree that good models which presents big ideas for the first time may be simple. But as more and more research goes on in that filed, themes of research gets on more complicated and neccessarily technical. So, the way economists use mathematics and language can not be considered mere addiction to do that. It might be neccessary. Of course, you will find cases of both sorts. BUt I am giving my overall impression about the field.

In corporates one would enjoy more monetary rewards. say a PhD in Financial economics/Markets would enjoy good economists position or trading position in bank and he would earn round about 200K initially.

I do not know much about Rudin as a mathematician except his book on real analysis. When John Nash visited my college in 2006-07, he said asthetics of the proofs is as much the part of mathematics as result itself. Rudin's book certainly fits in to this scheme !