LouisBD

Time series can be taught on many levels. Enders is a pretty applied text. It just gives you a quick intro. I like the text and benefited from it for my undergrad thesis. Lag-operators are pretty standard, you'll find them in Hamilton too (as far as I can recall); and Hamilton is considered to be the standard grad reference. If you go to the more advanced stuff then you'll encounter tons of Laplace transforms. Check the work by Gourieroux and Montfort for example. But this is pretty advanced and specialized stuff.

Learning Stata and Matlab is the best investment in terms of breadth. Stata is good for data cleaning and straightforward graphing. A large part of the empiricists (especially micro-econometrical) use Stata. Matlab covers much of the finance and macro economics researchers. R and Sas are more idiosyncratic within the econ community. R is nice for Bayesian stuff. Sas is used a lot by the market microstructure gang -as they often deal with huge datasets.

The linear regression is the most popular empirical tool but certainly not the only one. Let me just give two examples: In IO, structural econometrics is a big thing. This can be computationally pretty intensive sometimes, but big fun too! Since Berry, Levinsohn and Pakes this field really took off (important older contributions too eg. Mcfadden, but powerful computers allowed for more advacned simulation based approaches). As an example consider for example this cool project on last-in first-out oligopoly dynamics: Last-In First-Out Oligopoly Dynamics [i might as well take an example from my uni]. as you can see this goes well beyond OLS. Not everyone likes this research area but I think it is big fun (note that I am not doing empirical IO myself). Another example is macro-econometrics. A cool contribution in this area was the JMP by Primiceri: http://faculty.wcas.northwestern.edu/~gep575/tvsvar_final_july_04.pdf (although a bit technical). Lots of Bayesian stuff in this area (see the website by Christopher Sims).

If you have your mind set on experimental/behavioral stuff you may consider Tilburg too. Check out the TIBER website: Tiber Conferences - Tilburg University Some researchers you may consider to check out: Jan Potters (experimental) Jan Potters - Publications - Tilburg University Charles Noussair (neuroeconomics/behavioral) http://www.tilburguniversity.edu/research/institutes-and-research-groups/center/staff/noussair/cv.pdf (a bit goofy journals over there but also AER, JF and the like) Tilburg is not a top 20 place, so it isn't strong in all fields, but it does pretty well in the experimental scene. Big names visit pretty often (List comes nearly every year). Not that into experimental so I can't help you more than this.

If you really want you can always find a use I guess, for example, Agebraic Topology: http://www.carloalberto.org/files/no.94.pdf I once even saw a paper which combined quantum theory and game theory... So happy that I chose not to pursue the path of a pure theorist.

Hmm, I do not think it is "the" ideal place but if you are smart in the choice of your supervisor; recommender; teacher of electives then it may do you some good. The KULeuven sends each year one or two students to the US top schools, so if you are among the best if not the the best, then it may do you some good. It is a one year master,so the usual caveat applies...

I have seen a couple of times people with double phd's. Some that come to mind are Jun Pan: http://www.mit.edu/~junpan/JP_CV.pdf (MIT) Don Kim: FRB: Federal Reserve Economists: Don H. Kim (Fed reserve) Anna Mikusheva: http://econ-www.mit.edu/files/4937 (MIT) Bram De Rock: cannot open his webpage but publishes well: Bram De Rock at IDEAS (Ecares) ... Coming from a strong scieintific background, these people often tend to go into the more mathy fields. It may be that some schools do not like people who want an additional phd. but it seems possible. If you like finance and you can get in stanford gsb (ok, this is arguably one of the most difficult places to get into) then you can hone your physics skills in finance...Duffie can get pretty mathy.

Graciela Chichilnisky: (from a wiki) Born and raised in Buenos Aires, Chichilnisky completed no undergraduate studies, moving straight to PhD work in the MIT econ department. She later moved to the math department at Berkeley, where she earned her first PhD. She earned a secondBorn and raised in Buenos Aires, Chichilnisky completed no undergraduate studies, moving straight to PhD work in the MIT econ department. She later moved to the math department at Berkeley, where she earned her first PhD. She earned a second from Berkeley's econ department from Berkeley's econ department But these are exceptions (given that she obtained a math phd at MIT, she probably has good brains)

Concerning econometrics, I do not consider Cameron and Trivedi nor Greene good texts to learn from. However they are great if you already know some econometrics and you need to look something up or you want to pick up something new for your research (say you are interested in stochastic frontier analysis, which is not covered in a standard econometrics course, you can look in greene, or you need a particular type of bootstrap etc.) To study from cover to cover, Hayashi is arguably one of the best although a bit advanced (but at the level any phd student should be able to grasp with normal efforts). The book contains just the right amount of things but views the world through a GMM perspective -which I my opinion is very elegant. Probably you want to do go through a mainstream text first. I think Verbeek is very good in this respect. Fairly easy (assuming you are familiar with basic linear algebra and statistics), covers a lot and not that thick. I am not familiar with Davidson and Mckinnon, but as far as I've heard, it is an excellent text too. Concerning time series, Hamilton is "the" reference although not the easiest to use as a study text. Enders is pretty applied but also a bit slim. It is a much more readable text than Hamilton however. Just my 2 cents.

Do 1 thing and excel at it. Try to max the grades in 1 program. If you can position yourself in the top-1 (or as close as possible) of your year, you'll have a great shot.

I assume that with wooldridge you mean the intro book (and not the book on panel data). Then it is quite a jump to Davidson and Mckinnon. You might want to consider to walk through Verbeek (Guide to modern econometrics) before going to Davidson, but it will depend on your background. I feel that Verbeek is a very good book, although not on phdlevel, it is very concise and covers a lot of ground. If you master that book, transition to advanced books is much more gentle. Among the advanced books, I feel that Hayashi is one of the best. This feeling is shared by nearly everyone who has familiarity with that book and the reviews on amazon are uniformly excellent (which can only be said of very few econ textbooks). It is good to brush up the basics of linear algebra and math. statistics before going through the book (but only the basics).

This is not true. It saddens me that some have decided to destroy the reputation of CentER. Yes, this year there were some griefs about the bad communication by CentER but this is in the past now and I am pretty sure that this will not happen again in the future. For what it is worth, a little over 75% of all research masters who wanted to pursue a phd have been admitted. This amounts to 18 phd students in economics. You may argue about this but I am among these and I can name more than 6 students who stay for a phd in my track alone. What happened is very unfortunate and I really feel that the administration should have had somewhat more consideration. Scaring away potential students with these false stories is just wrong. I am not sure whether this forum should allow such actions.

Ending up at the top of the grade distribution in mathematics at Cambridge surely would boost your admission chances but, 1) Do not underestimate what this would demand from you. You would need to have more than average math affinity and probably would be in class with IMO stars. I know 2 students from my country would went to Cambridge to study maths and both students records in mathematics were stunning (Gold national math Olympiad, medals in the IMO). 2) It is sort of an overkill and you would have to immerse yourself in things which are basically irrelevant for economics (although good brain training without any doubt). 3) I suspect that it would take 3 additional years in which you will have little time to deal with economics. While adcoms will undoubtedly be impressed with your mathematical training, they may be less impressed with your revealed passion for economics. I am not sure how high your ambitions are (where you woud like to obtain your phd). If you would like to boost your chances you can consider doing another master degree but you would need to ensure that you are at the very top of the distribution and you could only apply a year later (when your grades are available, the phrase summa cum laude on your resume and the kille lors). I do not want to question your ability but since you have already studied at LSE and obtained merit, I think you should be able to answer yourself the following question: "Am I able to obtain the top grades in all courses in study X at LSE while enjoying my life at least a bit?" With X I am thinking about a good degree like Msc Economics or MSc EME at LSE... Just my 2 cents.

1) Yes a week in the fall 2) Core courses: There is one notoriously bad teacher. Not sure whether he will teach this year, it depends a bit. You'll notice who he is straight away. Micro is doable. Just make the homeworks. Macro can be a pain. Tons of slides, tons of dynamic programming etc. I guess this is the same everywhere. Econometric Theory can be a bit abstract. But it is a very eclectic course and I feel that everyone should take it. I am not sure whether it is mandatory, I think you can also take a lighter course. A very good is the microeconometrics course by Klein and Salm 3) Depends on your background I guess. For most it is pretty easy to get a good grade. Again depending on your background you better put enough effort in (even tough it may seem simple) as this will be very beneficial later on. I am not sure wether there is a real killer in the core courses of the 1st year.

About your last comment (that you edited) : I already work my *** off and am quite successful. So I dont need your wise *** commentary about my personal life. All I want to do is to inform people. Dont turn this into a personal matter. None of my friends were expecting to be rejected after getting 7.9 or 7.8 or 7.7 . I dont think they deserve to be rejected. If you try to talk to other students and coordinators (professors) you might see how disappointed most of them are. (and that they are not expecting 18 phd positions for gods sake) Good luck to you on your defensive endeavor I did not intent to give you advice, let alone "wise" advice. I am a bit disappointed on this matter too. I indicated this earlier. I haven't deserved you degrading post. But hey, for sure you are right and I am wrong. Your posts were also so balanced that it is clear to the outside observer that I am the one ranting. Please refrain of degrading me any further or using stars to mask insults. I do not have the habit of letting someone insult myself. I have entered this discussion without the intent of explicitly defending the administration and haven't concealed myself. I think this deserves a discussion partner who does not use stars -which typically are reserved for insults (the reason why I react).