B.Ec.+M.Ec. or B.Ec.+M.Sc.?
Hello everyone,
I'm getting my bachelor's degree in economics next spring. I've done an extensive minor (~60 credit points) in quantitative finance and learned some computer languages in the process. I'm planning to get a master's degree in order to become an expert in econometrics and perhaps pursue a PhD. However, I can't decide which major to choose. I'm currently considering the following alternatives:
Major in econ, double minor in applied mathematics and computer sciences Major in applied mathematics, double minor in statistics and economics Major in statistics, double minor in applied mathematics and computer sciences
Which alternative do you think would be the best choise with econometrics in mind? Is there some better alternatives?
it's marginally different.. I personally would like applied math & econ/stats, because this is the most flexible for Engineering depts, b-school and math/stats/CS departments.
Otherwise just don't risk youself in exit opportunities you don't like.
Thanks for the reply.
I'm thinking of taking some courses in advanced calculus and linear algebra. Do you think there's some specific courses that I definitely should take in addition to these? What about computer sciences? Do you think it would be a good idea to minor in this subject, given that I can already use R and some C++?
I have a math/finance background, but I'm no PhD, so ask around your professors etc as well. things I personally hope to take in the future with a bias in..... economics would be Game theory, strategy, math would be regression analysis (plus all kinds of regularization, nonlinears), stoichastic models/calculus CS would be infrastructure/architecture and high-performance computing.
it's often to see a CS star or a Economics/Business star. But it sucks that programmers can't run business because they don't know, and business workers can't write code when they know the processes best.
I think you'll be bound to do computations if you wanna do PhD in this type of fields, whether it is research, data analysis, algorithms or even for teaching intro classes, so yes I think CS type of things like architectures type of class is quite valuable. I don't have the resources to take them but had to learn VBA from rookie to expert in about 2 months.
But unless you're a theorist with pens and chalkboards talking theories, wouldn't applied stats include computing as a typical deal??
lastly, it sounds like you're locking the school you're going, but you're taking a Master's first? why? and why? if you could do PhD at a reputable place directly, which is hard but doable, it saves tons of $$ with PhD subsidies..
I live in Finland, so the education up to Master's degree is free, given that you get accepted into a university. I have been accepted for the Master's program in economics, but due to my aptitude in mathematics I've also been offered the chance to change my major to applied mathematics or statistics. Hence I'm quite reluctant to change schools at this point, although I'll probably go abroad for a PhD.
I've been about half and half for applied and theoretical statistics. I've mainly used R, although I think the computing I learn in applied statistics classes is quite inadequate given the level computations many PhDs do in econometrics. At this point I'm quite familiar with different methods of regression analysis, resulting in both linear and non-linear models; GARCH models, mixed models, VAR models, etc...
Would you care to opinionate which computing language(s) you find most useful?
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