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SlowLearner38

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Everything posted by SlowLearner38

  1. I'll reiterate what I always say in threads like this: Python. Python. Python. Learning Java from scratch for an economist is nuts. You're not building webapps with complicated user models, you're writing code to be used in research -- often nothing more than a simple script. Python is one of (if not the) easiest languages to learn. In fact, rarely do you need to have a deep understanding of Python to get something working. Sure C++ is marginally faster than off-the-shelf Python code, but for CPU-bound tasks, if you learn how to use standard Python libraries like multiprocessing (the goto method for doing parallel processing in Python), you can increase the speed of your code by a factor of N (where N == the number of cores on your CPU). Although I'm no longer in graduate school, I still do research with economics PhDs in academia and and IT consulting work for economics PhDs in industry, often helping them implement a programmatic solution to their problems. 90% of everything I do is in 1 of 2 language: Python or UNIX command line tools. Never once has my choice of language limited me. I have an open challenge for any economists to find a problem that they can do in another language that I can't replicate in Python. So far I'm batting 1.000. As others have said, you are an economist and not a computer scientist, which is the right attitude because you don't need to know the theory -- you just need to know how to use the tools to do the things you need to do. The best way to start down that path is to find a specific problem that you need solved and begin trying to implement it in Python. There are so many tutorials out there for Python it's incredible. Start there and learn as you go. Don't bother buying any books -- that's not a good approach for an economist to learn to program. Find tutorials online and try to replicate them, then tweak that code to your needs. Learning to program when you're not a computer scientist is best done with lots of hands on practice. Here is my blog where I have a handful of Python tutorials that you may or may not find useful: Python for Economists
  2. Hey hedgequant, I'm moving to Houston in July when the lab I work in moves down to its new home at Baylor College of Medicine and the CS & Applied Math departments at Rice. Looking forward to getting back to the south + not paying state income tax! I'd be happy to meet up once we're both settled in down there.
  3. I'm generally not a supporter of relying on others to collect and aggregate data for me, however, I recently came across Quandl - Intelligent Search for Numerical Data and it might be worth looking at. Basically, they have ways to access a variety of datasets from various sources using Python, R, MATLAB, Excel, etc.
  4. This is just a pet peeve of mine but the short name for Industrial Organization is not I/O, it's IO. The forward slash doesn't make sense. I/O is Input/Output. Just saying. :encouragement:
  5. If I would have instead picked Arizona around this time a few years back, I think I would probably still be in a PhD program. I agree with your assessment of their economics program. It also seems to be the program that you know the most about. Arizona is one of the few programs that doubles down on the microeconomic principles like game theory, IO, mechanism design, experimental/behavioral, networks and so on. In about 5 years from now, if you want a great paying economist or research scientist/associate type job at a tech company like Amazon, Google, Microsoft, Yahoo or eBay, then Arizona probably maximizes the probability of doing so. If you want to be a professor, then Arizona won't limit you from becoming one at a good school. Pick what ever school you want because at the end of the day it doesn't matter. The main influence on your eventual outcome is and will be you.
  6. Personally, I'd like to see Leontief input/output type models come back to fruition. [Then again, it'll be a cold day in hell before I ever step back into the realm of macroeconomics.] The idea that the macroeconomy can be reduced into a single model is insane. Heck, one has a hard enough time reducing measures like growth rates within a single industry into a 1 model.
  7. Wayback Machine to the rescue. Oldest record of the page is April 2009: FAQs : Doctoral Program : Department of Economics : Eller College of Management : The University of Arizona -- Verbal: 500, Quant: 770 Then the statistics changed in July 2011: FAQs : Doctoral Program : Department of Economics : Eller College of Management : The University of Arizona -- Verbal: 500, Quant: 780
  8. I've finally worked out a few bugs in a tool I've been building and I feel it's time to get some feedback. The tool is an ngram viewer/searcher for abstracts on SSRN -- here's the link: SSRN Ngram Viewer First of all, this is for searching unigrams and bigrams in the abstracts of research papers on SSRN over time and not the full text of the papers. Search queries can be filtered by academic institution as well as by the field which the paper was posted on SSRN (Economics, Financial Economics, Cognitive Science, etc). The point of the tool is to let people play around and spot trends across these categories, as well as help people find relevant research articles on SSRN. For a given query, click the dot on the line at a particular year to see a list of the research papers that make up the data for that point, along with the appropriate links to the abstract's page at SSRN to view the abstract and/or download a PDF of the paper. A couple disclaimers: It is against the Terms of Use of SSRN to automate the download of PDFs and I've done everything I can to respect all their policies. The website may go offline at anytime as I continue adding features and do maintenance. Respect the server or you'll be handled appropriately. On that note, feel free to share any interesting queries you come across or major bugs you see. This is still very much a "beta" version, so expect some bugs. Have fun!
  9. I'd rather call it privacy than anonymity, and privacy always boils down to economic trade offs. As it relates to this forum, I really don't care if people know who I am because everything I post is self-selected, which is the same rule of thumb I follow with any social network. It's a game that is solved using forward induction in my mind -- if I choose to release information that could jeopardizes my privacy in any way, then it must be that I feel the value added exceeds my loss of privacy. That being said, the Internet is written in ink, so playing the game improperly even once can result in potentially large losses. In general, I do feel that privacy is an extremely important topic for everyone. I remember in graduate school when I had a semester long debate with a professor about what the most important problem on the Internet is: I said privacy because it affects every single user of the Internet, he/she said something else. Even though I was confident I was right then, it's been nice to see evidence that economists are beginning to recognize the issue of privacy. For example, the most downloaded paper on SSRN right now is about privacy, and particularly why the "but I've got nothing to hide" argument is flawed. Also, if you've been following the FTC lately, you'll see that privacy is very high on their agenda (for example, in mobile apps). Information can be misrepresented, and the consequences of this can be huge. Think about it, let's say I apply for a million dollar life insurance policy. The insurance company will be more than happy to spend some money obtaining a profile about me that one of the data broker companies [which the public never hears about] has compiled. These black box profiles contain information aggregated across many avenues of technology that the Internet has made available. These black boxes are run by supervised algorithms that try to determine a person's type/preferences or whatever is relevant to their consumers -- marketing companies, insurance companies, HR divisions, etc. If I've learned one thing since moving my career more towards computation over the last few years, it's been the understanding of how 1 line of code on the backend of a website/app/etc, which the user will never see, can completely change their privacy experience. As it stands, these problems are going to persist for the foreseeable future for those who are uninformed, which is the majority (a digital divide problem). The fundamental problem is that the people who are doing the online tracking will always be more informed and have lower costs to become informed (economies of scale argument) than those being tracked. This is why I'm a supporter of movements like "Do Not Track" because the whole goal of it is to reduce the technical costs for those who care about privacy, but don't know how to actually protect it. The Do Not Track mechanism may not be perfect yet, but it's a step in the right direction. Sorry for the slight tangent, but I really believe these are important issues for everyone.
  10. Why is that unfortunate? Cleaning data properly often decides whether or not a project even gets off the ground. Being the data ninja in an academic environment like economics often leads to monopoly power and the thrill of gobbling up all the low hanging fruit.
  11. Good suggestion! There is a decent-sized learning curve for git, but it's definitely worth learning. The benefits of git are that it helps you keep track of changes you're making to scripts/files/etc that you are regularly working on, easier collaboration on these files and general increased productivity. If you're on a Linux/Ubuntu box, you can install git via apt-get by opening a terminal and entering: ~ $ sudo apt-get install git-core After installing git, cloning an existing repo (downloading it locally) is easy. For example, clone my public repo containing Python scripts for scraping data from newegg.com: ~ $ git clone git://github.com/econpy/newegg Moreover, here's the github documentation for creating a new repo: https://help.github.com/articles/create-a-repo. FWIW, students can obtain a paid account for free at github.com by following the directions here: https://github.com/edu. A paid account allows you to create private repos (free accounts can only create public repos). Fun fact about git: The creator of git is also the creator of the Linux kernel: Linus Torvalds.
  12. This thread seems fitting for a piece of motivational advice that I feel like sharing for all the new grad school hopefuls. It doesn't matter if you're in Economics, Sociology or Art History, the same logic applies: [video=youtube;STpd_VIZm-Y] The man, the legend. Bill F*cking Murray. The moral of the story is that if you know that what you're working on is important, then don't listen to anyone who tells you otherwise. At the end of the day, your biggest enemy in grad school will be yourself. Come to terms with who you are and what you want to do/change, because the sooner you do that, the better your plan of attack will end up being. "They can buy anything, buy that can't buy backbone."
  13. This may be among my top 5 favorite TM threads ever. I had the great pleasure of meeting Humanomics 2 months ago over some beers and grub in Chicago. Let me tell ya, that's a straight shooter with upper management written all over him. Well deserved! [clap]
  14. Not that I know of, but this dirt cheap book provides a great exposition to all topological topics that you'll come across in an economics PhD.
  15. If you have access to a Windows computer, then you can make a bootable Ubuntu USB drive using Linux Live.
  16. Hey, check your practicality at the door! I want overkill! :) I enjoy walking into my office, flipping on all the monitors and whispering to myself "Inform Lord Vader that the Death Star is now fully operational."
  17. If upgrading from a SSD with SATA2 to a SSD with SATA3, the marginal gain is only worth it if you need to be frequently moving very large files around (I'll say, 5GB+). The most worthwhile gain lies simply in moving from a HDD to a SSD of any speed.
  18. This is my main laptop: Amazon.com: HP Pavilion dv7-6b32us 17.3" Notebook (Intel Core i7-2670QM, 4GB DDR3, 640GB HD): Computers & Accessories I bought it from Microcenter about a year ago as an open-box, refurbished computer at a price of $580. The main draws to this laptop were the following: 17" screen 9-cell battery 2 hard drive bays Support for up to 16GB of ram i7 processor Obviously, the first thing I did was get rid of Windows. The 2 hard drive bays was a huge plus. I took the 640GB hard drive that came with it and put it in the 2nd bay and replaced the main hard drive with a solid state. I then upgraded the memory to 8GBx2=16GB of ram and was ready to roll. The total cost was somewhere in the neighborhood of $750 when all was said and done. By far the best laptop I've ever owned. I wouldn't hesitate to do anything on it. Long story short, when buying a laptop, you should look for one with the best set of core features that are not as easy to upgrade later on (see my 5 bullet points). Also, as another poster mentioned, desktops will always be faster than laptops. The reason is simple: heat. Comparing a laptop and a desktop with the same specs, the desktop will always be faster because it can disperse heat so much better. Heat is the enemy when it comes to a computers performance. For reference, the laptop I described above usually runs between 45 C - 70 C depending on the load, whereas my somewhat comparable desktop usually runs at 28 C - 45 C.
  19. Good, neither do I, because the answer is Linux (i.e. Ubuntu or Linux Mint). :) Now that the OS question is out of the way, let's tackle your other questions: The main difference is that 3rd generation i-Series processors use less power. This is not very important for your use case, so if the price difference is right, go 2nd generation. The i7 is a great processor (I own 2, one in a desktop and one in a laptop), but so is the i5 and the i3. The CPU is not going to be a bottleneck for a graduate student who wants a computer to do data related applications. The bottleneck is most likely to be memory. That being said, if you're debating between an i5 and an i7 and money is an issue, go with the i5. You will never have any regrets. If you go with an i-Series processor, it will have at least 4 physical cores. Some i7 processors have 4 physical cores but 8 virtual cores (i.e. the i7 2700k). I would not recommend an AMD processor to anyone unless they are on a very tight budget. That being said, I own 2 AMD processors that I have in desktop computers (4 core Phenom and a 6 core Phenom). From the benchmark tests I've done, it is incredible how much faster the i7 is than the AMD processors. Even my first generation i3 in an old laptop is faster than the 6 core AMD processor for most in-memory data analyses. In my mind, memory is the 2nd most important factor when buying a computer (#1 is the hard drive). You shouldn't be looking for how much memory the laptop has preinstalled, but rather, what the maximum amount of memory the laptop's motherboard can handle. Most laptops now max out at 8GB or 16GB and have 2 memory slots on the board. Memory has become so cheap that you should upgrade the memory after you buy the computer. Ideally, you'd find a laptop with, say, 4GB of memory but capable of handling up to 16GB. That way you aren't paying a premium for memory when you buy the laptop, because you should upgrade it on your own after the fact. I have 2 computers with 16GB of ram and one with 32GB and I would never go back to anything less than 16GB, but my use cases are probably much different than yours. Re: Hard drive -- similar to the memory situation, I'd advise you to find a laptop with a crappy hard drive or whatever size and plan to upgrade it to a solid state drive. Performance per dollar spent, a solid state drive is the best investment you can make in a computer these days. The performance gains are seriously incredible compared to a classic HDD that was moving parts. :2cents:
  20. Some of my favorites: IO: "A Model of Sales" Hal Varian (1980) "Hassle Costs: The Achilles' Heel of Price-Matching Guarantees" Morten Hviid & Greg Shaffer (1999) "Measuring Prices and Price Competition Online: Amazon and Barnes and Noble" Judith Chevalier & Austan Goolsbee (2003) "Empirical Industrial Organization: A Progress Report" Liran Einav & Jonathan Levin (2010) Macro: "Japan's Phillips Curve Looks Like Japan" Gregor Smith (2006)
  21. Interesting. I just rewrote most of their Python script on the website for fetching data from the Google Ngram Viewer to clean it up a bit. I'm going to shoot them an email with it to test the waters. Thanks for the tip!
  22. Good move by UT. I think there is growing demand for the MA in the US. There are lots of lucrative opportunities for people with an MA in Economics in the private sector, particularly in IT.
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