oxdk_day1a - Advanced Programming in Quantitative Economics...

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Advanced Programming in Quantitative Economics Introduction, structure, and advanced programming techniques 17 – 21 August 2009, Aarhus, Denmark Charles Bos [email protected] VU University Amsterdam Tinbergen Institute Advanced Programming in Quantitative Economics – p. 1
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Day 1 - Morning 9.30 Introduction Target of course Science, data, hypothesis, model, estimation Bit of background Concepts of Data, Variables, Functions, Addresses Programming by example Gauss elimination (Installation/getting started) 11.00 Tutorial: Do it yourself 12.30 Lunch Advanced Programming in Quantitative Economics – p. 2
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Target of course Learn structured programming and organisation (in Ox or other language) Not: Just learn more syntax... Advanced Programming in Quantitative Economics – p. 3
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What? Why? Wrong answer: For the fun of it A correct answer To get to the results we need, in a fashion that is controllable, where we are free to implement the newest and greatest, and where we can be ‘reasonably’ sure of the answers Data Hypothesis E= f(m) Model E= m c 2 Estimation E ² = m ² (c ² ) 2 0 1 0 0 0 1 1 0 1 0 0 0 0 1 0 Programming Science Advanced Programming in Quantitative Economics – p. 4
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Aims and objectives Use computer power to enhance productivity Productive Econometric Research: combination of interactive modules and programming tools Data Analysis, Modelling, Reporting Accessible Scientific Documentation (no black box) Adaptable, Extendable and Maintainable (object oriented) Econometrics, statistics and numerical mathematics procedures Fast and reliable computation and simulation Advanced Programming in Quantitative Economics – p. 5
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Options for programming GUI CLI Program Speed QuanEcon Comment EViews + - - +/- + Black box, TS TSMod + - +/- +/- + Alternative Stata +/- + - - - Less programming Matlab + + + + +/- Expensive, other audience Gauss +/- +/- + +/- + ‘Ugly’ code, unstable S+/R +/- + + - +/- Graph +, speed - Ox + +/- + + + Links to C, ectrics C(++)/Fortran - - + ++ - Very quick, difficult Here: Use Ox as environment, apply theory elsewhere Advanced Programming in Quantitative Economics – p. 6
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History There was once... C-Programmer Memory leaks Shell around C Matrices ...and Ox was born. More possibilities, also computationally: Timings for OLS (30 observations, 4 regressors): 2009 Neh 2.67Ghz 64b 670.000 /sec 2008 Xeon 2.8Ghz OSX 392.000 /sec 2006 Opt 2.4Ghz 64b 340.000 /sec 2006 AMD3500+ 64b 320.000 /sec 2006 AMD3500+ 4.04 273.000 /sec 2004 AMD3500+ 3.40 218.000 /sec 2004 PM-1200 147.000 /sec 2001 PIII-1000 104.000 /sec 2000 PIII-500 60.000/sec 1996 PPro200 30.000/sec 1993 P5-90 6.000/sec 1989 386/387 300/sec 1981 86/87 (est.) 30/sec Increase: ≈ × 1000 in 15 years ≈ × 10000 in 25 years. Advanced Programming in Quantitative Economics – p. 7
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OxMetrics A P P S C O R E PcGive STAMP PcGets TSP O X P ACKAGES + x12arima + SsfPack DPD, MSVAR + PcNaive Arfima, etc. Ox programs OxMetrics Ox interactive graphics numerical programming data manipulation computational engine results storage interface wrapper code editor Advanced Programming in Quantitative Economics – p. 8
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What is programming about?
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