Big Data Econometrics Course - ERMAS 2014

  • Description
    • With data sets becoming larger, there is an increasing need to master new statistical and econometric methods that predict variables while achieving dimension reduction and/or trading model complexity with model fit. The goal of this course is to give an applied, hands-on introduction to these methods, using as illustration the large microeconomic dataset PSID (panel study of income dynamics)
    • Link to free book
      • Trevor Hastie, Robert Tibshirani and Jerome Friedman (2009). The Elements of Statistical Learning: Data Mining, Inference and Prediction. Springer: New York.
      • READING: Chapters 3-7.
    • Link to free R software
  • Link to PSID Data
  • COURSE FILES - bottom of this page:
    • Slides.pdf : course slides - print or bring electronic copy
    • Data.pdf: extract of the PSID data
    • Small PSID: description of the variables extracted from PSID - print or bring electronic copy
    • SmallPSID.R: R code for all slides
  • Bringing a laptop is recommended
    • SCHEDULE