Teaching and Software

I regularly teach courses in Probability, Statistics and Econometrics, both at Undergraduate and  Graduate level, and supervise independent research projects for Undergraduate students majoring in Economics and Applied Mathematics and Statistics. 

In this page you can find the syllabi for the courses I teach and some useful resources for Statistics and Econometrics, including software.  

Undergraduate Econometrics and Statistics

• ECO 320 - Mathematical Statistics, Stony Brook University. 

• ECO 321 - Econometrics, Stony Brook University. 

• Resources

  • David M Diez, Christopher D Barr, and Mine Cetinkaya-Rundel, OpenIntro Statistics.

  • Francis X. Diebold, Econometric Data Science: A Predictive Modeling Approach. 

  • James H. Stock and Mark W. Watson, Companion website to Introduction to Econometrics, Pearson. 

  • Christoph Hanck, Martin Arnold, Alexander Gerber and Martin Schmelzer,  Introduction to Econometrics with R. 

Graduate Econometrics and Statistics

• ECO 520 - Mathematical Statistics, Stony Brook University. 

• ECO 521 - Econometrics, Stony Brook University. 

• Resources

  • Bruce Hansen, Econometrics.

• Samples of PhD Comprehensive Exam at Stony Brook University: Sample 1; Sample 2.

Software

• The R-project for Statistical Computing. 

• Using R for Introductory Econometrics

• Econometrics with R

• LaTeX Introductory Guides: Unix Users; Windows Users. 

• Racine, J. and Hyndman, R. (2002), Using R to teach econometrics. Journal of Applied Econometrics, 17: 175-189. 

• Meredith, E. and Racine, J. S. (2009), Towards reproducible econometric research: the Sweave framework. Journal of Applied Econometrics 24: 366-374.