Dr. Feng Li

  • Seminars
    • Guanghua Statistics Seminars (2025 fall)
  • Research
    • Publications
    • Talks and Interviews(学术报告和访谈)
    • Academic Services
    • NSFC Project: Efficient Bayesian Flexible Density Methods with High Dimensional Financial Data
  • Teaching
    • Big Data Computation and Forecasting (大数据计算与预测)
    • Forecasting with AI (人工智能驱动的预测方法)
    • Old Courses
  • Code
  • People
    • Students
    • Life Partner
  • Contact
  • KLLAB.org
  • 李丰

Econometrics (2014 Fall)

Contents

  • 1 News and announcements
  • 2 Course introduction
  • 3 Lecture notes
  • 4 R notes
  • 5 Additional materials
  • 6 Solutions to assignments

News and announcements

  • 2014-Sep-12. Computer labs will take place on 6#206 Shahe Campus on odd weeks (3rd-4th lecturer hours) starting from week 3.

Course introduction

  • EC-Courseplan

Lecture notes

  • EC-L1-Introduction-To-Econometrics
  • EC-L2-Two-Variable-Regression
  • EC-L3-CNLRM-Distribution-Interval-Testing
  • EC-L4-Two-Variable-Regression-Model-Extensions
  • EC-L5-Multiple-Regression
  • EC-L6-Dummy-Variable
  • EC-L7-Multicollinearity
  • EC-L8-Heteroscedasticity
  • EC-L9-Autocorrelation
  • EC-L10-ModelSpecification
  • EC-L11-QualitativeResponseRegression
  • EC-L12-PanelDataRegressionModels
  • EC-L13-TimeSeriesEssentials
  • EC-L14-AR-MA-Processes
  • EC-L15-TimeSeriesModeling

R notes

  • EC-C1-R-Intro
  • EC-C2-MatrixLinearRegression
  • EC-C3-R-RegressionWithDummies
  • EC-C4-Multicollinearity
  • EC-C5-Heteroscedasticity
  • EC-C6-Autocorrelation
  • EC-C7-QualitativeRegression
  • EC-C8-PanelDataRegression
  • EC-C9-AR-MA-Processes

Additional materials

  • ARIMA Models
  • Matrix-Derivatives

Solutions to assignments

  • EC-S1
  • EC-S2
  • EC-S3
  • EC-S4
  • EC-S5
  • EC-S6
  • EC-S7
  • EC-S8

 

Dr. Feng Li

{ computing, forecasting and learning with massive machines }