ECO 4354 / 6354 Forecasting

Fall 2026

Instructor: Zhan Gao
Course information: See Syllabus.

Lecture Notes

0. Course Overview
1. R Programming (Basic)
2. R Programming (Advanced)
3. Review: The Linear Regression Model
4. The Basics of Forecasting
   • 2024-07-fredmd.csv
5. Time Series Graphics
   • fcst4_interest.dat
   • liquor_sales.csv
   • fcst4_gdp.dat
6. Trend and Seasonality
   • retail_sales.csv
   • housing_starts.csv
   • liquor_sales.csv
   • GDPC1.csv
7. Cycles I: Stationarity and Autoregression
   • caemp.csv
8. Cycles II: ARMA Models and Forecasting
9. Assembling the Components, and Volatility Models
   • liquor_sales.csv
   • nyse_returns.csv
10. Unit Roots and Stochastic Trends
    • GDPC1.csv
    • exchange_rates.csv
    • 2024-07-fredmd.csv
11. Vector Autoregressions
    • housing_starts_completions.csv
    • 2024-07-fredmd.csv
12. Forecast Evaluation and Predictability
    • shipping_volume.csv
    • hw2_gdp_spread.csv
    • spf_median_rgdp_growth.csv
    • nyse_returns.csv
13. Forecast Combination
    • shipping_volume.csv
    • hw2_gdp_spread.csv
    • spf_median_rgdp_growth.csv
    • spf_individual_rgdp_growth.csv

Homeowrk Assignments

Test 1

• Test 1

Practice questions

• Practice Questions: Test 1