Course:FRE530
| FRE530:Econometrics with Time Series Data | |
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| FRE 530 | |
| Section: | |
| Instructor: | Kurt Niquidet, PhD |
| Email: | kurt.niquidet@ubc.ca |
| Office: | TBA |
| Office Hours: | By Appointment |
| Class Schedule: | Feb 23-Apr 10
Lecture Mon & Wed 5:30-7:00pm Lab Tues 10:00- 11:30 |
| Classroom: | MCML 154 |
| Important Course Pages | |
| Syllabus | |
| Lecture Notes | |
| Assignments | |
| Course Discussion | |
COURSE DESCRIPTION
This course aims to equip students with the practical skills to confidently apply time series methods in real-world modelling environments. Time series is a critical tool in the food, climate, and resource sectors, where forecasting, trend analysis, and responding to shocks can guide policy and business decisions. Students will gain the applied skills needed for roles in forecasting, market analysis, and macroeconomic research.
Specific topics include the basic techniques of time series econometrics including both univariate and vector processes; stationary and non-stationary forecasting models, asymptotic theory for time series, linear regression with time series data, Box-Jenkin’s modelling strategy (ARIMA), Vector Autoregression (VAR), and error correction models.
LEARNING OUTCOMES
After this course, students will be able to
- Estimate and interpret univariate and multivariate time series econometric models (basic and more advanced models).
- Apply estimated time series models to areas of policy analysis and forecasting.
- Understand the role of predictive analytics in the context of several applications to business, finance and resource economics.
- Be proficient using R Studio to exploratory time series analysis; apply advanced time series econometric methods and estimation methods to empirical data.
- Be capable of critically evaluating published econometric research that use advanced time-series econometrics methods.
REAL-WORLD APPLICATIONS IN CLIMATE, FOOD & ENVIRONMENT
- How can we determine whether movements in food, resource, or energy prices are driven by long-term trends, seasonal patterns, or short-run shocks?
- What role does time series modelling play in designing effective business strategies and policy responses in the food–climate–resource sectors?
- What is the best way to assess the forecast accuracy of your time series model?
ASSESSMENT
| Lab Quizzes | Quiz at end of lab 1-5, points for best 3 | 10 |
| Assignment 1 | Due beginning of week 3 | 10 |
| Assignment 2 | Due beginning of week 5 | 10 |
| GVAR Project & Presentation | Project Deliverables week 4 and 6. Presentation week 7. | 35 |
| Participation | Lab and Lecture attendance/engagement | 5 |
| Final Exam | TBD | 30 |
| TOTAL | 100 | |