Advanced Time Series Econometrics
This course will show how time series can be modelled and analysed. The aim is to provide understanding and insight into the methods used, as well as explaining the technical details. Statistical time series modelling will be demonstrated using the STAMP computer package and participants will be given the opportunity to use STAMP in class. The Time Series Lab (TSL) program enables the score-driven approach to nonlinear time series to be implemented. There will be a wide range of applications, ranging from assessing the impact of the UK seat belt law, modelling volatility in financial time series and predicting the spread of coronavirus.
Prerequisites
Please note to take this course you must first have completed Time Series Econometrics and Forecasting.
Delivery
Two-hour lectures per day over five days, plus a one-hour tutorial each day, with optional clinics on the final day. Sessions are live online and recorded.
Study Hours
Approximately 100 hours of study, of which 15 are contact hours and 85 are private study.
Software Used
OxMetrics 9
Credits
10 CATS credits
Programme Faculty
Key Outcomes
- —State space models and the Kalman filter
- —The modelling of univariate and multivariate time series
- —Practical time series modelling using the STAMP package
- —Nonlinear time series models, including volatility modelling and the score-driven approach
- —Practical time series modelling using the TSL package
Desired Skills
- —Understand the nature of time series models and the way they are applied in practice
- —Present, interpret and analyse information and results from STAMP and TSL
Lecture Programme
- WK 01
Lecture 1: Stationary time series
- ·Review of the basic concepts of stationary time series
- ·Unobserved components and signal extraction
- ·State space models and the Kalman filter
- WK 02
Lecture 2: Trends, seasonals and cycles
- ·ARIMA models
- ·Structural time series models
- ·Explanatory variables and intervention analysis
- ·STAMP package
- WK 03
Lecture 3: Multivariate time series models
- ·Common trends and co-integration
- ·Intervention analysis and control groups
- WK 04
Lecture 4: Nonlinear models
- ·Dynamic conditional score models
- ·The TSL program
- WK 05
Lecture 5: Modelling volatility
- ·Conditional heteroscedasticity
- ·Time-varying correlation and association
Assessment
Online coursework submission with the support of your module lecturer and tutor. All sessions are conducted live online at a scheduled time and recorded for review.