The course aims to develop students' econometric skills and provide practical guidance on how to forecast. Economics needs to forecast a non-stationary and evolving world, using a forecasting model that differs from the economic mechanism. The resulting framework, its basic concepts and main implications are sketched. Many famous theorems of economic forecasting no longer hold—rather their converses often do.
We will examine how standard macroeconometric models fail in many forecasting scenarios, which provides guidance in how to correct for such forecast failure. We shall also look at how the forecast theory developed can be applied to other disciplines. The course will be practical. All empirical examples will be worked through using the econometric software package OxMetrics.
This module can be taken alone or as part of a PG Certificate, PG Diploma or Full Masters Program.
Use the model selection software, Autometrics, to select macroeconometric models used for forecasting.
Compute point and interval forecasts using standard and robust forecasting devices.
Evaluate forecasts of macroeconomic variables.
Develop an understanding of when forecasts may or may not perform well.
By the end of this course, participants should have knowledge and ability to:
Engage in abstract thinking by extracting the essential features of complex systems to facilitate problem solving and decision-making.
Communicate and present complex arguments in oral and written form with clarity and succinctness.
Use statistical and other packages effectively, presenting, interpreting and analysing information in numerical form.
Apply basic statistical techniques to analyse economic and financial datasets.
By the end of this course, students should be able to:
Advanced Forecasting for Time Series is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.
The total number of contact hours is 15 hours. This leaves 85 hours for private study.
There will be an assessment at the end of the course
This module consists of 2- hour lectures per day, for 5 consecutive days, plus a 1 - hour tutorial per day.
There will be optional clinics on the last day of the course.