The lecture is entitled Empirical Model Discovery. In it Professor Hendry re-interprets model evaluation as discovering what is wrong, robust statistics as discovering which sub-sample is reliable, and model selection as discovering which model best matches the criteria.
Automatic methods enable formulation, selection, estimation and evaluation on a scale well beyond the powers of human intellect, including when there are more candidate variables than observations. Hendry will explain how major recent developments facilitate the discovery of models, despite the high dimensionality, non-linearity, inertia,
endogeneity, evolution, and abrupt change characteristic of economic data that interact to make modelling so difficult in practice. Live computer illustrations using Autometrics show the remarkable power and feasibility of the approach.
For more information on the lecture contact W/Prof. Darrell Turkington on 6488 2880 or
[email protected]
