There are numerous possible approaches to building a model of a given data set. In economics, imposing a `theory model’ on the data by simply estimating its parameters is common. This column makes the case for a combined theory-driven and data-driven approach under which it is almost costless in statistical terms to check the relevance of large numbers of other candidate variables when the theory is complete, yet there is a good chance of discovering a better empirical model when the theory is incomplete or incorrect.
Read the full article by INET Oxfords Prof Sir David Hendry & Dr Jennifer Castle here.