Dynamic Factor Models in EViews

One of the current buzz topics in macro-econometrics is that of dynamic factor models. 

Factor models allow researchers to work with a large number of variables by reducing them down to a handful (often two) components, allowing tractable results to be obtained from unwieldy data. 

A natural extension to factor models is to allow dynamics to enter the relationships.  These dynamic factor models have become extremely popular due to their ability to model business cycles, and perform both forecasting and nowcasting (predicting the current state of the economy).

Although EViews has built-in factor analysis, we do not (yet!) have dynamic factor models included. 

Luckily two researchers from the Ministry of Finance in Sweden have recently posted a paper, and corresponding code, that estimates dynamic factor models in EViews with a simple programming subroutine utilising EViews' state-space estimation object.

This paper looks fantastic - good job guys!

AutoRegressive Distributed Lag (ARDL) Estimation. Part 1 - Theory

One of our favorite bloggers, Dave Giles often writes about current trends in econometric theory and practice. One of his most popular topics is ARDL modeling, and he has a number of fantastic posts about it.

Since we have recently updated ARDL estimation in EViews 9.5, and are in the midst of adding some enhanced features to ARDL for the next version of EViews, EViews 10, we thought we would jot down our own thoughts on the theory and practice of ARDL models, particularly in regard to their use as a cointegration test.

This blog post will be in three parts. The first will discuss the theory behind ARDL models, the second will present the theory behind correct inference of the Bounds test, while the third will bring everything together with an example in EViews.