Using Indicator Saturation to Detect Outliers and Structural Shifts

One of the potential pitfalls when working with time series datasets is that the data may have temporary or permanent changes to its levels. These changes could be single time-period outliers, or a fundamental structural shift.

EViews 12 introduces a new technique to detect and model these outliers and structural changes through indicator saturation. in the recently released EViews 12, we thought we'd give another demonstration.

Nowcasting GDP with PMI using MIDAS-GETS

Nowcasting, the act of predicting the current or near-future state of a macro-economic variable, has become one of the more popular research topics performed in EViews over the past decade.

Perhaps the most important technique in nowcasting is mixed data sampling, or MIDAS. We have discussed MIDAS estimation in EViews in a couple of prior guest blog posts, but with the introduction of a new MIDAS technique in the recently released EViews 12, we thought we'd give another demonstration.

Wavelet Analysis: Part II (Applications in EViews)

This is the second of two entries devoted to wavelets. Part I was devoted to theoretical underpinnings. Here, we demonstrate the use and application of these principles to empirical exercises using the wavelet engine released with EViews 12.