Wednesday, January 20, 2021
Automatic Factor Selection: Working with FRED-MD Data
This is the first of two posts devoted to automatic factor selection and panel unit root tests with cross-sectional dependence. Both features were recently released with EViews 12. Here, we summarize and work with two seminal contributions to automatic factor selection by Bai and Ng (2002) and Ahn and Horenstein (2013).
Monday, December 21, 2020
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.
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.
Tuesday, December 8, 2020
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.
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.
Wednesday, December 2, 2020
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.
Monday, November 30, 2020
Wavelet Analysis: Part I (Theoretical Background)
This is the first of two entries devoted to wavelets. Here, we summarize the most important theoretical principles underlying wavelet analysis. This entry should serve as a detailed background reference when using the new wavelet features released in EViews 12. In Part II we will apply these principles and demonstrate how they are used with the new EViews 12 wavelet
engine.
Thursday, July 16, 2020
Time Series Methods for Modelling the Spread of Epidemics
Authors and guest post by Eren Ocakverdi
This blog piece intends to introduce two new add-ins (i.e. SEIRMODEL and TSEPIGROWTH) to EViews users’ toolbox and help close the gap between epidemiological models and time series methods from a practitioner’s point of view.
This blog piece intends to introduce two new add-ins (i.e. SEIRMODEL and TSEPIGROWTH) to EViews users’ toolbox and help close the gap between epidemiological models and time series methods from a practitioner’s point of view.
Wednesday, April 1, 2020
Mapping COVID-19: Follow-up
As a follow up to our previous blog entry describing how to import Covid-19 data into EViews and produce some maps/graphs of the data, this post will produce a couple more graphs similar to ones we've seen become popular across social media in recent days.
Subscribe to:
Posts (Atom)