Monday, August 12, 2024

Estimation of Local Linear Trend via Kalman Filter

Authors and guest post by Eren Ocakverdi

This blog piece intends to introduce a new add-in (i.e. LOCALLINEAR) that estimates local linear trends via Kalman filter.

Monday, August 5, 2024

Seasonal Adjustment in EViews 14 – Calendar Variables and Lunar New Year

In our previous blog post we examined how JDemetra+ can be used to perform seasonal adjustment in EViews, producing results identical to (or at least extremely similar to) those given by the ubiquitous X-13 package from the US Census.

The previous post didn’t discuss one of the more popular features of seasonal adjustment; calendar adjustments. In this post we’ll rectify that by demonstrating how to use calendar adjustments in JDemetra+, as well as how to create your own calendar effects, should you wish to build upon the built-in features. In particular we’ll demonstrate adding a Lunar (Chinese) New Year variable for JDemetra+.

Thursday, August 1, 2024

Seasonal Adjustment in EViews 14 – Comparing X-13 and JDemetra+

Seasonal Adjustment is a mainstay of modern macro-economic analysis. Many economic time series exhibit seasonal fluctuations that need to be removed from the underlying patterns of the data before econometric analysis can be performed. In this two-part series we'll use EViews 14 to compare JDemetra+ to X13 in Part 1 and look at how to use JDemetra+ with the Lunar New Year in Part 2.

Friday, February 9, 2024

Generalized Autoregressive Score (GAS) approach to univariate GARCH Models

Authors and guest post by Eren Ocakverdi

This blog piece intends to introduce a new add-in (i.e. GASMODELU) that estimates selected univariate GARCH models within the Generalized Autoregressive Score (GAS) framework.

Wednesday, November 29, 2023

From Bańbura et al. (2010) to Cascaldi-Garcia’s (2022) Pandemic Priors

Authors and guest post by Ole Rummel and Davaajargal Luvsannyam This is the second in a series of blog posts that will present EViews add-in, LBVAR, aimed at estimating and forecasting a large Bayesian VAR model due to Banbura, Giannone and Reichlin (2010). We will discuss and replicate Cascaldi-Garcia (2022) on this blog.

Wednesday, September 27, 2023

Principal Component Analysis for Nonstationary Series

Authors and guest post by Eren Ocakverdi

This blog piece intends to introduce a new add-in (i.e. HXPRINCOMP) that implements the procedure developed by Hamilton and Xi (2022).

Monday, September 11, 2023

Nowcasting US GDP During Covid-19 using Factor Augmented MIDAS

The COVID-19 pandemic sent waves through the global economy, triggering a macroeconomic shock and caused unprecedented challenges for economists trying to predict the current state of economies. In the quest for a more timely and accurate assessment of economic conditions during the COVID-19 era, economists and researchers turned to innovative solutions, and one of the most promising techniques emerged: MIDAS (Mixed-Data Sampling) estimation.