State Space Models with GARCH Errors

Authors and guest post by Eren Ocakverdi

This blog piece intends to introduce a new add-in (i.e. SSPACEGARCH) that extends the current capability of EViews’ available features for the estimation of univariate state space models.

NARDL in EViews 13: A Study of Bosnia's Tourism Sector

EViews 13 introduces several new features to extend the analysis of the well-known autoregressive distributed lag (ARDL) model (see our 3-part ARDL blog series: Part I, Part II, and Part III). In particular, estimation of ARDL models now accommodates asymmetric distributed lag (DL) regressors which extend traditional ARDL models to the increasingly popular nonlinear ARDL (NARDL) models. The latter allow for more complex dynamics which focus on modeling asymmetries both among the cointegrating (long-run) as well as the dynamic adjustment (short-run) relationships. To demonstrate these features, we will examine whether tourist arrivals and their length of stay (popular measures of tourism sector development) have asymmetric effects on the overall economic development (measured as gross domestic product (GDP)) in Bosnia and Herzegovina.

EViews 13 is Released!

We are pleased to announce that EViews 13 has been released! Packed with new features and enhancements, EViews 13 can be purchased as either an upgrade or a new purchase for single user licenses.  Volume license customers will be receiving their complimentary upgrades soon!

Simulation and Bootstrap Forecasting from Univariate GARCH Models

Authors and guest post by Eren Ocakverdi

This blog piece intends to introduce a new add-in (i.e. SIMULUGARCH) that extends the current capability of EViews’ available features for the forecasting of univariate GARCH models.

SpecEval Add-In - Part 2

Authors and guest post by Kamil Kovar

This is the second in a series of blog posts (the first can be found here) that present a new EViews add-in, SpecEval, aimed at facilitating development of time series models used for forecasting. This blog post will focus on the illustration of the basic outputs of the add-in by following a simple application, which will also illustrate the model development process that the add-in aims to facilitate. Next section provides brief discussion of this process, while the following section discusses the data and models considered. The main content of this blog post is contained in next two sections, which discuss basic execution before presenting the actual application.

Box-Cox Transformation and the Estimation of Lambda Parameter

Authors and guest post by Eren Ocakverdi

This blog piece intends to introduce a new add-in (i.e. BOXCOX) that can be used in applying power transformations to the series of interest and provides alternative methods to estimate the optimal lambda parameter to be used in transformation.

SpecEval Add-In

Authors and guest post by Kamil Kovar

This is the first in a series of blog posts that will present a new EViews add-in, SpecEval, aimed at facilitating time series model development. This blog post will focus on the motivation and overview of the add-in functionality. Remaining blog posts in this series will illustrate the use of the add-in.