Autoregressive approaches to import–export time series I: basic techniques

Autoregressive approaches to import–export time series I: basic techniques

This work is the first part of a project dealing with an in-depth study of effective techniques used in econometrics in order to make accurate forecasts in the concrete framework of one of the major economies of the most productive Italian area, namely the province of Verona. In particular, we devel...

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Main Author: Luca Di Persio
Format: Article
Language:English
Published: VTeX 2015-04-01
Series:Modern Stochastics: Theory and Applications
Subjects:
Econometrics time series
autoregressive models
Granger causality
cointegration
stochastic nonstationarity
AIC and BIC criteria
Online Access:https://vmsta.vtex.vmt/doi/10.15559/15-VMSTA22
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spelling doaj-566679b3481b42ddbdc637b07b0bc9572020-11-25T01:42:21ZengVTeXModern Stochastics: Theory and Applications2351-60462351-60542015-04-0121516510.15559/15-VMSTA22Autoregressive approaches to import–export time series I: basic techniquesLuca Di Persio0Dept. Informatics, University of Verona, strada le Grazie 15, 37134, ItalyThis work is the first part of a project dealing with an in-depth study of effective techniques used in econometrics in order to make accurate forecasts in the concrete framework of one of the major economies of the most productive Italian area, namely the province of Verona. In particular, we develop an approach mainly based on vector autoregressions, where lagged values of two or more variables are considered, Granger causality, and the stochastic trend approach useful to work with the cointegration phenomenon. Latter techniques constitute the core of the present paper, whereas in the second part of the project, we present how these approaches can be applied to economic data at our disposal in order to obtain concrete analysis of import–export behavior for the considered productive area of Verona.https://vmsta.vtex.vmt/doi/10.15559/15-VMSTA22Econometrics time seriesautoregressive modelsGranger causalitycointegrationstochastic nonstationarityAIC and BIC criteria
collection DOAJ
language English
format Article
sources DOAJ
author Luca Di Persio
spellingShingle Luca Di Persio
Autoregressive approaches to import–export time series I: basic techniques
Modern Stochastics: Theory and Applications
Econometrics time series
autoregressive models
Granger causality
cointegration
stochastic nonstationarity
AIC and BIC criteria
author_facet Luca Di Persio
author_sort Luca Di Persio
title Autoregressive approaches to import–export time series I: basic techniques
title_short Autoregressive approaches to import–export time series I: basic techniques
title_full Autoregressive approaches to import–export time series I: basic techniques
title_fullStr Autoregressive approaches to import–export time series I: basic techniques
title_full_unstemmed Autoregressive approaches to import–export time series I: basic techniques
title_sort autoregressive approaches to import–export time series i: basic techniques
publisher VTeX
series Modern Stochastics: Theory and Applications
issn 2351-6046
2351-6054
publishDate 2015-04-01
description This work is the first part of a project dealing with an in-depth study of effective techniques used in econometrics in order to make accurate forecasts in the concrete framework of one of the major economies of the most productive Italian area, namely the province of Verona. In particular, we develop an approach mainly based on vector autoregressions, where lagged values of two or more variables are considered, Granger causality, and the stochastic trend approach useful to work with the cointegration phenomenon. Latter techniques constitute the core of the present paper, whereas in the second part of the project, we present how these approaches can be applied to economic data at our disposal in order to obtain concrete analysis of import–export behavior for the considered productive area of Verona.
topic Econometrics time series
autoregressive models
Granger causality
cointegration
stochastic nonstationarity
AIC and BIC criteria
url https://vmsta.vtex.vmt/doi/10.15559/15-VMSTA22
work_keys_str_mv AT lucadipersio autoregressiveapproachestoimportexporttimeseriesibasictechniques
_version_ 1725037049584549888

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