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

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  • Luca Di Persio

Abstract

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.

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  • Luca Di Persio, 2015. "Autoregressive approaches to import-export time series I: basic techniques," Papers 1506.02940, arXiv.org.
    • Handle: RePEc:arx:papers:1506.02940
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    References listed on IDEAS

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    1. Gebhard Kirchgässner & Jürgen Wolters & Uwe Hassler, 2013. "Introduction to Modern Time Series Analysis," Springer Texts in Business and Economics, Springer, edition 2, number 978-3-642-33436-8, October.
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    Cited by:

    1. Luca Di Persio & Chiara Segala, 2015. "Autoregressive approaches to import--export time series II: a concrete case study," Papers 1506.01984, arXiv.org.

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