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Autoregressive approaches to import--export time series II: a concrete case study

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  • Luca Di Persio
  • Chiara Segala

Abstract

The present work constitutes the second part of a two-paper project that, in particular, deals 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. It is worth mentioning that this region is indubitably recognized as the core of the commercial engine of the whole Italian country. This is why our analysis has a concrete impact; it is based on real data, and this is also the reason why particular attention has been taken in treating the relevant economical data and in choosing the right methods to manage them to obtain good forecasts. In particular, we develop an approach mainly based on vector autoregression where lagged values of two or more variables are considered, Granger causality, and the stochastic trend approach useful to work with the cointegration phenomenon.

Suggested Citation

  • Luca Di Persio & Chiara Segala, 2015. "Autoregressive approaches to import--export time series II: a concrete case study," Papers 1506.01984, arXiv.org.
    • Handle: RePEc:arx:papers:1506.01984
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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, August.
    2. Luca Di Persio, 2015. "Autoregressive approaches to import-export time series I: basic techniques," Papers 1506.02940, arXiv.org.
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