Abstract
In this paper, a novel distance measure for evaluating the closeness of two vector autoregressive moving average models is presented and its main properties are discussed. The proposed distance is used to investigate the presence of spatial differences in the dynamic link between unemployment rate variation and GDP growth in some European Union countries.
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Notes
- 1.
Full results concerning the estimation of the VAR models are available from the authors on request.
- 2.
See [3]. From a nontechnical point of view, the purpose of MDS is to provide a visual representation of the pattern of given distances among a set of objects. Given a matrix of distances between various objects, MDS plots the objects on a map such that those objects that are very similar to each other are placed near each other on the map, and those objects that are very different from each other are placed far away from each other on the map. Present elaboration is conducted by the MDS package in Gretl.
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Di Iorio, F., Triacca, U. (2018). Distance Between VARMA Models and Its Application to Spatial Differences Analysis in the Relationship GDP—Unemployment Growth Rate in Europe. In: Rojas, I., Pomares, H., Valenzuela, O. (eds) Time Series Analysis and Forecasting. ITISE 2017. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-96944-2_14
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DOI: https://doi.org/10.1007/978-3-319-96944-2_14
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