The geographical situation in Europe of Estonia, Latvia and Lithuania, the Three Baltic States, forms an optimal environment for the study of the economic relationships present among them. The global magnitudes are very similar for the three States, with a little difference in favor of Lithuania regarding population and extension. The three States joined the European Union at the same time, May 1, 2004. A vector autoregressive model, a VAR model, relating the three economies in their temporal evolution is an appropriate model for this study. With the intervention of temporal lags, it is possible to formulate the dynamical relationship present in these economies regarding the percentage growth change in the respective gdp per capita. Our attention is directed to the evolution of this percentage growth rate for the period 1990-2020. The estimated VAR(2) model shows that the percentage change in the gdp per capita of Lithuania is dynamically related to the lagged growth changes of Estonia and Latvia in a direct way, with more complex dynamic relationships regarding the other two States, as explained in the Conclusion. This study is supplemented with the Impulse Response Analysis and the Forecast Error Variance Decomposition to measure the effects of random impulses in the evolution of the percentage growth change in the estimated model.
Published in | International Journal of Science, Technology and Society (Volume 11, Issue 2) |
DOI | 10.11648/j.ijsts.20231102.15 |
Page(s) | 74-80 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Baltic States, GDP Per Capita, Percentage Change, VAR Models, Impulse Response Analysis, Forecast Error Variance Decomposition, Vars Statistical Package
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APA Style
Agustín Alonso-Rodríguez. (2023). The Dynamic Relationship of the GDP Per capita Among the Three Baltic States (1990-2021). International Journal of Science, Technology and Society, 11(2), 74-80. https://doi.org/10.11648/j.ijsts.20231102.15
ACS Style
Agustín Alonso-Rodríguez. The Dynamic Relationship of the GDP Per capita Among the Three Baltic States (1990-2021). Int. J. Sci. Technol. Soc. 2023, 11(2), 74-80. doi: 10.11648/j.ijsts.20231102.15
AMA Style
Agustín Alonso-Rodríguez. The Dynamic Relationship of the GDP Per capita Among the Three Baltic States (1990-2021). Int J Sci Technol Soc. 2023;11(2):74-80. doi: 10.11648/j.ijsts.20231102.15
@article{10.11648/j.ijsts.20231102.15, author = {Agustín Alonso-Rodríguez}, title = {The Dynamic Relationship of the GDP Per capita Among the Three Baltic States (1990-2021)}, journal = {International Journal of Science, Technology and Society}, volume = {11}, number = {2}, pages = {74-80}, doi = {10.11648/j.ijsts.20231102.15}, url = {https://doi.org/10.11648/j.ijsts.20231102.15}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsts.20231102.15}, abstract = {The geographical situation in Europe of Estonia, Latvia and Lithuania, the Three Baltic States, forms an optimal environment for the study of the economic relationships present among them. The global magnitudes are very similar for the three States, with a little difference in favor of Lithuania regarding population and extension. The three States joined the European Union at the same time, May 1, 2004. A vector autoregressive model, a VAR model, relating the three economies in their temporal evolution is an appropriate model for this study. With the intervention of temporal lags, it is possible to formulate the dynamical relationship present in these economies regarding the percentage growth change in the respective gdp per capita. Our attention is directed to the evolution of this percentage growth rate for the period 1990-2020. The estimated VAR(2) model shows that the percentage change in the gdp per capita of Lithuania is dynamically related to the lagged growth changes of Estonia and Latvia in a direct way, with more complex dynamic relationships regarding the other two States, as explained in the Conclusion. This study is supplemented with the Impulse Response Analysis and the Forecast Error Variance Decomposition to measure the effects of random impulses in the evolution of the percentage growth change in the estimated model.}, year = {2023} }
TY - JOUR T1 - The Dynamic Relationship of the GDP Per capita Among the Three Baltic States (1990-2021) AU - Agustín Alonso-Rodríguez Y1 - 2023/03/21 PY - 2023 N1 - https://doi.org/10.11648/j.ijsts.20231102.15 DO - 10.11648/j.ijsts.20231102.15 T2 - International Journal of Science, Technology and Society JF - International Journal of Science, Technology and Society JO - International Journal of Science, Technology and Society SP - 74 EP - 80 PB - Science Publishing Group SN - 2330-7420 UR - https://doi.org/10.11648/j.ijsts.20231102.15 AB - The geographical situation in Europe of Estonia, Latvia and Lithuania, the Three Baltic States, forms an optimal environment for the study of the economic relationships present among them. The global magnitudes are very similar for the three States, with a little difference in favor of Lithuania regarding population and extension. The three States joined the European Union at the same time, May 1, 2004. A vector autoregressive model, a VAR model, relating the three economies in their temporal evolution is an appropriate model for this study. With the intervention of temporal lags, it is possible to formulate the dynamical relationship present in these economies regarding the percentage growth change in the respective gdp per capita. Our attention is directed to the evolution of this percentage growth rate for the period 1990-2020. The estimated VAR(2) model shows that the percentage change in the gdp per capita of Lithuania is dynamically related to the lagged growth changes of Estonia and Latvia in a direct way, with more complex dynamic relationships regarding the other two States, as explained in the Conclusion. This study is supplemented with the Impulse Response Analysis and the Forecast Error Variance Decomposition to measure the effects of random impulses in the evolution of the percentage growth change in the estimated model. VL - 11 IS - 2 ER -