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28.09.2023

Do the export reactions to exchange rate and exchange rate volatility differ depending on technology intensity? New evidences from the panel SVAR analysis

verfasst von: Caglayan Aslan, Ferdi Akpiliç

Erschienen in: Empirical Economics | Ausgabe 4/2024

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Abstract

This paper investigates the impact of exchange rate and exchange rate volatility on export performance by considering technological classification in addition to total exports. The study utilizes a panel SVAR methodology introduced by Pedroni P (2013) Structural panel vars. Econometrics 1(2):180–206. and analyzes panel data covering 58 countries and 48 quarters from the period of 2010Q1 to 2021Q4. Although the results suggest no precise evidence that exchange rate and exchange rate volatility shocks affect total export volumes, they exhibit heterogeneity across countries and vary in terms of technological density. Countries that have more flexible exchange rate policies and use large volumes of imported materials to produce export products demonstrate, on average, higher sensitivity to exchange rate volatility. Additionally, as the share of exports crossing more than one country border in total exports increases, the exposure of export to exchange rate volatility also rises. Countries described as commodity exporters and large energy consumers tend to be less responsive to exchange rate levels in their exports.

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Fußnoten
1
In the example of Argentina, only three of the exporting countries are mentioned to explain the process more simply. In calculating foreign income for each country, all countries with available GDP data are included in the calculation.
 
2
This claim is empirically supported by Pedroni (2013) by using Monte Carlo Simulations.
 
3
Since this approach also offers flexibility to work with unbalanced panel data, we describe the time series dimension part with sub-indicator i.
 
4
Although relationships are the same for composite and common shocks, prefer using composite one for demonstrations.
 
5
For the sake of robustness, we re-estimated the model by changing the order of variables such as E_I- EXP-ER_VOL- ER and we obtained broadly similar results. Since we work with a sectoral basis and have already presented many results, we prefer not to report these results to avoid complexity. These results are available from the authors upon request.
 
6
To generate these series, we developed correspondence tables that establish a link between Isıc REV 4 classification and ISUT classification. Detailed information about calculation processes is available upon request from the authors.
 
7
Technology classification of exports is typically applied to manufacturing sectors. Therefore, the sum of high-technology, high–medium-technology, low–medium-technology, and low-technology exports does not equal total exports. For this reason, the results of model estimates are also given for non-manufacturing exports.
 
8
Panel members-based variance decompositions related to technology intensity export streams (high technology, high–medium technology, low–medium technology, low technology, and non-manufacturing) are also available but are not included in the presented results to avoid unnecessary complexity. However, interested individuals can request these specific results from the authors.
 
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Metadaten
Titel
Do the export reactions to exchange rate and exchange rate volatility differ depending on technology intensity? New evidences from the panel SVAR analysis
verfasst von
Caglayan Aslan
Ferdi Akpiliç
Publikationsdatum
28.09.2023
Verlag
Springer Berlin Heidelberg
Erschienen in
Empirical Economics / Ausgabe 4/2024
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-023-02497-5

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