The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration Approach

This paper examines the dynamic effect of the economic determinants on bilateral trade intensity of the European Union (EU) region’s bioenergy industry outputs. The authors adopt the panel co-integration model approach to estimate annual trade intensity data of the EU-28 countries’ bioenergy industr...

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Main Authors: Mohd Alsaleh, Abdul Samad Abdul-Rahim
Format: Article
Language:English
Published: MDPI AG 2018-02-01
Series:Sustainability
Subjects:
Online Access:http://www.mdpi.com/2071-1050/10/2/565
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spelling doaj-02446123b2ae4ba9831dfec634c32eec2020-11-24T23:17:52ZengMDPI AGSustainability2071-10502018-02-0110256510.3390/su10020565su10020565The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration ApproachMohd Alsaleh0Abdul Samad Abdul-Rahim1Faculty of Economics and Management, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor DE, MalaysiaFaculty of Economics and Management, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor DE, MalaysiaThis paper examines the dynamic effect of the economic determinants on bilateral trade intensity of the European Union (EU) region’s bioenergy industry outputs. The authors adopt the panel co-integration model approach to estimate annual trade intensity data of the EU-28 countries’ bioenergy industry outputs from 1990 to 2013. This study investigated the long-term influence of the rate of real exchange, gross domestic product (GDP), and export price on the trade intensity of bioenergy industry applying fully modified oriented least square (FMOLS), dummy oriented least square (DOLS), and pooled mean group (PMG) models. In the current study, the findings boost the empirical validity of the panel co-integration model through FMOLS, indicating that depreciation has improved the trade intensity. This study has further investigated, through the causality test, a distinct set of countries. FMOLS estimation does find proof of the long run improvement of trade intensity. Thus, the result shows that the gross domestic product (GDP) and the real exchange rate have a positive and noteworthy influence on the EU-28 region trade intensity of the bioenergy industry. Moreover, the export price affects negatively and significantly the trade intensity of the bioenergy industry in the EU-28 countries.http://www.mdpi.com/2071-1050/10/2/565bioenergy industrytrade intensityEuropean
collection DOAJ
language English
format Article
sources DOAJ
author Mohd Alsaleh
Abdul Samad Abdul-Rahim
spellingShingle Mohd Alsaleh
Abdul Samad Abdul-Rahim
The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration Approach
Sustainability
bioenergy industry
trade intensity
European
author_facet Mohd Alsaleh
Abdul Samad Abdul-Rahim
author_sort Mohd Alsaleh
title The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration Approach
title_short The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration Approach
title_full The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration Approach
title_fullStr The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration Approach
title_full_unstemmed The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration Approach
title_sort economic determinants of bioenergy trade intensity in the eu-28: a co-integration approach
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2018-02-01
description This paper examines the dynamic effect of the economic determinants on bilateral trade intensity of the European Union (EU) region’s bioenergy industry outputs. The authors adopt the panel co-integration model approach to estimate annual trade intensity data of the EU-28 countries’ bioenergy industry outputs from 1990 to 2013. This study investigated the long-term influence of the rate of real exchange, gross domestic product (GDP), and export price on the trade intensity of bioenergy industry applying fully modified oriented least square (FMOLS), dummy oriented least square (DOLS), and pooled mean group (PMG) models. In the current study, the findings boost the empirical validity of the panel co-integration model through FMOLS, indicating that depreciation has improved the trade intensity. This study has further investigated, through the causality test, a distinct set of countries. FMOLS estimation does find proof of the long run improvement of trade intensity. Thus, the result shows that the gross domestic product (GDP) and the real exchange rate have a positive and noteworthy influence on the EU-28 region trade intensity of the bioenergy industry. Moreover, the export price affects negatively and significantly the trade intensity of the bioenergy industry in the EU-28 countries.
topic bioenergy industry
trade intensity
European
url http://www.mdpi.com/2071-1050/10/2/565
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