<b>Economic Studies of the Global Trade of Wood Pellets</b>
Notice bibliographique
Résumé
This thesis investigated the international trade dynamics of wood pellets within the context of renewable energy transitions amid climate change concerns. In the first chapter, by employing gravity models with different estimators and specifications, we analyzed the determinants of trade flows of wood pellets. Additionally, we forecasted the future trade values of wood pellets under five shared socioeconomic pathways (SSP) scenarios. Our results showed the effects of some factors such as GDP of exporters, contiguity, and the distance between the two trading countries, were consistent with the economic theory. On the other hand, some other factors exhibited unexpected effects or conflicting results across the models. Regarding projections under five SSP scenarios, our results indicated substantial growth in trade flows, although potential overestimations are acknowledged due to the imposed assumptions. SSP3, which reflects a nationalistic scenario, is projected to have the smallest trade flows, while SSP5 anticipates the highest trade flows due to diminishing inequality and high GDP growth. Also, regional shifts in trade patterns were forecasted, with East Asia and Southeast Asia gaining prominence in imports and exports, respectively. Conversely, Europe’s imports and exports as well as North America’s exports are expected to decrease their shares in the global trade. Overall, our findings emphasize the complexity of trade determinants and underscore the need for nuanced forecasting methodologies to anticipate future trade dynamics accurately amidst evolving global scenarios of wood pellet trade.The second chapter evaluated the effects of the Paris Agreement on the international trade of wood pellets. The growing concern about climate change has encouraged the global communities to take actions toward climate-change mitigation. As a form of such efforts, the Paris Agreement was signed in 2015 by 196 parties around the world and went into force in 2016. As a means to mitigate climate change, wood pellets have been used as fuels alternative to fossil fuels. Traditionally, Europe was the primary importer of wood pellets, mostly sourced from the United States and Canada. In the last decade, there has also been a significant uptake in East Asia, indicating shifting trade patterns and market dynamics in the wood pellet industry. This study employed an event-study framework to analyze the impact of the Paris Agreement on the global trade of wood pellets from 2014 to 2019, using import and export data at the regional level. Our results revealed distinct patterns in responses to the Paris Agreement in terms of adjustment speed and magnitude. Europe exhibited a rapid increase in both imports and exports immediately after the Paris Agreement. East Asia demonstrated a delayed yet substantial rise in imports, particularly after 2018. North America also swiftly expanded exports, following the agreement, while Southeast Asia emerged as an important exporter, particularly in supporting the East Asian market from 2017 onwards. We also found an increase in exports of non-pellet wood fuels from Africa. This finding indicates that international climate agreements not only contribute to the overall expansion of the global market of wood pellets but also reshape the market by involving more countries in international efforts to mitigate climate change.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».