<b>Economic Studies of the Global Trade of Wood Pellets</b>
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".