Essais sur l’économie de l’adaptation aux changements climatiques
Bibliographic record
Abstract
This research examines the effects of climate change adaptation measures on ecosystem services in the province of Quebec (Canada) and in the agricultural sector in Sub-Saharan Africa. It comprises three articles. The first article aims to evaluate the impact of adopting climate change adaptation strategies on the increase in agricultural yields, analyzing the effect of each strategy individually. To do this, it relies on data collected from 5,091 agricultural households in four African countries : Burkina Faso, Sao Tome and Principe, Sierra Leone, and Uganda. The study also includes the analysis of spatial climate data over a 30-year period, covering five climate variables. The results reveal that adaptation significantly increases agricultural yields, thanks notably to better access to credit and adequate information. I estimated a simultaneous equations model with endogenous switching to account for the heterogeneity in the decision to adapt or not, as well as for the unobservable characteristics of farmers and their farms. The results show that the adoption of adaptation measures increases agricultural yields by 281 kg, an increase of 23.3% compared to the average annual yield. The adoption of adaptation strategies, whether individual or combined, significantly increases agricultural yields. Thus, the combination of adjusting planting dates and choosing cultivated varieties is associated with the highest agricultural yields, namely 343.3 kg per hectare. The second article of this thesis uses the same data sets and methodology as the f irst to examine the effectiveness of climate change adaptation strategies in reducing farmers’ vulnerability to climatic hazards. The results indicate a significant reduction in this vulnerability due to the implementation of these measures. However, the impact of adaptation on reducing climate risks varies from country to country. The final article of this research examines the economic benefits of seven adaptation strategies aimed at improving both ecosystem services and open-water fishing in Lake Saint-Pierre, Quebec. For this, the analysis is based on data collected from recent visits of 212 fishermen across six different sites on the lake, as well as on responses obtained through discrete choice surveys. The results reveal that the implementation of these measures could result in annual gains estimated at about 9.62 million dollars for open-water f ishing. Moreover, this study provides important insights into the integration of data from revealed and stated preferences, highlighting a notable divergence between hypothetical choices and decisions made during actual fishing activities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".