Stabilisation du secteur caféier en Haïti par la promotion de la concurrence et la mise en oeuvre d'un plan d'assurance pour la gestion des risques agricoles
Bibliographic record
Abstract
Three indicators are used to measure the competitiveness and the comparative advantages of the arabica coffee for Haiti. The results show the interest of the coffee crop for the economy of the country. However this sector appears also rather vulnerable to the shocks which can strike the world market since the fluctuations in international price are transmitted to the local market. The study starts by analysing the coffee sector from the point of view of investment and supply. To this end, an investment model in plantation and a supply model based on factors of adjustment prices, in which the factor of risk is integrated, are estimated. The results show that uncertainty relating to retuns from coffee production can be one of the important causes of under-investment in this sector. Haiti's coffee market is characterized by an oligopsony and the degree of market power of the exporters is measured by the Lerner index. It shows a relatively strong market power in the exporters' cartel established by the association ASDEC (Association des exportateurs de café). The tax policy on the coffee trade adopted by the government is analysed within the framework of non competitive market. We evaluate and analyse the effect of the market structure and the tax policy on efficiency of the market, on the one hand, and, on price, supply, exports and local consumption of the coffee, on the other hand. The simulation of various scenarios of the model pleads for a more competitive market and free export taxes. In order to bring a response to the problems of production risks, we explore the possibility of an insurance plan for the sector. We provide a critical analysis of the agricultural systems of insurance of the countries : United States, Canada, Spain, Japan, and India which have this tradition already. The analysis shows that the experiences of these countries, particularly in United States, are disastrous. The programs are strongly subsidized and the governments pay not only one part of the premium, but also the majority of the costs of operating and administration. On this basis, we propose an alternative plan for the coffee crop in Haiti, quite different from traditional agricultural insurance systems. It takes into account realities specific to Haiti, being developing country, in term of financial and natural resources available. The proposed insurance is analysed in a comparative study « with and without insurance » simulating the impacts on the level and variance of producers' income.The program would allow for a relative reduction of approximately 23% in the riskiness of income of producers. This evaluation is reinforced by a stochastic analysis of entry and exit options in the sector. This plan, would not only response the constraint of uncertainty, but would also, through transmission effects, have positive impacts on other problems identified in particular in the strengthening of the institutions and the investment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".