Towards a More Inclusive Zanzibar Economy
Notice bibliographique
Résumé
This report assesses recent progress in poverty reduction in Zanzibar.It is based on Zanzibar's last three household budget surveys and considers the period between 2009 and 2019, with a focus on the last four years of this decade: 2015-2019.Poverty -based on household consumption -fell by 9 percentage points over the decade before the COVID-19 pandemic: it dropped from 34.9 to 25.7 percent.However, the pace of poverty reduction was slow relative to population growth and as such, the number of poor dropped by only 27,000.The drop was fastest in urban areas and because poverty levels were already lower than in rural areas, the gap between rural and urban poverty widened, driven by differences between the islands of Unguja and Pemba.Simulations suggest that the COVID-19 pandemic increased urban poverty increased by 1.8 percentage points in 2020-21 while rural poverty dropped by 0.8 percentage points.Substantial progress was also made across a range of non-monetary poverty indicators, notably in improved access to basic services including electricity and education.During the period 2009-2019, access to the electricity network increased from 38 to 57 percent, while education indicators also improved considerably.For example, between 2015 and 2019, lower secondary gross enrolment went up from 68 to 90 percent.Despite progress, gaps remain especially among the poor living in rural areas, notably in Pemba.Results from a multi-dimensional poverty index (MPI) calculated based on 3 dimensions and 13 indicators using the HBS 2019-20 indicate that 36.6 percent of Zanzibaris were multi-dimensionally poor, that is, they were deprived in at least a third of the MPI indicators used.The relationship between economic growth and poverty reduction was weak as during 2009-19 growth did not sufficiently translate into improved well-being of the poorest.Although during the period 2014 to 2020-21 Zanzibar witnessed a large shift of people out of low-productivity agriculture into services, particularly of women (a 10-percentage point shift according to labor force survey data), 'decomposition analysis' shows that population shifts to other sectors of work barely contributed to poverty reduction.Many likely adopted low-productivity work in the services sector.In fact, the creation of quality jobs was limited, and informality increased during this period.To accelerate poverty reduction in Zanzibar, a combination of policies are required to (i) make tourism, the main growth engine of the economy, more inclusive, for example through the diversification of tourism products; (ii) improve labor market outcomes for women and youth through better skills training and internship programs; (iii) improve the distribution of public spending in education and health to make it more pro-poor; and (iv) improve the business operating and regulatory environment of SMEs and better connect farm smallholders to high-value markets to enhance value addition, job creation and poverty reduction.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,006 |
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 source (Gemma direct ou Codex distillé), 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 ».