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Enregistrement W4253530706 · doi:10.1353/eco.0.0012

In Search of the Missing Resource Curse

2008· article· en· W4253530706 sur OpenAlex

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Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2008
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueNatural Resources and Economic Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCurseEconomicsResource curseStylized factNatural resourceCommodityProtectionismNeoclassical economicsInternational economicsMarket economyKeynesian economicsLawPolitical scienceSociology

Résumé

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In Search of the Missing Resource Curse Daniel Lederman (bio) and William F. Maloney (bio) Like Dracula, the notion of a natural resource curse reemerges periodically, haunting the development debate, striking fear into the hearts of Latin American policymakers, and causing quantities of ink to be spilled on the various ways in which being blessed with mineral, agricultural, or other natural wealth will lead to anemic growth performance. Adam Smith was perhaps the first to articulate a concern that mining was a bad use of labor and capital and should be discouraged.1 The idea reappeared in the mid-1950s in Latin America when Raúl Prebisch, on observing slowing regional growth, argued that natural resource industries had fewer possibilities for technological progress and were condemned to decreasing relative prices on their exports.2 These stylized facts helped justify the import substitution experiment to modify national productive structures. Subsequently, disenchantment with the inefficiencies of protectionism and the consequences of populist macroeconomic policies led to more open trade regimes and less intrusive microeconomic policies, partly with the example of East Asia's rapid export-led growth in mind. Over the interim, however, two stylized facts have emerged to convert a new generation of analysts to believers in the curse. First, the liberalizing economies, with some notable exceptions, did not become either manufacturing dynamos or major participants in what is loosely called the new knowledge economy. Growth results were not impressive, and in the case of Africa, [End Page 1] dramatic falls in commodity prices contributed to negative growth rates. With the increased popularity of cross-country growth regressions in the 1990s, numerous authors offered proof that, in fact, natural resources appeared to curse countries with slower growth.3 Sachs and Warner are arguably the most influential of this group, with several authors drawing on their data and approach.4 They contend that the resource-rich developing countries across the world have grown more slowly than other developing countries since the 1960s. In 2007, Macartan Humphreys, Jeffrey Sachs, and Joseph Stiglitz published Escaping the Resource Curse, which has recently added further credence to the myth.5 Consequently, the conventional wisdom once again postulates that natural resources are a drag on development, which contradicts the commonsense view that natural riches are riches nonetheless. Yet there has always been a countervailing current that suggests that common sense was not, in this case, misleading. Most recently, evidence supportive of a more positive view was brought together by Lederman and Maloney in Natural Resources, Neither Curse nor Destiny, but the debate goes back substantially farther.6 Notable observers such as Douglass North and Jacob Viner dissented on the inherent inferiority of, for instance, agriculture relative to manufacturing colonies.7 Even as Adam Smith was writing The Wealth of Nations, the American colonies were declaring their independence on their way to being one of the richest nations in history, based largely on natural resources through much of that process.8 Other success stories, including Australia, Canada, Finland, and Sweden, remain, to date, net exporters of natural resources.9 The disappointing experiences of Latin America [End Page 2] and Africa clearly offer a counterbalance to these success stories, but they do not negate them. The acknowledgment of the important heterogeneity of experiences has led tentatively to a greater circumspection about the impact of resources, although not necessarily less enchantment with the term curse. Humphreys, Sachs, and Stiglitz begin their book by noting that resource-rich countries often perform worse than their resource-poor comparators, while Dunning talks of a conditional resource curse—that is, there is a negative growth impact under certain conditions.10 This is undoubtedly a more careful way to frame the issue, one that moves explaining the heterogeneity to center stage. Nevertheless, the notion of a resource curse suggests more than the existence of a negative tail in the distribution of impact. Dracula's sinister reputation arises not from the occasional involuntary transfusion, but rather from the bloody parasitism that is the central tendency of his character (disclaimer: we have not carefully reviewed any of the relevant empirical literature on this topic).11 This article builds on our earlier work to argue that such a...

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,117
Score d'incertitude au seuil0,995

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0020,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

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.

Tête enseignante Opus0,324
Tête enseignante GPT0,482
Écart entre enseignants0,158 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle