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Record W4253530706 · doi:10.1353/eco.0.0012

In Search of the Missing Resource Curse

2008· article· en· W4253530706 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsCurseEconomicsResource curseStylized factNatural resourceCommodityProtectionismNeoclassical economicsInternational economicsMarket economyKeynesian economicsLawPolitical scienceSociology

Abstract

fetched live from OpenAlex

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...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.324
GPT teacher head0.482
Teacher spread0.158 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it