MétaCan
Menu
Back to cohort

From rent seeking to human capital: a model where resource shocks cause transitions from stagnation to growth

2008· article· en· W2126890923 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsYork University
Fundersnot available
KeywordsEconomicsResource curseProductivityRent-seekingExternalityEconomic stagnationGrowth modelHuman capitalPer capitaGrowth rateNatural resourceLabour economicsMonetary economicsMicroeconomicsMacroeconomicsMarket economyEcology

Abstract

fetched live from OpenAlex

Abstract. We present a growth model where agents divide time between rent seeking in the form of resource competition and working in a human capital sector. The latter is interpreted as trade or manufacturing. Rent seeking exerts negative externalities on the productivity of human capital. Adding shocks, in the form of fluctuations in the size of the contested resource, the model can replicate a long phase with stagnant incomes and high levels of rent seeking, interrupted by small, failed growth spurts, eventually followed by a permanent transition to a sustained growth path where rent seeking vanishes in the limit. The model also generates a rise and fall of the so‐called natural resource curse: before the takeoff, an increase in the size of the contested resource has a positive effect on incomes; shortly after the takeoff, the effect is negative; and on the balanced growth path the growth rate of per capita income is independent of resource shocks.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.131
GPT teacher head0.187
Teacher spread0.056 · 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