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Record W3121342163 · doi:10.3386/w18126

Decentralisation in Africa and the Nature of Local Governments' Competition: Evidence from Benin

2012· report· en· W3121342163 on OpenAlexaff
Émilie Caldeira, Martial Foucault, Grégoire Rota‐Graziosi

Bibliographic record

VenueNational Bureau of Economic Research · 2012
Typereport
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsUniversité de Montréal
FundersPrinceton University
KeywordsDecentralizationCompetition (biology)Political scienceDevelopment economicsGeographyPolitical economyEconomicsBiologyEcologyLaw

Abstract

fetched live from OpenAlex

Decentralization has been put forward as a powerful tool to reduce poverty and improve governance in Africa. The aim of this paper is to study the existence, and identify the nature, of spillovers resulting from local expenditure policies. These spillovers impact the efficiency of decentralization. We develop a two-jurisdiction model of public expenditure, which differs from existing literature by capturing the extreme poverty of some local governments in developing countries through a generalized notion of the Nash equilibrium, namely, the constrained Nash equilibrium. We show how and under which conditions spillovers among jurisdictions induce strategic behaviours from local officials. By estimating a spatial lag model for a panel data analysis of the 77 communes in Benin from 2002 to 2008, our empirical analysis establishes the existence of the strategic complementarity of jurisdictions' public spending. Thus, any increase in the local public provision in one jurisdiction should induce a similar variation among the neighbouring jurisdictions. This result raises the issue of coordination among local governments, and more broadly, it questions the effeciency of decentralisation in developing countries in line with Oates' theorem.

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.

How this classification was reachedexpand

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.292
GPT teacher head0.479
Teacher spread0.188 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2012
Admission routes1
Has abstractyes

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