MétaCan
Menu
Back to cohort
Record W2612404171

The Economics of First Possession Rights to a Heterogeneous Resource: Prior Appropriation Rights to Water

2015· article· en· W2612404171 on OpenAlexaboutno aff
Bryan Leonard, Gary D. Libecap

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsAppropriationPossession (linguistics)Property rightsLaw and economicsPolitical scienceBusinessNatural resource economicsLawEconomics
DOInot available

Abstract

fetched live from OpenAlex

We analyze the economics of first-possession property rights to a large heterogeneous resource allocated under incomplete information and competitive claiming by agents. Our focus is on prior-appropriation surface water rights used in 18 western US states and generally in at least 3 western Canadian provinces, with specific attention to Colorado, 1852-2013. Prior appropriation was an institutional innovation, replacing common-law riparian rights, in a setting where water supplies were scarce, unevenly distributed, and remote from production sites where water was a key input. Prior appropriation emerged very rapidly within 20 years or less to be the dominant rights regime covering an immense area of over 1,197,000 square miles, suggesting large economic advantages relative to the incumbent institutional regime. Voluntary, large-scale property rights changes are unusual empirically. Prior appropriation encouraged valuable search and narrowed the information required to establish ownership to that described in immediate water diversion rather than an entire river basin. It thereby also lowered individual bounding and enforcement costs. Beneficial use revealed how much water remained for subsequent rights claimants. We examine the economic advantages of prior appropriation. The benefits of prior appropriation in general depended upon how rights were obtained, an issue that we examine in detail. At the time of claiming water there was little information about water source characteristics, and the process of claiming revealed such information. Hence, there was a tradeoff between claiming at a particular time and waiting. At any time, water rights claimants were equal in their lack of knowledge of the best water diversion locations. Each round of claiming revealed new information, but the quantities of remaining high-quality diversion sites were reduced. Individual claims were based on observable resource characteristics, such as current stream flow or quantity, distance to stream head, terrain topography, and proximate soil quality. Because claiming initially took place under open-access conditions, there was potential for rent dissipation. Nevertheless, so long as search revealed critical resource characteristics, they were stable, and individual claims were recognized, there was no basis for rent dissipation, even in a rush to claim given the number of claimants and resource size. In this regard we differ from the literature on first possession that generally points to full dissipation. Prior appropriation water rights became the basis for water trade, investment in dams and canals, and expansion of irrigated agriculture and other activities critical for economic development. Prior appropriation rights endure, affecting the distribution of water ownership and exchange. Assessment of the prior appropriation’s welfare effects requires accounting for its role in generating property rights to water, investment, production, and the transaction costs of water exchange.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.013
GPT teacher head0.196
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicConservation, Biodiversity, and Resource ManagementFrench-language works237,207