MétaCan
Menu
Back to cohort
Record W2015004648 · doi:10.22004/ag.econ.273609

The Economic Opportunity Cost of Capital for Canada - An Empirical Update

2007· preprint· en· W2015004648 on OpenAlexaboutno aff
Glenn P. Jenkins, Chun‐Yan Kuo

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2007
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsOpportunity costNet present valuePresent valueInvestment (military)Economic costEstimationEconomic impact analysisSocial discount rateValue (mathematics)DiscountingCost of capitalInterest rateCost–benefit analysisPublic economicsMacroeconomicsMicroeconomicsFinanceProduction (economics)

Abstract

fetched live from OpenAlex

The social or economic discount rate is the threshold rate used to calculate the net present value of an investment project, a program or a regulatory intervention to see whether the proposed expenditures are economically worthwhile to undertake. The size of the economic rate of discount has been a policy issue in Canada for many years. The debate has been primarily concerned with the empirical measurement of the economic opportunity cost of funds. The purpose of this paper is to reexamine and update the empirical estimation of what is the appropriate economic discount rate for Canada. The results suggest that estimates of the economic discount rate can range from 7.78 percent to 8.39 percent real. As a consequence, we conclude that for Canada an 8 percent real rate is an appropriate discount rate to use when calculating the economic net present value of the flows of economic benefits and costs over time.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.080
GPT teacher head0.265
Teacher spread0.185 · 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.

Study designNot applicable
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

Citations29
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueAgEcon Search (University of Minnesota, USA)Same topicHousing Market and EconomicsFrench-language works237,207