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Record W3025877672 · doi:10.7939/r37d2qp9x

Canada's Beef Cattle Industry: Exchange Rates, Price Pass-Through and Feedlot Profitability Under Different Production Systems

2018· article· en· W3025877672 on OpenAlexaboutno aff
Jiaping Fan

Bibliographic record

VenueUniversity of Alberta Library · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsFeedlotProfitability indexBeef cattleProduction (economics)Beef industryAgricultural scienceAgricultural economicsBusinessAnimal productionEconomicsAnimal scienceEnvironmental scienceBiologyFinance

Abstract

fetched live from OpenAlex

This thesis examines two issues from different perspectives of Canada’s beef cattle industry. The first study undertakes the analysis of the exogenous variable’s threshold effect on the domestic price pass-through across the different market levels. The study employs a 3-step analysis: first, a threshold test to detect threshold effect of variable, in this case, exchange rate, on domestic price transmission pattern; second, the threshold autoregression (TAR) model to find the threshold value; and third, the threshold ECM to estimate the short-run adjustments of the farm level price and the wholesale level price regarding to any deviation from the long-run relationship. The results suggest that the trade-oriented variable, exchange rate, exerts threshold effect inducing two regimes. Furthermore, in each regime, farm level producer and wholesale level producer coordinate with each other regarding prices in different patterns. The second study examines the impact of production systems on cattle carcass quality and determinants of cattle feeding profitability. It assigns a unit price to each cattle based on its carcass characteristics with the guidance of Canadian Beef Grading System and calculates profit with the grid-based price. The study applies a three-part analysis. First, ordered logit model is built to investigate the probability of cattle carcass falling into different grades. Second, ordinary least square (OLS) regression model is estimated to examine the effect of production variables on the cattle feeding profitability. Third, simulation methodology is applied to generate expected profit; then break-even analysis is conducted. This study also takes price risks into account by conducting the last two analyses in typical input and output price scenarios. The results indicate that cattle’s breed composition, hormone growth promotants, ractopamine treatment, and diet exert impacts on cattle carcass’ grade outcome and cattle feeding profitability in different price scenarios.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.175
Teacher spread0.160 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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