The effect of grain elevator market concentration on Saskatchewan farmland prices
Bibliographic record
Abstract
In western Canada, grain elevators assume a central role in the Grain Handling and Transportation System (GHTS). Over the decades, the GHTS has undergone important changes. First, the number of grain elevators has declined rapidly, and older elevators have been replaced by larger and more efficient elevators. This resulted in increased average market concentration ratios of grain elevators and increased length of truck haul by farmers. Second, the removal of the single desk seller power of the Canadian Wheat Board in 2012 affected the way GHTS operates. After the removal of the CWB, grain elevator companies were left to handle both marketing and logistics (C¸ akir and Nolan, 2015). This change resulted in the removal of the CWB as an established participant in the GHTS and it became legal for Canadian grain farmers to sell their grain to whomever they choose. We examine the effect of grain elevator market concentration on Saskatchewan farmland prices. We present two models of market concentration. Market power is measured by the total number of elevators within a radius of farmland or by the distance between elevators. In order to measure efficiency, we consider the total capacity of elevators within a radius around a farmland or the capacities of the closest grain elevators. Our specification explains farmland prices based on market power and capacity variables. Overall, consistent with the economic theory, the models suggest that as the local market power measures increase, the farmland prices decrease after 2012. Furthermore, contrary to the general economic theory, the efficiency measures are negatively related to farmland prices. For the most part, the results of both models are consistent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".