Impact of Foodborne Illness Outbreaks on Price Transmission, U.S. Price Linkages in the International Wheat Market, and Spatial Price Dynamics in the U.S. Vegetable Sector
Bibliographic record
Abstract
In the first essay, a regime switching error correction model is applied to weekly shipping point and terminal market spinach prices in order to assess the spatial price transmission impact of the 2006 E. coli outbreak on the U.S. fresh spinach market. A food safety index (FSI) related to the outbreak is calculated and used as the regime switching mechanism for 11 alternative farm-to-wholesale spatially separated market pairs. Results suggest not all markets responded uniformly to the FSI. The majority of the markets with alternative sources of spinach exhibited nonlinearities, while those which were primarily supplied by California producers did not. In general, shorter adjustment speeds were seen in terminal markets that were closer in proximity to the California shipping point. Southern market pairs exhibiting threshold behavior saw increased efficiency after the outbreak (potentially due to increased self-regulation), while the remaining pairs saw a loss in efficiency. In the second essay, through applying time-series modeling techniques to weekly wheat prices, we evaluate the long-run price dynamics between the U.S. and other large wheat exporters, including the E.U., Canada, Australia, Argentina, and the Black Sea region. Testing for cointegration lead to the conclusion that aside from Canada, U.S. hard red winter wheat prices are cointegrated with the other top exporters and aside from Canada and Australia, U.S. soft red winter wheat prices are cointegrated with the other top wheat exporters. Threshold and asymmetric behavior were not present in the long-run relationship between the top exporters. In addition, Granger causality tests indicated that the U.S. has a significant impact on wheat prices in Argentina, Australia, the E.U., and even in the Black Sea region. Price transmission elasticities were all estimated to be above 0.78, and suggest the possibility that trade barriers are still preventing optimal market efficiency. The third essay investigates price transmission behavior in the U.S. fresh vegetable market, in particular looking at the top five vegetables consumed, including carrots, lettuce, onions, potatoes, and tomatoes. An asymmetric variable threshold autoregressive model (AvTAR) was used to estimate the price relationships between 54 separate terminal market pairs, while the parity bounds model (PBM) was used to estimate the probability of 28 shipping point to terminal market pairs behaving efficiently. Results for the AvTAR model provide evidence that the level of perishability impacts the level of market integration and of a common trend of increasing transaction costs among nearly 70% of the markets studied. Results for the PBM indicate that 18% of the markets studied had more than a 10% probability of behaving inefficiently, indicating that while the majority of markets behaved efficiently, there is room for improvement.
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 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".