Economic Analyses of Livestock Marketing and Production in China
Bibliographic record
Abstract
This dissertation comprises three interrelated essays on livestock marketing and production in China. In the first essay, the main objective was to propose and implement a procedure to estimate price’s budgetary and signaling effects on demand for goods in discrete choice experiments. A structural modeling procedure was developed and implemented to identify the double impact of price on utility and to guide the empirical approach. The application used data from an online survey of 622 Chinese consumers conducted in 2021. In addition to a choice experiment using beef brisket, the survey included questions about consumers’ perceived quality of the brisket. This study utilized a mixed logit model to explore consumers’ choice decisions and employed a panel linear regression model to estimate the price-quality relationship. Results show a positive and statistically significant effect of price on perceived product quality, suggesting that Chinese consumers use price as an indicator of quality, which might be related to uncertainty regarding beef brisket quality and distrust of the information presented on labels. However, this study found that the budgetary effect is greater than the signaling effect. Moreover, Chinese consumers are willing to pay premiums for overall quality improvements. These willingness to pay values would be smaller if consumers did not use price as a signal for quality. The second essay examined Chinese consumers’ preferences and willingness to pay for credence attributes of beef from the domestic market and beef from other large exporting countries. Three beef cuts were considered: steak, brisket, and tongue. Data was collected from an online survey incorporating choice experiments of 2,016 consumers from China in 2021. In the choice scenarios, each respondent was presented with three beef alternatives that differed in price, country of origin, food safety, and production certifications, and also included a “no purchase” option. Chinese consumers’ beef selections in the choice experiments were analyzed using a mixed logit model in willingness space. Results indicate the type of cut does not influence Chinese consumers’ evaluation of country of origin and credence attributes. Moreover, results show that Chinese consumers strongly prefer and are willing to pay more for domestic beef than imported beef products. Beef from New Zealand had the highest willingness to pay value among all the exporting countries included in the study, followed by Argentina, Australia, Canada, Uruguay, Brazil, and the United States. Also, enhanced food safety and Organic and Green Food certifications had positive willingness to pay values. Overall, the findings of this study offer evidence that Chinese consumers prefer safe and quality-assured beef products. The third and final essay examined the impacts of windfall income from picking and trading caterpillar fungus on pastoral households’ livestock production activities. Data was collected from a pastoral household survey (n=503) conducted in 2016 and 2017 in five Tibetan Autonomous Prefectures in China. This study employed propensity score matching procedures with the first nearest neighbor matching method to estimate the effect of participation in harvesting and trading the caterpillar fungus. The estimated results show that pastoral households with income from caterpillar fungus activities tend to maintain a smaller herd size, sell fewer animals for profit, slaughter more livestock for family consumption, and experience fewer livestock deaths compared to traditional pastoral households without caterpillar fungus income. Consequently, the new income source also decreases the grazing intensity. Moreover, the findings of this study provide evidence for promoting a more diversified and sustainable livelihood portfolio to decrease traditional pastoral households’ dependence on grasslands.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".