EAPSI: Analyzing the Relationship Between Livestock Grazing and Locust Activity in Inner Mongolia, China

在世界许多地区，蝗虫是一个破坏性问题，对农民和牧场主的潜在风险最高。本研究旨在量化蝗灾对中国内蒙古牲畜市场的影响。众所周知，高密度的蝗虫会与牲畜争夺食物，但了解这对肉类生产和价格的影响也很重要。此外，最近的生态学研究表明，当特定地区放牧的动物数量减少时，蝗虫密度会下降。利用与内蒙古农业大学合作收集的数据，该研究将量化该地区农民因蝗虫遭受的预期经济损失。利用肉类价格和产量数据，我们计算了内蒙古绵羊、山羊和其他牲畜在农场和零售层面的需求和供应的价格弹性和交叉价格弹性。这些值用于建立均衡位移模型，该模型计算由于生产冲击而导致的产量变化如何影响农场和零售层面的价格和供应。我们将研究两种情景：一种是代表性农民的高强度放牧，另一种是代表性农民的中等强度放牧。该模型的结果将用于检查农民在两种情况下因蝗虫而遭受的预期经济损失，这将用于确定蝗虫是否发生在农民身上？减少放牧强度作为一种缓解方法是最有利的。该奖项由国家科学基金会与中国科技部共同资助。

Locusts are a devastating problem in many regions of the world with the risk potential highest for farmers and ranchers. This research seeks to quantify the impact of a locust infestation on livestock markets in Inner Mongolia, China. Locusts at high densities are known to compete with livestock for food, but it is important to also understand how this impacts meat production and prices. Furthermore, recent ecological study has demonstrated that locust density decreases when the number of animals grazed on a given area is reduced. Using data collected in collaboration with Inner Mongolia Agricultural University, this research will quantify the expected financial loss farmers will experience from locusts in this region. Using data on meat prices and yields, we calculate the own-price and cross-price elasticities of demand and supply for sheep, goats and other livestock produced in Inner Mongolia at the farm and retail level. These values are used to build an equilibrium displacement model, which calculates how changes in yield due to a production shock impact price and supply at the farm and retail level. We will examine two scenarios: one where the representative farmer grazes at a high intensity and one where the representative farmer grazes at a moderate intensity. The results of this model will be used to examine the expected financial loss a farmer will experience due to locusts in both scenarios which will be used to determine whether or not it is in the farmer?s best interests to reduce grazing intensity as a mitigation method. This NSF EAPSI award is funded in collaboration with the Chinese Ministry of Science and Technology.