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将模型选择和不确定性纳入伴侣动物临床兽医劳动力市场经济状况预测中。

Incorporating model selection and uncertainty into forecasts of economic conditions in companion animal clinical veterinarian labor markets.

作者信息

MacLachlan Matthew J, Volk John, Doherty Christopher

机构信息

1Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY.

2Dyson School of Applied Economics and Management, SC Johnson College of Business, Cornell University, Ithaca, NY.

出版信息

J Am Vet Med Assoc. 2024 Nov 22;263(2):240-247. doi: 10.2460/javma.24.09.0624. Print 2025 Feb 1.

DOI:10.2460/javma.24.09.0624
PMID:39586176
Abstract

Following the onset of COVID-19, demand for US veterinary services rapidly increased, similarly driving up demand in upstream veterinary labor markets. This increasing demand starkly contrasted with the "excess capacity" period following the Great Recession, marked by fewer opportunities and low wages for veterinarians. Better models and forecasts of veterinary labor market conditions improve information for decision-making by veterinarians, relevant business owners, professional associations, and educational institutions. Well-performing approaches will adapt to new data as they become available and avoid the assumption that short-term market dynamics will persist permanently. In this paper, we modify an approach often used to identify the forecasting model best suited to the data. Then, using the best forecasting model, we generate forecasts and prediction intervals around them to meet the available data and realities of veterinary labor markets to 2035. This approach removes subjectivity, accommodates model refinements, and acknowledges that the future is unknown. We find that the supply and demand indicators for veterinary services both indicate continued growth. We do not find statistically significant or consistent differences in either supply or demand growth, which would be consistent with a competitive market for veterinary services and labor. The data do not support an expectation of a continued shortage in the US veterinarian labor markets, as suggested in previous studies. We identify several areas where improved data resources and further methodological advancements could shed more light on the economic conditions facing veterinarians.

摘要

在新冠疫情爆发后,美国对兽医服务的需求迅速增加,同样也推动了上游兽医劳动力市场需求的上升。这种需求的增加与大衰退后的“产能过剩”时期形成了鲜明对比,当时兽医的机会较少且工资较低。更好的兽医劳动力市场状况模型和预测能够改善兽医、相关企业主、专业协会和教育机构决策所需的信息。表现良好的方法会随着新数据的出现而进行调整,避免假设短期市场动态会永久持续。在本文中,我们修改了一种常用于确定最适合数据的预测模型的方法。然后,使用最佳预测模型,我们生成预测以及围绕预测的置信区间,以适应现有的数据和兽医劳动力市场到2035年的实际情况。这种方法消除了主观性,适应模型的改进,并承认未来是未知的。我们发现兽医服务的供需指标均显示持续增长。我们没有发现供需增长在统计上有显著或一致的差异,这与兽医服务和劳动力的竞争市场是相符的。数据并不支持先前研究中所暗示的美国兽医劳动力市场将持续短缺的预期。我们确定了几个领域,在这些领域中,改进的数据资源和进一步的方法进步可以更清楚地揭示兽医面临的经济状况。

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