Structural change in feedlot cattle death loss rates

育肥牛死亡率的结构性变化

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Abstract

INTRODUCTION: Industry reports and anecdotal evidence indicate that the death loss rate in cattle feedlots has increased over time. Such increases in death loss rates impact feedlot cost and thus profitability. OBJECTIVES: The primary objective of this study is to examine whether feedlot death loss rates in cattle have changed over time, to analyze the nature of any identified structural change, and to identify possible catalysts for that change. METHODS: Data from the Kansas Feedlot Performance and Feed Cost Summary from 1992 through 2017 is used to model feedlot death loss rate as a function of feeder cattle placement weight, days on feed, time, and seasonality in the form of monthly dummy variables. Commonly used tests of structural change, including the CUSUM, CUSUMSQ, and Bai and Perron methods, are implemented to examine the existence and nature of any structural changes in the proposed model. All tests indicate the presence of structural breaks in the model, including both systematic change and abrupt change. Following a synthesis of structural test results, the final model is modified to include a structural shift parameter for the period from December 2000 to September 2010. RESULTS: Models indicate that days on feed has a significant positive influence on death loss rate. Trend variables indicate that death loss rates have increased systematically over the period studied. However, the structural shift parameter in the modified model is positive and significant for December 2000 to September 2010, indicating that death loss is higher on average during this period. Variance of death loss percentage is also higher during this period. Parallels between evidence of structural change and possible industry and environmental catalysts are also discussed. CONCLUSIONS: Statistical evidence does indicate changes in the structure of death loss rates. Ongoing factors such as changes in feeding rations prompted by market forces and feeding technologies may have contributed to systematic change. Other events, such as weather events and beta agonist use could result in abrupt changes. No clear evidence directly connects these factors to death loss rates and disaggregated data would be required to facilitate such a study.

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