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| Cooper, Joseph C.; Langemeier, Michael R.; Schnitkey, Gary D.; Zulauf, Carl R.. |
| Yield variability can be significantly higher at the farm level than at more aggregated levels, including the county. However, due to a dearth of available farm level data, much stochastic analysis involving farm yields utilizes more aggregated yield data as a proxy for the farm level. We empirically evaluate farm-level variability using longitudinal farm level data sets available from the Kansas Farm Management Association and the Illinois Farm Business and Farm Management Association. For corn, soybeans, and wheat, we compare the farm level yield variability obtained from this data to that inferred from Federal crop insurance premiums. The farm management data exhibit lower yield variability than are implied by the crop insurance premiums. |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Yield variability; Crop insurance; Corn; Wheat; Soybeans; Agricultural and Food Policy; Crop Production/Industries; Research Methods/ Statistical Methods; Risk and Uncertainty. |
| Ano: 2009 |
URL: http://purl.umn.edu/49216 |
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| PELOIA,PAULO R.; RODRIGUES,LUIZ H. A.. |
| ABSTRACT In order to achieve more efficient agricultural production systems, studies relating to the patterns of influence factors on commercial blocks of outstanding performance can be performed to assist management practices. The performance is considered to be the difference between the yield of a given block and the average yield of the homogeneous group that it belongs to. The methods available to identify these outstanding blocks are usually subjective. The aim of this study was to propose an objective and repeatable approach to identify outstanding performance blocks. The proposed approach consisted of performance determination, using regression trees, and the classification of these blocks by k-means clustering. This approach was illustrated using... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Clustering; Regression tree; Yield variability. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162016000500895 |
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