Linking efficiency, profitability, and growth of Kansas farms

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dc.contributor.author O'Brien, Cody
dc.date.accessioned 2017-08-11T18:49:22Z
dc.date.available 2017-08-11T18:49:22Z
dc.date.issued 2017-08-01 en_US
dc.identifier.uri http://hdl.handle.net/2097/36249
dc.description.abstract The main objective of this analysis was to examine the profitability and efficiency of Kansas farms in order to draw inferences among the profitability, efficiency, and growth of agricultural producers in Kansas. The time period analyzed was 2005 to 2015. Farms in the sample include a mix of 564 crop and/or livestock operations with 11 years of continuous data through the Kansas Farm Management Association data-bank. Efficiency scores were calculated to determine how close each farm was to the production possibilities frontier, or their cost efficiency. Profitability measures, (operating profit margin and return on assets), were obtained for each farm. The profitability dynamics in 2014 and 2015 for these farms changed compared to previous years. Crop farms generated less profits in 2014 and 2015 compared to previous years, and relative profits from average fluctuated more for sampled farms in 2014 and 2015. Farms were also categorized into risk classes. These classifications aim at distinguishing farms that are profitable or not, and their level of solvency, utilizing their net farm income from operations and their debt to asset ratio. Farms are migrating from the low risk classification, showing that Kansas farms are becoming less profitable, but are not transitioning to a higher risk solvency state. These farms will need to focus on utilizing their inputs more efficiently to keep their solvency levels in check. After analyzing persistence in profitability, the results suggest that farms with higher return on assets tend to be more solvent, but farms with higher operating profit margin tend to be less solvent. The analysis also suggests that there might have been persistence in profits in the years prior to 2015. The analysis of relative positioning of farms in terms of return on assets suggests that during 2007-2011 some farms were able to consistently differentiate themselves by generating either below or above normal profits. Some farms were able to become more profitable in 2012 and 2013, while others lagged behind supported by regression results that signaled divergence of profitability levels. The relative positioning analysis for operating profit margin indicates that farms had similar operating profit margins from 2010 through 2014, and divergence occurred in 2015 by farms that were able to differentiate themselves more through the average operating profit margin. Next the efficiencies of the farms were examined. Analysis of the efficiency scores suggests that the cost efficiencies of Kansas farms are not explained by risk classification significantly, but the crop-labor percentage ratio significantly explains the cost efficiency of the farms. The relationship between cost efficiency and profitability measures proved to be the strongest out of the three performance measures due to their correlation. The final step in the analysis was to examine farm characteristics of the top performing farms. Farms were ranked by profitability measurements and the efficiency measure. Variables of interest that were significantly different between the top 25 percent and the bottom 25 percent of farms include total farm assets, value of farm production, crop-labor percentage, crop acres, number of workers, and age of operators. en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Kansas farms en_US
dc.subject Linking performance measures en_US
dc.subject Risk rating en_US
dc.subject Persistence in profits en_US
dc.subject Cost efficiency en_US
dc.title Linking efficiency, profitability, and growth of Kansas farms en_US
dc.type Thesis en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Agricultural Economics en_US
dc.description.advisor Elizabeth Yeager en_US
dc.date.published 2017 en_US
dc.date.graduationmonth August en_US


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