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Published Work

The Fruits of My Labor

The Cost of Being Faithful: What do Farmers Give Up to Keep the Sabbath?

July 25, 2019

Judeo-Christian beliefs and tradition include observing a Sabbath, or day of rest, by abstaining from work one day each week. In modern times, followers of the Jewish faith mark the Sabbath from Friday evening to Saturday evening and Christians do so on Sunday. For both groups, this practice is firmly entrenched to the point that many contend that working on Sunday is morally wrong. For many Christian workers in the United States, this practice often fits with their work schedule as Saturday and Sunday are typical days off doe many schools, government organizations, and businesses. There are exceptions to this and farmers are one of the most obvious. The demands of managing a farm do not conform to uniform weekly work schedules. To meet labor requirements, many Americans family farms rely upon unpaid family labor to perform tasks such as conducting field operations. Reliance on unpaid labor is becoming more prevalent due to lack of available laborers in many locations in the United States. A whole-farm linear programming model was parameterized as a limited resource Midwestern USA crop-producing farm. Model results estimate the costs of shutting down farm operations for differing levels of Sabbath observation across peak and non-peak seasonal time periods. Results indicate substantial costs are likely to occur, indicating that Sabbath-observing farm operators must perceive at least a base level of perceived benefits. These results are of interest to multi-generational farms attempting to balance work-life issues, researchers evaluating economics of religion, and rural development labor economists studying impacts of decaying populations on rural communities.

Estimating Value, Damages, and Remedies when Farm Data are Misappropriated

4th Quarter, 2018

Farm data valuation has been elusive across the industry, especially within the farm gate. The concepts of privacy, security, and ownership have clouded the discussion, leading to distrust by farmers. Farmers’ lack of trust regarding how other players may use data from their farms against them has led to discussions on the legal protection of farm data and what remedies exist to compensate for damages. Complementing previous work by legal specialists suggesting that farmers may claim damages reserved for trade secret violations after farm data are misappropriated, this article presents the process of the expert witness estimating relative economic losses and determining potential remedies.

Big Data in Agriculture: A Challenge for the Future

February 2018

Applied Economic Perspectives and Policy, 40,(1) pp79–96

This article examines the challenge and opportunities of Big Data, and concludes that these technologies will lead to relevant analysis at every stage of the agricultural value chain. Big Data is defined by several characteristics beyond size, particularly, the volume, velocity, variety, and veracity of the data. We discuss a set of analytical techniques that are increasingly relevant to our profession as one addresses these issues. Ultimately, we resolve that agricultural and applied economists are uniquely positioned to contribute to the research and outreach agenda on Big Data. We believe there are relevant policy, farm management, supply chain, consumer demand, and sustainability issues where our profession can make major contributions. The authors are thankful to the anonymous reviewers and editor Craig Gundersen for helpful comments. Support was provided by the Mississippi Agricultural and Forestry Experiment Station Special Research Initiative.

Managing the Kansas Mesonet for Site Specific Weather Information: proceedings of International Conference on Precision Agriculture

September 27, 2018

Weather data has become one of the most widely discussed layers in precision agriculture especially in terms of agricultural ‘big data’. However, most farmers (and even other researchers outside of meteorology) are not likely aware of the complexities required to maintain weather stations that provide data. These stations are exposed to the elements 24/7 and provide unique challenges for sustainment during extreme weather conditions. Based upon decades of experience, this paper discusses data acquisition from loggers and peripheral devices in terms of the network architecture. Numerous methods of quality control/assurance is paramount for detection of failure. Sensors measuring solar radiation, air temperature, relative humidity, wind speed/direction, precipitation, barometric pressure, and soil temperature/moisture are discussed. Once data becomes available, the Kansas Mesonet provides that data to a web-based portal for the public to utilize. Farmers and their advisors are able collect real-time and historic data from the portal via html or an application programming interface (API). Mesonet also integrates this data into agricultural tools critical in assisting with producer decision support. Some examples of these integrations include: evapotranspiration calculations, inversion monitoring, growing degree calculations, freeze monitoring and soil temperature decision tools.

Farm adoption of embodied knowledge and information intensive precision agriculture technology bundles

September 14, 2018

On-farm adoption of individual and groups of precision agriculture technologies has grown in the past fifteen years. Based on a sample of 545 farm observations collected by the Kansas Farm Management Association, farm adoption of bundles of embodied knowledge and information intensive technologies was analyzed using a Markov transition approach. Three separate analyses estimated transition probabilities to show the adoption of bundles of embodied knowledge technologies, the adoption of bundles of information intensive technologies, and the adoption of variable rate technologies contingent on prior adoption of embodied knowledge and/or information intensive technologies. Each analysis was estimated for two separate time periods (2009-2012) and (2013-2016). The probability that farms retain the same bundle or transition to a different bundle by the next time period are reported. The results indicate that persistence with the same technology bundle is the predominant behavior and that this behavior has strengthened in the study’s most recent time period.

Whole-farm Planning Models for Assessing Inter-Generational Transition

June 2018

Rosburg Farms is a crop farm in Northwest Iowa specializing in corn and soybean production. The oldest farm operator was looking toward retirement while the youngest generation was identifying an entry strategy into the operation. The overall goal of this research was to demonstrate how whole-farm planning models can be adapted to evaluate a potential intergenerational transition. Specific objectives were 1) to present how whole farm resources such as machinery, labor, and time constraints were collected and inventoried and 2) determine how additional rented land affects crop mix and machinery resource requirements. Data specific to Rosburg Farms were entered into an existing whole-farm linear programming model for regional- and farm-specific information. Farm-specific parameters included labor, machinery, crop rotations, and available acreage. Results indicated additional fieldwork could be completed with available labor and machinery. The process of adapting planning models is of interest to a wide spectrum of Extension personnel; and model results are applicable beyond the case study farm to other beginning farmers, farms anticipating intergenerational transition, and succession planning specialists.

Economic Investigation in Crop Selection in Lower Mississippi River Basin

May 2018

The conventional ethanol mandates set forth by the renewable fuel standards in the Energy Independence and Security Act of 2007 resulted in increased demand for corn. This study compares the economic viability of planting corn in the Southern Mississippi River Basin, an area traditionally characterized by rice and cotton farms. The Purdue Crop-Linear Programming model analyzed financial data to optimize crop selection. The cropping optimization was performed at eight commodity price levels and three input cost levels for 24 scenarios. The investigation indicated corn competed favorably with established SMRB crops only at specific price/input cost levels (7 of 24).

April 2018

Financial vulnerability has been observed across agricultural production regions; however, uncertainty regarding farms’ persistence within specific profitability categories exists. This study compared farm characteristics that persist in most and least profitable categories and then evaluated the probability that farms transitioned among profitability categories. Using 425 Kansas Farm Management Association (KFMA) farms that were present for the 20-year period 1994–2013, the persistence of remaining or transitioning to another profitability category was tested. Specifically, Markov transition probabilities were estimated for Kansas and the six regional KFMA regions. Comparisons of farms that persist in the highest and lowest profitability categories revealed no dramatic differences in acreage or other physical characteristics. Kansas farms tend to persist in their current profitability category, suggesting that operator skill and/or quality of farmland dominate random factors. In general, transition probabilities were greater for the highest and lowest profitability categories than for the middle categories. Farms were observed switching from highest to lowest profitability categories between 5% and 20% of the time within one year. Farmers were likely to stay in the highest profitability group more than half the time. By contrast, farmers were likely to stay in the lowest profitability group 42% of the time. Just like with the most profitable group, the least profitable group has a greater likelihood of remaining at the bottom, indicating that random events do not cause persistence.

Advancing U.S. Agricultural Competitiveness with Big Data and Agricultural Economic Market Information, Analysis, and Research

The purpose of this paper is to discuss economic issues relevant to the onset of various agricultural data sources, referring to the availability, capability, and use of Big Data in agricultural, food, and environmental systems. We aim to start the conversation about policy questions that need to be addressed as the sector experiences the dynamic changes that may occur with greater use of Big Data and Big Data analytics. The paradigm shift that is already occurring with these new technologies affords significant opportunities and risks.

October 25, 2016

Research Outlook: Complex Systems

January 25, 2025

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Uncovering Hidden Patterns Behind the Data

January 25, 2025

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Defining the Mechanisms of Action

January 25, 2025

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