Christopher A. Wolf, Mark W. Stephenson, Wayne A. Knoblauch and Andrew M. Novakovic
The purpose of this paper is to evaluate dairy farm financial performance over time utilizing farm financial ratios from three university business analysis programs. The…
Abstract
Purpose
The purpose of this paper is to evaluate dairy farm financial performance over time utilizing farm financial ratios from three university business analysis programs. The evaluation includes measures of profitability, solvency, and liquidity by herd size.
Design/methodology/approach
Financial ratios to reflect profitability (rate of return on assets), solvency (debt to asset ratio), and liquidity (current ratio) were collected from Cornell University, Michigan State University, and the University of Wisconsin for dairy farms from 2000 to 2012. The distribution of farm financial performance using these ratios was examined over time and by herd size. Variance component methods are used to examine the percent of variation due to individual firm and industry aspects. A simple credit risk score is calculated to examine relative farm risk.
Findings
Dairy farm profitability performance is similar across herd sizes in poor years but larger herds realized significantly more profitability in good years. Findings were similar with respect to liquidity. Large herds consistently carried relatively more debt. Large herds’ financial performance was more uniform than across smaller herds. Larger herds had more financial risk as measured by credit risk scoring but recovered quickly to industry averages in profitable years.
Originality/value
The variation of dairy farm financial performance in an era of volatile milk and feed price is assessed. The results have important implications for farm financial management and benchmarking farm financial performance. In addition to helping to evaluate the efficacy of various price and income risk management tools, these results have important implications for understanding the benefits of the new federal Margin Protection Program for Dairy that is available to all US dairy farmers.
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Christopher A. Wolf, J. Roy Black and Mark W. Stephenson
The purpose of this research is to understand US Upper Midwest dairy farm profitability performance over time and across herd size. Profitability is broken down into asset…
Abstract
Purpose
The purpose of this research is to understand US Upper Midwest dairy farm profitability performance over time and across herd size. Profitability is broken down into asset efficiency and operating profit margin. The primary objective is to determine how much information is required to accurately benchmark farm performance.
Design/methodology/approach
Financial ratios to measure profitability (rate of return on assets), profit margin (operating profit margin ratio), and asset efficiency (asset turnover) were collected from Michigan State University and the University of Wisconsin business analysis programs for dairy farms from 2000 through 2016. Financial ratio patterns were examined both across time and herd size. Annual distributions were divided into quartiles and the use of one to five-year averages were used to determine accuracy of quartile rank compared to true long-run farm profitability performance.
Findings
Financial performance across large herds was more uniform than across smaller herds. Small and large herd profitability performance converged in poor years but diverged in good years. Using three or more years performance greatly improved accuracy of benchmarking profitability.
Originality/value
The data utilized are very rich in the sense of the amount of variation across years and herd size. The results have important implications for farm financial management and benchmarking farm financial performance. Farm firms should benchmark multiple years of profitability before making major management changes to alleviate deficiencies.
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Leonard Polzin, Christopher A. Wolf and J. Roy Black
The purpose of this paper is to examine the use of accelerated depreciation deductions, which includes Section 179 and bonus depreciation, taken in the first year of asset life by…
Abstract
Purpose
The purpose of this paper is to examine the use of accelerated depreciation deductions, which includes Section 179 and bonus depreciation, taken in the first year of asset life by Michigan farms. The frequency, value and influence of accelerated depreciation on farm investment are also analyzed.
Design/methodology/approach
Accrual adjusted income statements, balance sheets, depreciation schedules, and income tax information for 66 Michigan farms from 2004 to 2014 provide data for the analysis. The present value of the accelerated deduction and change in the cost of capital were calculated. Finally, investment elasticities were used to arrive at the change in investment due to accelerated depreciation.
Findings
Accelerated depreciation was utilized across all applicable asset classes. Section 179 was used more often than bonus depreciation in part because it was available in all the examined years. Based on actual farm business use, accelerated depreciation lowered the cost of capital for the operations resulting in an estimated increase in investment of 0.27 to 11.6 percent depending on asset class.
Originality/value
The data utilized are of a detail not available in previous investigations which used either aggregate data or estimated rather than the observed use of accelerated depreciation. This analysis reveals that accelerated depreciation as used by commercial farms lowers the cost of capital and thus encourages investment particularly in machinery and equipment.
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Joleen C. Hadrich, Christopher A. Wolf and Kamina K. Johnson
The structural change of the dairy industry has been a long-term process with fewer, larger dairy herds in all regions. The purpose of this paper is to evaluate whether this…
Abstract
Purpose
The structural change of the dairy industry has been a long-term process with fewer, larger dairy herds in all regions. The purpose of this paper is to evaluate whether this structural change is leading to less income and wealth equality across dairy farms and how these factors differ across the USA.
Design/methodology/approach
Income and wealth inequality of US dairy farms was estimated by Gini coefficients using data from the 2000 and 2010 ARMS dairy costs and returns data. A population-level quantile regression was estimated at decile increments to determine the factors that affect net farm income (NFI) and net worth (NETW) and if they changed across the time periods.
Findings
Adjusted-Gini coefficients were estimated and indicated that income inequality was greater than wealth inequality across US dairy farms. Results of the quantile regressions confirm regional differences exist with dairy farms in Mountain regions consistently having lower NFI and NETW relative to farms in the Lake States region when factors such as herd size were equal. Life cycle effects were not observed for NFI, but present within NETW estimates across the ten years.
Originality/value
This analysis estimates industry-specific-adjusted Gini coefficients to determine if income and wealth inequality exist.
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Christopher A. Wolf, Frank Lupi and Stephen Harsh
The purpose of this paper is to determine which financial record‐keeping system farmers use, as well as what system attributes farmers value and to what degree.
Abstract
Purpose
The purpose of this paper is to determine which financial record‐keeping system farmers use, as well as what system attributes farmers value and to what degree.
Design/methodology/approach
This research uses a choice experiment to examine farmer's demand for attributes of financial record‐keeping systems. A sample from the general Michigan farm population is compared to samples from university and agribusiness record system clients.
Findings
Results reveal that university and agribusiness clients are willing to pay considerably more for a farm‐specific record system to backstop their farm management decisions.
Practical implications
The results provide an understanding of farmer demands for farm financial record systems and can be used to position record‐keeping systems to meet those demands.
Originality/value
This paper describes and analyzes farm financial accounting system use and preferences by type.
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Christopher A. Wolf, J. Roy Black and Joleen C. Hadrich
The purpose of this paper is to examine the sources and magnitude of variation in accrual adjusted gross farm revenue and farm revenue net of feed purchases on Michigan dairy…
Abstract
Purpose
The purpose of this paper is to examine the sources and magnitude of variation in accrual adjusted gross farm revenue and farm revenue net of feed purchases on Michigan dairy farms representative of Upper Midwest dairy farms. The paper aims to assess whether adjusted gross revenue‐type insurance instruments meet insurability conditions when applied to dairy farms.
Design/methodology/approach
Accrual adjusted dairy farm revenue and revenue net of feed purchased from Michigan dairy farm panel data from 1995 through 2006 were detrended and summarized. Variance decomposition was used to identify sources of variation in adjusted gross revenue and adjusted gross revenue less feed purchases. In‐sample insurance premiums were estimated and Monte Carlo simulations were used to adjust these premiums for out‐of‐sample considerations.
Findings
Milk price variation was the largest source of variation while milk production per cow varied little. Farms with smaller herds and those with larger percentages of farm revenue from crop sales had higher relative revenue variability and would trigger a higher frequency of indemnities under a whole farm revenue insurance contract.
Research limitations/implications
Because the data analyzed conclude in 2006, the volatility of the past couple of years is not reflected. Therefore, researchers are encouraged to test the proposed insurance feasibility further with more recent data.
Practical implications
The paper addresses considerations for the development and commercialization of a feasible dairy revenue insurance instrument.
Originality/value
This paper fulfils a need to understand magnitude and source of revenue variation on dairy farms and how insurance might mitigate negative consequences of this variation.
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Lyn M. Holley, Christopher M. Kelly, Jerome Deichert, Silvester Juanes and Loretta Wolf
The purpose of this paper is to disseminate a new model that addresses the urgent social challenge of providing adequate long-term care in rural circumstances through innovative…
Abstract
Purpose
The purpose of this paper is to disseminate a new model that addresses the urgent social challenge of providing adequate long-term care in rural circumstances through innovative use of existing resources, and to suggest future research.
Design/methodology/approach
This paper is exploratory in and is based upon the analysis of qualitative observations (interviews and site visits) framed in the financial and operational records of the facility studied, macro- and micro-level demographics, and the scholarly and practice literatures.
Findings
Significant cost savings upon implementation, improvements in quality of care and both worker and client satisfaction were observed.
Research limitations/implications
The model has been in operation only one year; the trend has been positive, however, more research is needed to identify its stability and develop a more refined description of its components: while essential features of this innovative model can be applied in any residential long-term care situation, replicating its success is obviously linked with the skill and authority of the director. Evaluation research is currently in progress.
Practical implications
The paper suggests budget-neutral solutions to persistent challenges of caring for older adults in rural circumstances.
Social implications
Quality and financing of long-term residential care for elders is insufficient and worsening. This model addresses problems central to financing and quality of care by connecting existing resources in new ways. It does not require additional funding or changes in qualifications required for jobs.
Originality/value
The model is the original creation of a residential long-term care facility director working with a network of partnerships that he discovered and developed: partnerships include a broad range of organizations in the public and non-profit sectors, and the state university.
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Mario Ortez, Nicole Olynk Widmar, Mindy Lyn Mallory, Christopher Allen Wolf and Courtney Bir
This article quantifies public sentiment for dairy products using online media and investigates potential relationships between online media, both volume and sentiment, and future…
Abstract
Purpose
This article quantifies public sentiment for dairy products using online media and investigates potential relationships between online media, both volume and sentiment, and future prices of Class III milk.
Design/methodology/approach
Netbase, an online media listening platform, was used to quantify US generated online media sentiment and number of mentions regarding dairy products. Granger-causality tests and Impulse Response Functions (IRFs) were used to study relationships between online media derived data and dairy futures prices.
Findings
Milk and cheese have more mentions in online media than yogurt and ice cream. Online media net sentiment around milk was the lowest of the dairy products studied. Granger-causality tests showed that Class III milk price Granger-causes net sentiment of dairy as a whole and of fluid milk. Price additionally Granger-causes mentions of milk, ice cream and yogurt. Notably, milk and ice cream mentions Granger-cause the Class III milk price. IRF's reveals that increases in mentions have a positive, albeit small, effect on the Class III milk price that is statistically significant for ice cream, but not for milk. IRF's directionality of the relationship from price to online media derived data was mixed.
Originality/value
This is the first time that relationships between online media -volume and sentiment- and futures prices of an agricultural commodity are researched. Exploration of futures markets alongside online media advances the use of online media to glean insights in financial, along with food and agricultural markets.