Farm Characteristics and Business Risk in Production Agriculture

Schurle, Bryan W.; Tholstrup, Mike

doi:10.2307/1349106

Cited by 7 publications

(8 citation statements)

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“…However, we show that those farms are also most likely to be the largest beneficiaries of the three major farm programs that provide over 70% of all federal funds paid to farmers. Further, these farms are also likely to be the least vulnerable to production and price shocks that adversely affect their revenues and costs (Schurle and Tholstrup 1989;Purdy, Langemeier, and Featherstone 1997;Barry, Escalante, and Bard 2001).…”

Section: Discussionmentioning

confidence: 99%

“…The data indicate that producers who receive the majority of total PLC and ARC programs and crop insurance subsidy payments also own the largest farms, generate the highest crop sales revenues, and have the highest amounts of wealth. Farms who fall into the upper part of the size, sales, and wealth distributions are also generally the least vulnerable to adverse shocks in production and market prices (Schurle and Tholstrup 1989;Purdy, Langemeier, and Featherstone 1997;Barry, Escalante, and Bard 2001). While such subsidies aid these producers in overcoming financial challenges during unfavorable periods, it is also likely that a potentially significant proportion of these payments are not required to help farm operations to bridge periods of financial downturns.…”

Section: Analysis Of Policy Changes On Payments Across the Farm Distrmentioning

confidence: 99%

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Does Farm Size Matter? Distribution of Crop Insurance Subsidies and Government Program Payments across U.S. Farms

Bekkerman

Belasco

Smith

2018

Applied Eco Perspectives Pol

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This study uses farm-level information from the ARMS database to evaluate the distribution of payments from major 2014 Farm Bill safety net programs-federal crop insurance, Agricultural Risk Coverage, and Price Loss Coverage-across farm size. Results indicate that farms within the top decile for crop sales receive over two-thirds of the total payments from these programs. Recent legislative proposals to implement payment caps on each farm are shown to impact a relatively small percentage of farms that are almost entirely within the top decile of crop sales. However, implementing these caps is likely to result in as much as $2.51 billion in taxpayer savings. These help provide direction for continued efforts to design cost-effective, equitable agricultural safety net policies.A series of studies over the past sixty years, some of which predate Johnson's call, have consistently found that farm subsidies are directed toward larger-scale commercial farms and relatively high-income households. This pattern has persisted over the past 65 years, notwithstanding the substantial changes that have taken place in the mix of programs through which farms have received federal government support. Taken together, these studies raise substantive questions about the economic equity of the distribution of the benefits of federal farm programs, and whether those programs play a substantive role in sustaining smaller, less financially-secure farms.Bonnen (1968), for example, estimated that in the mid 1960s, regardless of how farm size is measured, the largest 20% of farms received over 50% of federal farm program benefits, while the lowest 40% received less than 15% of such benefits. Two studies in the early 1970s (Schultze 1971;Lidman 1973), using data from the 1964 and 1969 Censuses of Agriculture, reported that the largest 4% to 7% of farms, in terms of value of sales, received over 40% of government support payments but farms in the lowest 41% received only 3% to 7% of those payments. Johnson and Short (1983) found that the largest 1% of farm businesses received approximately 17% of net agricultural program benefits, and the largest 10% of farm businesses received 55% of those benefits. More recent studies (Hopkins

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Section: Discussionmentioning

confidence: 99%

Section: Analysis Of Policy Changes On Payments Across the Farm Distrmentioning

confidence: 99%

Does Farm Size Matter? Distribution of Crop Insurance Subsidies and Government Program Payments across U.S. Farms

Bekkerman

Belasco

Smith

2018

Applied Eco Perspectives Pol

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“…Larger farms may also be more adept at coping with risk either due to greater management ability or to greater access to risk-management strategies ranging from credit reserves to hedging (Velandia et al, 2009;Goddard et al, 1993). However, this ability to cope with risk may induce larger farms to take on greater farm income variance relative to smaller operations and several studies have estimated a positive relationship between size and net farm income volatility (Dunn and Williams, 2000;Schurle and Tholstrup, 1989;Pope and Prescott, 1980). However, Barry et al (2001) and Purdy et al (1997) found that farm size had no effect on the risk/return tradeoff.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

“…Specialization increases risk and therefore variability according to portfolio theory (O'Donoghue et al, 2009). Shurle and Tholstrup (1989) found that both specialization and variance in returns correlates with average net farm income implying movement along the tradeoff curve between mean returns and business risk. However, the empirical evidence on the effect of diversification on farm income variance is mixed.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

“…While income variation remains a focus of public policy programs, the factors affecting its variability are not well-understood. Schurle and Tholstrup (1989) found income variability for Kansas farms to be influenced by factors affecting business risk such as enterprise mix, returns and size. Using an updated sample of the same Kansas farms, Purdy et al (1997) found specialization and business risk position increased the variance of returns on equity.…”

Section: Introductionmentioning

confidence: 99%

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Factors affecting variability in farm and off‐farm income

Poon

Weersink

2011

Agricultural Finance Review

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The purpose of this paper is to examine the factors affecting the relative variability in farm and off-farm income for Canadian farm operators. Previous attempts have been limited by the lack of available data combining both farm and off-farm income levels for farm operations over time. Statistic Canada's Farm Micro-Longtidinal Dataset of 17,000 farm operators from 2001 to 2006 allowed such an analysis. The coefficient of variation (CV) in farm income is significantly greater than that for off-farm income but both measures are inversely related to the permanence of the income source to the operation. The greater the reliance on farm income and the greater the labour demand within the farm, the lower (greater) the relative variability in farm (off-farm) income. Larger commercial operations tend to experience larger farm income volatility either because they are less risk averse and/or have the ability to manage more risk. Diversification and off-farm employment appear to be substitute for risk management strategies for commercial operations. Pension and lifestyle farms have lower coefficient of variation for both farm and offfarm income compared to business-focused farms since they are possibly more risk averse and benefit from a permanent stream of off-farm revenue. Government payments have mixed effects on the relative variability of both income sources, which may be due the lag between the time of the income reduction and the time at which the aid is received. Résumé Cet article examine les facteurs qui influent sur la variabilité relative des revenus agricoles et hors ferme des exploitants agricoles canadiens. Les tentatives précédentes ont été limitées par le manque de données chronologiques combinant les revenus agricoles aux revenus hors ferme des exploitations agricoles. Notre analyse utilise de la banque de données de Statistiques Canada Farm Micro-Longtidinal Dataset qui compile de l'information sur 17000 exploitants agricoles de 2001 à 2006. Le coefficient de variation (CV) du revenu agricole est nettement supérieur à celui du revenu hors ferme, mais les deux mesures sont inversement proportionnelles à la permanence de la source du revenu considéré. Plus grande est la dépendance à l'égard du revenu agricole et plus grande la demande de travail au sein de la ferme, plus faible (grande) sera la variabilité du revenu agricole par rapport au revenu hors ferme. Les grandes exploitations commerciales ont tendance à afficher une plus grande volatilité du revenu agricole, soit parce qu'elles sont moins sensibles au risque et/ou ont une capacité accrue de gestion des risques. La diversification et un emploi hors ferme semblent être des substituts pour des stratégies de gestion des risques pour les fermes commerciales. Les fermes appartenant à un retraité et les fermes d'agrément ont un plus faible coefficient de variation pour les revenus agricoles et non agricoles par rapport aux fermes commerciales possiblement parce que les opérateurs sont plus riscophobes et bénéficient d'un flux permanent de revenus hors fe...

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