Regulation and the financial performance of Canadian agribusinesses

Schaufele, Brandon; Sparling, David

doi:10.1108/00021461111152573

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…This wealth effect of government policy suggests the impact of a support program on farm income volatility is indeterminate. Schaufele and Sparling (2011) looked at the effect of government regulation announcements rather than funding levels and found that the regulatory changes did not correspond to abnormal stock market valuations for Canadian agribusinesses.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

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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Section: Conceptual Frameworkmentioning

confidence: 99%

Factors affecting variability in farm and off‐farm income

Poon

Weersink

2011

Agricultural Finance Review

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“…an event). These price changes manifest through abnormal stock returns as a reflection of inherent changes in private revenue and cost changes by the affected firms (Pozo and Schroeder, 2016; Pruitt and Peterson, 1986; Salin and Hooker, 2001; Schaufele and Sparling, 2011) to the extent that the particular event is unanticipated by investors (Brown and Warner, 1980).…”

Section: Introductionmentioning

confidence: 99%

Agribusiness value impacts from highly pathogenic avian influenza

Thompson

Trejo‐Pech

Pendell

2019

AFR

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Purpose The purpose of this paper is to determine the impact of 2014–2015 highly pathogenic avian influenza (HPAI), the largest animal health emergency in US history to date, on agribusinesses’ market values. Design/methodology/approach Using the 2014–2015 HPAI outbreaks in US commercial poultry, event study analysis of meat processing and marketing companies is conducted to estimate the effects HPAI had on firm value and how these effects differed across meat marketing firms over distinct disease event dates. The analyses include an overall aggregate event study, chronological outbreak studies, and an analysis that separated firms specifically marketing poultry products from those marketing all other types of meat. Findings By tracing abnormal stock returns through the event dates, the results show heterogeneity of investors responses based on the nature of the event (i.e. backyard vs commercial flocks affected), timing of the event over the course of the entire HPAI outbreak, and if a firm marketed poultry products. Overall, negative abnormal returns, ranging from 2 to 4 percent of publicly traded meat processors’ equities, are predominant post-disease event. These negative effects are slightly higher, above 5 percent, for firms marketing poultry products. Originality/value This study is the first to analyze the effects of an HPAI outbreak on the market value of US agribusiness firms.

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“…The potential difficulty associated with date choice is evidenced by a study of the Canadian stock market in which it was found that official regulatory announcements in the agribusiness sector in Canada do not move stock prices. Similar effects associated with official dates and announcements may exist in the US agribusiness sector (Schaufele and Sparling, 2011). For the long-window analysis the CAPM model was applied in a similar fashion using monthly return data, rather than daily return data, and the model was estimated using 36 months of monthly data ending 4 months before the first event.…”

Section: Methodsmentioning

confidence: 99%

The impact of the Food Safety and Modernization Act on firm value

Johnson

Lawson

2016

Agricultural Finance Review

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to determine the impact of the passage and signing of P.L. 111-353, the Food Safety Modernization Act (FSMA), on the market value of agribusiness firms. Design/methodology/approach -The authors conduct an event study of the shareholder value effects of FSMA. The short-window analyses estimate the three-, five-, and seven-day market responses to three key event dates: passage by the House, passage by the Senate, and the signing of FSMA by President Obama. The long-window analyses examine a time period that encompasses the three informational events, as well as the 30 months after the signing of FSMA. To control for the effects of market-wide fluctuations, the authors use two alternative models of the returns generating process to calculate abnormal returns, the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model. Findings -The short-window analyses show no evidence of a significant reaction to the passage of FSMA by the House or the Senate, but evidence of a significant negative reaction to the signing of FSMA by President Obama. The long window results which span the of passage by House, passage by the Senate and signing by the President indicate a decline in the average market value of agribusiness firms on the order of -10 percent over the period. Additionally, the authors find some evidence that this effect is not evenly spread out across different types of agribusiness firms (wholesale, grocery, and processing). Originality/value -The study is the first to examine the impact of P.L.111-353 on the market value of agribusiness firms.

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Regulation and the financial performance of Canadian agribusinesses

Cited by 5 publications

References 10 publications

Factors affecting variability in farm and off‐farm income

Factors affecting variability in farm and off‐farm income

Agribusiness value impacts from highly pathogenic avian influenza

The impact of the Food Safety and Modernization Act on firm value

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