Marketing contract choices in agriculture: The role of price expectation and price risk management

Ricome, Aymeric; Reynaud, Arnaud

doi:10.1111/agec.12675

Cited by 14 publications

(14 citation statements)

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“…, 2019) or the use of hurdle models such as the Tobit model to explore the factors influencing the quantity of product entered into a forward contract (Woolverton and Sykuta, 2009; Franken et al. , 2012; Ricome and Reynaud, 2021). Structural Equation Modelling (SEM) is used in some instances (Giampetri et al.…”

Section: Methodsmentioning

confidence: 99%

The empirical demand for farm insurance in Ireland: a quantile regression approach

Loughrey

Vidyaratne

2023

AFR

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PurposeThe purpose of this paper is to analyse the association between farm/farmer characteristics and unsubsidized farm insurance premium expenditure in Ireland. The distribution of farm insurance expenditures is wide, and it is important to understand the extent to which individual factors influence demand for different levels of insurance premium.Design/methodology/approachThe quantile regression approach and farm accountancy data from the Teagasc National Farm Survey are used to model the association between farm/farmer characteristics and farm insurance demand in Ireland.FindingsAsset values (livestock, buildings and machinery) are positively associated with total insurance expenditure. Both forestry area and crop area are significantly associated with farm insurance expenditure with a stronger influence on the middle and upper part of the distribution. The interaction between farm income and farmer age is positively associated with insurance expenditure pointing to the importance of farm income protection.Research limitations/implicationsThe research is mainly concerned with insuring against substantive risks, which are capable of threatening the asset base and continuation of the farm business. Future research can integrate questions in relation to farm safety and farmer health with research on the economic survival of the farm business.Practical implicationsFarmers in Ireland adopt unsubsidized farm insurance as a risk management tool. This situation is relevant to other EU member states including Belgium, Denmark, Germany and Sweden. The findings can be used to inform stakeholders and policymakers about the relative impact of different factors on insurance expenditure.Originality/valuePrevious research has typically focused on the linear relationship between farm/farmer characteristics and insurance demand without accounting for variability across the size distribution. This research is based on the quantile regression approach where the association between farm/farmer characteristics and farm insurance expenditure can be assessed at different points of the distribution.

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Section: Methodsmentioning

confidence: 99%

The empirical demand for farm insurance in Ireland: a quantile regression approach

Loughrey

Vidyaratne

2023

AFR

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“…Only recently has the importance of taking into account farmers’ expectations when analysing their preferences regarding risk and uncertainty been recognized (Cerroni, 2020; Menapace et al., 2013; Ricome & Reynaud, 2022). Even though consequences of adverse risks are particularly severe in these settings, to date there is still little empirical evidence on the individual‐specific determinants of expectations about uncertain events elicited specifically from decision‐makers in developing countries and/or rural contexts (Attanasio, 2009; Delavande, 2014; Eisele et al., 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Only recently has the importance of taking into account farmers' expectations when analysing their preferences regarding risk and uncertainty been recognized (Cerroni, 2020;Menapace et al, 2013;Ricome & Reynaud, 2022).…”

Section: Expectation Formation Of Farmersmentioning

confidence: 99%

Experience of shocks, household wealth and expectation formation: Evidence from smallholder farmers in Kenya

Freudenreich

Kebede

2022

Agricultural Economics

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When faced with uncertain events, decision-makers form expectations about the events' likelihood of occurrence. However, the drivers and moderators of such expectations are still poorly understood, especially for farm decision-makers in developing countries whose incomes are very risky by nature. This article analyses the dynamic shock expectation formation process of farmers in Kenya with regard to a range of shock events using a unique panel dataset. The results suggest that farmers are more likely to update their expectation regarding a specific adverse shock when they have recently been affected by that shock or by more shocks in general. In case of price shocks, farmers are also more likely to update expectations when a larger proportion of fellow village members was affected. However, household wealth moderates the relationship between shock expectation and experience, such that wealthier households are less likely to update their expectations following a shock. A better understanding of the drivers of expectation formation can help in the design of better risk management instruments that increase farmers' resilience.

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“…Farmers' confidence in agricultural production recovery refers to the psychological state in which farmers are optimistic about agricultural production prospects and believe that agricultural income can be restored to average levels before disasters or shocks [37][38][39]. Risk expectation refers to farmers' subjective assessment and cognition of risk characteristics and disaster impacts in agricultural production [40,41]. According to the risk perception theory, farmers' subjective perception of risk has a specific impact on their behavioral decisions [42].…”

Section: The Impact Of Risk Expectation On Farmers' Confidence In Agricultural Production Recoverymentioning

confidence: 99%

Determinants of Farmers’ Confidence in Agricultural Production Recovery during the Early Phases of the COVID-19 Pandemic in China

et al. 2021

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The COVID-19 pandemic has adversely impacted the agricultural supply chain, export of agricultural products, and overall food security. However, minimal exploration has been attempted of farmers’ confidence in agricultural production recovery after the COVID-19 pandemic. Therefore, this study intends to explore the determinants of farmers’ confidence in agricultural production recovery in China during the early stages of the COVID-19 pandemic. More specifically, we analyzed the relationship between risk expectation and social support on the farmers’ confidence in agricultural production recovery by using the ordered probit model. Cross-sectional survey data were collected from February to March 2020 from 458 farm households in the 7 provinces of China to produce the findings. We found that the risk expectation of farmers had a significant negative impact on farmers’ confidence in agricultural production recovery. Social support seemingly had a significant positive impact on the farmers’ confidence in agricultural production recovery, and could play a supportive role in moderating the relationship between risk expectation and farmers’ confidence in recovery. However, social support alleviates the adverse effect of risk expectation on farmers’ confidence in agricultural production recovery to a certain extent. In addition, there were intergenerational differences in the effects of risk expectation and social support on farmers’ confidence in agricultural production recovery. These results imply that policies establishing the risk early warning mechanisms for agricultural production and strengthening the social support from governments and financial institutions are likely to significantly impact agricultural development in the post-COVID-19 era. The formal and informal risk minimization mechanisms should extend their support to vulnerable sectors such as agribusiness.

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Marketing contract choices in agriculture: The role of price expectation and price risk management

Cited by 14 publications

References 44 publications

The empirical demand for farm insurance in Ireland: a quantile regression approach

The empirical demand for farm insurance in Ireland: a quantile regression approach

Experience of shocks, household wealth and expectation formation: Evidence from smallholder farmers in Kenya

Determinants of Farmers’ Confidence in Agricultural Production Recovery during the Early Phases of the COVID-19 Pandemic in China

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