Farm Level Analysis of Risk and Risk Management Strategies and Policies

Kimura, Shingo; Thi, Christine Le

doi:10.1787/5kg6z83f0s34-en

Cited by 7 publications

(8 citation statements)

References 8 publications

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“…Similarly, the majority of observations shows negative price and yield correlations except for wheat in Brazil. This is consistent with the findings in OECD countries (Kimura et al 2011). The majority of producers benefit from the natural hedging effect of negative price and yield correlations.…”

Section: -Smallholder Risk Management In Developing Countries Oecd Fosupporting

confidence: 92%

“…The method applied in previous OECD reports on risk management requires at least five years of longitudinal data (Kimura and Le Thi 2011). Representative panel data (data following the same households over time) is relatively rare in developing countries.…”

Section: Risk Assessment Using Short Panel Datamentioning

confidence: 99%

“…However, data on consumption and farm household size are not available, thus limiting the scope of risk assessment to agricultural production and farm household income. The methodology as described in Kimura and Le Thi (2011) is applied to assess farm-level risk exposure: the structural trends in yield and income growth were first removed from the longitudinal database, and the risks were measured by individual farm households in term of coefficients of variation and correlation of risk variables.…”

mentioning

confidence: 99%

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Smallholder Risk Management in Developing Countries

Cervantes-Godoy

Kimura

Antón

2013

OECD Food, Agriculture and Fisheries Papers

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Section: -Smallholder Risk Management In Developing Countries Oecd Fosupporting

confidence: 92%

Section: Risk Assessment Using Short Panel Datamentioning

confidence: 99%

mentioning

confidence: 99%

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Smallholder Risk Management in Developing Countries

Cervantes-Godoy

Kimura

Antón

2013

OECD Food, Agriculture and Fisheries Papers

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“…Climatology of rainfall in Australia and crop yield Nix (1975) drew attention to the relative importance of rainfall as a climatic constraint in Australian grain production compared with cold temperatures in North America, Europe and Asia and high temperatures and high humidity in India. Australian grain farmers thus face a higher production volatility than most other grain-exporting countries (Kimura and Le Thi 2011). According to Podbury et al (1998), the coefficient of variation of de-trended Australian wheat yield from 1960 to 1997 was 19%, compared with 7% for the USA.…”

Section: Wheat In Winter-rainfall Environmentsmentioning

confidence: 99%

Interactions between water and nitrogen in Australian cropping systems: physiological, agronomic, economic, breeding and modelling perspectives

et al. 2016

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This paper reviews the interactions between water and nitrogen from physiological, agronomic, economic, breeding and modelling perspectives. Our primary focus is wheat; we consider forage crops, sorghum and legumes where relevant aspects of water-nitrogen interactions have been advanced.From a physiological perspective, we ask: How does nitrogen deficit influence the water economy of the crop? How does water deficit influence the nitrogen economy of the crop? How do combined water and nitrogen deficit affect crop growth and yield? We emphasise synergies, and the nitrogen-driven trade-off between the efficiency in the use of water and nitrogen. The concept of nitrogen-water co-limitation is discussed briefly.From agronomic and economic perspectives, the need to match supply of nitrogen and water is recognised, but this remains a challenge in dryland systems with uncertain rainfall. Under-fertilisation commonly causes gaps between actual and water-limited potential yield. We discuss risk aversion and the role of seasonal rainfall forecasts to manage risk.From a breeding perspective, we ask how selection for yield has changed crop traits relating to water and nitrogen. Changes in nitrogen traits are more common and profound than changes in water-related traits. Comparison of shifts in the wheat phenotype in Australia, UK, Argentina and Italy suggests that improving yield per unit nitrogen uptake is straightforward; it requires selection for yield and allowing grain protein concentration to drift unchecked. A more interesting proposition is to increase nitrogen uptake to match yield gains and conserve protein in grain. Increased stomatal conductance is a conspicuous response to selection for yield which partially conflicts with the perception that reduced conductance at high vapour pressure deficit is required to increase water-use efficiency; but high stomatal conductance at high vapour pressure deficit may be adaptive for thermal stress.From a modelling perspective, water and nitrogen are linked in multiple ways. In crops where water limits growth, reduced biomass reduces nitrogen demand. Reciprocally, nitrogen limitation during crop expansion reduces leaf area index and increases the soil evaporation : transpiration ratio. Water-nitrogen interactions are also captured in the waterdriven uptake of nitrogen by mass flow and diffusion and in the water-driven processes of nitrogen in soil (e.g. mineralisation).The paper concludes with suggestions for future research on water-nitrogen interactions.

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“…Shalloo et al (2004), Finneran et al (2011) and Clancy et al (2012) but none of these deal with the main grain crops. We develop a stochastic microsimulation model for the risk associated with uncertain prices and yields in the production of Spring Barley, the most commonly produced crop on Irish tillage farms (Holden et al 2003;Kennedy and Connery 2005).…”

Section: Introductionmentioning

confidence: 99%

A Microsimulation Model for Risk in Irish Tillage Farming

Loughrey¹,

Thorne²

2015

IJM

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Tillage farmers must manage numerous economic risks including uncertain yields and prices. Despite the presence of government payments, these factors can generate a relatively high variability in farm income. The improved management of farm income variability can contribute towards stability in household consumption, support for farm investments, further investment in child education and a reduction in the mental stress associated with variable incomes. In this paper, we develop a new farm-level stochastic microsimulation model to simulate the degree of risk attached to the production of Ireland's main tillage grain crop i.e. spring barley for animal feed usage. Forward contracting is the main available risk management tool for Irish tillage farmers. Our microsimulation model is extended in order to estimate the impact of forward contracting on farm income risk. Our results show that forward contracting can reduce farm income risk significantly but that other stable sources of income are probably necessary to contain the exposure to the income risk attached to cereal production. The model is capable of addressing the income risk associated

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Farm Level Analysis of Risk and Risk Management Strategies and Policies

Cited by 7 publications

References 8 publications

Smallholder Risk Management in Developing Countries

Smallholder Risk Management in Developing Countries

Interactions between water and nitrogen in Australian cropping systems: physiological, agronomic, economic, breeding and modelling perspectives

A Microsimulation Model for Risk in Irish Tillage Farming

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