The value of preventing a farm fatality in northern ireland
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The Value of Preventing a Farm Fatality in Northern Ireland. C. Cockerill & Prof G. Hutchinson (QUB) Prof S. Chilton (University of Newcastle upon Tyne). Background/Rationale. Agriculture is a significant component of NI economy

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The Value of Preventing a Farm Fatality in Northern Ireland

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The value of preventing a farm fatality in northern ireland

The Value of Preventing a Farm Fatality in Northern Ireland

C. Cockerill & Prof G. Hutchinson (QUB)

Prof S. Chilton (University of Newcastle upon Tyne)


Background rationale

Background/Rationale

  • Agriculture is a significant component of NI economy

  • High occupational fatality rate: 24.1 fatalities/10,000 workers ie. 6/21 occupational fatalities in one year between 2002/3 (HSENI)

  • Valuation is important to ensure costs of policy to reduce risk of accidents are outweighed by the benefits

  • Valuation techniques are well developed

    eg. DETR (UK) adopted value for the prevention of a road fatality from Carthy et al (1999)

  • Previous efforts (Monk et al, 1986 (UK); Tormoehlen & Field, 1995 (US); Low & Griffith, 1996 (Australia)) to calculate a value for farm safety are general deficient.


The value of preventing a farm fatality in northern ireland

Aims

  • To generate a value for reducing the risk of a fatal farm accident to farmers in Northern Ireland

  • To investigate if this estimate is transferable to other accident contexts or if a context premium exists

    This study will provide a prototype that can be applied for all farm accidents types as a means of obtaining a more accurate value for a prevented farm fatality


Methods

Methods

  • Stated preference techniques:

    • Contingent Valuation - Modified Standard Gamble

    • Matching

  • CV-MSG:

    • CV elicits a value for the pain, grief and suffering associated with a non-fatal farm injury

    • MSG elicits a risk-risk trade-off between the pain, grief and suffering associated with a non-fatal injury and chance of recovery of death

    • These results are “chained” to estimate the value of preventing a farm fatality

  • Matching:

    • elicits preference based values for preventing farm fatalities caused by one accident context relative to another accident context

    • asks respondent to state the number of deaths prevented from one type of accident that is equivalent to x deaths prevented from another accident


Advantages of adopted methods

Advantages of Adopted Methods

  • Captures the costs of pain, grief and suffering

  • Does not rely on wage rates (human capital approach) or the purchase of a safety product (revealed preference approach)

  • Avoids difficulty of directly trading off risk of death for wealth, e.g.

    • lack of comprehension of small probabilities associated with fatal risk (Beattie et al, 1998)

  • Provides estimates for different accident contexts without the need to repeat the CV-MSG task, which would be time consuming and potentially result in respondent fatigue.


Survey

Survey

  • Face to face interviews

  • 2 versions of the questionnaire to allow checks for scope insensitivity, sequencing effects, internal consistency

    Table 1: Summary Descriptions of severity associated with non fatal injuries

    (Jones Lee et al, 1985)


Sample

Sample

  • 293 Farms in Northern Ireland

  • Representative of full time, commercial, specialised farms, where farmer, spouse and at least one child under 18 years of age resided on the farm site

  • Farms selected using a 3 stage approach:

    • Geographical clusters of 3-4 electoral wards in each of 12 rural districts (i.e. 2 per county)

    • Farms selected by systematic sampling with proportional allocation in relation to six strata (3 types: Dairy; Cattle & Sheep; Cereal and 2 sizes: 16-40 ESU and 40+ ESU)

    • Farms were then contacted by telephone to ensure that a spouse and child under 18 years resided on the farm site


Results value for preventing a fatality

Results: Value for Preventing a Fatality

Table 4: Estimates for Value of Preventing a Farm Machinery Fatality

Table 5: Lower and Upper bounds for Value of Preventing a Farm Machinery Fatality


Results context effects

Results: Context Effects

Table 6: Mean relativities (VPF1/VPF2)

M = Machinery AccidentF = Fall

L = Livestock AccidentD = Drowning in Slurry


Conclusions

Conclusions

  • Conservative estimate of Machinery VPF is £1.5 – 2.5 million (€2.2 - 3.6 million)

  • Total cost requires addition of direct costs, e.g. medical costs

  • VPF from a road accident was £1 – 1.6 million (Carthy et al, 1999).

  • Why is road fatality valued less than farm fatality?

    • Farmers are less constrained by budget

    • Farmers place a higher value on life and good health

    • Farmers are self-employed

    • Farmers sampled were parents

    • Inflation

  • No significant context premium, therefore the Machinery VPF could be applied to other types of fatal accidents


Questions

Questions?


Calculating a value for preventing a fatality

Calculating a Value for Preventing a Fatality

  • VPF = pop. mean of marginal rates of substitution of wealth for risk of death (md)

  • CV elicits:

    • WTA compensation for sustaining non-fatal injury (upper bound)

    • WTP for treatment which provides a quick recovery (lower bound)

    • mi marginal rate of substitution of wealth for risk of injury, mi is calculated from WTA and WTP for 4 functional forms of utility (Carthy et al, 1999)

  • MSG elicits a trade off between risk of death for risk of injury

    • Offers a choice between 2 treatments with chances of success or failure

    • Treatment 1: Probability of injury i v. Given probability of Death

    • Treatment 2: Probability of normal health v. Probability of Death

    • What is the maximum acceptable probability of death for Treatment 2?

    • This elicits a ratio md/mi (Carthy et al, 1999)

  • These results are chained: md = md/mi * mi (Direct Approach)

  • Indirect Approach: md = md/mX * mX/mF * mF


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