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

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.
slide3
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 Accident F = Fall

L = Livestock Accident D = 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
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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