1 Civil Systems Planning Benefit/Cost Analysis Scott Matthews Courses: and Lecture /6/2002

and Specifics on Saving Lives  Cost-Utility Analysis  Quantity and quality of lives important  Just like discounting, lives are not equal  Back to the developing/developed example  But also: YEARS are not equal  Young lives “more important” than old  Cutting short a year of life for us vs  Cutting short a year of life for 85-year-old  Often look at ‘life years’ rather than ‘lives’ saved.. These values also get discounted

and Economic valuations of life  Miller (n=29) $3 M in 1999 USD, surveyed  Wage risk premium method  WTP for safety measures  Behavioral decisions (e.g. seat belt use)  Foregone future earnings  Contingent valuation

and Contingent Valuation  Analysis method used when there is no observable market  Example: water quality at national parks  Asks questions to population  Is a last resort option!  Called ‘contingent’ since you never really pay  Valuing use non-controversial  Valuing ‘non-use’ VERY controversial

and Example  Asked for valuations of a certain good  Then estimate overall WTP for it - similar to travel time demand functions  Extrapolated to entire population  Assumes random sample!

and Criticisms of CV  Extrapolation of ‘all CV studies’ to average consumer would take over their budget  Normal statistical problems (sampling, non-response, biases, etc.)  Surveying opinions is imprecise  Problems tend to be complicated

and WTP versus WTA  Economics implies that WTP should be equal to ‘willingness to accept’ loss  Turns out people want MUCH MORE in compensation for losing something  WTA is factor of 4-15 higher than WTP!  Also see discrepancy shrink with experience  WTP formats should be used in CVs  Only can compare amongst individuals

and Measuring Lives Saved  Life years (prevented fatalities) not equal  Qualitative and quantitative issue  Need to consider tradeoffs  Simple example from text  Status quo: no newborns survive a condition  Alt. A: 5 live, but with permanent disability  Alt. B: 2 live, but with low levels of disability  Which option (SQ, A, B) is preferable?  Assume Y increasing, H increasing

and Simple Example

and The Quality/Quantity Game  Assume “preference” for  Increased number of years lived  Increased level of health  Would your preferences be the same?  If so, SQ “dominated” by A and B  But which of A or B is better?  We all understand difference in years  Come up with an index of health status

and Health Status Index Death 0 Severely Disabled Minimally Disabled HealthModerately Disabled  Derived from asking experts  But this says nothing about tradeoff!  Can perform tradeoff survey  Value of “shorter Y, higher H” vs. opposite

and Methods  Health Rating method (see above)  Time tradeoff method  Standard gamble method  Discounting life years

and Risk Analysis  Study of the interactions between decision making, judgment, and nature  Evidence : cost-effectiveness of risk reduction opportunities varied widely - orders of magnitude  Economic efficiency problems

and Cost-Effectiveness of Life-Saving Interventions  From “500 Life-saving Interventions and Their Cost-Effectiveness”, Risk Analysis, Vol. 15, No. 3,  ‘References’ (eg #1127) are all other studies  Model:  Estimate costs of intervention vs. a baseline  Discount all costs  Estimate lives and life-years saved  Discount life years saved  CE = C I -C B /E I -E B

and Specific (Sample) Example  From p Ref no  Rear outboard lap/shoulder belts in all (vs. 96%) of cars  Intervention: require all cars made after 9/1/90 to have belts - 96% already had them  Thus costs only apply to remaining 4% of cars  Target population: occupants over age 4  Others would be in child safety seats  What would costs be?

and Example (cont)  1986 Costs (from study): $6 cost per seat  Plus added fuel costs (due to increased weight) = total $791,000 over life of cars  Effectiveness: expect 23 lives saved during 8.4 year lifetime of cars  But 95.8% already exist, thus only lives  Or lives per year (of use of car)  But these lives saved do not occur all in year 0 - they are spread out over 8.4 years. We thus need to discount the effectiveness of lives saved per year into ‘year 0’ lives..

and Cost per life saved  With a 5% discount rate, the ‘present value’ of lives for 9 years =  This is basically an annuity factor  So cost/life saved = $791,000/0.817  Or $967,700 per life (in “$1986/1986 lives”)  Using CPI: 145.8/ > $1,287,326 in $1993  But this tells us only the cost per life saved  We realistically care more about quality of life, which suggests using a quality index, e.g. life- years saved.

and Cost per life-year saved  Assume average age of fatality in car accident was 35 years  Life expectancy tables suggest a 35 year old person would on average live to age 77  Thus ‘42’ life years saved per fatality avoided  1 life year for years  $1993 cost/life-year = $1,287,326/17.42  2 sig. figures: ~$74,000 as in paper

and Overall Results  Some had $10B  Median $42k per life year saved  Some policies implemented, some only studied  Variation of 11 orders of magnitude!  Some maximums - $20 billion for benzene emissions control at tire factories  $100 billion for chloroform standards at paper mills

and Comparisons

and Agency Comparisons  $1993 Costs per life year saved for agencies:  FAA (Aviation): $23,000  CPSC (Consumer Products): $68,000  NHTSA (Highways): $78,000  OSHA (Worker Safety): $88,000  EPA (Environment): $7,600,000!  Are there underlying causes for range? Hint: are we comparing apples and oranges?