Title: Lecture Notes
1Lecture Notes ECON 437/837 ECONOMIC
COST-BENEFIT ANALYSIS Lecture Twelve
2RISK ANALYSIS AND MANAGEMENT
3Decision-Making Under Uncertainty
- What is risk?
- Risk generally describes the possible deviation
from a project outcome. - To project any uncertain outcome into the future,
you need to have a predictive model, which
could be a simple formula or a very complex
worksheet. - Risk analysis
- How to identify, analyze, and interpret the
expected variability in project outcomes - Risk diversification and management
- How to diversify unsystematic risk
- How to redesign and reorganize projects in order
to reallocate risk
4Risk Analysis
- 1. WHY?
- Project returns are spread over time
- Each variable affecting NPV is subject to a high
level of uncertainty - Information and data needed for more accurate
forecasts are costly to acquire - Need to reduce the likelihood of undertaking a
"bad" project while not failing to accept a
"good" project
5Deterministic or Base Case
- Inputs are projected as certainties.
- By that we assign 100 probability that the
single value of the input we use in the
projection will actually arise. - However, any deviation in any of the critical
input variables from the base case values will
generate a new scenario with a different outcome. - There are potentially an infinite number of
combinations of input values possible, each
causing a different set of results.
6Alternative Methods of Dealing with Risk
- Sensitivity Analysis
- Scenario Analysis
- Monte Carlo Risk Analysis
- (or Simulation Analysis)
7Sensitivity Analysis
- Test the sensitivity of a project's outcome (NPV
or the key variable) to changes in value of one
parameter at a time - - "What if" analysis
- - Allows you to test which variables are
important as a source of risk - A variable is important depending on
- - Its share of total benefits or costs
- - Likely range of values
- Sensitivity analysis allows you to determine the
direction of change in the NPV. - Break-even analysis allows you to determine how
much a variable must change before the NPV or
these key variable moves into its critical range
turns negative.
8Another Important Use of Sensitivity Analysis
- Sensitivity analysis on the PV of each row of the
spreadsheet (Bankers, Owners and Economys
point of view) is the best way to de-bug a
spreadsheet. - If results do not make sense, it is likely that
there is an computation or logistical error in
the spreadsheet.
9Sensitivity Analysis for the Mindanao Poverty
Reduction Case-- Tomato Paste in the Philippines
--
- Inflation
- Rate
- 5
- 8
- 11
- 14
- 17
- 20
- 23
- 26
- 29
- 32
- 35
- Capacity
- Utilization
- Factor
- 60
- 65
- 70
Real NPV (Million Pesos) 161 147 136 126 118 111
105 99 94 89 84 Real NPV (Million
Pesos) -189 -147 -105 -63 -21 21 63 105 147 189 2
31
World T.P. Price (S.F. FOB) US/Ton 587 637 687 73
7 787 837 887 937 987 1037 1087 Divergence
from Original Cost Estimate -10 -5 0 5 10 15
20 25 30 35 40
Real NPV (Million Pesos) -228 -103 22 147 272 397
522 647 772 897 1022 Real NPV (Million
Pesos) 190 169 147 125 103 82 60 38 17 -5 -27
10Tomato Paste (contd)
- For Tomato Paste Plant Capacity Utilization is
critical. - What can cause Capacity Utilization to be low?
- Technical problems with the plant.
- The demand for product does not exist at the
price that covers the costs. - The plant can not get adequate supplies of raw
materials. - Fact sheet
- this plant eventually run into financial troubles
- could not attain adequate supplies of raw
materials
11Cautionary Notes for Sensitivity Analysis
- 1. Range and probability distribution of
variables - Sensitivity analysis doesn't represent the
possible range of values - Sensitivity analysis doesn't represent the
probabilities for each range. Generally there is
a small probability of being at the extremes. - 2. Direction of effects
- For most variables, the direction is obvious
- a) Revenue increases NPV increases
- b) Cost increases NPV decreases
- c) Inflation Not so obvious
12Cautionary Notes for Sensitivity Analysis (contd)
- 3. One-at-a-Time Testing is Not Realistic
- One-at-a-time testing is not realistic because of
correlation among variables - a) If Q sold increases, costs will increase.
- Profits Q (P - UC)
- b) If inflation rate changes, all prices change.
- c) If exchange rate changes, all tradable goods'
prices and foreign liabilities change. - One method of dealing with these combined or
correlated effects is scenario analysis.
13Scenario Analysis
- Scenario analysis recognizes that certain
variables are interrelated. Thus, a small number
of variables can be altered in a consistent
manner at the same time. - What is the set of circumstances that are likely
to combine to produce different "cases" or
"scenarios"? - a) Worst case / Pessimistic case
- b) Expected case / Best estimate case
- c) Best case / Optimistic case
- Note Scenario analysis does not take into
account the probability of cases arising - Interpretation is easy when results are robust
- a) Accept project if NPV gt 0 even in the worst
case - b) Reject project if NPV lt 0 even in the best
case - c) If NPV is positive in some cases and
negative in other cases, then results are not
conclusive.
14Monte Carlo Method of Risk Analysis
- A natural extension of sensitivity and scenario
analysis is a Monte Carlo analysis - Simultaneously takes into account different
probability distributions and different ranges of
possible values for key project variables - Allows for correlation between variables
- Generates a probability distribution of project
outcomes (NPV) instead of just a single value
estimate - The probability distribution of project outcomes
may assist decision-makers in making choices, but
there can be problems of interpretation and use.
15Steps in Building a Monte Carlo Simulation
- 1. Project evaluation spreadsheet for
deterministic case - 2. Identify variables which are sensitive and
uncertain - 3. Define uncertainty
- Establish a range of options (minimum and
maximum) - Allocate probability distribution
- Normal distribution
- Triangular distribution
- Uniform distribution
- Step distribution
- 4. Identify and define correlated variables
- Positive or negative correlation
- Strength of correlation
- 5. Simulate model
- 6. Analysis of results
- Statistics
- Distributions
16Sensitivity Analysis
17Deterministic vs Simulation Analysis
18Foundations of Risk Analysis Probability
Distributions (under 3 Symmetrical Distributions)
19Correlated Variables
20Simulation Runs
21Results of Simulation Analysis
- Statistics
- Expected Value of Outcome
- Standard Deviation and Variance
- Range Minimum and Maximum Values
- Coefficient of Variability
- Distribution of Outcome
- Generate the potential outcomes with their
likelihood of occurrence
22Distribution of results (net cash flow)
23Case 1 Probability of negative NPV0
24Case 2 Probability of positive NPV0
25Case 3 Probability of zero NPV greater than 0
and less than 1
26Case 4 Mutually exclusive projects(given the
same probability, one project always shows a
higher return)
Case 4 Non-intersecting cumulative probability
distributions of project return for mutually
exclusive projects
27Case 5 Mutually exclusive projects (high return
vs. low loss)
Case 5 Intersecting cumulative probability
distributions of project return for mutually
exclusive projects
28Cost of Uncertainty
29Expected Loss RatiosExample of project
outcomes expected value of project
Expected value of losses
Expected value of gains
30Expected Loss Ratios (contd)
31Risk under Conditions of Limited Liability
32Advantages of Risk Analysis
- Highlights project areas that need further
investigation and guides the collection of
information - Aids the reformation of projects to suit the
requirements of the investors - Bridges the communication gap between the analyst
and the decision maker - Provides the information to facilitate a more
efficient allocation and management of risk among
various parties involved in a project
33Steps to Undertake Risk Analysis
- 1. Complete the financial and economic analysis
of project -- Deterministic Case - 2. Identify Risk Parameters, which are
sensitive and uncertain - 3. Choose a Probability Distribution and
Correlations for risk variables. - 4. Identify Risk Forecasts such as NPVs, Debt
Services Ratios - 5. Run a Risk Simulation, using Crystal Ball
Software. - 6. Prepare a Risk Report a summary of the risk
assumptions and the final results of the
simulation. - 7. Interpret and Analyze Results.
34Crystal Ball implements Monte Carlo Simulation in
three steps
- For every assumption cell, Crystal Ball generates
number according to the probability distribution
you defined in places into spreadsheets. - Crystal Ball commands the spreadsheets to
recalculate itself. - Crystal Ball then retrieves a value from every
forecast cell and adds it to the graph in the
forecast windows.
35Risk Management
- Problem
- Many projects have
- large investment outlays
- long periods of project payout
- incomplete sharing of information and technology,
especially with foreign investors - differences in the ability of the parties to bear
risks - unstable contracts
- Projects may be attractive in aggregate but are
unattractive to one or more parties due to
uncertainties about sharing risks and returns - The result is that attractive projects are not
being undertaken
36Principles of Contracting, Risk Sharing and Risk
Reduction
- Case A
- A Cement Additives Plant
- in Indonesia
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38Cash Flows Total Investment Perspectives
39Cash Flows Equity Holders Perspective
40Sensitivity Analysis for Cement Additives Plant
(Quick Fix)
41Risk Analysis
Evaluation of a Cement Additives Plant Risk
Variables, and Probability Distribution
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43Risk ReallocationSources of Contracting Benefits
- Risk Shifting
- Differing risk preferences. e.g., less risk
averse investor willing to accept a lower return
on a risky asset - Differing capacity to diversify. e.g., foreign
investors may be able to diversify risk in more
efficient capital markets - Differing outlooks or predictions of future.
e.g., some investors are more tolerant and some
are more optimistic - Risk Management
- Differing ability to influence project outcomes
44Risk Shifting
- The following options are available
- Contracts that limit the range of values of a
particular cash flow item, or of net cash flow. - For example, a purchaser may agree to purchase a
minimum quantity or to pay a minimum price in
order to be sure of delivery these measures
would put a lower bound on the sales revenue. - Similar measures would include
- limited liability
- a limited product price range
- a fixed price growth path
- an undertaking to pay a long-run average price
- specific price escalator clauses that would
maintain the competitiveness of the product,
e.g. indexing price to the price of a
close substitute
45Censored DistributionCase of a floor price, Pf
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47 Restructuring Intra-project Correlations
- Risk-sharing contracts that reduce the risk borne
by investors by increasing the correlation
between sales revenue and some cost items, e.g., - profit sharing contract with labor
- bonds with interest rates indexed to the
products sales price - Risk-sharing contracts that decrease the
correlation between benefit items or
alternatively between cost items.
48- Restructuring Intra-Project Correlations (contd)
- The benefits from restructuring correlations are
based on the formula for the variance of the sum
of two random variables (x and y) - v (ax by) a2v (x) b2v (y) 2ab cov (x,y)
- where a and b are parameters or constants.
- For example, let
- x revenues (R) y costs (C) and a
1, b -1 - v(net profit) v(R-C) v(R) v(C) - 2
cov(R,C) - Any measure that will increase the positive
correlation between R and C will increase
cov(R,C) and reduce the variance of the net
profit (provided, of course, that the measure
does not increase the variance of a cost item by
more than twice the cov)
49- Example A Profit-Sharing Agreement
- Assume that wages are the only cost
- Without the agreement total cost C
- With the agreement
- Let g proportion of the costs that is still
paid to workers - as a wage,
- h labors share of profit after wages
have been paid. - Thus, total cost gC h(R - gC)
- Net profit R - gC - h(R - gC)
- (1-h)R - g(1 - h)C
- v(net profit) (1-h)2v(R) g2(1-h)2v(C) -
2g(1-h)2cov(R,C) - If 0lt g lt 1 and 0lt h lt 1, then the variance of
net profit will be - lower than it was without the agreement.
50Expected Value of NPV 23.72 Standard Deviation
34.53 Expected loss from accepting
2.82 Expected loss from rejecting 26.53
Re Quickfix Project - contract with supplier
that establishes a cost ceiling of 12 -
correlated initial selling price (po) and unit
cost (Co) such that 18ltPolt20 and correlation
between Co Po 0.6
51Re Quickfix Project - cost ceiling of
12 -contract for selling price linked to initial
costs (Co) If Co lt 9, Po 16 otherwise Po 20
Expected Value of NPV 48.73 Standard Deviation
28.24 Expected loss from accepting
0.09 Expected loss from rejecting 48.82
52Principles of Contracting, Risk Sharing and Risk
Reduction
- Case B
- Mexican Cheese Operation
53Mexican Cheese Operation Queso OAXACA Inc.
- Project to build cheese processing plant in
Mexico. - Product sold 70 percent in the U.S. and 30
percent in Mexico - Investment of 2.0 million pesos, financed by 23
equity and 77 debt - Initially loans and equity all from Mexican
sources - Investment during first year, operations for a
ten-year period. - No imported inputs
54QUESO OXACA Inc.
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57Sensitivity Analysis
58QUESO OAXACA Inc. Risk Variables Report
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63Risk Analysis Results
DETERMINISTIC NPV (in 000 Pesos) 1,461
64Management and Alleviation of other Project Risks
- A. Pre-Completion Risks
-
- Examples of Ways to Reduce or Shift
- Types of Risks Risk Away from Financial
Institution - Participant Risks
- - Sponsor commitment to project - Reduce
magnitude of investment - - Require Lower Debt/Equity ratio - Finance
investment through equity and - then by debt
- - Financially weak sponsor - Attain third party
credit support for weak sponsor (e.g., letter of
credit) - - Cross default to other sponsors
- Construction/Design defects - Experienced
Contractor - - Turn key construction contract
65Management and Alleviation of Risks
- A. Pre-Completion Risks (contd)
-
- Examples of Ways to Reduce or Shift
- Types of Risks Risk Away from Financial
Institution - Process failure - Process / Equipment warranties
-
- Completion Risks
- Cost overruns - Pre-agreed overrun funding
- - Fixed (real) price contract
- Project not completed - Completion guarantee
- - Tests mechanical/financial for
completion - Project does not attain - Assumption
of debt by sponsors if mechanical efficiency
not completed satisfactorily
66B. Post-Completion Risks
-
- Examples of Ways to Reduce or shift
- Types of Risks Risk Away from Financial
Institution - Natural Resource/Raw Material
- Availability of raw materials - Independent
reserve certification - - Example Mining Projects reserves twice
planned mining volume - - Firm supply contracts
- - Ready spot market
- Production/Operating Risks
- Operating difficulty leads to - Proven
technology - insufficient cash flow - Experienced
operator/management team - - Performance warranties on equipments
- - Insurance to guarantee minimum cash
-
67B. Post-Completion Risks (contd)
- Examples of Ways to Reduce or Shift
- Types of Risks Risk Away from Financial
Institution - Market Risk
- Volume cannot sell entire output - Long term
contract with creditworthy buyers take-or-pay
take-and-pay - Price cannot sell output at profit - Minimum
volume/floor price provisions - Price
escalation provisions - Force Majeure Risks
- Strikes, floods, earthquakes, etc. - Insurance
- - Debt service reserve fund
68- Examples of Ways to Reduce or shift
- Types of Risks Risk Away from Financial
Institution - Political Risk
- Covers range of issues from - Host govt.
political risk assurances nationalization/expropri
ation, - Assumption of debtchanges in tax and
other laws, - Official insurance e.g., EXIM - currency inconvertibility, etc. - Private
insurance e.g., LLOYDS - - Offshore Escrow Accounts
- Abandonment Risk
- Sponsors walk away from project - Abandonment
test in agreement for - banks to run project
-
- Other Risks Not really project risks
- but may include
- Syndication risk - Secure strong lead financial
institution - Currency risk - Currency swaps / hedges
- Interest rate exposure - Interest rate swaps
- Rigid debt service - Built-in flexibility in
debt service - obligations
69Evaluation of Regulations
- Example
- Cost-Benefit Analysis of Reductions of the
Sulphur Level in Gasoline in Canada
70Regulatory Policy
- In November 1999, the Government of Canada
instituted the policy that a cost-benefit
analysis must be carried out for all significant
regulatory proposals to assess their potential
impacts on the environment, workers, business,
consumers, and other sectors of society. - In 2006, all regulatory departments and agencies
are expected to show that the recommended option
maximizes the benefits in relation to costs and
yields greater net benefits over time than any
other type of regulatory or non-regulatory
action. -
- Other countries and international communities
such as the United States, Australia, European
Commission, etc. have also come to recommend that
a cost-benefit analysis is the centre of
regulatory analysis.
71Identification of Policy Issues
- In 1997, the sulphur content of Canadian gasoline
and diesel fuels varied widely across the
country. - Fuels with high sulphur levels affect tailpipe
emissions of motor vehicles and contribute to air
pollution. - Emissions of pollutants from vehicles cause harm
to the health of Canadians and to the
environment. - High sulphur fuels hinder the development of more
fuel efficient motor vehicles needed for the
future control of greenhouse gas emissions.
72Setting Objectives
- Development of alternative regulatory and
non-regulatory policy options to reduce
concentration of sulphur in motor fuels - - Non-regulatory options include use of economic
instruments, i.e., taxes. (Economic instruments
not suitable because of difficulty of having a
national tax policy on motor fuels) - - Regulatory options in terms of the level of
sulphur concentration. - Cost-benefit analysis is a tool to assess the
benefits and costs of alternative options.
73Development of Alternative Scenarios
- The alternative scenarios and the base case are
developed on the basis of the sulphur reductions
in gasoline and diesel fuels that would come into
effect on January 1, 2001. - The base case is established with the maximum
level of sulphur maintained at 410 ppm over the
period from 2001 to 2020. - Six alternative scenarios are related to the
reduction of sulphur in gasoline and three
options are associated with the reduction of
sulphur in diesel fuels. - General rules All scenarios are required to have
a maximum annual level of sulphur in gasoline or
diesel fuels and the level of sulphur at any
point in time must never exceed a specified level
of sulphur.
74Approaches to Measure the Benefits and Costs of
Alternative Scenarios
- Two alternative approaches
- - first, estimate both the gross annual benefits
and costs of alternative scenarios and the base
case - - second, estimate the incremental annual
benefits and costs of alternative options in
excess of the baseline scenario. - Principle for measuring the economic benefits is
WTP while for measuring the economic costs it is
the opportunity cost of the resources used.
75Measurement of Economic Costs
- Compliance costs by the private sector
- - 17 refineries produce fuels in Canada
- - Each refinery employs different strategies to
meet the specification of each scenario - - Capital costs reflect changes in facilities
required by refineries to meet the regulation set
by each scenario - - Annual operating costs are increased to
operate the facilities with lower levels of
sulphur. - Administrative costs by governments to enforce
the regulations. - Additional social costs are accounted for as a
result of refinery closure.
76Measurement of Economic Benefits
- Using an atmospheric model, the change in
sulphate concentration is estimated brought about
by changes in the level of sulphur in gasoline
and diesel fuels for each of seven cities. - Using the benefit transfer approach,
- - take the estimates from related research of
the impact on human health and then adjust to
reflect the circumstances of the situation in
Canada - - assign probability weights for low, central
and high estimates to account for uncertainty. - Measure the impact on health and environment in
monetary value.
77Sulphate Concentration Reductions for Selected
Scenarios in Years 2001 and 2020 (µg/m3)
- Scenario 4 (150 ppm)
- 2001 2020
- - Halifax 0.08 0.09
- - Toronto 0.25 0.30
- - Vancouver 0.04 0.05
- Scenario 6 (30 ppm)
- 2001 2020
- - Halifax 0.11 0.13
- - Toronto 0.31 0.38
- - Vancouver 0.08 0.11
- Scenario 7 (400 ppm)
- 2001 2020
- - Halifax 0.15 0.20
- - Toronto 0.15 0.18
- - Vancouver 0.12 0.16
78Estimated Health Responses for a 1 µg/m3 Change
in Sulphate Concentration
- Mortality
- Range Weights
- - Low 1.14x10-5 22
- - Central 2.54x10-5 67
- - High 5.70x10-5 11
-
- Morbidity
- Chronic Respiratory Risk
- Range Weights
- - Low 7.06x10-5 25
- - Central 1.35x10-4 50
- - High 2.00x10-4 25
- Respiratory Hospital admissions
- Range Weights
- - Low 1.30x10-5 25
- - Central 1.60x10-5 50
- - High 1.80x10-5 25
79Total Reductions of Yearly Health Effects for
Scenario 6
-
- 2001 2010 2020
- Premature Mortality 84 103
129 - Morbidity Effects
- - Chronic Respiratory Disease 302 372
469 - - Respiratory Hospital Admissions 52
65 82 - - Cardiac Hospital Admissions 43 53
66 - - Emergency Room Visits 270 333
420 - - Asthma Symptom Days 131,402 161,680
203,570 - - Restricted Activity Days 63,721
78,392 98,686 - - Acute Respiratory Symptoms
438,197 538,961 678,317 - - Child Lower Respiratory Illness 3,683
4,553 5,764
80Health Effects in Monetary Values
- Principles for measuring the benefits is WTP. If
WTP estimates are not available, cost-of-illness
estimates are used and adjusted upward to reflect
the economic benefits. - Central Value per Case
- (1994 prices)
- Mortality (Age-weighted average) 4m
- Morbidity Effects
- - Chronic Respiratory Disease 291k
- - Respiratory Hospital Admissions 65,000
- - Cardiac Hospital Admissions 8,300
- - Emergency Room Visits 600
- - Asthma Symptom Days 49
- - Restricted Activity Days
74 - - Acute Respiratory Symptoms 14
- - Child Lower Respiratory Illness 360
81Measurement of Gross Health Benefits
- The size of benefits is directly related to the
reductions of the sulphur content of fuels - - for the most stringent scenarios, the health
benefits accrue to individuals across the
country - - for the less stringent cases, only the areas
with high sulphur at the present time are
affected. - The benefits generated from avoiding premature
mortality risks account for more than
three-quarters of the total benefits.
82Measurement of Net Economic Benefits (a)
- The net benefits are derived from the gross
economic benefits minus the incremental economic
costs. - E.g., for scenario 6, the amounts of benefits and
costs are expressed in millions of 2000
prices NPV _at_7 - Gross Economic Benefits 6,127.37
- Economic Costs
- - Compliance Costs 3,307.66
- - Administrative Costs Federal 0.64
- Provincial (14.12)
- - Closure of Refineries 19.29
- Net Economic Benefits 2,813.90
83Net Health Benefits for Canada (b)
- Using the 7 discount rate, the NPV of net
economic benefits are positive for scenarios 1 to
7 while scenarios 8 and 9 would result in a
negative net benefit. - Some omissions and uncertainties should be noted,
e.g., - - pollutants other than sulphate may have
independent health effects - - the impact of the long-range transport of air
pollution is not accounted for - - the impacts on agriculture, forest, and
fishing are not quantified.
84NPV of Net Economic Benefits for Alternative
Scenarios (millions of dollars in 2000 prices)
- Max. Never NPV Annual
to _at_7 Average Exceed (ppm)
(ppm) - Gasoline - Scenario 1 360 420 1,985.8
- - Scenario 2 250 300 2,330.3
- - Scenario 3 200 250 2,694.3
- - Scenario 4 150 200 2,879.4 -
Scenario 5 100 150 2,994.6 - - Scenario 6 30 80 2,813.9
- Diesel - Scenario 7 400 300 2,498.0
- Scenario 8 300
350 (136.4) - - Scenario 9 50 100 (709.1)
85Dealing with Uncertainty and Risk
- Risk variables and probability distribution
- - capital costs, /- 40, normal distribution
- - operating costs, /- 25, normal distribution
- - responses of premature mortality to sulphate
with 22, 67 and 11 for low, central and high
estimates (1.14x10-5, 2.54x-5, and 5.70x-5), step
distribution - - values of statistical life with 33, 50 and
17 for low, central and high estimates (2.4m,
4.0m, and 7.9m), step distribution. - Perform Monte Carlo simulations for scenarios 4,
6 and 7 - - the expected value of the NPV of net benefits
for each scenario is very close to the value of
the respective deterministic cases - - there is zero probability of getting the
negative net benefit.
86Distribution of Net Benefits by Stakeholders
- The oil refiners are required to comply with the
regulation by incurring capital expenditures and
additional operating costs. However, a
significant portion of the costs would be passed
forward to consumers in the higher prices of
gasoline fuels. - Individuals are the main beneficiaries of the
regulations because having cleaner air lowers the
risks of premature mortality and morbidity. - Some refinery workers will suffer temporary
income losses as a result of refinery closures. - Provincial government will save costs of medical
care. Savings arise because of lower hospital
admissions due to avoided health effects. - Finally, the federal government will incur
marginal administrative costs to monitor and
enforce the regulations.
87PV of Net Benefits by Stakeholders
- Refinery Consumers Government
- Refiners Workers /Individual Prov.
Fed. Total - Scenario 1 (117.0) 0 2,097.6
5.8 (0.6) 1,985.8 - Scenario 2 (272.9) 0 2,595.9
7.9 (0.6) 2,330.0 - Scenario 3 (339.7) (4.8) 3,029.9
9.6 (0.6) 2,694.3 - Scenario 4 (444.8) (14.5) 3,328.4
10.8 (0.6) 2,879.4 - Scenario 5 (578.4) (19.3) 3,580.5
12.4 (0.6) 2,994.6 - Scenario 6 (826.9) (19.3) 3,646.6
14.1 (0.6) 2,813.9 - Scenario 7 (238.0) (4.8) 2,733.6
7.9 (0.6) 2,498.0 - Scenario 8 (189.2) 0
51.9 1.5 (0.6) (136.4) - Scenario 9 (542.6) (4.8)
(164.5) 3.4 (0.6) (709.1)
88Conclusions
- Lowering the sulphur levels in gasoline will
generate a substantial amount of health benefits
to Canadians for all alternative scenarios. - The most stringent scenario 6 may not be the
scenario with the largest amount of benefits.
However, it is the scenario that will create a
suitable regulatory environment because it would
generate not only a considerable amount of
benefits but also a number of benefits that are
not easily taken into account in the quantitative
analysis. They are - - help vehicle control systems function more
efficiently - - help Canada control greenhouse gas emissions
in the future. - In the case of sulphur level in diesel, the NPV
of the net benefits are negative for both
scenarios 8 and 9. However, scenario 7 with a
modest change in the sulphur level to 400 ppm
would produce a significant health benefit for
Canadians.
89Ex Post Assessment
- Regulations The sulphur in gasoline regulations
was set at a maximum level of 30 ppm with a
never-to-be-exceeded maximum of 80 ppm beginning
in January 2005. An interim step was to have the
sulphur level in gasoline limited to 150 ppm with
a level never exceed 200 ppm starting July 2002
to the end of 2004. - The levels of sulphur in gasoline have followed
closely those set by the Regulations. These
results show a significant improvement in the air
quality in Canada. - There has been no closure of any refineries since
the introduction of the regulations. Some
refineries have even skipped the phase-in
approach and moved directly to the sulphur level
of 30 ppm.
90Recommendations for Improved Evaluations
- All refineries should be obliged to submit a
record of their actual capital expenditures to
Environment Canada. - A careful assessment of the administrative costs
by the public sector should be carried out. - To facilitate the cost-benefit analysis of a
regulation, both the capital and operating costs
incurred by the private sector should be broken
down into detailed categories.