Keith Vodden Dr. Douglas Smith - Transports Canada

Ontario Model
Supporting the overall model are two spreadsheets. The first (A—Assumptions &
Values) provides social values for the various impacts of collisions. It also allows the
analyst control over some model parameters. Parameters include whether the model
produces estimates using Willingness to Pay (WTP) or Discounted Future Earnings
(DFE); whether a high (WTP—H), low (WTP—L), or medium (WTP—M) estimate is
used for WTP 1 ; and whether social costs are calculated using values for 2004 or another
year.
The second spreadsheet (B—Calculations) provides the calculations needed by
the model to adjust for cases of under-reporting and misreporting of collision effects.
These provide the mechanism to go from raw data (available from secondary sources) to
adjusted data that have been corrected for cases of under-reporting and misreporting
observed in data from other secondary sources. The exhibit also provides the set of
calculations needed to identify other effects of collisions such as the use of resources by
police, fire, and ambulance services.
Two other spreadsheet models not linked to the social cost model are the model
used to produce DFE estimates and the model that estimates delay costs. Output from
these models is entered as fixed parameters in the social cost model.
1. Ontario model
The Ontario model has three printable spreadsheets:
• O1—Raw data will display raw data extracted from the Ontario Road Safety
Annual Report (ORSAR) and Accident Database System (ADS) on the effects or
characteristics of collisions in Ontario that are Highway Traffic Act (HTA)
reportable.
• O2—Adjusted data will provide revised collision characteristics based on
adjustments for cases of under-reporting and misreporting in the raw data. It also
displays other estimated characteristics of motor vehicle collisions (ambulance,
fire, tow truck and police services for example) that are valued in other parts of
the model.
• O3—Social costs provides the total social cost estimated based on the collision
characteristics and the values and selected parameters (assumptions) of
spreadsheet A—Assumptions and Values.
The core Ontario model enters data (in O1—Raw data) on the characteristics of
collisions in Ontario as reported in ORSAR. These are adjusted to reflect cases of underreporting
and misreporting and to add other impacts of the collision, such as use of police
1 The high and low estimates are based on alternate willingness-to-pay estimates for the value of statistical
life available in the literature. The medium estimate averages the other two.
TNS Canadian Facts, Social and Policy Research 7