Keith Vodden Dr. Douglas Smith - Transports Canada

Appendix B—Making Changes to the Models
recorded for years 2000 to 2005 and the model estimates values based on each series for
2006 to 2015.
The analyst could enter actual data for each price index when available and reestimate
values for remaining years in the series. These data are record in B!J6:B!L21.
2. Coroner estimates of deaths
For a number of reasons ORSAR data may not capture all deaths related to
collisions. Given the high social value assigned to a fatality in the analysis it would be
useful to have an estimate based on more than a single year of data concerning the
difference between Coroner and ORSAR data related to the number of fatalities. This
factor, found in B!G68, could be revised based on further analysis covering additional
years.
3. MOH&LTC data to estimate major and minor injuries
The model pools MOH&LTC data related to hospital stays, emergency room use,
by those involved in motor vehicle collisions in two years—2003/2004 and 2004/2005.
These are then compared to data available from ORSAR on the number of major and
minor injuries. Although there is a high degree of consistency across the two years it may
be useful to combine additional years of data and compare them to ORSAR data to better
assess the factors used to increase major (those admitted to hospital who do not die) and
minor (emergency room visit) injuries. These factors are found in cells B!H147 for major
injuries and B!H148 for minor injuries.
4. Fuel prices
Delay cost calculations include the cost of fuel expended. Due to the current
variability in the price of fuel the model allows for the adjustment of fuel costs explicitly
by changing the value found in cell A!B328.
A cautionary note prices recorded in this cell should be in 2004$ as the model will
implicitly handle all adjustments for inflation. As a result the model will handle any
changes in fuel prices that are purely inflationary. However the analyst may wish to
change the fuel price in cell A!B328 if for example there is some shock to the world price
for oil that causes the opportunity cost of fuel to change.
5. Vehicle occupancy factor
The model uses a vehicle occupancy factor of 1.5 to represent the average number
of occupants in all vehicles. This is an assumed value based on studies of average
automobile occupancy in the GTA of from 1.1 to 1.2. Recall that the 1.5 value is to
account for all forms of vehicles including buses. The analyst can replace this value in
cell A!B330.
TNS Canadian Facts, Social and Policy Research 163