02 Jun Question In early 2003, the Glasure Transportation A
Question
In early 2003, the Glasure Transportation Authority, a public agency responsible for serving the commuter rail
transportation needs of a large city, was faced with rising operating deficits on its system. Also, because of a fiscal
austerity program at both the federal and state levels, the hope of receiving additional subsidy was slim.
The board of directors of GTA suggested that because it has been over five years since the last basic fare increase,
a fare increase from the current level of $1 to a new level of $1.50 should be considered. Accordingly, the board
ordered the manager to conduct a study of the likely impact of this proposed far hike.
You, the system manager, have collected data on important variables thought to have a significant impact
on the demand for riders on the Glasure Transportation Authority (UTA). These data have been collected
over the past 24 years and include the following variables:
1. Price per ride (in cents) — This variable is designated P. Price is expected to have a negative impact
on the demand for riders on the system.
2. Population in 1,000s in the metropolitan area serviced by GTA — It is expected that this variable has a positive
impact on the demand for rides on the system. This variable is designated T.
3. Disposable per capita income — This variable was initially thought to have a positive impact on the demand
for rides on GTA. This variable is designated I.
4. Parking rate per hour in the downtown area (in cents) — This variable is expected to have a positive impact
on the demand for riders on GTA. It is designated H.
5. Weekly riders in 1,000s. It is designated Y.
You have decided to perform a multiple regression on the data to determine the impact of the rate increase.
Based on the demand analysis you learned in chapter 5, determine first the dependent variable
for the estimating demand equation.
Questions:
1. Write the estimated demand model for the data given above (use a 3decimal points for the estimated coefficients.
2. Provide an economic interpretation for each of the coefficients in the estimated demand equation you have
computed.
3. What is the value of the coefficient of determination? How would you interpret this result?
4. Calculate the price elasticity using 2012 data. Explain the estimated coefficient of the price elasticity you just
computed.
5. Calculate the income elasticity using 2012 data. Explain the estimated coefficient of the income elasticity
you
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