Dhruv [email protected]
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Assignment on Demand estimation
Q1. What is the dependent variable in this demand study?Ans. The
dependent variable of the demand study is the number of weekly
riders.
Q2. What are the independent variables?Ans. The independent
variables of the study are the Prices, Population, Parking rate and
Per Capita Income.
Q3. What are the expected signs of the variables thought to
affect transit ridership on STA?Ans. The equation is QD =
a-bP+cPop+-dInc+ePark For price, the relation or sign is negative
because an increase in price will result in a fall in demand. For
population, the relation or sign is positive because a rise in the
no. of people travelling by the train will lead to a rise in
demand. As far as income is concerned, the relation could be either
or positive, depending on commuter preference. Rail transportation
could be a factor depending on the type of product it is, if its a
normal good, the relation or sign will be positive, else it will be
negative. Parking rates have an inverse relation with the train
ridership as a higher parking rate will result in increase in the
no. of riders who commute by train.
Q4. Using a multiple regression program available on a computer
to which you have access, estimate the coefficients of the demand
model for the data given in Table 1.Ans. On the separate excel
sheet
Q5. Provide an economic interpretation for each of the
coefficients in the regression equation you have computed.Ans.
Since price is negative the weekly riders shall go down. Population
is positive, Income is negative so it is considered as an inferior
goods because people prefer to travel by public transport which is
much cheaper. As parking fees go up people prefer more of public
transport.
Q6. What is the value of the coefficient of determination? How
would you interpret this result?Ans. The coefficient of
determination is 0.96, according to the data the coefficient of
determination is defined as the ratio of the sum of the squared
errors from the regression effect to the total sum of squared
errors. 0.96 will mean that there was no cut off point for the
value of the R2 statistic.
Q7. Calculate the price elasticity using the 1992 data?Ans. The
price elasticity is calculated using the following formula:Ep =
Change in Quantity X Price Change in Price QuantityUsing the 1992
data we know that, Ep = Change in Quantity is -1.62, Price is 100
and Quantity is 955. Change in Price
Ep = -1.62 x 100 955Ep = -0.16 Therefore, Demand is
inelastic.
Q8. Calculate the income elasticity using 1992 data.Ans. EI =
Change in Quantity X Income Change in Income Quantity Using the
1992 data we know that, EI = Change in Quantity is -0.55, Income is
8,100 and Qunatity is 955. Change in Income
EI = -0.05 X 8100 955 EI = -0.43 Therefore, demand is quite
inelastic.
Q9. If the fare is increased to $1.50, what is the expected
impact on weekly revenues to the transit system if all other
variables remain at their 1992 levels?Ans. The impact on weekly
revenues to the transit system if the fare is increased to $1.50
can be assessed by substituting the 1992 data in the
equation.Original Data: Fare = $1.00QD = 85.44 1.62 (100) + 0.64
(1.610) 0.05 (8100) + 1.94 (200)QD = 85.44 162 + 1030.40 405 +
388QD = 936.84Revised Data: Fare = $1.50QD = 85.44 1.62 (150) +
0.64 (1.610) 0.05 (8100) + 1.94 (200)QD = 85.44 243 + 1030.40 405 +
388QD = 855.84Weekly revenue is (1.5) (855.84) = $1783.76Therefore,
when price is raised to $1.50, the weekly revenue is also
higher.
