Suppose that to examine the demand for TriMet bus rides (BR_t) in the Portland region, we constructed the following aggregate demand regression model:

= ₀+ ₁ + ₂+ ₃+ ₄_ + ₁ +

Where BR_trepresents thousands of bus rides demanded in a particular month t, Price is the fare for bus rides ($), Income is the average income level (thousands $), Population is the current population (thousands), Price_Uber is the price of an equivalent Uber ride ($) and Pandemic is a dummy variable (0 or 1) representing whether or not there was a pandemicrelated stay at home order in the state during that month.

1. Assume that 1 = -3, 2 = 5, 3 = 0.5, 4 = 0.05, 1 = -10 are the estimated coefficients for this model. We also have calculated some dataset averages: average BR is 300, average price of a bus ride is $3, average Income is 45 (thousand $), average price of an equivalent Uber ride is $10 and average Population is 850 (thousand) in this dataset.
   1. Suppose that the price of bus rides has increased by $2. What would be the impact on bus rides being taken in Portland every month according to the regression results?
   2. Explain how the change in bus ride consumption from part (i) might be attributed to any substitution or income effects. (It may be helpful to utilize a consumer utility maximization graph to illustrate the substitution and income effects with bus rides on the horizontal axis and all other goods on the vertical axis.)
   3. The Population Research Center at PSU estimates that there may be 50,000 more people migrating into the region. What will be the impact on TriMet bus ride demand according to the regression results?
   4. Explain the relationship between TriMet bus rides and Uber rides according to the results of this regression model.