The following data show the demand for an airline ticket dependent on the price of this ticket. For the assumed cubic and log-log regression models, Demand = β₀ + β₁Price + β₂Price²+ β₃Price³+ ε and ln(Demand) = β₀ + β₁ln(Price) + ε, the following regression results are available. Which of the following does the slope of the obtained log-log regression equation ln ( ) = 26.3660 - 3.2577 ln(Price) signify? A) For every 1% increase in the price, the predicted demand declines by approximately 3.2577%. B) For every 1% increase in the demand, the expected price increases by approximately 3.2577%. C) For every 1% increase in the demand, the expected price decreases by approximately 3.2577%. D) For every 1% increase in the price, the predicted demand increases by approximately 3.2577%.

Question

Quizplus · Accepted Answer

The slope coefficient of -3.2577 for the ln-log model signifies that a 1% increase in the price is associated with a 3.2577% decrease in the predicted demand. This is because the coefficient represents the elasticity of demand with respect to price, which is the percentage change in demand for a 1% change in price.

The Following Data Show the Demand for an Airline Ticket