Estimate the demand of one of your Hotels

As the manager of a local hotel chain, you have hired an econometrician to estimate the demand of one of your Hotels (H). The Estimation has resulted in the following demand function: Q (H) = 2,000 - (PH) - 1.5 (PC) - 2.25P ( P SE) + 0.8 (P OH)+ .01 (M) Where the following to solve: P= Price (H) is Hotels, (PH) is the price of the room at your hotel, (PC) is is the price of concerts in your area, (SE) price of sporting events in your area, (P OH) is the average room price of at other hotels in your areas, and (M) is the average of income in the United States. What would be the impact on your firm of: 1. A $500.00 increase in income? 2. A $10.00 reduction in the Price charged by... click for more

Elastic, Inelasticity, Unitary Elastic Problem

The Demand for Jet Air Travel Services and Hotels (X) is estimated to be: Q (x) = 22,000 - 2.5 (Px) + 4 (Py) - 1 (M) + 1.5(Ax) where Ax represents the the amount of advertising spent on X and other variables have their usual interpretations. Suppose the price of good X is $450.00, good Y sells for $40.00, the company utilizes 3,000 units of advertising, and consumer income is $20,000.00 1. Calculate the own price elasticity of demand at these values of prices, income, and advertising. 2. Is demand elastic, inelastic, or unitary elastic? Why? 3. How will your answers to parts a and b change if the price of Y increases to $50.00? Thanks!

Inverse Demand Relation Problem

An Econometrician has estimated the inverse demand relation as: P = a + b Q + e and found that a = 400, b = -2.75, e (a) = 8, e (b) = 0.75. Find the approximmate 95% confidence interval for the true values of a and b.

Statistics for economists/econometrics

See attached file for full problem description --- Consider the following relationship between the amount of money spent by a province on health care (Y) and the province's GDP (X):... ---

Hypothesis tests in STATA

1. The file cocaine.dta contains 56 observations on variables related to sales of cocaine powder in northeastern California over the period 1984- 1991. The variables are price = price per gram in dollars for a cocaine sale quant = number of grams of cocaine in a given sale qual = quality of the cocaine expressed as percentage purity trend = a time variable with 1984 =1 up to 1991 =8. Consider the regression model price = B1 + B2quant + B3qual + B4trend + e (1) (a) What proportion of variation in cocaine price is explained by variation in quantity, quality, and time? (b) It is claimed that the greater the number of sales, the higher the risk of getting caught; and thus, seller... click for more