Exam 5: Demand Estimation

Ordinary least squares is used to estimate a linear relationship between a firm's quantity sold per month and its total promotional expenditures, and the slope of the linear function is found to be positive and significantly different from zero. Assuming that all other variables, including product price, were constant during the period covered by the data set, this result implies that

The identification problem would prevent estimation of a demand curve from price and quantity data if, over the time period sampled, the only thing that varied was the

Regression line can be best described as

OLS (ordinary least squares) is used to estimate a linear relationship between a firm's quantity of laptops sold per year and its total promotional expenditures, and the slope of the linear function is found to be positive but not significantly different from zero. Assuming that all other variables, including product price, were constant during the period covered by the data set, this result implies that

The application of multiple regression analysis to a time-series data set yields a calculated Durbin-Watson statistic that is equal to 1.00. If the lower test value at the 1 percent level is 1.28 and the upper value is 1.51, then

A multiple regression analysis based on a data set that consists of 500 observations yielded the following estimated demand equation: Q = 120 - 1.1P + 0.04I + 0.90A - 0.04P_Z Where P is price, I is income, A is advertising, and P_Z is the price of a related good. If the standard errors of the independent variables are 0.25, 0.5, 0.3, and 0.01, respectively, which of the four variables should be dropped from the equation?

The use of electronic devices designed to gather information about which television stations people are watching is an example of observational research.

A multiple regression analysis based on a data set that consists of 30 observations yielded the following estimated equation: Q = 120 - 1.1P + 3.7I + 0.09A Where P is price, I is income, and A is advertising. If the coefficient of determination is 0.80, then the F statistic is

Using market experiment approach, data is obtained from

Florid Technologies is a manufacturer of exercise machines. Their best-selling device, a mechanical swimming simulator, has been on the market for several years. The demand function for the simulator was estimated in log-linear form using time-series data. The results are presented below. Q_X = 110P_X^-0.20 P_Y^0.30 P_Z^-0.10 A^0.10 I^0.01 The number of simulators sold per week (Q_X) was found to depend on the price charged for a simulator (P_X), the average monthly cost of membership at a health club (P_Y), the cost of an accessory package designed for use with the simulator (P_Z), monthly advertising expenditures (A) in thousands, and average annual household income (i)in thousands. (i) If $P _ { X } = \$ 595 , P _ { Y } = \$ 45 , P _ { Z } = \$ 99.85 , A = \$ 11,000$ , and $I = \$ 44,000$ , how many simulators can Florid Technologies expect to sell in a week? (ii)Interpret the price elasticity, cross-price elasticities, advertising elasticity, and income elasticity of demand for simulators. (iii)The president of Florid Technologies plans to increase the simulator's price by 10 percent and to increase advertising expenditures by 5 percent. By what percentage can sales of simulators be expected to change? Will total revenue increase, decrease, or remain the same? Explain your answer. (iv) If the price of a simulator is increased by 10 percent and the cost of an accessory package is reduced by 20 percent, what effect will this have on simulator sales?

The adjusted value of the coefficient of determination

If ordinary least squares is used to estimate a linear function, then the sum of the e_t will always be equal to zero.

If a regression line that was calculated by ordinary least squares is plotted on a scatter diagram, all of the points in the data set will be on the line.

A multiple regression analysis based on a data set that consists of 30 observations yielded the following estimated demand equation: Q = 120 - 1.1P + 0.04I + 0.90A Where P is price, I is income, and A is advertising. If price is equal to $1,000, income is equal to $20,000, and advertising expenditures are equal to $5,000, then the predicted quantity demanded (Q) is

If the F test statistic is greater than the appropriate critical value, it means that at least one of the estimated slope coefficients is significantly different from zero.

Autocorrelation may be the result of

If the t ratio for the slope of a simple linear regression equation is equal to 1.614 and the critical values of the t distribution at the 1 percent and 5 percent levels of significance, respectively, are 3.499 and 2.365, then the slope is

Unexplained variation in the Y variable is denoted e_t.

You have found the b estimate to be $\widehat { b } = 2.55$ with standard error $s _ { \hat { b } } = 0.95$ . Assuming you had a large sample, compute the confidence interval for the 5% significance level

A multiple regression analysis based on a data set that consists of 30 observations yielded the following estimated equation: Q = 120 - 1.1P + 3.7I + 0.90A Where P is price, I is income, and A is advertising. If the coefficient of determination is 0.80, then the adjusted coefficient of determination is