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Exam 5: Demand Estimation

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Question 51

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Use the method of least squares to calculate the intercept and slope of the linear relationship between quantity demanded (Q) and price (P) from the data set that follows. $\begin{array} { l l } Q & P \\2 & 6 \\3 & 5 \\5 & 3 \\2 & 7\end{array}$

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Question 52

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Application of simple linear regression analysis to the estimation of a demand equation has yielded the following: Q = 24 - 2P If the current product price is P = $6 and the quantity sold per time period is Q = 10, then the error (e) for the current time period is equal to

A) 1.
B) -1.
C) 2.
D) -2.

E) None of the above
F) A) and B)

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Question 53

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Heteroscedasticity refers to violation of the assumption that the mean of the error terms is zero.

The application of multiple regression analysis to a time-series data set yields a calculated Durbin-Watson statistic that is equal to 2.00. From this result, it is clear that

One difference between foreign and domestic demand for a commodity exported by the United States is that

The identification problem would not prevent estimation of a demand curve from price and quantity data if, over the time period sampled, the only thing that varied was the

One of the crucial assumptions of regression analysis is that the error term has a normal probability distribution.

Just the Fax, Inc. (JTF) has hired you as a consultant to analyze the demand for its line of telecommunications devices in 35 different market areas. The available data set includes observations on the number of thousands of units sold by JTF per month (Q_X), the price per unit charged by JTF (P_X), the average unit price of competing brands (P_Z), monthly advertising expenditures by JTF (A), and average gross sales (in thousands of dollars) of businesses in the market area (i). The results of a regression analysis (with standard errors in parenthesis) are given below. $Q x = \begin{array} { r r r c c } 300 & - 6 P _ { X } & + 2 P _ { Z } & + 0.04 A & + 0.01 I \\( 200 ) & ( 1.8 ) & ( 0.8 ) & ( 0.03 ) & ( 0.004 )\end{array}$ $R ^ { 2 } = 0.91 \quad \text { S.E.E. } = 3.6$ (i)Evaluate the statistical significance of the equation as a whole and of each of its coefficients. (ii)The average values of the independent variables in the data set used to estimate the equation are P_X = $195, P_Z = $225, A = $11,000, and I = $200,000. Calculate a point estimate of JTF's average sales and a 95 percent interval estimate of sales based on these values.

If one finds estimate of b to be equal with standard error , using a critical value of 1.96, what is the confidence interval for the true b coefficient?

The coefficient of correlation is

Use the method of least squares to calculate the intercept and slope of the linear relationship between quantity demanded (Q) and advertising (A) from the data set that follows. $\begin{array} { l l } Q & A \\2 & 0 \\3 & 1 \\5 & 4 \\10 & 7\end{array}$

In the linear function Y = a + bX, Y is the intercept and X is the slope of the function.

If R² is equal to 1, then the coefficient of correlation must also be equal to 1.

The coefficient of determination is equal to the explained variation in the Y variable divided by the unexplained variation in the Y variable.

Ordinary least squares maximizes the coefficient of determination.

If the t ratio for the slope of a simple linear regression equation is equal to 3.614 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

Behavioral economics extends the understanding of economic behavior by considering which of the following factors?

Omission of an important independent variable from a multiple regression model tends to bias estimates.

A t test on the slope takes as its alternative hypothesis the position that there is no relationship between the dependent variable and the relevant independent variable.

The estimation of consumer demand by monitoring actual purchasing and consumption behavior by a sample of consumers is called the