When we have an omitted variable, the beta estimated can be written: B₁ =B1 + B₂01 The "bias" (how far off our estimate is from the true B1) is B2 times d1. What is d1?
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- Is it true of false that the classical errors in variables (CEV) assumption is that the measurement error is correlated with the unobserved true value of the explanatory variable.The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales S vary jointly with disposable personal income Y and the population between ages 15 and 40, Z, and inversely with the price of the snowmobiles P. Based on past data, the best estimate of this relationship isS = k (YZ/ P)where k has been estimated (with past data) to equal 100.a. If Y = $11,000, Z = $1,200, and P = $20,000, what value would you predict for S?b. What happens if P is reduced to $17,500?c. How would you go about developing a value for k?d. What are the potential weaknesses of this model?An independent variable in a model is also called:a. explained variable.b. unexplained variable.c. explanatory variable.d. dependent variable.
- The error term in a regression equation is said to exhibit homoskedasticty if ____________. a) it has the same variance for all values of the explanatory variable(s). b) None of the other possible answers correctly finish the sentence. c) it takes the value of one given any values of the explanatory variable(s). d) it has the same value for all values of the explanatory variable(s). e) it has a zero conditional mean.The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales S vary jointly with disposable personal income Y and the population between ages 15 and 40, Z, and inversely with the price of the snowmobiles P. Based on past data, the best estimate of this relationship is S=kYZP where k has been estimated (with past data) to equal 100. If Y=11,000,Z=1,200, and P=20,000, what value would you predict for S? What happens if P is reduced to $17,500? How would you go about developing a value for k? What are the potential weaknesses of this model?The demand function for a product is given by P = 4000/ln (x+10), where P is the price per unit in dollars when x units are demanded.i. Find the rate of change of price with respect to the number of units sold when 40 units are sold ii. Find the rate of change of price with respect to the number of units sold when 90 units are sold.iii. Find the second derivative to see whether the rate at which the price is changing at 40 units is increasing or decreasing.
- Eastman Publishing Company is considering publishing an electronic textbook about spreadsheet applications for business. The fixed cost of manuscript preparation, textbook design, and web site construction is estimated to be $172,000. Variable processing costs are estimated to be $5 per book. The publisher plans to sell single-user access to the book for $42. Through a series of web-based experiments, Eastman has created a predictive model that estimates demand as a function of price. The predictive model is demand = 4,000 − 6p, where p is the price of the e-book. (a) Construct an appropriate spreadsheet model for calculating the profit/loss at a given single-user access price taking into account the above demand function. What is the profit estimated by your model for the given costs and single user access price (in dollars). $ (b) Use Goal Seek to calculate the price (in dollars) that results in breakeven. (Round your answer to the nearest cent.) $ (c) Use a data table that varies…Suppose we estimate the following econometric model with OLS: What does OLS do? OLS chooses and to minimize the sum of residuals. OLS chooses and to minimize the sum of squared residuals. OLS chooses and to minimize the error term OLS chooses and to minimize the error termThe owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2). The estimated regression equation was ŷ = 83.7 + 2.23x1 + 1.60x2. The computer solution, based on a sample of eight weeks, provided SST = 25.4 and SSR = 23.445. (a)Compute and interpret R2 and Ra2.(Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is (??) . Adjusting for the number of independent variables in the model, the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is (??).
- In general, what is true about the relationship between the Sum of Squared Residuals in the restricted and unrestricted model? a. SSRr = R-squared * SSRur b. SSRr < SSRur c. SSRr > SSRur d. SSRr = SSRurWhat is the model constant when the dummy variable equals 1 in the following equations, where x1 is a continuous variable and x2 is a dummy variable with a value of 0 or 1? a. Ŷ = 4 + 8x1 + 3x2 b. Ŷ = 7 + 6x1 + 5x2 c. Ŷ = 4 + 8x1 + 3x2 + 4x1x2Which of the following statements is true? a) None of the other possible answers are true. b) Under the Classical Linear Model assumptions, the OLS estimator has the highest variance among unbiased estimators. c) Taking the natural log of a non-normal distribution often yields a distribution that is closer to normal. d) The Central Limit Theorem (CLT) assumes that the dependent variable is unaffected by unobserved factors. e) The mean of a non-normal distribution is 0 and the variance is σ2.