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- 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 $156,000. Variable processing costs are estimated to be $9 per book. The publisher plans to sell single-user access to the book for $41. 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 price…Estimate the following model: purchase = β0 + β1traditional + β2aggregator + β3substackWhat is event modeling? Multiple Choice The event model adjusts data for each of the events identified to distort the trend and seasonal patterns of the time series. The event model adds a growth factor to the moving average as a way of adjusting for the event. The event model adds a smoothing constant for the events identified as important in the historical data. The event model initializes events so they can be selected to initialize or warm up the model.
- Suppose we are interested in evaluating the impact on wages of being a college graduate and of residing in California. To this end we define the following dummy variables if college graduate if not college graduate coll = ncoll = if not college graduate if college graduate 1 cali = if residing in California S 1 if not residing in California ncali = if not residing in California if residing in California and for wages denoting yearly wages, we estimate the following model of returns to education wages = B1 coll+ B2ncoll + B3 cali + B4(coll x cali) + e where E[e|coll, cali] = 0. Which parameter or combination of parameters measures the increase in expected wages from obtaining a college degree (comparing to not having a college degree) when residing California? O a. None of the other options is correct O b. Bi – B2 O c. B1 – B2 + ß4 O d. B4 O e. Bi + B3 – ßi – B4 O f. Bi + B4 – ß2 – B4 Clear my choice6. Next, show that as long as the model is correctly specified (assume it reflects the true data generating process), Bo = Bo + ² Σi=1 li Ui n i=1 xWrite first-order model relating E(y) to four quantitative independent variables.
- Suppose the researcher considers the following model : Wage = Bo+B,Female + u, and runs OLS, using wage data on 250 randomly selected male workers and 280 female workers. The researcher has obtained the estimated equation as Wage = 15 (1.00) 3 Female, R = 0.05. (0.5) In the equation, Wage is measured in dollars per hour, Female is a binary variable that is equal to 1 if the person is a female and O if the person is a male. The numbers in the parentheses are the standard errors of the coefficients. Which Statement is NOT correct? The coefficient of Female, -3.00, is statistically significant at 5%. O The p-value for the test that Ho: B = 0, H : B 0 is less than 0.05. This regression may suffer omitted variable bias. R Since insignificant. is too low, the wage difference between men and women is The researcher can increase R- by including more regressors in the model.Imagine you are trying to explain the effect of square footage on home sale prices in the United States. You collect a random sample of 100,000 homes that recently sold. a) Homes can be one of three types: single-family houses, townhomes, or condos. How would you control for a home’s type in a regression model? b) Write down a regression model that includes controls for home type, square footage, and number of bedrooms. c) How would you interpret the es3mated coefficients for each of the variables from part b? Be specific.Question 8/27 With Logit model, an estimated econometric model has information as follows: Dependent variable is the probability to be in the labor force (inlbforce): Inlbforce: =1 if being in the labor force; 2 independent variables: Age: age in years; Educ: education level; Kids6: number of kids less than 6 years old. All indep variables are statistically significant. The estimated coefficient of Age equals -0.035; The estimated coefficient of Edh equals 0.0261; The estimated coefficient of Kids6 equals -0.103; Intercept coefficient equals-1.283 The right value of z when age = 45, educ = 13, kids6 = 2 equals: O -2.7247 O -3.7256 O 3.7247 Go to question * PREVIOUS NEXT > Address
- Question 7 1) Listen Cities often want to determine how much additional law enforcement will decrease their murder rates. A simple model with cross-section data at the provincial level to address this question is (1) murdpc-Bo+Bipolpc+Bzincpc+Bapvty+u where murdpc is murders per capita, polpc is number of police officers per capita, incpc is income per capita and pvty is the percent of people in the city that are below a poverty line and u is the error term. Suppose that the supply of polpc is a function of murdpc described by the following equation (2) polpc=6o+8ımurdpc+5zincpc+53stax+v where stax is the percent of sales tax in the province in which the city is located and v is the error term. The reduced form equation of murdpc is a regression model of this variable as a function of the following variables plus an error term incpc, stax O incpc, stax, pvty O none of the other answers are correct O stax, pvty O incpc, pvtyConsider the following regression model: wage-Bi+Bamalerpumalexedu Buedutu, where wage is the hourly wage measured in dollars: male is a dummy variable for males edu is the years of education: maleedu is the interaction of male and edu variables. The parameter estimates for B parameters are P-1.27: B1.29: Br-0,16: Be-0.82. What is the predicted marginal effect of years of education for males?Describe the recommended approach towards determining model specification.How does the R2 help in determining an appropriate model? Is theideal model the one with the highest R2? Should a regressor be included in the model if it increases the model R2?
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