A major advantage of the __________________ production function is that it can be easily transformed into a linear function, and thus can be analyzed with the linear regression method. cubic power quadratic none of the above.
For the regression equation Q = 100 - 10X1 + 25X2, which of the following statements is true? X2 is the more important variable because it is positive When X1 decreases by one unit, Q decreases by 10 units. When X1 increases by 10 units, Q decreases by 1 unit. When X1 increases by one u
Evaluate the following statement: "It is easier to build an economic model that accurately reflects events that have already occurred than to build an economic model to forecast future events." Do you think that this is true or not? Why? What does this imply about the difficulties of building good economic models? Thank you
A major advantage of the __________________ production function is that it can be easily transformed into a linear function, and thus can be analyzed with the linear regression method. Cubic Power Quadratic None of the above
From a management policy perspective, which regression result is the most useful? a regression equation that passes the F-test. a regression equation whose explanatory variables all passed the t-test. a regression equation that has the highest R2. a regression equation that has the least n
When the R2 of a regression equation is very high, it indicates that: All the coefficients are statistically significant. The intercept term has no economic meaning. A high proportion of the variation in the dependent variable can be accounted for by the variation in the independent variables. There is a g
Which of the following refers to a relatively high correlation among the independent variables of a regression equation?
Which of the following refers to a relatively high correlation among the independent variables of a regression equation? autocorrelation the identity problem statistically insignificant regression coefficients multicolinearity
1.A Taiwan electronics company exports personal computers (PCs) to the U.S. Their PC sales (in thousands) over the past five years are given below: Year Sales 1 6 2 9 3 13 4 15 5 20 WHat is the regression equation if the company wants to predict sales? a.Y = 2.4 + 3.4X b
Please see the attached file. Explain your answer briefly and clearly, showing any necessary calculations. Your answer should be in an Excel file. 1. Westminster Company has had the following experience over the past five quarters: Units produced Electricity cost ($)
Overheard at the water cooler: My regression model of demand is better than the one that the consultant prepared for us because it has a higher R2. Besides, my equation has three more independent variables and so is more complete then the consultant's. Comment on this statement. Would you agree with the speaker? Explain.
You have been retained to assist a regional food marketer, FoodKing, to forecast the demand for pies that are mass-produced and marketed under the name Ms. Smith's Homemade Pies. To assists with your analysis, you are provided with data that was collected for 8 consecutive quarters and 6 geographic markets. If you use Excel or a
You are the team leader of a unit of a US nonprofit organization based in Banjul Gambia (Capital City). The nonprofit's mission is to ensure that rural populations worldwide have access to health and sanitation-related supplies. Due to the sudden departure of one of your team leaders, you are taking over responsibility for orde
Qty. Price Advertise Distance 180 475 1100 120 590 400 2400 65 430 450 1500 50 250 550 3100 75 275 575 3400 45 720 375 2200 20 660 375 1200 50 490 450 2400 75 700 400 2200 45 210 500 1000 55 A firm's marketing dept. obtained data from 10 of the firm's outlets. The data consists of the qty. and price of the product
1. A firm experiences increasing returns to scale; that is, doubling all its inputs more than doubles its output. What can be inferred about the firm's short-run costs i.e. what is the connection between economies of scale and the short run average variable cost? 2. Which indicator(s) will always improve when more variables
Please complete the following two questions: 1. Which indicator(s) will always improve when more variables are added to a regression equation? 2. A firm experiences increasing returns to scale; that is, doubling all its inputs more than doubles its output. What can be inferred about the firm's short-run costs?
Estimating Successful Bid Price of Singapore Certificate of Entitlement. See attached file for full problem description.
A firm used a combination of inputs that was to the left of its isocost line, it would indicate that a. it is exceeding its budget. b. it is not spending all of its budget. c. it is operating at its optimal point because it is saving money. d. None of the above. When the exponents of a Cobb-Douglas production func
1. Consider the single-index model. The alpha of a stock is 0%. The expected return on the market is 12%. The risk-free rate of return is 6%. The expected return on the stock exceeds the risk free rate by 10%. What is the beta of the stock? 2. You estimate an index (CAPM) model running a regression of rHP - rf on a constant a
1. Describe the overall explanatory power of this regression model, as well as the relative importance of each continuous variable. (attached) 2. Based on the importance of the binary or dummy variable that indicates superstore competition, do superstores pose a serious threat to Columbia's profitability? 3. What factors m
In the volume, Consumer Demand in the United States: Analyses and Projections (Cambridge, Mass.: Harvard University Press, 1970), H.S. Houthakker and L.D. Taylor presented the following results for their estimated demand equation from 1929 to 1961 (excluding the 1942 through 1945 war year in the United States: Qt = 19.575
There is a large gap between the earnings of married women and married men, even if individuals of both sex have the same level of education. Everyone knows there is sexual discrimination. Few people know, however, that certain aspects of Human Capital theory can explain over 38% of the gap. How so? Explain in detail and
Question: Forecast Aggregate Demand by Month for the year 2005 (See Excel attachment for the past forecast from January - December 2000 to January to December 2004. (It may be easier to use Excel). See attached file for full problem description.
Table 10.2 Effects of Firm Size on Profitability (t statistics are in parentheses) Dependent Variable Size Measure Intercept Size Coefficient R Squared F Statistic Profits Sales 2,560.5660 0.0497 36.1% 15.8 (2.2900) (3.98) Profits Net Worth 723.9516 0.01491 64.6% 51.6 (0.80) (7.15) Profit margin (MGN
See attached table and data chart: A. What firm-specific and industry-specific factors might be used to explain differences among giant corporations in the amount of revenue per employee and profit per employee? B. A multiple regression analysis based upon the data contained in the attached table reveals the following (t s
The following equation was estimated for the fall and second semester students: (See attached) Here, trmgpa is term GPA, crsgpa is a weighted average of overall GPA in courses taken, cumgpa is GPA prior to current semester, tothrs is total credit hours prior to the semester, sat is SAT score, hsperc is graduating percentile
Answer this question (question 17) and questions 18 and 19 on the basis of the following regression results, standard errors in parentheses, n = 200) Qd = -500 - 100Pa + 50Pb + .3I + .2A (250) (50) (30) (.1) (.08) R2 = .12 Where Qd = 10,500 quantity demanded of pro
1) What were the alternative methods used by the FTC and the merging firms to determine whether or not an Office Depot and a Staples outlet were in the same geographical market? 2) How did this differentiation in geographical market measurement affect the pricing behavior estimated by the FTC and by the merging firms? What i
Please help interpret the regression results. I regressed LogCost on LogSeatMiles, LogPriceLabor, LogPriceMaterials Log PriceFuel Here are the results: Variable Coefficient Log SeatMiles .8958442 Log PriceLabor .287488 Log PriceMaterials -.0987056 Lo
I have a few different regression results, and need some help interpreting them. On a few, I put some of my answers to the questions in brackets - I'd like to know if I am correct, if not, some assistance would be appreciated. The results are as follows A. PSoda Hat = .956 + .1149882 PrBlack + 1.60 income Where: P
1. Portray the following data on a two variable diagram Academic Year Total Enrollment Enrollment in ECon 1994-95 3000 300 95-96 3100 325 96-97 3200 350 97-98 3300 375 98-99