EBK MACROECONOMICS
EBK MACROECONOMICS
4th Edition
ISBN: 8220103648165
Author: KRUGMAN
Publisher: MAC HIGHER
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Chapter 14, Problem 9P
To determine

Concept Introduction:

Money Supply:

It refers to that amount of money which is in circulation within the economy at a particular point of time. It includes cash currency and all the liquid assets which can be converted into cash on demand.

Effect of each situation on money supply.

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Problem 2: A manufacturer of computer workstations gathered average monthly sales figures from its 56 branch offices and dealerships across the country and estimated the following demand for its product: Q=+15,000-2.80P+150A+0.3P+0.35Pm+0.2Pc (5,234) (1.29) (175) (0.12) (0.17) (0.13) R²=0.68 SER 786 F=21.25 The variables and their assumed values are P = Price of basic model = 7,000 Q==Quantity A = Advertising expenditures (in thousands) = 52 P = Average price of a personal computer = 4,000 P. Average price of a minicomputer = 15,000 Pe Average price of a leading competitor's workstation = 8,000 1. Compute the elasticities for each variable. On this basis, discuss the relative impact that each variable has on the demand. What implications do these results have for the firm's marketing and pricing policies? 2. Conduct a t-test for the statistical significance of each variable. In each case, state whether a one-tail or two-tail test is required. What difference, if any, does it make to…
You are the manager of a large automobile dealership who wants to learn more about the effective- ness of various discounts offered to customers over the past 14 months. Following are the average negotiated prices for each month and the quantities sold of a basic model (adjusted for various options) over this period of time. 1. Graph this information on a scatter plot. Estimate the demand equation. What do the regression results indicate about the desirability of discounting the price? Explain. Month Price Quantity Jan. 12,500 15 Feb. 12,200 17 Mar. 11,900 16 Apr. 12,000 18 May 11,800 20 June 12,500 18 July 11,700 22 Aug. 12,100 15 Sept. 11,400 22 Oct. 11,400 25 Nov. 11,200 24 Dec. 11,000 30 Jan. 10,800 25 Feb. 10,000 28 2. What other factors besides price might be included in this equation? Do you foresee any difficulty in obtaining these additional data or incorporating them in the regression analysis?
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