Managerial Economics
5th Edition
ISBN: 9781337681599
Author: Luke M. Froeb; Brian T. McCann; Michael R. Ward
Publisher: Cengage Limited
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Question
Chapter 5, Problem 5.7IP
(a)
To determine
The short-run decision of the firm.
(b)
To determine
The long-run decision of the firm.
(c)
To determine
The shutdown price of the firm in the short run.
(d)
To determine
The shutdown price of the firm in the long run.
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Please answer questions D-H, I have already answered A , B,C but it may help you to still solve them yourself. Thank you!
2. A firm’s production function is given by:Q = 10KLThe unit capital and labour costs are 2 and 1 pounds respectively. The firm is contracted to produce2000 units.(a) Write out the optimisation problem of the firm. (b) Express this problem using a Lagrangian function. (c) Find values of K and L which fulfil the contract with minimal cost to the firm. (d) Calculate the total cost to the firm.
3. Consider the following estimated regression equation, estimated using a sample of firms, where RDis total firm spending on research and development in USD ($), Revenue is total firm revenuein USD ($), and W ages is the firms’ total spending on wages in USD ($) (standard errors inparentheses):RDd = 1000(600)+ 0.5(0.1)Revenue + 1.5(0.5)W ages,(a) Interpret the coefficients on each of the explanatory variables. (b) Which of the three coefficients are statistically significant at the 5% level of significance? Howdo you know? A researcher runs a two-sided statistical test of the null hypothesis that both the coefficients onthe explanatory variables above are jointly equal to 0.25 (mathematically, that β1 = β2 = 0.25),and reports a p-value of 0.045.(c) What does this p-value mean for the outcome of the test? (d) What would an appropriate two-sided alternative hypothesis look like?
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- 4. Consider the following regression equation, where Google is equal to 1 if an individual in thesample has worked at Google and 0 otherwise, and Earnings is annual earnings in thousands ofpounds (standard errors in parentheses):Earnings \ = 25000(12.5)+ 42000(7.0)Google,(a) Interpret the coefficient on Google.(b) Is the coefficient on Google statistically significant at the 5% level? How do you know?(c) Suppose that instead of Google we had used a variable called NeverGoogle, equal to 1 if anindividual has never worked at Google and 0 otherwise. (i) How would the slope coefficientchange? (ii) What would happen to the intercept? (d) What prevents us from interpreting the coefficient on Google as a causal effect? Give examplesin your answer.arrow_forward4. Examine the regression table below before answering the questions that follow.Throughout, the Log() function represents the natural logarithm, so that Log(e) =1:Dependent Variable: Log(Expenditures on Cigarettes + 1)Method: Least SquaresVariable Coefficient Std. ErrorConstant 0.50 0.41Log(Income+1) −0.02 0.002(a) Why are the dependent and explanatory variables in the form log(1+x), ratherthan log(x)? (b) Which of the above coefficients are statistically significant? How do you know?(c) Interpret the coefficient on Log(Income+1). (d) What is the predicted level of Log(Expenditures on Cigarettes + 1) for anobserved individual with income of e10 − 1? (4arrow_forward3. Consider the following three (fictional) data points:Country Ultima Thule Narnia NeverlandGDP per capita (US $, 2021, in thousands) 10 30 20Deaths from COVID-19 as of Jan. 2023, millions 0.24 0.16 0.05(a) What is the slope of the line of best fit through these three points, whereDeaths from COVID-19 is the dependent variable and GDP per capita is theexplanatory variable? (b) The standard error for the slope parameter is 0.009. What does this standarderror measure? (c) Is the slope parameter statistically significant at the 5% level of significance?(The relevant critical value is not the usual value, but 4.303, due to the tinysample size). Explain what this means. (d) Why might this slope parameter be a misleading indicator of the relationshipbetween these two variables?arrow_forward
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