EBK MICROECONOMICS: PRIVATE AND PUBLIC
16th Edition
ISBN: 8220103612142
Author: Gwartney
Publisher: Cengage Learning US
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Chapter 4, Problem 5CQ
To determine
Tax on cigarettes.
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EBK MICROECONOMICS: PRIVATE AND PUBLIC
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- What is absolute advantage?arrow_forwardGood Day, Kindly requesting assistance with this also Briefly explain how elasticity affects government health policies in the following cases:● Taxes on unhealthy products (cigarettes, alcohol, sugary drinks)● Subsidizing Preventive Care (e.g., vaccines, screenings)● Drug Price Controls & Generic Substitutions● Co-Payments & Insurance Designarrow_forwardGood Day, Kindly assist with the following query: ● Cost–benefit Analysis● Cost-effectiveness analysis● Cost–utility analysis● Cost analysis or Cost Minimization Analysis For each of the following health policy questions listed below, identify and briefly explain which type of economic evaluation in question above would be most appropriate to use: ● The Ministry of Finance wants to know whether it is worth investing further resources into malaria control or building new primary schools? ● The Ministry of Health wants to compare the costs of receiving intravenous antibiotics in a hospital with receiving the same antibiotics (at the same doses) at home via a home health care service. ● The Ministry of Health wants to compare the costs and outcomes of two interventions for the treatment of early stage breast cancer: mastectomy without breast reconstruction compared to breast conserving surgery and radiotherapy (breast conservation). ● A malaria control programme wants to use economic…arrow_forward
- Substitute X=20. Can you show me how to do question 1 pleasearrow_forwardBlue Air Inc., has net sales of $740,000 and accounts receivables of $163,000. What is the firm's accounts receivables turnover?arrow_forwardPlease answer questions D-H, I have already answered A , B,C but it may help you to still solve them yourself. Thank you!arrow_forward
- 2. A firm’s production function is given by:Q = 10KLThe unit capital and labour costs are 2 and 1 pounds respectively. The firm is contracted to produce2000 units.(a) Write out the optimisation problem of the firm. (b) Express this problem using a Lagrangian function. (c) Find values of K and L which fulfil the contract with minimal cost to the firm. (d) Calculate the total cost to the firm.arrow_forward3. Consider the following estimated regression equation, estimated using a sample of firms, where RDis total firm spending on research and development in USD ($), 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?arrow_forward4. 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_forward
- 4. 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_forwardConsider the following estimated regression equation, where both Rent and Earnings aremeasured in pounds (£) at the individual level (standard errors in parentheses):log(\Rent) = 6.9(0.69)+ 0.9(0.3)log(Earnings),(a) Interpret the coefficient on log(Earnings). (b) If we divided Earnings by 1000, so that it is measured in 1000s of pounds instead of pounds,how would (i) the slope, (ii) the intercept change in the above equation? Now suppose the variable London is added, which is equal to one if an individual iives inLondon, and zero otherwise. The estimated regression equation changes to:log(\Rent) = 6.22(0.622)+ 0.5(0.05)log(Earnings) + 2(0.5)London,(c) Interpret the coefficient on London. (d) Explain why the coefficient on log(Earnings) when London is included in the regression andthe coefficient on log(Earnings) when London is not included in the regression are not thesame.arrow_forward
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