EBK PRINCIPLES OF MACROECONOMICS
7th Edition
ISBN: 9781337342155
Author: Mankiw
Publisher: CENGAGE LEARNING - CONSIGNMENT
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Chapter 5, Problem 6QCMC
To determine
Choosing the right explanation for the cause.
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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 Design
Good 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…
Substitute X=20. Can you show me how to do question 1 please
Chapter 5 Solutions
EBK PRINCIPLES OF MACROECONOMICS
Ch. 5.1 - Define the price elasticity of demand. Explain the...Ch. 5.2 - Define the price elasticity of supply. Explain...Ch. 5.3 - Prob. 3QQCh. 5 - Prob. 1QRCh. 5 - List and explain the four determinants of the...Ch. 5 - Prob. 3QRCh. 5 - Prob. 4QRCh. 5 - If demand is elastic, how will an increase in...Ch. 5 - What do we call a good with an income elasticity...Ch. 5 - How is the price elasticity of supply calculated?...
Ch. 5 - If a fixed quantity of a good is available, and no...Ch. 5 - Prob. 9QRCh. 5 - A life-saving medicine without any close...Ch. 5 - Prob. 2QCMCCh. 5 - A linear, downward-sloping demand curve is a....Ch. 5 - Prob. 4QCMCCh. 5 - An increase in the supply of a good will decrease...Ch. 5 - Prob. 6QCMCCh. 5 - Prob. 1PACh. 5 - Prob. 2PACh. 5 - Suppose the price elasticity of demand for heating...Ch. 5 - A price change causes the quantity demanded of a...Ch. 5 - Prob. 5PACh. 5 - Suppose that your demand schedule for pizza is as...Ch. 5 - Maria has decided always to spend one-third of her...Ch. 5 - The New York Times reported (Feb. 17, 1996) that...Ch. 5 - Prob. 9PACh. 5 - Prob. 10PACh. 5 - You are the curator of a museum. The museum is...Ch. 5 - Prob. 12PA
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- 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?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_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_forward
- 3. 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_forward3. Consider the following regression equation, where Cigs is daily spending on cigarettes in poundssterling (£), Y earsEduc is years of education, and F emale equals one if an individual is femaleand zero otherwise (standard errors in parentheses):Cigs [ = 4(1.6)− 0.08(0.032)Y earsEduc − 0.5(0.2)F emale,(a) Interpret the coefficients on Y earsEduc and F emale. (b) What does the model predict the average daily spending on cigarettes would be for womenwith 12 years of education? (c) Form the 95% confidence interval for the coefficient on F emale. (d) Economists are often interested in estimating production functions of the Cobb-Douglas form(Yiis the ith firm’s output, Liits spending on labour, and Kiits spending on capital):Yi = ALαi Kβi,How might someone estimate α and β from this equation using linear regression?arrow_forward
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