## (Solved) Written essay: Explain why the English alphabet alone is not a

health economics
1

a. Consider a utility function where for someone who is trying to quit smoking.

Suppose utility in period if a person quits is 8, and utility in period t+1 is 16. On the other hand if they don?t quit, their utility in period t is 14, and their utility in period t+1 is 8. Consider two scenarios.

If the person has discounts geometrically across future utilities, with ? = 0.8, how does the person feel about quitting today? What about quitting 7 days from now?

b. Alternatively, suppose an individual hyperbolically discounts, so the discount factor applied to period is 1/(1+t). How does the person feel about quitting today? What about quitting 7 days from now?

2.Utilize data from the BRFS file.

a. What is the average BMI by gender? For those under 40? For those over 40?

b. Construct a density plot of the BMI distribution (type kdensity bmi). Compare the the BMI of distribution of 2009 with the BMI distribution of 1985 using the the twoway command (type twoway (kdensitybmi if year==1985) (kdensity bmi if year==2009, lpattern(dash)).

b. Construct a density plot of the BMI distribution (type kdensity bmi). Compare the the BMI of distribution of 2009 with the BMI distribution of 1985 using the the twoway command (type twoway (kdensity bmi if year==1985) (kdensity bmi if year==2009, lpattern(dash)).

b. Construct a density plot of the BMI distribution (type kdensity bmi). Compare the the BMI of distribution of 2009 with the BMI distribution of 1985 using the the twoway command (type twoway (kdensity bmi if year==1985) (kdensity bmi if year==2009, lpattern(dash)).

c. Collapse the data to generate average BMIs by year and gender (meaning type collapse (mean) bmi,by(year sex). Create a time series plot that has the BMI distribution for males, and the BMI distributionfor females. To do so, type tsset sex year, and then tsline bmi if sex==1, and then tsline bmi if sex==2.

3. Consider now using information on two types of crimes. Underage drinking and selling alcohol tominors.

a. If you consider running the regression crimei = ?0 + ?1 ? over21i + f(agei) + ui, discuss why using a the 21 drinking age can be thought of as a natural experiment of sorts.

b. Utilize the data crime21.dta. Estimate regression discontinuity models with the crimes as the left hand side variables where you control for age relative to 21 ?age?, a dummy variable for being over 21 ?over21?, and the interaction between age and being over 21 ?ageint?. I rescaled the age so it is already relative to turning 21 (otherwise you would need to do that). Estimate a similar same regression also including a squared term for age, and that squared term interacted with over21 (you need to create those variables. Based on those linear and quadratic regression discontinuity models, how does underage drinking (?underage?) and selling alcohol to minors (?minor?) change at 21.

c. Using the ?scatter? command, type ?scatter minor age, xline(0)?, and ?scatter underage age, xline(0)?. Do the graphs reveal changes in criminality at age   21?

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This question was answered on: Oct 15, 2019

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