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What is the difference in the probability of smoking between workers affected by a workplace smoking ban and workers not affected by a workplace smoking ban?

INSTRUCTIONS TO CANDIDATES
ANSWER ALL QUESTIONS

INSTRUCTIONS:  Solve the following questions to the best of your ability.   Come see me and ask me if you do not know how to solve any of these questions, even before the due date. I will work with you if you are having trouble solving these.

first of all, for this problem set, you will have to submit the Stata log file. Stata can record your session into a file called a log file but does not start a log automatically; you must tell Stata to record your session. By default, the resulting log file contains what you type and what Stata produces in response, recorded in a format called Stata Markup and Control Language (SMCL). The file can be printed or converted to plain text for incorporation into documents you create with your word processor. You can find more information here: https://www.stata.com/manuals13/u15.pdf.

So, in the beginning of your Stata .do file write the following command: log using session (or a different file name). Then, at the very end of your .do file, include translate session.smcl session.pdf. This would translate SMCL files to plain text, which is a format more useful for inclusion into a word processing document. Or, even better, you can translate your Stata SMCL log files directly into PDF files and then use Adobe Acrobat to merge PDF files together. You will need to turn in this log file to receive full credit for this assignment.

I would strongly suggest compiling the log file in Stata after you have completed all of your code and can run it smoothly without any errors. In that way, your log file would not contain any lines of code that does not produce any results or any duplicate results. Please do your best to include comments in your code (using the sign in your Stata .do file) and to make the solutions to the different problems as clearly marked as possible. Otherwise, the graders might have to penalize you, if they cannot follow your work. And then I will have to re-grade your work and the whole process becomes highly inefficient.
Part I - Smocking.xlsx Data.
 
Believe it or not, workers used to be able to smoke inside office buildings. Smoking bans were introduced in several areas during the 1990s. Supporters of these bans argues that in addition to eliminating the externality of secondhand smoke, they would encourage smokers to quit by reducing their opportunities to smoke. In this assignment, you will estimate the effect of workplace smoking bans on smoking, using data on a sample of 10,000 U.S. indoor workers from 1991 and 1993.
 
Smoking is a cross-sectional data set with observations on 10,000 indoor workers, which is a subset of a 18,090-observation data set collected as part of the National Health Interview Survey in 1991 and then again (with different respondents) in 1993. The data set contains information on whether individuals were, or were not, subject to a workplace smoking ban, whether or not the individuals smoked and other individual characteristics. These data were provided by Professor William Evans of the University of Maryland and were used in his paper with Matthew Farrelly and Edward Montgomery “Do Workplace Smoking Bans Reduce Smoking?” American Economic Review, September 1999, Vol. 89, No. 4, 728-747.Use the data to complete the following:Problem 1. Estimate the probability of smoking for (i) all workers, (ii) workers affected by workplace smoking bans, and (iii) workers not affected by workplace smoking bans.Problem 2. What is the difference in the probability of smoking between workers affected by a workplace smoking ban and workers not affected by a workplace smoking ban? Use a linear probability model to determine whether this difference in statistically significant.

Problem 3. Estimate a linear probability model with smoker as the dependent variable and the following regressors: smkban, female, age, age2, hsdrop, hsgrad, colsome, colgrad, black, hispanic. Compare the estimated effect of a smoking ban from this regression with your answer from Problem 2. Suggest an explanation, based on the substance of this regression, for the change in the estimated effect of a smoking ban between Problem 2 and Problem 3.

Problem 4. Test the hypothesis that the coefficient on smkban is 0 in the population version of the regression in Problem 3 against the alternative that it is nonzero, at the 5% significance level.

Problem 5. Test the hypothesis that the probability of smoking does not depend on the level of education in the regression in Problem 3. Does the probability of smoking increase or decrease with the level of education?

Problem 6. Repeat Problem 3 - Problem 5 using a probit model. Problem 7. Repeat Problem 3 - Problem 5 using a logit model. Problem 8.

a)    Mr.  A is a white, non-Hispanic, 20 years old, and a high school dropout.  Using the

probit regression and assuming that Mr. A is not subject to a wrokplace smoking bank, calculate the probability that Mr. A smokes. Carry out the calculation again, assuming that he is subject to a workplace smoking ban. What is the effect of the smoking ban on the probability of smoking?

b)    Repeat a) for Ms. B, a female, black, 40-year-old college graduate.

c)   Repeat a) and b) using the linear probability model.

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