Question 3 Empirical

Believe it or not, workers used to be able to smoke inside office buildings. Smoking bans were introduced in several areas during the 1990s. In addition to eliminating the externality of secondhand smoke, supporters of these bans argued that they would encourage smokers to quit by reducing their opportunities to smoke. In this question 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 to 1993 (Smoking data in your folder).

The data set contains information on whether individuals were or were not subject to a workplace smoking ban, whether the individuals smoked, and other individual characteristics. A detailed description is given in Smoking- Description, available in your folder.

• a. Estimate a linear probability model with smoker as the dependent variable and the following regressors: smkban, female, age, age2, hsdrop, hsgrad, colsome, colgrad, black, and hispanic.

• b. i. Mr. A is 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 workplace smoking ban, 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?

ii. Repeat (i) using the linear probability model.

iii. Based on your answers to (i)–(ii), do the probit, and linear probability models differ? If they do, which results make most sense? Are the estimated effects large in a real work sense?

Data