3. This problem uses the cell phone and traffic data set described in Chapter 5 (page 163) to analyze the relationship between cell and texting bans and traffic fatalities. We add two variables: cell_ban is coded 1 if it is illegal to operate a handheld cell phone while driving and 0 otherwise; text_ban is coded 1 if it is illegal to text while driving and 0 otherwise.
(a) Add the dummy variables for cell phone bans and texting bans to the model from Chapter 5 (page 163). Interpret the coefficients on
these dummy variables.
(b) Based on the results from part (a), how many lives would be saved if California banned cell phone use while driving? How many lives would be saved if Wyoming had a implications for the proper specification of the such a ban? Discuss model.
FIGURE 6.14: Marginal Effect of Text Ban as Total Miles Changes
(c) Estimate a model in which total miles is interacted with both the cell phone ban and the prohibition of texting variables. What is the estimated effect of a cell phone ban for California? For Wyoming? What is the effect of a texting ban for California? For Wyoming? What is the effect of total miles?
(d) This question uses material from page 193. Figure 6.14 displays the effect of the cell phone ban as a function of total miles. The dashed lines depict confidence intervals. Identify the points on the fitted lines for the estimated effects for California an d Wyoming from the results in part (c). Explain the conditions under which the cell phone ban has a statistically significant effect.