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3) Estimating externalities: Perhaps one of the most difficult parts of being an economist (and one that requires the most creativity) is taking regression results

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3) Estimating externalities: Perhaps one of the most difficult parts of being an economist (and one that requires the most creativity) is taking regression results and using them to make policy recommendations. One central concept used in policy is the estimate of the dollar value of an externality. In class we talked about how Carpenter and Dobkin estimated the value of the negative externality generated by moving the drinking age back to 18: they estimated the total costs from lost lives and the total increases in drinks consumed. By dividing total costs by total drinks they estimate that under-age drinkers should pay a price of an additional SIS per drink to compensate society for a lower drinking age. In the following problem we will consider how to take the estimated coefficient from Adams and Cotti (2008) and derive the value of an externality. On Husky CT, I have posted the paper "How Dangerous are Drinking Drivers" by Steven Levitt and Jack Porter. Begin by reading the introduction (pages 1198-1201) and pages 1226-1229 (starting with Section V. Externalities...). Levitt and Porter discuss several statistics and parameters they use to back out the value of an externality of per mile of drunk driving. I took the following useful statistics estimated by Levitt and Porter for you to consider Parameter Value Statistical value of a life 3 million dollars. Fraction of deaths in accidents that involved a drinking 15.3% driver such that one who died was not drinking and driving or the passenger of a drinking and driver. Annual miles driven by non-sober drivers from 56.6 billion. 8:00 PM to 5:00 AM Annual miles driven by sober drivers from 313.4 billion. 8:00 PM to 5:00 AM Value of the negative externality generated per mile 16 cents per mile. driven by an inebriated driver. a. Now, we want to think about the externality in terms of increased drinking and driving) caused by an indoor smoking ban in an average county. One way to calculate this externality would be to calculate the total value in terms of lost innocent lives 1) Total Externality = A innocent traffic fatalities from ban value of a life Where "innocent traffic fatalities are deaths of those who were not drinking and driving or the passenger of a drinker and driver. Using the estimated effect of drunk driving ban from Adams and Cotti, your answer to 2.d. and the number of innocents killed per accident estimated in Levitt and Porter, back out a value for the total externality in a year. b. Alternatively, Levitt and Porter estimated that an externality of 16 cents per "inebriated mile driven. Therefore, we could use Levitt and Porter's externality estimate to back out the total increase in miles driven drunk caused by the cigarette ban. Consider the following relationship: 2) A traffic innocent fatalities. Value of Life -= Negative Externality per mile driven A# of miles driven enibriated Use equation 2), the estimates from Cotti and Adams, and the parameters from Levitt and Porter to estimate the total number of additional drunk miles driven caused by the traffic ban. 3) Estimating externalities: Perhaps one of the most difficult parts of being an economist (and one that requires the most creativity) is taking regression results and using them to make policy recommendations. One central concept used in policy is the estimate of the dollar value of an externality. In class we talked about how Carpenter and Dobkin estimated the value of the negative externality generated by moving the drinking age back to 18: they estimated the total costs from lost lives and the total increases in drinks consumed. By dividing total costs by total drinks they estimate that under-age drinkers should pay a price of an additional SIS per drink to compensate society for a lower drinking age. In the following problem we will consider how to take the estimated coefficient from Adams and Cotti (2008) and derive the value of an externality. On Husky CT, I have posted the paper "How Dangerous are Drinking Drivers" by Steven Levitt and Jack Porter. Begin by reading the introduction (pages 1198-1201) and pages 1226-1229 (starting with Section V. Externalities...). Levitt and Porter discuss several statistics and parameters they use to back out the value of an externality of per mile of drunk driving. I took the following useful statistics estimated by Levitt and Porter for you to consider Parameter Value Statistical value of a life 3 million dollars. Fraction of deaths in accidents that involved a drinking 15.3% driver such that one who died was not drinking and driving or the passenger of a drinking and driver. Annual miles driven by non-sober drivers from 56.6 billion. 8:00 PM to 5:00 AM Annual miles driven by sober drivers from 313.4 billion. 8:00 PM to 5:00 AM Value of the negative externality generated per mile 16 cents per mile. driven by an inebriated driver. a. Now, we want to think about the externality in terms of increased drinking and driving) caused by an indoor smoking ban in an average county. One way to calculate this externality would be to calculate the total value in terms of lost innocent lives 1) Total Externality = A innocent traffic fatalities from ban value of a life Where "innocent traffic fatalities are deaths of those who were not drinking and driving or the passenger of a drinker and driver. Using the estimated effect of drunk driving ban from Adams and Cotti, your answer to 2.d. and the number of innocents killed per accident estimated in Levitt and Porter, back out a value for the total externality in a year. b. Alternatively, Levitt and Porter estimated that an externality of 16 cents per "inebriated mile driven. Therefore, we could use Levitt and Porter's externality estimate to back out the total increase in miles driven drunk caused by the cigarette ban. Consider the following relationship: 2) A traffic innocent fatalities. Value of Life -= Negative Externality per mile driven A# of miles driven enibriated Use equation 2), the estimates from Cotti and Adams, and the parameters from Levitt and Porter to estimate the total number of additional drunk miles driven caused by the traffic ban

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