Suppose that in efforts to combat drunk driving, the government introduced harsher legislation criminalizing driving under the influence (DUI). This study evaluates empirically whether this policy had any causal effect on recidivism. The policy, enacted on January 1, 2000, introduced a strict threshold for Blood Alcohol Content (BAC) to establish punishment (e.g., fines, or other restrictions on driving) for DUI. Suppose you have individual records for the period 2010 to 2020 on a measure of recidivism, BAC, gender, race, age, and region of residence. Note: The horizontal axis refers to BAC, the vertical axis refers to recidivism. Points represent the averages, with fitted values based on local linear models in black lines. The vertical black line represents the legal threshold at 0.08. The bin width is 0.002. (a) Describe the empirical method that you'd estimate to produce the figure above. Motivate how this method is the most appropriate given this research design. Also, outline the regression model carefully describing all regressors. (b) Briefly describe the main assumptions behind the proposed method. Propose strategies to test empirically whether these assumptions are met. (c) Now suppose that the legislation changes the conditions for arrest for DUI as follows. People caught driving with alcohol level above the 0.08 threshold have their case evaluated by one of a pool of judges. Each judge can decide to wave any fine (hint: assume judges have different levels of leniency). What are the implications of this for the proposed method at point a? Describe how you would modify your proposed method including its empirical implementation. .05 .08 .1 .12.14 .16 о
Suppose that in efforts to combat drunk driving, the government introduced harsher legislation criminalizing driving under the influence (DUI). This study evaluates empirically whether this policy had any causal effect on recidivism. The policy, enacted on January 1, 2000, introduced a strict threshold for Blood Alcohol Content (BAC) to establish punishment (e.g., fines, or other restrictions on driving) for DUI. Suppose you have individual records for the period 2010 to 2020 on a measure of recidivism, BAC, gender, race, age, and region of residence. Note: The horizontal axis refers to BAC, the vertical axis refers to recidivism. Points represent the averages, with fitted values based on local linear models in black lines. The vertical black line represents the legal threshold at 0.08. The bin width is 0.002. (a) Describe the empirical method that you'd estimate to produce the figure above. Motivate how this method is the most appropriate given this research design. Also, outline the regression model carefully describing all regressors. (b) Briefly describe the main assumptions behind the proposed method. Propose strategies to test empirically whether these assumptions are met. (c) Now suppose that the legislation changes the conditions for arrest for DUI as follows. People caught driving with alcohol level above the 0.08 threshold have their case evaluated by one of a pool of judges. Each judge can decide to wave any fine (hint: assume judges have different levels of leniency). What are the implications of this for the proposed method at point a? Describe how you would modify your proposed method including its empirical implementation. .05 .08 .1 .12.14 .16 о
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
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Transcribed Image Text:Suppose that in efforts to combat drunk driving, the government introduced harsher legislation criminalizing driving
under the influence (DUI). This study evaluates empirically whether this policy had any causal effect on recidivism. The
policy, enacted on January 1, 2000, introduced a strict threshold for Blood Alcohol Content (BAC) to establish
punishment (e.g., fines, or other restrictions on driving) for DUI. Suppose you have individual records for the period
2010 to 2020 on a measure of recidivism, BAC, gender, race, age, and region of residence. Note: The horizontal axis
refers to BAC, the vertical axis refers to recidivism. Points represent the averages, with fitted values based on local linear
models in black lines. The vertical black line represents the legal threshold at 0.08. The bin width is 0.002. (a) Describe
the empirical method that you'd estimate to produce the figure above. Motivate how this method is the most
appropriate given this research design. Also, outline the regression model carefully describing all regressors. (b) Briefly
describe the main assumptions behind the proposed method. Propose strategies to test empirically whether these
assumptions are met. (c) Now suppose that the legislation changes the conditions for arrest for DUI as follows. People
caught driving with alcohol level above the 0.08 threshold have their case evaluated by one of a pool of judges. Each
judge can decide to wave any fine (hint: assume judges have different levels of leniency). What are the implications of
this for the proposed method at point a? Describe how you would modify your proposed method including its empirical
implementation.
Transcribed Image Text:.05
.08 .1 .12.14 .16
о
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