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These findings highlight that, even when a policy effectively reduces pollution during regulated hours, unintended consequences during non-regulated hours should also be considered in policy evaluation.
These findings highlight that, even when a policy effectively reduces pollution during regulated hours, unintended consequences during non-regulated hours should also be considered in policy evaluation.
Increased policy avoidance translates into health costs. More stringent events led to larger increases in air pollution during non-crackdown hours. Using an exposure–response function and real-time hourly population data, I provide rough estimates of the resulting health costs
Increased policy avoidance translates into health costs. More stringent events led to larger increases in air pollution during non-crackdown hours. Using an exposure–response function and real-time hourly population data, I provide rough estimates of the resulting health costs
Moreover, the magnitude of policy avoidance is proportional to the degree of policy stringency when compared 'across' multiple policy events. In other words, the more stringent the policy event was, the more increase in policy avoidance we see.
Moreover, the magnitude of policy avoidance is proportional to the degree of policy stringency when compared 'across' multiple policy events. In other words, the more stringent the policy event was, the more increase in policy avoidance we see.
Empirically, I confirm that this theoretical prediction holds. Each policy-strengthening event is associated with a rise in policy avoidance behavior: traffic during non-regulated hours increased for the treated group relative to the control group following each policy event.
Empirically, I confirm that this theoretical prediction holds. Each policy-strengthening event is associated with a rise in policy avoidance behavior: traffic during non-regulated hours increased for the treated group relative to the control group following each policy event.
The theoretical model predicts that the number of policy avoiders—individuals who legally circumvent the policy by exploiting loopholes (analogous to tax avoidance, in contrast to tax evasion)—increases as the policy becomes more stringent.
The theoretical model predicts that the number of policy avoiders—individuals who legally circumvent the policy by exploiting loopholes (analogous to tax avoidance, in contrast to tax evasion)—increases as the policy becomes more stringent.
Existing works typically treat policy implementation as a 'dichotomous' event when assessing policy effectiveness. Instead, my paper leverages several policy-intensifying events, and examines how the magnitude of policy avoidance evolves across multiple rounds of policy strengthening.
Existing works typically treat policy implementation as a 'dichotomous' event when assessing policy effectiveness. Instead, my paper leverages several policy-intensifying events, and examines how the magnitude of policy avoidance evolves across multiple rounds of policy strengthening.
I exploit the gradual intensification of Seoul’s low-emission-zone driving ban on high-polluting vehicles—an increasingly common policy tool to reduce urban pollution worldwide. I focus on shifts in travel time to non-regulated hours as a form of policy avoidance behavior.
I exploit the gradual intensification of Seoul’s low-emission-zone driving ban on high-polluting vehicles—an increasingly common policy tool to reduce urban pollution worldwide. I focus on shifts in travel time to non-regulated hours as a form of policy avoidance behavior.
Website: sites.google.com/view/hayeonj...
Research Areas: Environmental Economics, Behavioral Economics, Applied Microeconomics
Website: sites.google.com/view/hayeonj...
Research Areas: Environmental Economics, Behavioral Economics, Applied Microeconomics