Replication data for: Clunkers or Junkers? Adverse Selection in a Vehicle Retirement Program
Principal Investigator(s): View help for Principal Investigator(s) Ryan Sandler
Version: View help for Version V1
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LICENSE.txt | text/plain | 14.6 KB | 10/13/2019 03:20:AM |
Project Citation:
Sandler, Ryan. Replication data for: Clunkers or Junkers? Adverse Selection in a Vehicle Retirement Program. Nashville, TN: American Economic Association [publisher], 2012. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-13. https://doi.org/10.3886/E114803V1
Project Description
Summary:
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Vehicle retirement programs have become popular tools of public policy for reducing pollution. The efficacy of these programs is difficult to measure, as it is difficult to tell how much a vehicle would have polluted otherwise. I estimate that counterfactual using data from a long-running local program in California. I utilize the universe
of emissions inspections from the California Smog Check Program to construct vehicle usage histories of retired cars and similar vehicles which did not retire early. I find that the program's cost-effectiveness steadily declined over time because of the depreciation of the vehicle fleet, while adverse selection remained a problem throughout. (JEL D82, Q53, Q58, R48)
Scope of Project
Subject Terms:
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vehicle emissions inspections
JEL Classification:
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D82 Asymmetric and Private Information; Mechanism Design
Q53 Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
Q58 Environmental Economics: Government Policy
R48 Transportation Economics: Government Pricing and Policy
D82 Asymmetric and Private Information; Mechanism Design
Q53 Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
Q58 Environmental Economics: Government Policy
R48 Transportation Economics: Government Pricing and Policy
Geographic Coverage:
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California, U.S.
Time Period(s):
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1998 – 2010
Universe:
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Vehicle emissions inspections in California
Data Type(s):
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administrative records data
Methodology
Data Source:
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California Bureau of Automotive Repair Smog Check database
Unit(s) of Observation:
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vehicles,
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