Evidence That the Accuracy of Self-Reported Lead Emissions Data Improved: A Puzzle and Discussion
Journal of Risk and Uncertainty
We investigate the accuracy of facility-reported data both within and across emissions and off-site transfer inventories of lead (Pb) in time. We build on recent work using Benford's Law to detect statistical anomalies in large data sets. Our application exploits a regulatory experiment to test for systematic changes in firm behavior triggered by the 2001 implementation of the Final Rule, a major regulatory change governing the U.S. Environmental Protection Agency's (EPA) oversight of lead emissions. Statistical results show that the EPA's Final Rule functioned to significantly improve the accuracy of facility-reported lead data. This finding is surprising because abatement requirements increased and both the probability of firm audit and expected penalties for misreporting apparently decreased in the post-Final Rule period. To explain this counterintuitive result we develop a reporting model for the firm. We argue that organizational investments made in response to specific requirements of the Final Rule, as well as rising public awareness of the risks of lead, may have induced firms to report more accurately.
Zahren, Sammy, Terrence Iverson, Stephan Weiler, and Anthony Underwood. "Evidence That the Accuracy of Self-Reported Lead Emissions Data Improved: A Puzzle and Discussion." Journal of Risk & Uncertainty 49, no. 3 (2014): 235-57.