Principal investigator: Eduarda Miller Figueiredo
Original title: Escalation of Scrutiny: The Gains from Dynamic Enforcement of Environmental Regulations
Authors: Wesley Blundell, Gautam Gowrisankaran and Ashley Langer.
Location of the Intervention: United States
Sample Size: 107.705 factories
Sector: Environment
Primary Variable of Interest: Value of fines and damages caused by pollution.
Type of Intervention: Inspection
Methodology: GMM
Summary
O Clean Air Act This refers to legislation aimed at reducing pollution in the United States, where the U.S. Environmental Protection Agency (EPA) uses dynamic enforcement as a method of accountability in cases of non-compliance with environmental legislation. In other words, the EPA designates repeat offenders as “high priority violators"(HPV), exposing them to a high level of investigation and fines. This article quantifies the gains from dynamic enforcement, also taking into account its benefit in reducing the damage caused by pollution. The results demonstrate that dynamic fines are effective in reducing the damage caused by pollution."
- Policy Problem
In the United States, legislation to reduce pollution (Clean Air ActThe regulation reduced air pollution damage by US$35.5 trillion from 1970 to 1990. However, this same regulation also had a significant impact on all industrial facilities in the country due to compliance costs: US$831 billion. Therefore, understanding the efficiency of regulatory monitoring and enforcement mechanisms for pollution control is crucial.
The United States Environmental Protection Agency (EPA)[1] It uses dynamic application, where regulatory actions are based on the firm's past performance history to enforce amendments. Clean Air Act (CAA) (Landsberger and Meilijson, 1982; Shimshack, 2014). Specifically, the EPA designates repeat offenders as “high priority violators(HPV)[2], exposing them to a high level of scrutiny and fines. Dynamic enforcement can add value when imposing fines is costly for the regulator and also when the regulator cannot afford the compliance costs of regulatory policies.
The work analyzed here seeks to quantify the gains from the dynamic application of CAA, also taking into account its benefit in reducing the damage caused by pollution and weighing this against the compliance costs for plants and regulators.
- Implementation and Evaluation Context
Figure 1: Application of Clean Air Act EPA Regulatory Status
Source: Blundell et al. (2020).
Figure 1 shows the average inspection rates, violation rates, and fines for compliant factories, regular violators, and “violators of high priority"(HPVs). In each case, it is clearly shown that the level of scrutiny increases dramatically with HPV status."
The EPA divides the United States into ten geographic regions, with the agency's guidance being that regions and states may adopt varying approaches to improve state enforcement programs (EPA, 2013). Thus, EPA regions and states represent geographic areas in which the interpretation of federal policy and enforcement preferences may vary.
- Policy/Program Details
A Clean Air Act It was approved in 1963 in the United States as an effort to improve air quality. The EPA was created to enforce air pollution standards and other environmental legislation.
The CAA grants the EPA the authority to regulate air pollution criteria.[3] and various hazardous air pollutants. The CAA primarily requires command and control regulations, which mandate that pollution from plants be at or below limits achievable with best technologies and practices. The enforcement regime includes a permitting system, inspections, violations, and fines.
All factories – whether compliant or not – could be inspected regularly. The frequency of these inspections depended not only on differences between states and regions in budgets and implementation priorities, but also on the size of the factory and whether the factory was in an area not covered by the National Ambient Air Quality Standards (NAAQS).[4].
Fines are calculated using two main components: the activity of the violation and the economic benefit the factory received from the violation (EPA, 1991). The severity component of each violation is determined primarily from the actual or potential harm of the violation: (i) level of violation; (ii) toxicity of the pollutant; (iii) the sensitivity of the environment into which the pollutant is released; and (iv) the duration of the violation.
- Assessment Method
To carry out the research, the following databases were used: (i) Online Environmental Compliance History (ECHO)[5]; (ii) Texas Commission on Environmental Quality (TCEQ)[6]National Emissions Inventory[7]ECHO Air Emissions Data[8], National Ambient Air Quality Standards (NAAQS), AP3 (Clay et al., 2019). The study was limited to seven of the most polluting industrial sectors of the North American Industrial Classification System (NAICS), which are: mining and extraction, utilities, manufacturing: food and textiles; manufacturing: wood and petroleum, manufacturing: metal, transportation, educational services. The data covers 107.705 unique factories.
In the dynamic model used for this research, plant decisions are a function of their regulatory status. First, the authors estimate the cost for industrial facilities complying with the EPA's current dynamic approach. Then, they simulate the value of alternative enforcement regimes to affect plant emissions and compliance with the EPA's regulatory framework. Furthermore, the authors specified a fixed grid of potential cost parameters and estimated the population weights for each. Finally, they used the Generalized Method of Moments (GMM). From the estimated cost parameters, they evaluated the gains of the dynamic application by calculating pollution damage, assessed fines, and other outcomes when plants optimize under counterfactual regulatory policies.
- Main results
The estimation results demonstrated that investments, inspections, violations, fines, and HPV status are costly for factories, with significant effects on investments, fines, and HPV status. Estimates of the GMM random coefficients showed that investments equate to a $450.000 fine, HPV status equates to a $5.600 fine per quarter, and each inspection equates to a $37.400 fine.
The authors emphasize that understanding the absolute magnitude of the coefficients found is complicated by the fact that fines can be more expensive than the value assessed by the EPA. That is, resolving fines involves additional legal work for the factory and damages its reputation. Therefore, the cost to the factory of a $1 fine can be substantially greater than $1, which, in turn, implies that if an investment is equivalent to $450.000 in fines, then the cost to the factory will be far beyond that amount.
It is also shown that 1,9% of factories have a small but negative average investment cost, equivalent to a US$ -20.300 fine per investment. These factories have extremely high inspection costs (equivalent to a US$ 330.000 fine), violations (a US$ 266.600 fine), and HPV status (a US$ 323.900 fine per quarter), and can be very averse to environmental enforcement activities relative to the investment.
By modeling how EPA enforcement activities, investments, overall compliance, and air pollution damage would change under different EPA policies, large increases are found in the share of factories in HPV status and pollution damage. In particular, they find that HPV status would increase from 1,4% to 30,8%. However, the investment rate falls only moderately, suggesting that heterogeneity in the types of factories investing and the timing of their investment is important.
Furthermore, given the higher level of factories with HPV status, much higher levels of damage caused by air pollution are also found. Damage caused by air pollutants increases from US$1,5 million per factory/quarter to US$4 million per factory/quarter. This is strong evidence that dynamic fines are effective in reducing pollution damage, conditional on the level of the fine.
- Lessons in Public Policy
The authors provide evidence that dynamic enforcement is valuable when fines are costly for the regulator: removing dynamic enforcement would increase pollution damage by 164% if fines were kept constant. They also demonstrate that increasing the scale of fines with regulatory status would add little additional value.
References
Clay, Karen, Akshaya Jha, Nicholas Muller and Randall Walsh. 2019. “Database for “External Costs of Transporting Petroleum Products: Evidence from Shipments of Crude Oil from North Dakota by Pipelines and Rail.” Data can be accessed from Nicholas Muller, https://public.tepper.cmu.edu/nmuller/APModel.aspx.
Environmental Protection Agency (EPA). 1991. “Clean Air Act Stationary Source Civil Penalty Policy.” Washington, DC: EPA.
Environmental Protection Agency (EPA). 2013. “National Strategy for Improving Oversight of State Enforcement Performance.” Washington, DC: EPA.
Landsberger, Michal, and Isaac Meilijson. 1982. “Incentive Generating State Dependent Penalty System: The Case of Income Tax Evasion.” Journal of Public Economics 19 (3): 333-52.
Shimshack, Jay P. 2014. “The Economics of Environmental Monitoring and Enforcement.” Annual Review of Resource Economics 6: 339-60.
[1] U.S. Environmental Protection Agency (EPA).
[2] High Priority Violator (HPV).
[3] Ozone (), particulate matter (PM), carbon monoxide (CO), nitrogen oxides (
), sulfur dioxide (
) and lead (Pb).
[4] National Ambient Air Quality Standards (NAAQS).
[5] Environmental Compliance History Online (ECHO).
[6] Texas Commission on Environmental Quality (TCEQ).
[7] National Emissions Inventory.
[8] ECHO's Air Emissions.
