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Business and Environment

Paper Session

Monday, Jan. 4, 2021 10:00 AM - 12:00 PM (EST)

Hosted By: Association of Environmental and Resource Economists
  • Chair: Paige Weber, University of North Carolina-Chapel Hill

Pollution and Acquisition: the Environmental Justice Effects of Mergers

Irene Jacqz
,
Harvard University and Iowa State University

Abstract

I estimate the effect of mergers and acquisitions on both facility-level high-risk air pollution, and also the distribution of toxic air pollution within firms as the number and geographic distribution of their held facilities changes. This work improves our understanding of the supply-side of neighborhood-level pollution, which has been widely shown to threaten long-term health and cognition, particularly for vulnerable populations.
Even though the majority of Toxics Release Inventory facilities—the major contributors of harmful point-source industrial emissions at scale in the U.S.—are owned by parent companies who control at least ten, and sometimes hundreds of separate plants, we know relatively little about the role of firm decisions in the allocation of high-risk air pollution across plants.
The effect of a merger on facility emissions is not obvious: acquiring companies tend to be larger and better-resourced, and may implement more efficient pollution control; on the other hand, a merger may enable firms to reduce risky emissions in more advantaged communities, where the expectation of regulation is higher. Since acquisition is endogenous to the operation and emissions of an event study design that allows for treatment effect heterogeneity.
Over the study period from 2001–2018, I find emissions fall substantially at target facilities after an acquisition, and many close down entirely. Reductions are consistent with parent companies reducing activity and improving pollution-control practices. However, with a larger set of facilities available to polluting firms, I also find evidence of a redistribution of pollution within parent companies to facilities in more-disadvantaged neighborhoods. This result suggests consolidation in polluting sectors may enhance environmental inequality, and raises the question of whether regulators should consider the distributional effects of mergers in heavily polluting industries.

Public Pressure and Heterogeneous Effects of Voluntary Pollution Abatement

Ruohao Zhang
,
Binghamton University
Neha Khanna
,
Binghamton University

Abstract

With widespread environmental awareness, polluters face abatement pressure from two sources: formal regulation pressure and informal public pressure. While the impact of formal regulation on plant emissions is well understood, the role of public pressure in reducing pollution is less clear. We build a conceptual model highlighting the role of public pressure in environmental regulation in the context of voluntary pollution abatement. The launch of a voluntary pollution abatement program affects both regulatory pressure and public pressure albeit differently for participants and non-participants. Our theory describes these changes as well as the emission choices. We show that the effectiveness of a voluntary pollution abatement program depends on the cost from public scrutiny of participating firms and the associated risk of being labeled greenwashers: greater public scrutiny yields fewer program participants who free-ride thereby increasing the effectiveness of the program. Our model, which provides a framework for reconciling the mixed empirical results on the effectiveness of voluntary pollution abatement programs, is supported by data from the EPA's 33/50 program.

Does Uber Increase Congestion and Pollution? Evidence from California

Chandra Krishnamurthy
,
Swedish University of Agricultural Sciences
Nicole Ngo
,
University of Oregon

Abstract

Transport Network Companies (TNCs), like Uber and Lyft, organize transportation services using smartphone-based applications that match passengers to drivers with personal vehicles offering up rides. In the past few years, Uber and Lyft have rapidly expanded into several hundred cities across the world and continue to grow. While research is emerging on the social welfare impacts of TNCs, ranging from congestion to public health, less is known regarding the impacts of Uber on congestion and air quality in urban areas. A priori, it is unclear if TNCs should worsen or improve congestion, making it also difficult to assess its effects upon air quality. We observe the effects of TNCs, specifically Uber, at a more granular temporal resolution that allows us to investigate variation across and within days. We focus on local and regional air pollutants. We leverage a natural experiment and exploit the spatial and temporal variation of Uber’s entry into different urban areas in California using a difference-in-difference (DiD) model. This variation is exogenous, in that other factors affecting congestion or air quality are likely not correlated to Uber enters the market in a given city (which is based partly on market and bureaucratic factors). We utilize a rich dataset on different congestion measures along freeways in California through the Caltrans Freeway Performance Management System (PeMS), which has information on traffic congestion at the hourly level. In addition, we observe the effects of TNCs on air quality in these counties, where vehicle emissions are a major pollution source. Our preliminary results suggest that the entry of Uber into a county is associated with significant reductions in NOx and CO and marginally significant to insignificant reductions in PM2.5 and PM10.

The Effect of Peer Comparisons on Polluters: A Randomized Field Experiment among Wastewater Dischargers

Paul J. Ferraro
,
Johns Hopkins University
Dietrich Earnhart
,
University of Kansas

Abstract

To help achieve environmental policy goals, behavioral scientists advocate a new breed of voluntary approaches. Proponents of these approaches argue that self-enforcing, voluntary behavioral change can be achieved cost-effectively by leveraging attributes of decision-making that deviate from the traditional neo-classical economics model of human behavior.
One increasingly popular approach leverages social norms through the provision of peer, or social, comparisons. Peer comparisons combine descriptive and injunctive messages about social norms. Dozens of field experiments report that these comparisons encourage pro-environmental behaviors among consumers. Consumers, however, are not the only sources of environmental externalities. Firms and other organizations also damage the environment. Organizations, however, may not respond to peer comparisons in the same way that consumers respond because organizations have different objectives, constraints, and decision-making processes than consumers have. Whether the results of prior studies of peer comparisons generalize to polluting facilities is thus an open question.
To help answer this question, and to shed light on the intrinsic motivations of facility managers, we ran a randomized field experiment with a registered, pre-analysis plan. We randomized 328 municipal wastewater treatment facilities to a treatment group or a control group. Facilities in the treatment group received a certified letter that contrasted, using text and a graphic, each facility’s discharge behavior to the behaviors of all municipal facilities in the state. The control group received nothing (status quo condition). With a pre-treatment period of one year and post-treatment period of two years, we estimated the short-run and longer-run treatment effects on the degree to which facilities complied with discharge limits under the U.S. Clean Water Act. We also explored how the effects were moderated by facility size, compliance history, and degree of regulatory scrutiny. We conclude the presentation with an update on an ongoing replication to more states and more economic sectors.
Discussant(s)
Ralf Martin
,
Imperial College London
Andreas Gerster
,
University of Mannheim
Jonathan D. Hall
,
University of Toronto
Paige Weber
,
University of North Carolina-Chapel Hill
JEL Classifications
  • Q5 - Environmental Economics