Funded Faculty Research

Prakash Mishra, Applied Economics Doctoral Candidate, The Wharton School; Arthur van Benthem, Associate Professor of Business Economics and Public Policy, The Wharton School 

Since 1982, carbon emissions from deforestation are valued at $2 trillion of damages with a $51 social cost of carbon. Agriculture drives half of these emissions. I ask how much of agriculture-induced deforestation is efficient, and where efficient deforestation should occur. Using a globally estimated trade general equilibrium model over 1.6 million plots of land, I establish three descriptive empirical facts concerning globally efficient deforestation. First, at a 95% confidence interval, I reject 80% of deforestation since 1982 as inefficient. This deforestation has too low an economic return for a high environmental damage. In the numbers, efficient deforestation at a $51 social cost of carbon costs 12% of global agricultural production. Second, the deforestation tax is regressive across countries. The bottom quartile of countries by income bear nearly 100% of global abatement costs. I explore how to create a just and equitable forest pricing policy which alleviates these costs to world’s poorest. Third, should the EU propose bilateral trades, such as a payment for ecosystem services, with forested nations, it can support nearly efficient forest levels in most tropical nations. However, when the EU does not internalize full marginal benefits of carbon damages, they should preserve African or Russian forest over the Amazon to save forest at low cost. These experiments provide a blueprint for implementing value-add in global offset markets and REDD+ contracts like the Amazon Fund. In sum, this paper situates much of the prior literature’s focus on the Brazilian Amazon in a globally consistent framework for measuring marginal abatement costs for deforestation.

Ben Keys, Rowan Family Foundation Professor, Professor of Real Estate, Professor of Finance, The Wharton School; Philip Mulder, Assistant Professor of Risk and Insurance, University of Wisconsin-Madison School of Business

The goal of this research project is to understand how increasing homeowner’s insurance costs due to climate change are affecting housing markets. First, we will show geographically where homeowners premiums have been rising the most and how those changes are related to insurance market competition and regulation, the cost of building materials and labor, and physical risk. Second, we will show how higher premiums have affected home prices as well as the kinds of coverage homeowners buy and how they shop for homeowner’s insurance.

Arthur van Benthem, Associate Professor of Business Economics and Public Policy, The Wharton School; Joseph Shapiro, Associate Professor of Agriculture & Resource Economics, UC Berkeley

This research quantifies the social welfare consequences of a prominent environmental policy for transportation, and then assesses the distribution of economic costs and environmental benefits across racial and income groups. We study smog check vehicle inspections, which regulate emissions of older vehicles owned by households in the US, which are responsible for an enormous share of local air pollution. This policy has regressive costs but potentially progressive environmental benefits, making incidence complex but important to quantify. We will use an individual-vehicle data set on where cars are registered, where they are driven, how much pollution they emit before and after testing,
and how emissions reductions translate to environmental and health benefits at a very granular geographical level. The findings of this research project should fill an important gap in our understanding of the efficiency and fairness of mobile-source pollution policies.

Santiago Gallino, Charles W. Evans Distinguished Faculty Scholar, Associate Professor of Operations, Information and Decisions, The Wharton School; Alexander Hübner, Professor of Business Administration, Technical University of Munich; Konstantin Wink, Research Associate and Doctoral Student, Technical University of Munich

This research project, in collaboration with faculty from TUM and a leading German retail chain, aims to address a critical gap in retail operations research by empirically investigating the impact of grocery store characteristics on food waste. Leveraging a rich dataset provided by our industry partner, this study examines how factors such as sales area, market type, assortment depth, managerial decisions, and external elements like neighborhood purchasing power and market competition density influence food waste in the retail sector. This research not only contributes to academic knowledge by filling a research void but also provides actionable insights for the retail sector, enhancing both economic efficiency and environmental sustainability.

Jean-Marie Meier, Visiting Assistant Professor of Finance, The Wharton School; Steven Xiao, Associate Professor of Finance and Managerial Economics, Naveen Jindal School of Management, The University of Texas at Dallas

How do ESG practices, in particular environmental and social (E&S) practices, diffuse throughout the economy? Moreover, how does the diffusion of E&S practices differ at the firm-level compared to the economy-wide level? At the microeconomic level, a firm could improve the E&S performance of its existing products. Alternatively, the same firm could replace its “brown” products with “green” products. Or are companies offering both green and brown products and within-firm consumer demand for these different products changes over time, resulting in different market shares for these products? At the economy-wide level, an improvement in aggregate E&S policies could arise from existing companies offering more E&S-friendly products or from “brown” firms (potentially incumbents) exiting the marketplace while “green” firms (potentially start-ups) enter.

Sandra Schafhaütle, Assistant Professor of Accounting, The Wharton School; Gurpal Sran, Assistant Professor of Accounting, NYU Stern

We study the effects of local environmental regulations on the disclosure decisions and real behaviors of firms at various points in the supply chain. We exploit countries’ ratification of various local environmental regulations as a shock to firms’ disclosure and investment incentives. Because firms positioned in the upstream, midstream, or downstream of supply chains have different economic incentives, we expect differences in their disclosure behavior regarding commitments to address environmental outcomes (such as deforestation) and differences in real activities (such as supplier audits). With our research, we aim to shed light on how firms throughout the supply chain face not only heterogeneous disclosure incentives but also heterogeneous costs and benefits in taking real actions in line with their disclosed commitments.

R. Jisung Park, Assistant Professor of Business Economics and Public Policy, The Wharton School; Nora Pankratz, Economist, Federal Reserve; A. Patrick Behrer, Research Economist, Developmental Economics, World Bank

Adapting to climate change will require economic agents to make a wide range of investments. Central to the debate is the role of government intervention in facilitating such adaptation. One view is that firms and their employees will manage this process efficiently, voluntarily engaging in protective investments that increase resilience. An alternative possibility is that take up of protective technologies and behaviors is hindered by market frictions, necessitating government intervention. For instance, in the case of real estate, emerging evidence suggests that information asymmetries, local spillovers and other market imperfections may limit adaptation investment.

A controversial approach to encouraging climate adaptation among firms is to mandate investments in resiliency. Mandatory standards may help overcome potential market imperfections and foster broader adoption of such investments. However, in a world with heterogeneous employers and workers, some may find themselves coerced into making costly investments they would have preferred to avoid, even if market participants are fully informed and costs are fully internalized. The regulator may also misjudge the magnitude of the risk relative to the costs of mitigation, in which case such policies may increase costs and cause firms to go out of business. Despite potentially wide-ranging implications, there is little empirical evidence regarding the efficacy of mandated adaptation investments and their effects on firms and their employees.

In this paper, we consider the case of workplace heat safety standards in the state of California. The number of days with potentially damaging heat is increasing rapidly and will continue to increase even with aggressive greenhouse gas mitigation. Currently, the heat wave season in the United States is nearly three times longer than in the 1960s, and in the summer of 2022 alone, a record-breaking 400 U.S. locations experienced unprecedented monthly temperatures (Lipton et al. 2018; Stevens and Samenow 2022). Climate models project increased frequency and intensity of extreme heat events due to ongoing climate change (IPCC 2021). Given its effects on energy costs (Auffhammer, 2018), labor productivity (Hsiang 2011; Somanthan et al, 2021), and worker health (Dillender, 2019), managing the risks posed by heat may pose significant costs on firms.

While there are currently no national workplace protections pertaining to heat exposure, in 2005 California became the first and at the time only state to adopt a mandatory workplace heat safety standard. The standard required firms with outdoor work sites to provide access to shade, water, and rest breaks for all employees, as well as training and safety protocols specific to heat-illness prevention. It was intensively enforced, with over 15,500 inspections, 19,700 citations, and $23.3 million in penalties being issued for the standard over the period 2005 to 2020, and its provisions became binding above an explicit daily temperature threshold, which enables a regression-discontinuity-in-differences (RDiD) research design.

We provide the first comprehensive evaluation of the effect of this mandate on both worker health and productivity and how sensitive they are to changes in temperature (“worker resilience”), as well as its effects on firm costs and profitability, including on such measures as costs of goods sold and how sensitive they are to changes in temperature (“firm resilience”). We then assess how these effects vary along dimensions commonly associated with a range of commonly studied market imperfections, including potential information, labor market, and credit market frictions.

Our analysis takes advantage of detailed administrative data from the nation’s largest worker’s compensation system, which comprises over 16 million injury records matched to injury dates and employer locations over the period 2000 to 2021. Importantly, our approach is robust to potential endogeneity of safety inspections, unlike many previous analyses that rely on publicly available data on workplace injuries and safety violations reported to OSHA (for instance, Zhao 2023). It is also robust to potential selection on firm characteristics, as we can observe the outcomes for a panel of treated and untreated firms over time. In addition to exploiting the plausible exogeneity of the policy itself, which was adopted as an “emergency order” following a high-profile workplace accident in agriculture, we also leverage the fact that its most stringent provisions are binding only on days above an explicit temperature threshold and to a subset of industries and firms with a large fraction of work tasks occurring outdoors.

We find that hotter temperatures increase workplace injuries significantly. A day with temperatures in the 80F to 90F range increases injuries relative to milder days in the 50s and 60s by 5 to 9 percent. The effect of heat on worker injuries is significantly mitigated after the implementation of the standard. The causal effect of daily temperature above 95 degrees F falls dramatically following the policy, decreasing by over 60 percent relative to the years immediately preceding its adoption.

In ongoing work, we explore whether the standard reduces injuries more acutely in firms with greater baseline exposure, using firm-level measures of outdoor work intensity derived from task-based measures of occupational exposure from O*NET, and detailed industry-level employment characteristics from the OEW. To better understand the broader implications for adaptation policy, we assess the effects of the policy on firms’ costs, leveraging firm-level financial information from COMPUSTAT, as well as on employment and wages of affected workers.

Sergey Sarkisyan, Doctoral Candidate in Finance, The Wharton School; Mirko Heinle, Associate Professor of Accounting, The Wharton School; Irina Luneva, Doctoral Candidate in Accounting, The Wharton School

We study cost and sources of debt for companies with poor ESG performance. We find that, while both loan and bond financing is costlier for borrowers with poor ESG performance, “brown” firms face a lower extra premium for borrowing from banks than “green” firms. In addition, companies with poorer ESG performance obtain larger bank loans and borrow smaller amounts from the public bond market, gradually shifting their debt structure towards more bank-loan-heavy. We test three explanations for our findings: banks’ closer relationship with borrowers allowing them to charge a lower premium for poor ESG performance, public debt holders’ inherent preference for high ESG performance firms, and public debt holders being subject to stricter ESG regulation than banks.

Susanna Berkouwer, Assistant Professor of Business Economics and Public Policy, The Wharton School; Joshua Dean, Assistant Professor of Behavior Science and Economics, Booth School of Business, University of Chicago

What investments should businesses, governments, and civil society target to maximally reduce greenhouse gas emissions? Economic efficiency would prioritize investment opportunities that generate the largest reduction in greenhouse gas emissions per dollar spent. Through two related research projects, this research will evaluate what types of opportunities will best enable maximal reduction in greenhouse gas emissions, and what barriers the global economy currently faces in achieving this allocation.

In the first research project, I plan to quantify a low-cost emissions reduction investment: the switch from biomass cooking (charcoal or wood) to electric induction stoves. This generates not only large environmental benefits (a charcoal stove generates roughly the same emissions per year as a gasoline vehicle) but also large private benefits for low-income families (through reductions in energy expenditures, since electricity is significantly more efficient in converting energy to heat). I study this in the context of an induction stove developed by a Kenyan company, with a factory in Nairobi.

In the second research project, I study why firms based in the U.S. might invest in high-cost types of abatement (such as Amazon’s recent electric vehicle announcement) instead of lower-cost abatement, such as the cookstoves. Specifically, I explore how customer perceptions of ethics and morals drive a preference for companies that undertake the former.

Serguei Netessine, Dhirubhai Ambani Professor of Innovation and Entrepeneurship, Professor of Operations, Information and Decisions, Senior Vice Dean for Innovation and Global Initiatives, The Wharton School; Vishrut Rana, PhD. Candidate in Operations, Information and Decisions, The Wharton School; Christian Kaps, Assistant Professor of Business Administration, Harvard Business School

Grid-scale electricity storage technologies enable better matching of electricity supply with demand by storing excess electricity during periods of low demand and releasing it during periods of high demand. As the share of variable renewable energy resources, like wind and solar, increases, the supply of electricity becomes more intermittent, and storage technologies serve as an important complement that help smooth out fluctuations in generation. Due to this, storage – like lithium ion batteries that account for 90% of US electricity storage capacity – is widely regarded as a crucial part of the clean energy transition. While batteries can earn revenues from multiple streams in wholesale electricity markets, a significant portion of the revenue comes from arbitrage – charging when prices are low, often in periods of high renewable electricity production, and discharging when prices are high, often when renewable generation falls and/or as total system demand increases.

Because of this arbitrage-driven revenue, battery operators choose to locate their resources in locations with high variability in nodal prices (i.e., locational marginal price). However, current practices for locating battery investments are unable to account for changes in price volatility at the location of interest under changing market conditions of the future, and may potentially overestimate future volatility leading to inefficient investments. To address this challenge of selecting locations for batteries, we develop a structural model for electricity price formulation using historical price, demand, renewable generation, and transmission data from various nodes in Texas. Using this model, we estimate revenues from arbitrage and predict future revenues under changing market conditions. Results from our model can help battery operators identify optimal locations for storage investments and help system operators study market performance under different demand and renewable generation growth scenarios in the presence of storage technologies.

In the first research project, I plan to quantify a low-cost emissions reduction investment: the switch from biomass cooking (charcoal or wood) to electric induction stoves. This generates not only large environmental benefits (a charcoal stove generates roughly the same emissions per year as a gasoline vehicle) but also large private benefits for low-income families (through reductions in energy expenditures, since electricity is significantly more efficient in converting energy to heat). I study this in the context of an induction stove developed by a Kenyan company, with a factory in Nairobi.

In the second research project, I study why firms based in the U.S. might invest in high-cost types of abatement (such as Amazon’s recent electric vehicle announcement) instead of lower-cost abatement, such as the cookstoves. Specifically, I explore how customer perceptions of ethics and morals drive a preference for companies that undertake the former.

Vinay Subramanian, Doctoral Student in Management, The Wharton School; Tyler Wry, Associate Professor of Management, The Wharton School 

We would like to empirically study the role played by impact investors in investments. We will build a panel dataset of impact and non-impact portfolio firms to investigate the selection and treatment effects of impact investors. These effects would potentially include the additionality and “extra-financial” value add of impact investors. We would like to augment data available from WRDS and other Wharton sources with paid data from Pitchbook as well as webscraped data and other textual sources. In addition, we would also like to explore collaboration with the impact investing research lab, especially with regards to potential usage of the leading impact finance database (IFD). We would like to pursue this line of enquiry further to study if impact funds engage in “greenwashing” and understand heterogeneity within impact investors.

Guilherme Siqueira, Doctoral Student of Legal Studies & Business Ethics, The Wharton School; Brian Feinstein, Assistant Professor of Legal Studies & Business Ethics, The Wharton School

Firms often break the law expecting to benefit from it, corruption practices being a typical example. Although there is a growing body of literature on explaining why firms adopt illegal strategies, almost no attention has been paid thus far to the strategic dimensions involved in pursuing unlawful strategies. While research has usually focused on explaining the selection of unlawful courses of action vis-a-vis law-abiding alternatives, the selection of a particular unlawful strategy among equally law-breaking alternatives remains largely unclear. That gap might be explained partly due to the challenge of gathering data on corporate illegality, which is usually surrounded by secrecy.

In 2014, Brazilian law enforcement authorities initiated what many consider to be the largest anticorruption investigation in history – Operation Car Wash, which sent ripples across Latin America. In Brazil, the investigation lasted seven years and resulted in over 300 convictions, including top executives from some of the largest companies in Latin America, such as Petrobras, Odebrecht and J&F. Through its investigations, Car Wash was able to gather an unprecedented volume of documents and information on wrongdoings committed by multiple Brazilian corporations, including long testimonies from hundreds of executives and records of illegal transactions spanning almost three decades. Given the well-known challenges of gathering data on corporate illegal behavior, Car Wash’s unique collection of data provides a rare opportunity to dive into the details of the illegal strategies pursued by the companies involved.

Although the majority of those records are no longer covered by judicial secrecy, that incredibly rich source of data remains largely unexplored by organizational scholars, and much of it risks being lost. The “Car Wash Archive” is an effort to collect and systematize archival data from Operation Car Wash, thus enabling a wide range of research projects to be derived from it.

The first stage of the project (for which funding is now requested) consists in gathering the documents and testimonies that resulted from plea-agreements with six large construction companies: Odebrecht, Andrade Gutierrez, Camargo Correa, OAS, UTC and Engevix. This incredibly valuable dataset would allow unprecedented insight into decision-making processes of law-breaking firms.

Sagar Saxena, Assistant Professor of Business Economics and Public Policy, The Wharton School; Shresth Greg, Doctoral Candidate in Economics, Harvard Business School

The Indian government spends almost 1% of India’s GDP on payments to fertilizer producers as part of a scheme to subsidize fertilizers for agricultural use. In particular, the government awards fertilizer producers a fixed price for their output, determined by production and investment costs, and then sells the fertilizers to farmers at a highly subsidized price. This scheme is an important part of the government’s strategy aimed at enhancing food security and increasing farmer incomes. However, for decades, this scheme has been subject to widespread criticism and remains a hotly debated issue among economists and policymakers. While there is evidence suggesting that the subsidies have spurred increased fertilizer use and agricultural productivity, critics argue they also distort market dynamics and diminish incentives for producers to enhance efficiency and reduce costs. Despite being in place for nearly six decades, the scheme has been subject to minimal reforms. In this paper, we study the equilibrium impact of fertilizer subsidy reform on the supply-side of this market. In particular, we examine how entry, exit, investment, and production decisions would change under alternative subsidy mechanisms. To do so, we develop a dynamic structural model of the fertilizer industry in India which we will estimate using firm-level data on production and investment decisions. Using this structural model, we plan to simulate several counterfactuals including (1) no subsidy, (2) entry/investment subsidy, (3) production subsidy, and (4) competitive procurement auctions wherein the government buys fertilizers from the lowest bidder. These counterfactuals will allow us to understand the equilibrium effects of alternative subsidy mechanisms and provide insights for policymakers.

Seyoun Kim, Doctoral Student in Healthcare Management and Economics, The Wharton School; Claudio Lucarelli, Associate Professor of Healthcare Management, The Wharton School

The global population is aging rapidly, and this progression will put increasing pressure on society to care for the growing population of elderly. This means a growing demand for caretaking support, both informal and formal. The United States has relied on congregate living settings such as nursing homes to provide formal caretaking support, however, the COVID-19 pandemic highlighted the advantages of aging at home and in the community. Concurrent to the aging population is the increasing secularization of society. Participation in religious communities has steadily declined over the past few decades. Historically, religious communities were a source of social support that the elderly could rely upon as they aged at home. The elderly that no longer go to church lose the community and support that helps them live independently and may be more at risk of needing formal caretaking in a setting such as a nursing home. The historical decline in religious participation may be a useful case study in understanding how the attrition of longstanding community institutions affect society as it increasingly moves into the virtual realm, especially with the rise of artificial intelligence.

Zorina Chen, Doctoral Student in Management, The Wharton School; Matthew Bidwell, Xingmei Zhang and Yongge Dai Professor, Professor of Management, The Wharton School

Despite research documenting the persistent labor market challenges experienced by immigrants, little is known about how immigrants navigate the recruitment process of elite industries in the United States. Drawing on the cultural matching theory, I will comparatively examine how first-generation immigrants from East Asian countries perceive and cope with the sociocultural inequalities facing them as they seek elite jobs in the US based on interviews with first-generation and second-generation East Asian immigrants and White Americans. Ethnographic observations of networking events, career fairs, and career panels will be conducted to generate additional insights. By exploring mechanisms embedded in social interactions that reproduce inequalities in elite labor markets–whose recruitment processes are known to be networking-intensive–I attempt to expand the current understanding of immigrants in labor markets and how certain hiring practices reinforce socioeconomic inequalities.

Aparajita Agarwal, Doctoral Candidate in Management, The Wharton School; Tyler Wry, Associate Professor of Management, The Wharton School

This study examines the trade-offs involved as organizations either scale “up” for widespread impact or scale “deep” for localized, enduring impact in resource-constrained emerging markets. Employing a randomized control trial in two settings – first, with 400 community female agents (intermediaries) of a digital platform and second, with 120 agents of an agri-tech firm in rural India, we investigate the implications of these scaling strategies on agent-level behavior and outcomes and on the social impact created. The study intends to examine the trade-offs among transaction activity, agent satisfaction, and agent engagement with low-income customer segments that accompany the scaling choice. The research seeks to extend the discussion on scaling to include agent-level outcomes, thereby offering nuanced insights into scaling trade-offs in complex environments in the management literature.

Ashley Litwin, Doctoral Student in Applied Economics, The Wharton School; Judd Kessler, Howard Marks Professor of Business and Economic Public Policy, The Wharton School

Hospital emergency departments (ED) play a critical role in the U.S. healthcare system. In 2019, there were over 151 million ED visits across the country, or 46.6 visits per 100 people (Cairns, Ashman and Kang, 2022). Under federal law, emergency departments are required to provide care to all patients (Lulla and Svancarek, 2022). However, hospitals have substantial discretion as to the timeliness of care. The primary system that determines a patient’s wait time, and potentially their subsequent health outcomes, is triage, designed so that the sickest patients are seen by the doctor first. Despite the importance of this process, little is known about how triage decisions are made in practice.

Aparajita Agarwal, Doctoral Candidate in Management, The Wharton School; Tyler Wry, Associate Professor of Management, The Wharton School

This study examines the trade-offs involved as organizations either scale “up” for widespread impact or scale “deep” for localized, enduring impact in resource-constrained emerging markets. Employing a randomized control trial in two settings – first, with 400 community female agents (intermediaries) of a digital platform and second, with 120 agents of an agri-tech firm in rural India, we investigate the implications of these scaling strategies on agent-level behavior and outcomes and on the social impact created. The study intends to examine the trade-offs among transaction activity, agent satisfaction, and agent engagement with low-income customer segments that accompany the scaling choice. The research seeks to extend the discussion on scaling to include agent-level outcomes, thereby offering nuanced insights into scaling trade-offs in complex environments in the management literature.

Harriet Jeon, Doctoral Candidate in Healthcare Management, The Wharton School; Hummy Song, Assistant Professor of Operations, Information and Decisions, Associate Professor of Healthcare Management, The Wharton School; Song-Hee Kim, Associate Professor of Operations Management, Seoul National Unversity; Kyeongsu Kim, Samsung Medical Center; Sang Won Seo, Samsung Medical Center; Jeong Hee Hong, Samsung Medical Center

Shifts are the dominant way to work in many contexts requiring 24/7 coverage, including call centers, police departments, and hospitals. While the detriments of shift work are well-documented both at the individual and organizational levels, its deployment is often unavoidable given round-the-clock staffing needs. We explore a potential operational lever—incorporating heterogeneous preferences over shift design—to mitigate ramifications of shift work in the context of acute care bedside nurses. Using survey, administrative, and shift data, we examine whether and the extent to which individual choice over dimensions of their shifts mitigates the impact of shift work on work (dis)satisfaction and turnover of nurses.

Ruochen Sun, Doctoral Candidate in Healthcare Management, The Wharton School; Abby Albert, Assistant Professor of Healthcare Management, Dorinda and Mark Winkelman Distinguished Faculty Scholar, The Wharton School

Regulating the provision of product information is common in many industries. Increasing the provision of product information could improve consumer’s choices while the provision of product information imposes private and social costs. This project studies this trade-off in the context of the pharmaceutical industry’s provision of pediatric clinical trial data. Up to 60% of prescription medications given to children in the U.S. are for off-label, non-FDA approved uses lacking safety and efficacy data for pediatric populations. By linking drug patents, clinical trials, and health insurance claims data, we document the equilibrium level of pediatric trial provision and patterns of off-label prescription drug use among children. We then estimate a structural model to quantify the costs and benefits of additional pediatric trial requirements and simulate alternative policy options.

Ben Keys, Rowan Family Foundation Professor, Professor of Real Estate, Professor of Finance, The Wharton School; Philip Mulder, Assistant Professor of Risk and Insurance, University of Wisconsin-Madison School of Business

The goal of this research project is to understand how increasing homeowner’s insurance costs due to climate change are affecting housing markets. First, we will show geographically where homeowners premiums have been rising the most and how those changes are related to insurance market competition and regulation, the cost of building materials and labor, and physical risk. Second, we will show how higher premiums have affected home prices as well as the kinds of coverage homeowners buy and how they shop for homeowner’s insurance.

Jean-Marie Meier, Visiting Assistant Professor of Finance, The Wharton School; Steven Xiao, Associate Professor of Finance and Managerial Economics, Naveen Jindal School of Management, The University of Texas at Dallas

How do ESG practices, in particular environmental and social (E&S) practices, diffuse throughout the economy? Moreover, how does the diffusion of E&S practices differ at the firm-level compared to the economy-wide level? At the microeconomic level, a firm could improve the E&S performance of its existing products. Alternatively, the same firm could replace its “brown” products with “green” products. Or are companies offering both green and brown products and within-firm consumer demand for these different products changes over time, resulting in different market shares for these products? At the economy-wide level, an improvement in aggregate E&S policies could arise from existing companies offering more E&S-friendly products or from “brown” firms (potentially incumbents) exiting the marketplace while “green” firms (potentially start-ups) enter.