Empirical Applications on Industrial and environmental Hazards€¦ · Industrial and environmental...

Empirical Applications on Industrial and environmental

Hazards

Philippe Gagnepain

Paris School of Economics- Université Paris 1 Panthéon Sorbonne

References

• Alberini, A., & Austin, D. (1999). On and off the liability bandwagon: Explaining state adoptions of strict liability in hazardous waste programs. Journal of regulatory Economics, 15(1), 41-64.

• Ringleb, A. H., & Wiggins, S. N. (1990). Liability and large-scale, long-term hazards. Journal of Political Economy, 98(3), 574-595.

• Sigman, H. (2010). Environmental liability and redevelopment of old industrial land. The Journal of Law and Economics, 53(2), 289-306.

Ringleb and Wiggins (1990)Introduction

• Exposure to large-scale, long-term hazards has emerged as a pressing policy concern.

• Consumers and workers are exposed to health risks associated with radiation, cigarette smoking, saccharin, occupational carcinogens, asbestos, and numerous other latent hazards.

• Numerous studies have also linked occupational cancer to such basic materials as petroleum, coal, paraffin, wood, leather, iron ore, nickel, and chromium, all of which are fundamental inputs to production.

• Tort liability, permits compensation for injuries to be made after parties determine the extent of damages associated with hazardous products and activities.

• Liability can produce both appropriate incentives for firms to provide safety and implicit insurance to injured workers or consumers.


• With latent hazards, liability appears attractive because it permits injury-based compensation in an area in which dangers are difficult to foresee.

• This paper analyzes the use of a liability system in the latent hazard setting.

• It argues that a major option to minimize liability exposure is for firms to segregate risky activities in small corporations.

• Such segregation becomes valuable when latent injuries later manifest themselves and the claimants are restricted to the assets of the small corporation to pay the associated liability damages.

• The authors present empirical evidence that suggests that such firm efforts to avoid liability are widespread.

• This empirical evidence is generated by econometrically analyzing the pattern of entry by small corporations into the U.S. economy over the period 1967-80.

• The analysis shows that changes in liability appear to be closely linked to substantial increases in the number of small firms operating in hazardous sectors.


• The entry of these small firms seems designed primarily to avoid liability.

• The implication is that liability may be difficult to enforce because these small firms have insufficient assets to pay substantial damage awards.

• Hence liability may not lead to large damage awards in long-run equilibrium, but instead may simply lead to a restructuring of enterprises.

Ringleb and Wiggins (1990)Latent hazard and liability

• Latent hazards differ from other hazards both because of the severe nature of potential injuries and because of the long separation between exposure to substances and the manifestation of injury.

• The problem with latent injuries is that potential liabilities are sufficiently large that they can easily come to dwarf the assets of even large, profitable corporations.

• Latent injuries remain dormant for long periods, ranging anywhere from 4 to 40 years and averaging roughly 20 years.

• This latency period creates distinctive enforcement problems for traditional liability systems because such systems are injury-based.

• In other words, damages are generally assessed only for actual and not for speculative or hypothetical damages.

• Hence damages are assessed only after an injury manifests itself.

Ringleb and Wiggins (1990)Latent hazard and liability

• With latent injuries an injury-based system creates a long separation between the activities that lead to injury and damage awards.

• This separation creates severe enforcement problems because it means that damage obligations accrue for many years.

• As time passes, the accumulated damages can become formidable.

• This accumulation is then exacerbated by the nature of the associated injuries.

• The net result is a large incentive to escape payment.

• In such equilibrium, small corporations handle hazards.

• Example: Operation of nuclear reactor is quite safe and involves minimal health hazards. In contrast, cleaning vessel involves intense exposure and hazards.

• These firms then turn over at a high rate to avoid damage payments.

• Then, liability leads neither to incentives for safety nor to compensation for injury.

Ringleb and Wiggins (1990)Empirical model

• The key issue then becomes the empirical question of how steep the trade-off is regarding the cost of vertical divestiture compared with the benefit of avoiding liability payments.

• How do firms respond to recent changes in the liability system?

• The natural way to examine divestiture is to examine how recent changes in the liability system have affected the structure of organizations in risky sectors of the economy.

• The obvious period to examine for these effects is 1967-80, the period surrounding rapid changes in liability law.

• Prior to the mid-1960s, the law offered substantial obstacles to workers seeking damages for latent injuries.

• State workers' compensation programs routinely rejected claims for latent injuries, particularly when the latency period was long and the injury seemed similar to "the ordinary diseases of life.“


• Further, the workers' compensation statutes in nearly all states precluded workers from seeking redress through the court system under tort law.

• Beginning in the late 1960s, numerous changes in the legal environment.

• These changes allowed workers to more easily seek compensation for injuries under tort law.

• Substantial medical and scientific evidence linking occupational exposures to latent disease began to emerge.

• If divestiture is an important response to liability, then these changes in liability should lead to substantial increases in the number of small corporations operating in hazardous sectors of the economy.


• Data: Small corporations operating in various sectors of the economy for the years 1967 and 1980.

• The year 1967 was chosen to precede the rapid changes in the liability system, which occurred primarily in the first half of the 1970s.

• 1980 was chosen to enable firms sufficient time to respond to the changes.

• Small corporations were defined as ones with assets of less than S250,000 in 1980 dollars.

• The data are derived for manufacturing industries using Internal Revenue Service (IRS) data.


• The primary task is to determine the effect of changing liability costs on the rate of entry of small corporations.

• Changing liability costs are created by worker exposures to carcinogens, which translated into increased expected liability costs when workers were given more ready access to tort actions.

• Accordingly, one way to measure expected liability costs is to measure the exposure of workers to carcinogens in the workplace.

• Hence worker exposure in, say, the early 1970s measures prospective future liabilities that would become apparent in the late 1980s or early 1990s.

• Reorganization is unlikely to avoid past liabilities.

• Hence the primary motive for divestiture would be for firms to avoid liability associated with future activities.


• Entry by small firms is denoted as

• Ei is the rate of entry of small corporations in industry i between 1967 and 1980.

• Hi is worker exposure to carcinogens workplace in industry i.

• Xi is a set of other factors affecting entry rates of small firms:‒ Industry growth.

‒ Energy cost.

‒ Level of concentration and the advertising to sales ratios (used as a product differentiation measure as a barrier to small-firm entry).

‒ Regional market variables.

Alberini and Austin (1999)Introduction

• In the US, the federal program Superfund imposes liability on:‒ The current or prior operators of a contaminated site. ‒ Generators and transporters of hazardous waste. ‒ Under certain circumstances, even on other parties.

• Any “potentially responsible” party (PRP) is subject to strict liability for cleanup costs and damages at a contaminated site, without proof of negligence or intent.

• At sites where it is difficult to ascertain the individual contribution of waste of many parties, one party can be even held liable for the entire cost of cleanup.

• The agency in charge (EPA) forces PRPs to clean up sites at their expense, and to seek reimbursement of expenses for cleanups initiated by the agency.

• The States participate in federal Superfund program in various ways, but remain solely responsible for hazardous waste sites that do not qualify for the federal "priority list" (NPL) and, hence, for federally funded remediation.


• To address such sites, many states approved state cleanup programs within a few years after the passage of the federal Superfund law.

• Most of these state "mini-superfund" programs have authorities and capabilities similar to those of the federal Superfund program.

• Many states where the original hazardous waste cleanup laws prescribed negligence-based liability have recently switched to a strict liability approach.

‒ They may have been responding to the public's demand for improved environmental quality, or reacting to changes in firms' operating environments that affected their level of usage or care in the handling of hazardous wastes.

• Differences in the timing of states‘ responses have created a natural experiment on the role of state-specific factors in a state's likelihood of adopting strict liability attributes in its "mini-superfund" program.


• This paper explains differences in timing using data on states' industrial activities, environmental programs, wealth and education, and political orientation.

• Theoretical model in which the state adopts the liability regime and the program attributes that it sees as having the greater net benefits.

• Test of the model's adoption hypothesis by estimating logit equations explaining the presence or absence of strict liability within a state hazardous waste cleanup program.

• Result: The likelihood of a state incorporating strict liability is positively associated with the number of chemical-intensive plants located in that state but is negatively associated with the number of large extractive or mining establishments.

Alberini and Austin (1999)State Mini-Superfund Programs

• The federal Superfund program imposes substantial responsibilities on the States.‒ It requires them to take a lead role in pursuing PRPs and share the cost of cleanup at

NPL sites where cleanup is not financed by private PRPs.

‒ States each nominate one site for inclusion in the first 100 sites on the NPL, but bear full responsibility for non-priority hazardous waste sites.

• Since the early 1980s, many states have enacted laws similar to the federal Superfund program, providing for emergency response to, and long-term remediation at, non-priority hazardous waste sites.

• By 1989, thirty-nine states had cleanup statutes granting funding and enforcement authorities. By 1995, that number had climbed to 45.

• Differences in the timing of the state program introductions give rise to the variability analyzed here.

Alberini and Austin (1999)State Mini-Superfund Programs

• States may opt in favor of strict liability when ‒ It is objectively difficult for the regulator to establish the negligence standard (the

minimum level of care below which the firm's behavior would be deemed negligent) or,

‒ to ascertain whether a party has or has not met the negligence standard, once the latter has been determined.

• More likely to happen in states where the composition of manufacturing calls for many different chemicals or where pollutants have tended to be released in the past.

• Economic theory (Shavell 1984) shows that strict liability promotes a higher level of care than negligence-based liability when there is much variability in the distribution of damages to the environment across firms.

Alberini and Austin (1999)The model

• A state adopts the type of liability and other program attributes to maximize the net benefits (the reduction in the expected health damages incurred by the population) of the program:

where‒ Δr is the mitigation-induced change in the risk of developing health problems,

‒ N is the number of people exposed,

‒ Q is the quantity (volume) of toxic substance released,

‒ V is the (dollar) value of a statistical life.

‒ Q is allowed to vary with the presence of strict liability (S; S = 0,1), joint-and-several liability (J; J = 0,1) and other attributes A.

‒ Z denotes the type and composition of the state economic activity.


• State costs are assumed to be proportional to the quantity released:

where‒ a is the average administrative and litigation cost per unit of volume of the chemical,

‒ p denotes the fraction of all mitigation costs which the state must absorb,

‒ c is the average total cost of mitigation per unit of volume released.

• The net benefits are thus


• The State will select the type of liability S (strict or negligence-based) and J (joint-and-several or proportional to contribution), and the other attributes of the program A to maximize the net benefits of the program, subject to a resource constraint.

• Hypotheses: ‒ The size of the exposed population is proxied using the state's population density.

‒ The quantity of uncontrolled toxics grows with the extent of manufacturing and mining activity within the state, proxied by the numbers of establishments involved in those activities.

‒ Firms' contributions to total uncontrolled toxics vary with their scale (small or large) and type (manufacturing or mining).


• Overall:

‒ LMINE and SMINE: Numbers of Iarge and small mining outfits in the state,

‒ LMEG and SMFG: Counts of large and small manufacturing firms,

‒ MEDHHINC: state median household income,

‒ LESSTHS: Fraction of state residents 25 years old/older without high school diploma,

‒ HIGHSCH: Percentage who have completed high school, excluding the college-educated,

‒ X: state expenditure per capita, and state expenditures on environmental programs.


• The coefficients of the model depend on the type of program (k) in place in a state.

• The authors focus on three types of choices: Strict liability, joint-and-several liability, and punitive damages.

• Adoption of all of these three policies implies that the net benefits from doing so outweigh the net benefits of only adopting any one or two of the policies or of maintaining a negligence standard:

NB(S=1, J=1, D=1) > NB(S=1, J=0, D=0), ... , NB(S=1, J=1, D=1) > NB(S=O, J=0, D=0).

• S is the indicator for strict liability, J is the indicator for joint-and-several liability, and D is an indicator for provisions allowing punitive damages.

• Multinomial logit model for the choice of a particular liability structure.

Alberini and Austin (1999)Data

• State-level annual data.

• 1987 to 1995.

• 51 states.

Sigman (2010)Introduction

• Environmental liability and redevelopment of old industrial land.

• Many communities seek to encourage the redevelopment of sites that are idle or underused because of potential contamination.

• They are known as brownfields.

• Redevelopment of these sites is desirable because they are a disamenity and because their use is seen as a substitute for the use of relatively pristine land (greenfields).

• A survey by the U.S. Conference of Mayors found approximately 25,000 brownfield sites in the 205 cities that responded.

• Environmental liability (the threat of being compelled to pay for cleanup of contamination) is perceived as a significant barrier to redevelopment.


• In 2002, the U.S. Congress passed the Small Business Liability Relief and Brownfields Revitalization Act which included several provisions to reduce the presumed liability deterrent.

• Reuse of contaminated land remains an active issue for state and federal policy in the United States and abroad.

• Here the authors uses panel data on cities across the United States to estimate the effects of variation in environmental liability on the prices and vacancy rates of industrial land.

• Most industrial land is potentially contaminated and may be affected by liability, even if it is not formally designated a brownfield.

• The variation in liability comes from differences in state liability regimes ‒ Whether they rely on strict liability and on joint and several liability. ‒ These regimes affect the level and the distribution of expected private cleanup costs.


• The author finds a negative effect of joint and several liability on industrial real estate prices in central cities (-16 to -26%) and a positive effect of joint and several liability on industrial vacancy rates.

Sigman (2010)Liability as a Deterrent to Redevelopment

• Liability for cleanup of contaminated sites may be imposed on past and present owners of the site and parties who contributed or transported contaminants to the site.

• The purchaser of land thus faces the risk of liability should the site turn out to be contaminated.

• The previous literature suggests three reasons why inefficiency might arise:‒ Sellers of the land and potential buyers may have asymmetric information about the

level of contamination and the nature of the required cleanup.

‒ If the cost of cleanup exceeds the value of the site when it is clean, the property may remain undeveloped.

‒ Shifting liability to buyers can result in inefficiently few sales when sellers may be judgment proof.

Sigman (2010)Liability as a Deterrent to Redevelopment

• Strict liability means that any action that causes contamination may give rise to liability.

‒ Negligence rules trigger liability only if the defendant failed to meet the legal standard of care in avoiding or cleaning up contamination.

‒ Strict liability thus should increase expected private cleanup costs by expanding the set of sites at which private parties may be held liable.

• When some parties are judgment proof, joint and several liability obliges solvent parties to pick up costs attributable to parties that have gone or might go bankrupt.

Sigman (2010)Data

• All U.S. states have “superfund” programs that impose liability for the cleanup of contaminated sites not covered by the federal Superfund.

• States vary in the nature of the liability rules that they apply.

• Data 1: Status of the two liability rules in states from 1989 to 2000.

• Although 96% of observations with joint and several liability have strict liability, 60 percent of observations without joint and several liability have strict liability.

• Data 2: Prices of industrial real estate and vacancies in many U.S. cities beginning in the early 1980s.

• They are the expert opinions of local realtors rather than transaction data.

Sigman (2010)Econometric model

• The equation to be estimated is:

‒ pit is the price or the vacancy rate, and Li,(t-1) is a vector of state liability rules.

‒ The equations also include time fixed effects and either city fixed-effects or region fixed effects.

‒ Eit denotes economic conditions (city population, unemployment rate, and manufacturing share of employment).

‒ Git denotes government variables (highway density and real estate taxes).

‒ Vit denotes measures of State environmental policies: # of lawyers working with contaminated-site issues, the League of Conservation Voters’ score for the House of Representatives delegation of the state, and an abatement cost index.

Sigman (2010)Data on Reported Brownfields

Hamilton and Viscusi (1999)

• Market reaction to site risks.

• Another way to study perceptions of and reactions to risk is to analyze the decisions of homebuyers near superfund sites.

• If superfund sites are perceived to generate health risks, houses closer to sites would sell for lower prices.

• Here the authors use housing price data from Michigan to analyze how residents react to risk when they spend their own money to avoid potential harm.

• It is usually expected that the homeowners’ assessment of risk is much higher than the assessment of experts.

• This may suggest that the public overestimates the low probability of hazardous waste risks.

Hamilton and Viscusi (1999)

• The authors use a hedonic housing price framework to estimate residents’ reaction to risk.

• They suggest that people tend to overestimate low probability risks.

• This overreaction could lead to a higher willingness to pay for a risk reduction.

• However, when residents are properly informed of the risks, their choices indicate that there is no risk of overreaction.

Hamilton and Viscusi (1999)Modeling homebuyers’ reactions to risk

• They develop first a model of the homebuyers’ reaction to Superfund site risks.

• Individual have a prior cancer risk assessment of p, which has associated informational content 𝜑0.

• People update their risk perceptions taking into account the probability q, which is implied by information provided by the EPA, with informational content 𝜉0.

• People also update their risk perceptions taking into account the probability r, which is implied by information provided by the news media, with informational content 𝜅0.

• The cancer risk perception function takes the form:


• By denoting the fraction of the total informational content associated by each information source as:

the risk perception is rewritten as

• Individuals maximize expected utility over two states of the world, with 𝑈1representing utility in the sick (cancer) state and 𝑈2 representing utility in the healthy (non-cancer) state.

• Utility is a function of a vector of the characteristics of the house, z, a composite good, x, and the visual disamenities of the site, s.


• The price of a house is h and the consumer’s income is y.

• Consumers maximize expected utility as follows:

• By construction, 𝜋 𝑝, 𝑞, 𝑟 is an increasing function of p and q.

• Te equilibrium conditions for the effect of higher informational risk value on housing prices and the expected signs are:


which, since and , reduces to


• The marginal price is equal to the marginal willingness to pay for an incremental decrease in objective risk.

• The willingness to pay for risk reduction increases or decreases given the information provided by the EPA’s remedial investigation.

• Given the theoretical model, the hedonic price function is expressed as:

See variables description.


• The model can be expanded as:

thus the regression indicates how different risk information affects prices and also which informational source has a greater weight in consumer judgements.

• The values of p, q, and r capture prior signals available to residents: Area of the closest Superfund site, ranking of the closest site on the EPA’s national priorities list, and the type of site (landfill or industrial chemical plant).


• The first hedonic price function to be estimated is:

See variables definition.

• Data: ‒ 16928 houses sold in the greater Grand Rapids area, 1988-1993.‒ Contains 7 Superfund sites. ‒ # of bedrooms, bathrooms, basement, garage, median household revenue,

education, distance to business district, age <19, crime rate, year and city dummies.

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