Product Liability
NERA economists have experience consulting and testifying on a variety of product liability matters, including personal injury claims (e.g., exposure to salmonella, asbestos, or handguns), property damage claims (e.g., failure of hardboard siding), consumer class actions (e.g., allegations of predatory lending), and high profile product recalls (e.g., automotive vehicles.)
Through our extensive experience, we have developed proprietary resources, including claims databases and forecast programs. We have analyzed publicly available data, including data from the Consumer Product Safety Commission, National Highway Traffic Safety Administration, Healthcare Cost and Utilization Project, and the Federal Motor Carrier Safety Administration), have estimated the likelihood of recalls and, when a product recall occurs, we have modeled product failure rates and anticipated uptake rates. We have also compiled historical information on labor statistics and turnover in numerous occupations that allows us to estimate the potentially affected population in cases involving personal injury claims.
NERA experts have developed claim forecasting models, which rely on scientific analysis and behavioral economics. We project both the incidence of disease, type and severity of injury, or product failures and the likelihood that the injury or product defect will result in a claim being filed. We then value any projected claims. We have experience modeling both young torts (with limited data and uncertain filing patters) as well as more mature torts (in which filing and settlement trends may be more established).
In cases where losses are associated with marketable assets such as real estate (e.g., drywall litigation) or automobiles (e.g., major product recall litigation), it may be possible to quantify damage claims to estimate diminution in value claims. For example, diminution in value of recalled vehicles can be analyzed using data on vehicle demand. Event study and time series analysis techniques are also be useful to measure changes in historical blue book prices coincident with a recall. While the immediate impact of a recall may be evident from contemporaneous data, the historical experience of other recalls may provide evidence of a subsequent recovery expected recovery in resale value. Econometric techniques can be used to measure the value to consumers of vehicle attributes, which may be useful to distinguish an effect of a correctable defect from the impact of a recall on corporate reputation or brand value.
NERA experts have an expertise in coding claim files and developing protocols to avoid errors or bias in coded data. Applying rigorous statistical techniques, we determine whether the coded sample is representative of the population and, if so, make observations about the characteristics of the population, e.g., types of product failures or claimed exposure.
In the area of asbestos alone, through our work for companies, insurers or acquirers, we have analyzed the claims data of more than 70 defendants and have been following trends in claim filings, settlements and dismissals both nationally and by state. We have studied the impact of claim filings on the likelihood of the passage of tort reforms, as well as the effect of such reforms on future filings and settlement values.
Our work encompasses a broad array of industry sectors and product lines, including:
- Food additives, including diacetyl
- Automotive vehicles and products
- Building products
- Railroad cars
- Off-road utility vehicles
- Pharmaceuticals and medical devices
- All terrain vehicles
- Tobacco
- Firearms
Our work is used in a variety of contexts, including:
- Quantifying the Medicare component of settlements
- Assessing reserve adequacy
- Optimizing litigation strategy
- Preparing financial reports
- Informing merger due diligence
- Sizing bankruptcy trusts
- Appraising proposed tort reforms
- Negotiating insurance buy-backs
- Identifying unimpaired claimants/unfounded claims
- Tracking litigation trends
- Developing claims databases
- Evaluating fraudulent conveyance allegations
- Predicting insurance exhaustion
- Valuing contingent liabilities
