Danial Asmat & Sharon Tennyson “Tort Liability and Settlement Failure: Evidence on Litigated Auto Insurance Claims” Comment by Dan Klerman USC Law School Conference on Empirical Legal Studies Duke Law School November 18, 2016

Plan Quick summary 4 Suggestions Consider effects on primary behavior Interpret Priest & Klein (1984) as a 2-sided asymmetric information model Analyze unconditional litigation rates Note small sample size

Quick Summary Analysis of impact of tort of bath faith denial of insurance coverage on litigation and settlement Using closed claims insurance data from 1977, 1987 and 1997 Key finding Difference in short term and long-term effects Short term: Litigation and trial rates when up after tort was introduced Although oddly only for states that introduced the tort by 1977 Long term: Litigation and trial rates went down Short-term increase in litigation can be explained in 2 ways Increase in uncertainty Consistent with Priest & Klein (1984) Increase in damages consistent with Priest & Klein (1984) and Bebchuk (1984) Long-term decrease in litigation Explained by abatement of uncertainty Perhaps consistent with Priest & Klein (1984) Not predicted by Bebchuk (1984)

Effects on Primary Behavior Reduction in uncertainty cannot explain finding that trial and litigation rates are LOWER in the long-run in tort states If change in law results in temporary increase in uncertainty, would expect legal uncertainty to eventually return to baseline levels 2 explanations for result Risk aversion Increasing damages INCREASES settlement when parties are risk averse Change in primary behavior Selection models assume that underlying behavior remains constant If looking at employment litigation data, need to consider 2 effects of increase in damages Change in rate of employment discrimination (primary behavior) Not modeled by selection models Change in settlement behavior Tricky to analyze here Really 2 insurer decisions Whether to deny UM claim (primary behavior) Whether to settle disputes over UM claims (settlement behavior) Maybe insurers in tort states became more careful about whether they would deny UM claims (primary behavior) Which is why there is less litigation Not clear that explains fewer trials conditional on litigation

Priest & Klein as Asymmetric Information Model Like much of the literature, Asmat & Tennyson contrast divergent expectations models to asymmetric information models Divergent expectations. Priest & Klein (1984) Asymmetric information models. Bebchuk (1984) False contrast Divergent expectations models can be interpreted as 2-sided asymmetric models Daughety & Reinganum (2012); Lee & Klerman (2016) So real contrast is between 1-sided and 2-sided asymmetric information models Not surprising that 2-sided models tend to predict better Will not affect theoretical predictions or empirical results

Analyze Unconditional Trial Rate Paper analyzes Litigation Fraction of UM claims filed with insurer that result in lawsuit Trial conditional on litigation Fraction of lawsuits that result in trial Might be helpful to analyze trial rate Fraction of UM claims that result in trials Settlement can happen before or after lawsuit filed So unconditional trial rate may be best overall measure of settlement failure Probably won’t change results

Sample Size Although dataset is relatively large Almost 6K closed claims Number of litigated claims is small Number of trials is tiny Especially problematic for subcategories In 1997 closed 113 litigated claims in tort states Only 3 trials 45 litigated claims in non-tort states Only 4 trials Small number of litigated and tried cases should be more prominently noted and discussed

Conclusion Very nice paper Interesting and plausible result Even better if Consider effects on primary behavior Interpret Priest & Klein (1984) as 2-sided asymmetric information model Analyze unconditional litigation rate Note small sample size

Could do more with asymmetric information models Bebchuk model might have predictions regarding increase in variance Also need to analyze Reinganum & Wilde (1986) signaling model Similar results with increasing damages

Analysis of Increase in Damages Proposition 1 asserts increasing damages has an ambiguous effect on settlement rates Increase in damages itself DECREASES the settlement rate But increase in damages increases litigation costs, which INCREASES settlement rate Overall effect AMBIGUOUS Better analysis If litigation costs increase proportionally with damages, then increasing damages has NO EFFECT on settlement If litigation costs increase less than proportionally with damages, then increasing damages DECREASES the settlement rate If one or both parties are risk averse, then increase in damages INCREASES settlement rate True under Priest & Klein and under 1-sided asymmetric info models So, can better get ambiguous result of Proposition 1 by considering risk aversion