1. 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

2. 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

3. 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)

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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