GDL

Recent work has discussed and formalized the conditions under which liability rules are superior to


property rules in a world with “one-sided” incomplete information. These studies demonstrated how


liability rules achieve higher social welfare by harnessing one party’s private information about its


own valuation to the process of optimally allocating the entitlement between the parties. This article


introduces a new family of liability rules hitherto neglected by courts and legal scholars. A regime of


modular liability rules is one in which the court applies legal rules for which the traditional liability


rules are building blocks; these rules harness both parties’ private information.Whereas in an efficient


liability rule 2 (for example) a polluter is granted a call-option to purchase the right to the air (so


to speak) with an exercise price that equals the resident’s harm, in modular liability rule 6 + 5 (for


example) a pair of options, rather than a single one, is allocated; the resident gets a put option to force


a transfer of the entitlement (as under rule 6), but the polluter has a consecutive put option to sell the


entitlement back to the resident, if he wishes (as under rule 5). Interestingly, the maximizing joint


welfare exercise-price equals, in general and for uniform distributions, an amount that is the average


of one party’s maximum estimated valuation and the other party’s minimum estimated valuation. Two


paradigmatic worlds of two-sided incomplete information are studied: a symmetric world, in which


the court’s best estimate of the parties’ private valuations is that they are identically distributed, and an


asymmetric world. In the symmetric world, modular liability rules are in some respects more efficient


and more fair (exact definitions are discussed in the article) than the conventional liability rules. In


the two-sided and asymmetric world, modular liability rules yield higher joint payoffs than regular


liability rules if, and only if, the difference between the parties’ means is larger than the difference


between their amount of private information (represented by the distribution’s support). A practical


way to implement these insights in real life situations is offered.

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