Judges’ consistency & the role of predictive analysis

1. Judges’ consistency & the role of predictive analysis Benito ARRUÑADA Pompeu Fabra University Workshop on “Law & Economics for European Law” EALE & University of Luxembourg Luxembourg, November 10, 2006

2. Judges’ consistency requirespredictive analysis Benito ARRUÑADA Pompeu Fabra University Workshop on “Law & Economics for European Law” EALE & University of Luxembourg Luxembourg, November 10, 2006

3. Uncontroversial claim Judges need good analysis to use their discretion well

4. 1. Which analysis is “good”?

5. Testable analyses are able to predict human behavior • Only predictive ability makes possible to compare & choose between alternative analyses, identifying the best analysis • Two consequences: • The ‘economic’ adjective is misleading • Even wrong: e.g., evolutionary biology explains more for adoption and crime on children (Owen Jones works) • Doubts on the value of legal positivism, in essence taxonomy: • Systematic analysis • Analogy • Authority

6. Doubts on legal positivism • Does not predict behavior  not testable, dogmatic • Useful to guide judges fitting cases into the law  Enough for judges applying ‘good’ law (robot judges)—But • How to produce good law? (admittedly a question relevant for law-makers , not for robot judges) • 19th century relied on analysis: Law & Econ—e.g., property law • 20th century? E.g., car dealers, payment delays (Arruñada et al, JLEO, 2001, 03; JLE 05; RLE 05)) • Less adequate the greater the discretion of judges • Greater in the Common Law • judges traditionally decide according to rules of equity and nature of circumstances • But increasing in many Civil Law jurisdictions

7. 2. Why do judges need predictive analyses?

8. Judges need predictive analysis • To achieve any of two possible standards when exercising their discretion: • Not only ‘socially desirable’ or ‘efficient’ decisions • But merely decisions consistent with the judge’s objectives

9. The compassionate judge • Worried for the poor, this judge uses her discretion to favor a poor party (e.g., a tenant) • Is her decision consistent with her objectives? • Obvious: Little “predictive analysis” necessary to know that a poor party is now richer • Not so: She cared for the poor, not for a poor • She needs predictive analyses to ascertain systemic consequences: those for the millions of poor in society (i.e., no flats for rent)

10. 3. Generalizing the argument

11. Necessary conditions for markets* • Efficient definition of the exchange • Freedom of contract ex ante (contracting) • Use of new information ex post (fulfillment) • Enforcement • Property rights • Contractual agreements * i.e. using a broad concept of ‘market,’ so that it includes implicit human exchanges

12. How judges enable markets • Efficient definition of the exchange • PROTECT Freedom of contract ex ante • EXPLOIT New information ex post • Enforcement • DEFINE & PROTECT Property rights • EXECUTE Contractual agreements

13. Examples of judicial failures • Defining the exchange • Wrongly ‘improving’ on freedom of contract • Hindsight biases in an uncertain exchange • Jurisdictional failure: ad nutum (“at will”) termination of car dealers (or even workers) • Enforcement failures • mortgages in Brazil, Lima, etc

14. Dominant feature of judicial failures: inconsistency b/w goals & means • An idea of “justice” for the case, for an individual in a class, within a contract • Useful for judicial decisions with a mere taxonomic function within given law • But insufficient for rulemaking judicial activity because it forgets about systemic consequences • Because it precludes the same idea of justice (whatever good) for the whole class of individuals, especially through potential contracts that become nonviable

15. Conclusion • The use of analyses predicting human behavior in a comparable manner is essential for judges to the extent that they enjoy discretion and they want to use it sensibly—‘sensibly’ meaning consistently with their objectives, whatever these may be.

16. Judges’ consistency requires predictive analyses Thank you for your attention