Presentation on theme: "Law and Econometrics Enrique A. Bour August 2010."— Presentation transcript:
Law and Econometrics Enrique A. Bour August 2010
You probably already know that Law & Economics is one of the main areas of research in economics - The works by Coase, Demsetz, Manning, Becker and Posner are very well-known (not to mention Calabresi, Hirshleifer, Rubin, Easterbrook, and many others who did active research in this area). In the past twenty or thirty years there has been a strong revival of L&E using statistics. Let me point to some examples:
David H. Kaye & David A. Freedman, Reference Guide on Statistics, in Reference Manual on Scientific Evidence (3d ed. 2009). Joseph L. Gastwirth, Statistics in the Courtroom (2007). Joseph B. Kadane ed., Statistics in the Law (2008). Hans Zeisel & David Kaye, Prove It With Figures: Empirical Methods in Law and Litigation (1997). For example, the organizing thesis of the latter book is the problem of determining causation--causation defined not in a philosophical sense but rather intended for the practical needs of dispute settlement. By combining the research literature for examples of how social research has been used by the authors and by others to discern causation, Zeisel and Kaye have come close to writing a handbook for general social science research.
This presentation shares the spirit of Robert M. Lawless, Jennifer K. Robbennolt, & Thomas S. Ulens recent book, Empirical Methods in Law (2010), whose Table of Contents is the following: Part I: Why Gather, Organize, and Evaluate Data: An Overview of Empirical Methods Chapter 1. Thinking Empirically Chapter 2. Research Design Part II: How to Gather Data: Empirical Research Methodologies Chapter 3. Asking Questions: Surveys and Interviews Chapter 4. Experiments Chapter 5. Archival Methods Chapter 6. Sampling Chapter 7. Coding
Part III: How to Evaluate the Data: Statistical Techniques Chapter 8. Distributions and How to Describe Them Chapter 9. Hypothesis Testing Chapter 10. Inferential Statistics Chapter 11. An Introduction to Correlation and Regression Analysis Chapter 12. Advanced Regression Techniques Part IV: Communicating Your Results Chapter 13. Reading, Presenting, and Writing About Empirical Matters Chapter 14. Conclusions
Some previous clarifications... I wont bother you with econometrics nor law. Ill suggest the interested reader to follow my article. Its very important to distinguish the Economic Analysis of Law (L&E) from Economic Law. In the legal system of the Soviet Union, economic law was the legal theory and system under which economic relations were a legal discipline independent of criminal law and civil law. In the Law of the United States and some other legal systems this approximately corresponds to the commercial law (business law). (Source: wikipedia)
Additional clarifications Law and economics (also known as the economic analysis of law) is an approach to legal theory that applies methods of economics to law. It includes the use of economic concepts to explain the effects of laws, to assess which legal rules are economically efficient, and to predict which legal rules will be promulgated.
Duality As pointed by Dr Julio H. G. Olivera in La Doble Intersección de la economía con el derecho, in the Tribute to Alfredo J. Canavese (U. di Tella, April 16th, 2010) there is a duality link between both approaches. My interpretation of his remarks is as follows: given the rules of the game as fixed by the Economic Law, the duality theorem allows to examine and solve the dual problem of minimizing distortions produced by Law, contributing thereby to maximize wealth (the Theorem of Posner).
Influence of L&E In the United States, economic analysis of law has been extremely influential. Judicial opinions utilize economic analysis and the theories of law and economics with some regularity. The influence of law and economics has also been felt in legal education. Many law schools in North America, Europe, and Asia have faculty members with a graduate degree in economics. In addition, many professional economists now study and write on the relationship between economics and legal doctrines. According to Anthony Kronman, former dean of Yale Law School,"the intellectual movement that has had the greatest influence on American academic law in the past quarter-century [of the 20th Century] is law-and-economics.
However, a lot remains to be done Michael Myerson (in Significant Statistics: The Unwitting Policy Making of Mathematically Ignorant Judges, 2010) explores several areas in which judges, hampered by their mathematical ignorance, have permitted numerical analysis to subvert the goals of the legal system. He examines the perversion of the presumption of innocence in paternity cases, where courts make the counter-factual assumption that regardless of the evidence, prior to DNA testing, a suspect has a 50/50 chance of being the father. He also explores the unnecessary injection of race into trials involving the statistics of DNA matching, even when race is entirely irrelevant to the particular case. Next, he discusses how courts use race- and gender- based statistics to reduce damages in tort cases for women and racial minorities, and silently assert that past racism and sexism will continue. Finally, he examines how judges have improperly allocated the risk of error in cases such as securities fraud, so as to reward those who have attempted to manipulate stock prices illegally.
Also, William Buiter said in his blog (2008): Excepting some lawyers, generally they know nothing. They ignore the difference between a necessary and a sufficient condition, or between an Error of Type I or of Type II. To be precise, any probabilistic concept escapes to them. They dont understand concepts of trade-off or opportunity cost. They cant establish the difference between a positive and a normative statement. (See Philip R. Wood, Lawyers and Economists: Who Rules the World?, May 2010)
To return to our argument, these defficiences explain the surge of Magisters in L&E everywhere in the world, But let us indicate a danger pointed by the great philosopher and sociologist Jon Elster, in an exposition at the universidad Di Tella on November 1, 2010, on The Crisis in the Social Sciences. Elster denounced the empty character of many works in several areas of knowledge – including economics, L&E, psychology, etc
Elster said: Many areas of the social sciences are being now plagued by void models of behavior and/or merely abstracts statements without empirical support, and this happens with more and more frequency. Now one can present a mathematical paper at a prestigious journal and get it published without major obstacle. I approached the author of Ulysses Unbound and asked him if his concepts couldnt be considered as obscurantists, as a certain level of mathematical and statistical literacy is absolutely necessary to appraise a legal argument.
Elster agreed with it, and considered that econometrics as put forward in the Reference Manual on Scientific Evidence (US) is a good point, as it is a simple ellaboration of good ideas in law. I have some doubts about this idea. As exemplified in the text by Lawless, Robbennolt, & Ulen, once causal statements are introduced, hypothesis testing and some advanced regression techniques will be employed more and more. Well see more of it in the future!
Now, a Short Summary of my paper: I begin with a recent example: The U.S. v. Microsoft case, which is an appealing case for analizing the economics of antitrust policies. It is also interesting because it gathered three very important economists around it: Franklin Fisher and Daniel Rubinfeld (both of them testifying for the Government) and Richard Schmalensee (as an expert of the pleading).
United States v. Microsoft was a set of consolidated civil actions filed against Microsoft Corporation pursuant to the Sherman Antitrust Act on May 18, 1998 by the United States Department of Justice (DOJ) and 20 U.S. states. The plaintiffs alleged that Microsoft abused monopoly power on Intel-based personal computers in its handling of operating system sales and web browser sales. The issue central to the case was whether Microsoft was allowed to bundle its Internet Explorer (IE) web browser software with its Microsoft Windows operating system. Bundling them together is alleged to have been responsible for Microsoft's victory in the browser wars as every Windows user had a copy of Internet Explorer.
Microsoft stated that the merging of Microsoft Windows and Internet Explorer was the result of innovation and competition, that the two were now the same product and were inextricably linked together and that consumers were now getting all the benefits of IE for free. Those who opposed Microsoft's position countered that the browser was still a distinct and separate product which did not need to be tied to the operating system, since a separate version of Internet Explorer was available for Mac OS. They also asserted that IE was not really free because its development and marketing costs may have kept the price of Windows higher than it might otherwise have been.
To be short, on November 2, 2001, the DOJ reached an agreement with Microsoft to settle the case. The proposed settlement required Microsoft to share its application programming interfaces with third-party companies and appoint a panel of three people who will have full access to Microsoft's systems, records, and source code for five years in order to ensure compliance. On August 5, 2002, Microsoft announced that it would make some concessions towards the proposed final settlement ahead of the judge's verdict. On November 1, 2002, Judge Kollar-Kotelly released a judgment accepting most of the proposed DOJ settlement. Nine states (California, Connecticut, Iowa, Florida, Kansas, Minnesota, Utah, Virginia and Massachusetts) and the District of Columbia (which had been pursuing the case together with the DOJ) did not agree with the settlement, arguing that it did not go far enough to curb Microsoft's anti-competitive business practices. On June 30, 2004, the U.S. appeals court unanimously approved the settlement with the Justice Department, rejecting objections from Massachusetts that the sanctions were inadequate.
Microsoft's obligations under the settlement, as originally drafted, expired on November 12, However, Microsoft later "agreed to consent to a two-year extension of part of the Final Judgments" dealing with communications protocol licensing, and that if the plaintiffs later wished to extend those aspects of the settlement even as far as 2012, it would not object. The plaintiffs made clear that the extension was intended to serve only to give the relevant part of the settlement "the opportunity to succeed for the period of time it was intended to cover", rather than being due to any "pattern of willful and systematic violations". The court has yet to approve the change in terms as of May 2006.
Open Letter on Antitrust Protectionism On June 2, 1999, 240 distinguished economists signed an open letter that called for an end to speculative antitrust enforcement efforts. The ad, sponsored by The Independent Institute, appeared in the June 2, 1999, editions of The Washington Post and The New York Times. Consumers of high technology have enjoyed falling prices, expanding outputs, and a breathtaking array of new products and innovations. High technology markets are among the most dynamic and competitive in the world, and it is a tribute to open markets and entrepreneurial genius that American firms lead in so many of these industries. But, these same developments place heavy pressures on rival businesses, which must keep pace or lose their competitive races. Rivals can legitimately respond by improving their own products or by lowering prices. Increasingly, however, some firms have sought to handicap their rivals races by turning to the government for protection. The letter points out that such antitrust efforts, based upon speculative rather than actual harm to consumers, short circuit market forces and replace consumer choices with bureaucratic and political decisions. The results of this, the letter noted, include weakened U.S. firms and reduced international competitiveness.
Other criticism The late Nobel economist Milton Friedman believed that the antitrust case against Microsoft set a dangerous precedent that foreshadowed increasing government regulation of what was formerly an industry that was relatively free of government intrusion and that future technological progress in the industry will be impeded as a result. Jean-Louis Gassée, CEO of Be Inc., claimed Microsoft was not really making any money from Internet Explorer, and its incorporation with the operating system was due to consumer expectation to have a browser packaged with the operating system. For example, BeOS comes packaged with its web browser, NetPositive, and Mac OS X with Safari. Instead, he argued, Microsoft's true anticompetitive clout was in the rebates it offered to OEMs preventing other operating systems from getting a foothold in the market
Nowadays, using multiple regression has become a useful practice in the US courtoom: In a case, the district court was unpersuaded by a statistical analysis of capital sentencing, in part because of various imperfections in the study, including discrepancies in the data and missing data; concurring and dissenting opinion concludes that the district courts findings on missing and misrecorded data were clearly erroneous because the possible errors were not large enough to affect the overall results Compare EEOC (that is, the U.S. Equal Employment Opportunity Commission) v. Sears, Roebuck & Co., 839 F.2d 302, 312 & n.9, 313 (7th Cir. 1988) (EEOCs regression studies showing significant differences did not establish liability because surveys and testimony supported the rival hypothesis that women generally had less interest in commission sales positions), with EEOC v. General Tel. Co., 885 F.2d 575 (9th Cir. 1989) (unsubstantiated rival hypothesis of lack of interest in non-traditional jobs insufficient to rebut prima facie case of gender discrimination); cf. the problem of confounding and the effect of omitting important variables from a regression model.
In United States v. Shonubi, 895 F. Supp. 460 (E.D.N.Y. 1995), revd, 103 F.3d 1085 (2d Cir. 1997), a government expert estimated for sentencing purposes the total quantity of heroin that a Nigerian defendant living in New Jersey had smuggled (by swallowing heroin-filled balloons) in the course of eight trips to and from Nigeria. He applied a method known as bootstrapping.He drew 100,000 independent simple random samples of size seven from a population of weights distributed as in customs data on 117 other balloon swallowers caught in the same airport during the same time period; he discovered that for 99% of these samples, the total weight was at least grams. Thus, the researcher reported that there is a 99% chance that Shonubi carried at least grams of heroin on the seven [prior] trips.... However, the Second Circuit reversed this finding for want of specific evidence of what Shonubi had done. Although the logical basis for this specific evidence requirement is unclear, a difficulty with the experts analysis is apparent. Statistical inference generally involves an extrapolation from the units sampled to the population of all units. Thus, the sample needs to be representative. In Shonubi, the government used a sample of weights, one for each courier on the trip at which that courier was caught. It sought to extrapolate from these data to many trips taken by a single courier trips on which that other courier was not caught.
Empirics As said by Ulen & others, Once one starts to think empirically about the world and about the particular issues and problems that one faces, it is difficult to imagine what one did before one thought empirically. It is hoped that the lawyer will find that knowing how to look for and evaluate empirical evidence will broaden his horizons. It may give him access to an entirely new literature that was previously beyond his ability to read and appreciate. It may allow him to ask new questions about the law and to suggest methods by which those questions might be answered. It may even inspire him to do empirical work of his own and thereby contribute to our understanding of how legal institutions work.
The expert & the Parties Multiple regression analysis is taught to students in extremely diverse fields, including statistics, economics, political science, sociology, psychology, anthropology, public health, and history. As emphasized by D. Rubinfeld, any individual with substantial training in and experience with multiple regression and other statistical methods may be qualified as an expert. The decision to qualify an expert in regression analysis rests with the court. Clearly, the proposed expert should be able to demonstrate an understanding of the discipline.
In general, a clear and comprehensive statement of the underlying research methodology is a requisite part of the discovery process. The expert should be encouraged to reveal both the nature of the experimentation carried out and the sensitivity of the results to the data and to the methodology. To the extent possible, the parties should be encouraged to agree to use a common database. Even if disagreement about the significance of the data remains, early agreement on a common database can help focus the discovery process on the important issues in the case. A party that offers data to be used in statistical work, including multiple regression analysis, should be encouraged to provide the following to the other parties: (1) a hard copy of the data, along with the underlying sources; (2) computer disks or tapes on which the data are recorded; (3) complete documentation of the disks or tapes; (4) computer programs that were used to generate the data; and (5) documentation of such computer programs. The parties should be encouraged to resolve differences as to the appropriateness and precision of the data to the extent possible by informal conference. The court should make an effort to resolve differences before trial. This is a requirement that goes along the lines recently put forward by our Supreme Court.
Some Bibliography American Bar Association Section of Antitrust Law Economics Committee, Selected Readings in Antitrust Economics: Applied Econometrics (July 2008). Fisher, Franklin M. Multiple Regression in Legal Proceedings, 80 Colum. L. Rev. 702, Fisher, Franklin M. and Daniel L. Rubinfeld, U.S. v. Microsoft - An Economic Analysis, The Antitrust Bulletin, Spring Jonathan B. Baker and Daniel L. Rubinfeld, Empirical Methods in Antitrust: Review and Critique, American Law and Economics Review, Fall 1999, pp Lawless Robert M., Jennifer K. Robbennolt, & Thomas S. Ulen, Empirical Methods in Law (2010). Lichtman, Allan J. Passing the test - Ecological Regression Analysis in the Los Angeles County Case and Beyond, Evaluation Review (ER), Vol.15, Nº 6, Dec Meyerson, Michael I. Significant Statistics: The Unwitting Policy Making of Mathematically Ignorant Judges, Pepperdine Law Review and SSRN, Rubinfeld, Daniel L. Econometrics in the Courtroom, Columbia Law Review, June 1985, pp Rubinfeld, Daniel L. Reference Guide on Multiple Regression, in Reference Manual on Scientific Evidence, 2nd ed., Federal Judicial Center (2000), pp Sykes, Alan O. An Introduction to Regression Analysis, Chicago Working Paper in Law & Economics.