prior probability

The Republic of Ghana is making her debut appearance in this year’s Venice Biennale. Lynette Yiadom-Boakye, one of our favorite contemporary artists, is also one of several artists representing the West African nation. Below is a sample of her work:

Following up on my previous post, it turns out that one of the earliest manuals on the practice of dueling–“Il Duello” by Girolamo Muzio, a.k.a. Mutio Iustinopolitano, b.1496—d.1576–was published in Venice in 1550. I am unable to locate an English translation of this 16th-century Venetian manual, nor am I able to find any reliable statistics about the number of duels in European history, so for now I have ordered Barbara Holland’s classic book on the history of dueling. Also, here are some bonus links for our loyal followers: (1) a vintage Marginal Revolution blog post about the economics of dueling; (2) this history of dueling in 16th-century Italy by David Quint; (3) this comparative study by Mehrdad Vahabi and Behrooz Hassani Mahmooei (review of dueling in England, France, and Germany); and (4) this formal paper by Douglas W. Allen and Clyde G. Reed (presenting a costly-signalling model of dueling).

The Republic of Venice lasted for over 1000 years (726-1797 A.D.). Three things about “Old Venezia” continue to fascinate me: (1) How common were duels in Venice? (2) Why did such a small city-state have so many chapels, churches, and other houses of worship? And (3) why did the Venetian Republic develop such a complicated and cumbersome multi-stage electoral system? We will explore all three of these features of Old Venezia (duels, religion, and voting rules) in future blog posts, but for now let’s focus on the third one. Among other things, Venice’s bygone voting system poses a difficult theoretical and practical puzzle: What is the optimal level of electoral complexity and randomness? Below is a brief survey of the literature:

1. Marji Lines, “Approval voting and strategy analysis: A Venetian example” (1986) (gated version).
2. Jay S. Coggins and C. Federico Perali, “64% Majority Rule in Ducal Venice: Voting for the Doge” (1998) (available here).
3. Miranda Mowbray and Dieter Gollmann, “Electing the Doge of Venice: Analysis of a 13th Century Protocol” (2007) (available here).
4. Dalibor Rohac, “Mechanism Design in the Venetian Republic” (2013) (available here).
5. Toby Walsh and Lirong Xia, “Venetian Elections and Lot-based Voting Rules” (not dated) (available here).

We will be attending some lectures on “realist jurisprudence and its competitors” by Dr Brian Leiter at the EHESS in Paris, so we will be blogging much less frequently during the next few weeks.

The oracles of SCOTUS decided Gamble v. U.S. today (17 June), upholding the nefarious “separate sovereigns” exception by a 7-2 margin. Here are three of our previous posts about this fascinating case:

1. Be like Bayes (part 3) (30 December 2018), in which we build a simple Bayesian model to predict whether the Supreme Court will overturn the “separate sovereigns” exception to the Double Jeopardy Clause when it decides Gamble v. U.S. (Our prediction turned out to be wrong.)

2. Be like Bayes (part 2) (29 December 2018), in which we estimate the base rate or the historical frequency in which a precedent is overturned by the Supreme Court in those cases in which a party is asking the Court to take such an action.

3. Forecasting the forecasts (31 December 2018), in which we describe a method for scoring the accuracy of our Gamble v. U.S. forecast via a simple scoring method that was first proposed by Glenn Wilson Brier, an early advocate of probability forecasting and the use of probability forecasts in decision making.

To my friends–law professor colleagues and students alike–beware! All three of the above posts are somewhat technical and mathematical in nature. In short, instead of focusing on the legal arguments in Gamble v. U.S. or the “merits” of the case (we agree with Brian Leiter, Richard Posner, and other legal realists that law in close cases is indeterminate), we attempt to build a simple Bayesian forecasting model based on the number of amicus briefs submitted by third parties to the Supreme Court.

The wait is over …

We have been addressing the following question in our last five blog posts: How does law get started? To sum up our Humean answer in two words, law and legal systems are just protection rackets (nothing more, nothing less), at least in their beginning stages, although we could easily extend this protection-racket logic to modern legal systems; after all, what are taxes but a form of legalized extortion? But our protection-racket conception of law raises a whole new set of troubling questions. To begin with, most, if not all, protection rackets are always compulsory, not voluntary, affairs: people are forced to buy “protection,” even if they don’t want to. (Check out the popular culture depictions of mob bosses and racketeers below.) So, realistically speaking, far from solving the forced rider problem, protection rackets make this problem worse. Is there any way around this problem?

Maybe there is an “optimal” number of protection rackets per territory. When there is a market for protection, would-be racketeers and proto-lawmen will have to compete with one another to attract new clients and maintain old ones, so they will have a built-in incentive to provide services of value and to avoid overcharging for their protection services. (Think again of Mancur Olson’s rational profit-maximizing “stationary bandit.”) On this view, the more racketeers the better! Or perhaps the solution resides in the threat of competition. That is, even if there is only one dominant protection racket, as long as new entrants are free to form their own rival protection agencies, this threat alone should curb the dominant agency’s destructive tendencies.

None of these libertarian or Planglossian responses, however, are entirely satisfactory because there is no meta-protection agency to protect independents and forced riders (persons who don’t want to pay for “protection”) or to resolve disputes among the racketeers themselves and their rival protection rackets. Ultimately, then, there is an inherent tension here. On the one hand, some form of law, however crude, is useful to promote cooperation, but at the same time, any legal system or protection racket will inevitably produce abuses of its own. There is thus an optimal level of “protection”–too much protection is no doubt a bad thing, but so is too little! In short, the optimal level is not zero. Seen this way, law is just a trial-and-error method of finding the optimal level of protection.

How does law get started? In my previous post “Hume’s meadow” I sketched a possible three-step solution to the group cooperation problem. First, we must think of law not as some rarefied or unique realm but rather as an ordinary run-of-the-mill business or “protection racket” (think of Mancur Olson’s “stationary bandit“). Next, we must find a sufficient number of partners to go into business with, and lastly, we must then find a way of separating ownership (citizenship) and control, either through elections or some other method of tacit consent of the governed. This business-like approach to the origins of law has two virtues: it not only solves the regress problem; it also solves the forced rider problem too!

The forced rider problem is solved (at least at the law’s formation stage) because our “law business” is a voluntary protection racket or “mutual protection association” (to borrow Robert Nozick’s euphemistic phrase). No one who doesn’t want to join or “buy in” the protection association is compelled to, at least not initially. Similarly, the regress problem is solved because the potential expected benefits–both in total and at the margin–of creating a law business should attract a sufficient number or critical mass of “legal entrepreneurs” to overcome the free rider and defection problems that plague any common enterprise. In fact, I would venture to speculate that the problem with my business or partnership model of law is not going to be a lack of “legal entrepreneurs.” The problem is going to be just the opposite. That is, instead of too few protection rackets, we are probably going too have too many! But is this really a problem, and if it is, how should we solve it? I will consider those questions in my next post.

Hat tip: u/Pytheastic (via Reddit)