Jurimetrics
Jurimetrics is the application of quantitative methods, and often especially probability and statistics, to law. In the United States, the journal Jurimetrics is published by the American Bar Association and Arizona State University. The Journal of Empirical Legal Studies is another publication that emphasizes the statistical analysis of law.
The term was coined in 1949 by Lee Loevinger in his article "Jurimetrics: The Next Step Forward". Showing the influence of Oliver Wendell Holmes, Jr., Loevinger quoted Holmes' celebrated phrase that:
The first work on this topic is attributed to Nicolaus I Bernoulli in his doctoral dissertation De Usu Artis Conjectandi in Jure, written in 1709.
Common methods
- Bayesian inference
- Causal inference
- *Instrumental variables
- Design of experiments
- * Vital for epidemiological studies
- Generalized linear models
- * Ordinary least squares, logistic regression, Poisson regression
- Meta-analysis
- Probability distributions
- *Binomial distribution, hypergeometric distribution, normal distribution
- Survival analysis
- *Kaplan-Meier estimator, proportional hazards model, Weibull distribution
Applications
- Accounting fraud detection
- Airline deregulation
- Analysis of police stops
- Ban the Box legislation and subsequent impact on job applications
- *Statistical discrimination
- Calorie labeling mandates and food consumption
- *Risk compensation
- Challenging election results
- Condorcet's jury theorem
- Cost-benefit analysis of renewable portfolio standards for greenhouse gas abatement
- Effect of compulsory schooling on future earnings
- Effect of corporate board size on firm performance
- Effect of damage caps on medical malpractice claims
- Effect of a fiduciary standard on financial advice
- False conviction rate of inmates sentenced to death
- Legal evidence
- Legal informatics
- Ogden tables
- Optimal stopping of clinical trials
- Peremptory challenges in jury selection
- Personality predictors of antisocial behavior
- Predictive policing
- Predictors of criminal recidivism
- Prevalence of Caesarean delivery and malpractice claims risk
- Prosecutor's fallacy
- Reference class problem
Gender quotas on corporate boards
Using the binomial distribution, we may compute what the probability is of violating the rule laid out in Senate Bill 826 by the number of board members. The probability mass function for the binomial distribution is:where is the probability of getting successes in trials, and is the binomial coefficient. For this computation, is the probability that a person qualified for board service is female, is the number of female board members, and is the number of board seats. We will assume that.
Depending on the number of board members, we are trying compute the cumulative distribution function:With these formulas, we are able to compute the probability of violating Senate Bill 826 by chance:
3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
0.50 | 0.31 | 0.19 | 0.34 | 0.23 | 0.14 | 0.09 | 0.05 | 0.03 | 0.02 |
As Ilya Somin points out, a significant percentage of firms - without any history of sex discrimination - could be in violation of the law.
In more male-dominated industries, such as technology, there could be an even greater imbalance. Suppose that instead of parity in general, the probability that a person who is qualified for board service is female is 40%; this is likely to be a high estimate, given the predominance of males in the technology industry. Then the probability of violating Senate Bill 826 by chance may be recomputed as:
3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
0.65 | 0.48 | 0.34 | 0.54 | 0.42 | 0.32 | 0.23 | 0.17 | 0.12 | 0.08 |
Bayesian analysis of evidence
states that, for events and, the conditional probability of occurring, given that has occurred, is:Using the law of total probability, we may expand the denominator as:Then Bayes' theorem may be rewritten as:This may be simplified further by defining the prior odds of event occurring and the likelihood ratio as:Then the compact form of Bayes' theorem is:Different values of the posterior probability, based on the prior odds and likelihood ratio, are computed in the following table:If we take to be some criminal behavior and a criminal complaint or accusation, Bayes' theorem allows us to determine the conditional probability of a crime being committed. More sophisticated analyses of evidence can be undertaken with the use of Bayesian networks.
Screening of drug users, mass shooters, and terrorists
In recent years, there has been a growing interest in the use of screening tests to identify drug users on welfare, potential mass shooters, and terrorists. The efficacy of screening tests can be analyzed using Bayes' theorem.Suppose that there is some binary screening procedure for an action that identifies a person as testing positive or negative for the action. Bayes' theorem tells us that the conditional probability of taking action, given a positive test result, is:For any screening test, we must be cognizant of its sensitivity and specificity. The screening test has sensitivity and specificity. The sensitivity and specificity can be analyzed using concepts from the standard theory of statistical hypothesis testing:
- Sensitivity is equal to the statistical power, where is the type II error rate
- Specificity is equal to, where is the type I error rate
- We screen welfare recipients for cocaine use. The base rate in the population is approximately 1.5%, assuming no differences in use between welfare recipients and the general population.
- We screen men for the possibility of committing mass shootings or terrorist attacks. The base rate is assumed to be 0.01%.
Even with very high sensitivity and specificity, the screening tests only return posterior probabilities of 60.1% and 0.98% respectively for each action. Under more realistic circumstances, it is likely that screening would prove even less useful than under these hypothetical conditions. The problem with any screening procedure for rare events is that it is very likely to be too imprecise, which will identify too many people of being at risk of engaging in some undesirable action.