Mechanism of Instrumental Game Theory in the Legal Process via Stochastic Options Pricing Induction

Economic theory has provided an estimable intuition in understanding the perplexing ideologies in law, in the areas of economic law, tort law, contract law, procedural law and many others. Most legal systems require the parties involved in a legal dispute to exchange information through a process called discovery. The purpose is to reduce the relative optimisms developed by asymmetric information between the parties. Like a head or tail phenomenon in stochastic processes, uncertainty in the adjudication affects the decisions of the parties in a legal negotiation. This paper therefore applies the principles of aleatory analysis to determine how negotiations fail in the legal process, introduce the axiological concept of optimal transaction cost and formulates a numerical methodology based on backwards induction and stochastic options pricing economics in estimating the reasonable and fair bargain in order to induce settlements thereby increasing efficiency and reducing social costs.

Bootstrapping the Early Exercise Boundary in the Least-Squares Monte Carlo Method

This paper proposes an innovative algorithm that significantly improves on the approximation of the optimal early exercise boundary obtained with simulation based methods for American option pricing. The method works by exploiting and leveraging the information in multiple cross-sectional regressions to the fullest by averaging the individually obtained estimates at each early exercise step, starting from just before maturity, in the backwards induction algorithm. With this method, less errors are accumulated, and as a result of this, the price estimate is essentially unbiased even for long maturity options. Numerical results demonstrate the improvements from our method and show that these are robust to the choice of simulation setup, the characteristics of the option, and the dimensionality of the problem. Finally, because our method naturally disassociates the estimation of the optimal early exercise boundary from the pricing of the option, significant efficiency gains can be obtained by using less simulated paths and repetitions to estimate the optimal early exercise boundary than with the regular method.

Agent-Relative Prerogatives and Suboptimal Beneficence

The first part of Chapter 11 uses considerations of sequential choice to argue that suboptimal beneficence is impermissible. The second part shows how the prohibition on suboptimal beneficence follows from an agent-relative theory that understands permissible actions in terms of a dominance principle defined over both the agent-relative and the agent-neutral ordering. This theory incorporates agent-relative prerogatives that ensure that agents are not required to do what is impartially best, yet rules out suboptimal beneficence. The third part shows that the prohibition on suboptimal beneficence is in tension with dynamic consistency, since it leads to violations of expansion consistency condition BETA. If an agent makes use of myopic choice principles (which are purely forward-looking) or sophisticated choice principles (that make use of backwards induction), then there can be cases in which he can, by means of a sequence of permissible choices, bring about an outcome that is deemed to be impermissible from the outset. This problem is addressed by developing global choice principles that ensure dynamic consistency.

Challenges to Inference in the Study of Crisis Bargaining

The possibility that actors strategically condition their behavior on partially unobservable factors poses a grave challenge to causal inference, particularly if only some of the actors whose behavior we analyze are at risk of experiencing the outcome of interest. We present a crisis bargaining model that indicates that targets can generally prevent war by arming. We then create a simulated data set where the model is assumed to perfectly describe interactions for those states engaged in crisis bargaining, which we assume most pairs of states arenot. We further assume researchers cannot observe which states are engaged in crisis bargaining, although observable variables might serve as proxies. We demonstrate that a naïve design would falsely (and unsurprisingly) indicate a positive relationship between arming and war. More importantly, we then evaluate the performance of matching, instrumental variables, and statistical backwards induction. The latter two show some promise, but matching fares poorly.

Does WTO Dispute Settlement Enforce or Inform?

Whereas some researchers emphasize how World Trade Organization (WTO) dispute settlement reduces complexity and clarifies legislation, others argue that dispute rulings promote co-operation by providing an enforcement mechanism. This article identifies empirical implications from these distinct arguments and tests them on WTO disputes from 1995 to 2006. The study's analytical approach combines a three-step coding of dispute escalation with a strategic bargaining model and statistical backwards induction to account for governments’ forward-looking behavior. It finds strong support for the argument that WTO dispute settlement primarily serves as an enforcement device. It finds much less support for the argument that dispute settlement reduces complexity and clarifies trade law. These results suggest that the role of WTO dispute settlement in generating information on acceptable trade policy standards is less relevant than proponents of the complexity argument tend to assume.