Why Punish? Social reciprocity and the enforcement of prosocial norms

Recently economists have become interested in why people who face social dilemmas in the experimental lab use the seemingly incredible threat of punishment to deter free riding. Three theories with evolutionary microfoundations have been developed to explain punishment. We survey these theories and use behavioral data from surveys and experiments to show that the theory called social reciprocity in which people punish norm violators indiscriminately explains punishment best.JEL Classification: C91, C92, D64, H41 Correspondence to: Jeffrey P. CarpenterWe thank Carolyn Craven, Corinna Noelke and two referees for comments, and Middlebury College for financial assistance. In addition, Carpenter acknowledges the support of the National Science Foundation (SES-CAREER 0092953).     

Toward a Phylogenetic Reconstruction of Organizational Life

Synopsis Classification is an important activity that facilitates theory development in many academic disciplines. Scholars in fields such as organizational science, management science and economics and have long recognized that classification offers an approach for ordering and understanding the diversity of organizational taxa (groups of one or more similar organizational entities). However, even the most prominent organizational classifications have limited utility, as they tend to be shaped by a specific research bias, inadequate units of analysis and a standard neoclassical economic view that does not naturally accommodate the disequilibrium dynamics of modern competition. The result is a relatively large number of individual and unconnected organizational classifications, which tend to ignore the processes of change responsible for organizational diversity. Collectively they fail to provide any sort of universal system for ordering, compiling and presenting knowledge on organizational diversity. This paper has two purposes. First, it reviews the general status of the major theoretical approaches to biological and organizational classification and compares the methods and resulting classifications derived from each approach. Definitions of key terms and a discussion on the three principal schools of biological classification (evolutionary systematics, phenetics and cladistics) are included in this review. Second, this paper aims to encourage critical thinking and debate about the use of the cladistic classification approach for inferring and representing the historical relationships underpinning organizational diversity. This involves examining the feasibility of applying the logic of common ancestry to populations of organizations. Consequently, this paper is exploratory and preparatory in style, with illustrations and assertions concerning the study and classification of organizational diversity.     

The Effect of Respondent Experience/Knowledge in the Elicitation of Contingent Values: An Investigation of Convergent Validity,Procedural Invariance and Reliability

Tests of convergent validity and procedural invariance were used to investigate whether individuals lacking direct experience with a commodity can provide valid responses to contingent-valuation questions eliciting ex post use values. Convergent validity between samples with and without experience was shown to hold for dichotomous-choice responses, but not for open-ended responses.     

Strategic Firm Behavior Under Average-Revenue-Lagged Regulation

Price caps have been shown to have incentive properties superior to traditional rate of return regulation. Average-revenue-lagged regulation (ARL) is attractive in that steady-state prices are known to be efficient. We show that the ARL scheme can be manipulated by the firm so as to yield the unregulated global profit maximum. While tests exist that can provide the regulator with evidence of this strategic behavior, we also demonstrate that the unregulated global profit maximum will not be attainable if Laspeyres (L) regulation is employed.Jel classification: L43, L51I would like to thank Michael Crew and an anonymous referee for their extremely helpful suggestions.     

Replicating portfolio approach to capital calculation

The replicating portfolio (RP) approach to the calculation of capital for life insurance portfolios is an industry standard. The RP is obtained from projecting the terminal loss of discounted asset–liability cash flows on a set of factors generated by a family of financial instruments that can be efficiently simulated. We provide the mathematical foundations and a novel dynamic and path-dependent RP approach for real-world and risk-neutral sampling. We show that our RP approach yields asymptotically consistent capital estimators if the chaotic representation property holds. We illustrate the tractability of the RP approach by three numerical examples.     

An expansion in the model space in the context of utility maximization

In the framework of an incomplete financial market where the stock price dynamics are modeled by a continuous semimartingale (not necessarily Markovian), an explicit second-order expansion formula for the power investor’s value function—seen as a function of the underlying market price of risk process—is provided. This allows us to provide first-order approximations of the optimal primal and dual controls. Two specific calibrated numerical examples illustrating the accuracy of the method are also given.     

A risk-neutral equilibrium leading to uncertain volatility pricing

We study the formation of derivative prices in an equilibrium between risk-neutral agents with heterogeneous beliefs about the dynamics of the underlying. Under the condition that short-selling is limited, we prove the existence of a unique equilibrium price and show that it incorporates the speculative value of possibly reselling the derivative. This value typically leads to a bubble; that is, the price exceeds the autonomous valuation of any given agent. Mathematically, the equilibrium price operator is of the same nonlinear form that is obtained in single-agent settings with worst-case aversion against model uncertainty. Thus, our equilibrium leads to a novel interpretation of this price.     

Chebyshev interpolation for parametric option pricing

Recurrent tasks such as pricing, calibration and risk assessment need to be executed accurately and in real time. We concentrate on parametric option pricing (POP) as a generic instance of parametric conditional expectations and show that polynomial interpolation in the parameter space promises to considerably reduce run-times while maintaining accuracy. The attractive properties of Chebyshev interpolation and its tensorized extension enable us to identify broadly applicable criteria for (sub)exponential convergence and explicit error bounds. The method is most promising when the computation of the prices is most challenging. We therefore investigate its combination with Monte Carlo simulation and analyze the effect of (stochastic) approximations of the interpolation. For a wide and important range of problems, the Chebyshev method turns out to be more efficient than parametric multilevel Monte Carlo. We conclude with a numerical efficiency study.     

Explosion in the quasi-Gaussian HJM model

We study the explosion of the solutions of the SDE in the quasi-Gaussian HJM model with a CEV-type volatility. The quasi-Gaussian HJM models are a popular approach for modeling the dynamics of the yield curve. This is due to their low-dimensional Markovian representation which simplifies their numerical implementation and simulation. We show rigorously that the short rate in these models explodes in finite time with positive probability, under certain assumptions for the model parameters, and that the explosion occurs in finite time with probability one under some stronger assumptions. We discuss the implications of these results for the pricing of the zero coupon bonds and Eurodollar futures under this model.     

Stochastic evolution equations in Banach spaces and applications to the Heath–Jarrow–Morton–Musiela equations

The aim of this paper is threefold. Firstly, we study stochastic evolution equations (with the linear part of the drift being a generator of a \(C_{0}\)-semigroup) driven by an infinite-dimensional cylindrical Wiener process. In particular, we prove, under some sufficient conditions on the coefficients, the existence and uniqueness of solutions for these stochastic evolution equations in a class of Banach spaces satisfying the so-called \(H\)-condition. Moreover, we analyse the Markov property of the solutions.Secondly, we apply the abstract results obtained in the first part to prove the existence and uniqueness of solutions to the Heath–Jarrow–Morton–Musiela (HJMM) equations in weighted Lebesgue and Sobolev spaces.Finally, we study the ergodic properties of the solutions to the HJMM equations. In particular, we find a sufficient condition for the existence and uniqueness of invariant measures for the Markov semigroup associated to the HJMM equations (when the coefficients are time-independent) in the weighted Lebesgue spaces.Our paper is a modest contribution to the theory of financial models in which the short rate can be undefined.