Penalized Pseudolikelihood Inference in Spatial Interaction Models with Covariates

Given spatially located observed random variables ( x , z = {( x _i , z _i )} _i , we propose a new method for non-parametric estimation of the potential functions of a Markov random field p ( x | z ), based on a roughness penalty approach. The new estimator maximizes the penalized log-pseudolikelihood function and is a natural cubic spline. The calculations involved do not rely on Monte Carlo simulation. We suggest the use of B-splines to stabilize the numerical procedure. An application in Bayesian image reconstruction is described.     

Medical Students' Attitudes and Opinions About Human Sexual Behaviour

In their professional capacities doctors are often confronted with clients who present with psycho-sexual problems. At the present time Australian medical students are provided with very little instruction in the areas of human sexual behaviour. This paper examines the attitudes and amount of information possessed by a cohort of second year medical students compared with groups of first and fifth year students; these attitudes and levels of information are then related to students' sex, religious affiliation, strength of religious conviction, where this is seen to be relevant. It is shown that some areas of ignorance exist. The paper concludes by outlining some aspects relevant to courses in human sexual behaviour.     

全球视野中的西方历史思想:十个命题

所谓“西方”,本身是一个历史的建构。欧洲特定的文化背景,历史上一系列的文化及社会运动,对历史思想和历史书写都产生了重大影响,使得西方史学具有了一定程度上的独特性,譬如强调进步和发展等等。然而这种独特性并不是一连串独一无二的特征,也不意味着西方历史著作的方式在所有方面都优于其他方式。归根到底,正是不同体系之间的冲突,尤其是不同“力量”之间的动态平衡,才构成西方历史思想和历史书写的特点。     

TWO-PIECE VON NEUMANN-MORGENSTERN UTILITY FUNCTIONS*

Thirty empirically assessed utility functions on changes in wealth or return on investment were examined for general features and susceptability to fits by linear, power, and exponential functions. Separate fits were made to below-target data and above-target data. The usual “target” was the no-change point. The majority of below-target functions were risk seeking; the majority of above-target functions were risk averse; and the most common composite shape was convex-concave, or risk seeking in losses and risk averse in gains. The least common composite was concave-concave. Below-target utility was generally steeper than above-target utility with a median below-to-above slope ratio of about 4.8. The power and exponential fits were substantially better than the linear fits. Power functions gave the best fits in the majority of convex below-target and concave above-target cases, and exponential functions gave the best fits in the majority of concave below-target and convex above-target cases. Several implications of these results for decision making under risk are mentioned.     

Dynamic reasoning and time pressure: Transition from analytical operations to experiential responses

Based upon the Decision Field Theory (Busemeyer and Townsend 1993), we tested a model of dynamic reasoning to predict the effect of time pressure on analytical and experiential processing during decision-making. Forty-six participants were required to make investment decisions under four levels of time pressure. In each decision, participants were presented with experiential cues which were either congruent or incongruent with the analytical information. The congruent/incongruent conditions allowed us to examine how many decisions were based upon the experiential versus the analytical information, and to see if this was affected by the varying degrees of time pressure. As expected, the overall accuracy was reduced with greater time pressure and accuracy was higher when the experiential and analytical cues were congruent than when they were incongruent. Of great interest was the data showing that under high time pressure participants used more experiential cues than at other time pressures. We suggest that the dynamic reasoning paradigm has some future potential for predicting the effects of experiential biases in general, and specifically under time pressure.     

Identifying Latent Structures in Panel Data

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered—penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier‐Lasso (C‐Lasso) that serves to shrink individual coefficients to the unknown group‐specific coefficients. C‐Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C‐Lasso also achieves the oracle property so that group‐specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C‐Lasso is preserved in some special cases. Simulations demonstrate good finite‐sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented.     

A Business Model Innovation Typology

An effective business model is the core enabler of any company's performance. Business model innovation is not only becoming more and more important due to increasing and globalizing competition, but also an enormous challenge, both theoretically and practically. Although many managers are eager to consider more disruptive changes to their business model, they often do not know how to articulate their existing or desired business model and, even less so, understand the possibilities for innovating it. One of the steps toward developing more theoretical insight and practical guidelines is the identification of types and the development of a typology of business model innovations. Ten retrospective case studies of business model innovations undertaken by two industrial companies provide the empirical basis for this article. We analyzed the characteristics of these innovations as well as their success rates. The findings suggest that there are indeed various business model innovation types, each with its own characteristics and challenges.