Simultaneous equations with binary outcomes and social interactions

This paper introduces a discrete-choice simultaneous-equation social interaction model. We provide a microfoundation for the econometric model by considering an incomplete information game where individuals interact in multiple activities through a network. We characterize the sufficient condition for the existence of a unique BNE of the game. We discuss the identification of the econometric model and propose a two-stage estimation procedure, where the reduced form parameters are estimated by the NPL algorithm in the first stage and the structural parameters are recovered from the estimated reduced form parameters by the AGLS estimator in the second stage. Monte Carlo experiments show that the proposed estimation procedure performs well in finite samples and remains computationally feasible when networks are large. We also provide an empirical example to illustrate the empirical relevance of the proposed model.     

Complement to a comparative analysis of heuristics for the <Emphasis Type=Italic>p</Emphasis>-median problem

A recent comparison of evolutionary, neural network, and scatter search heuristics for solving the p-median problem is completed by (i) gathering or obtaining exact optimal values in order to evaluate errors precisely, and (ii) including results obtained with several variants of a variable neighborhood search (VNS) heuristic. For a first, well-known, series of instances, the average errors of the evolutionary and neural network heuristics are over 10% and more than 1000 times larger than that of VNS. For a second series, this error is about 3% while the errors of the parallel VNS and of a hybrid heuristic are about 0.01% and that of parallel scatter search even smaller.     

基于BP神经网络的S＆P500指数期权定价

期权定价理论源于影响期权价格的变量和期权价格之间的非线性关系,传统的Black-Scholes期权定价公式过于严格的假设削弱了该公式在现实中的适用性,使其在理论与应用上均存在缺陷。因此,能够以任意精度近似复杂非线性系统的神经网络运用于期权定价。分别利用BP神经网络和Black-Scholes期权定价公式对S＆P 500指数看跌期权进行定价,实证结果表明BP神经网络的定价结果要优于Black-Scholes定价公式。     

A LINEAR PROGRAMMING APPROACH TO THE STEADY-STATE ANALYSIS OF REFLECTED BROWNIAN MOTION

Abstract

We consider a flow of data packets from one source to many destinations in a communication network represented by a random oriented tree. Multicast transmission is characterized by the ability of some tree vertices to replicate received packets depending on the number of destinations downstream. We are interested in characteristics of multicast flows on Galton–Watson trees and trees generated by point aggregates of a Poisson process. Such stochastic settings are intended to represent tree shapes arising in the Internet and in some ad hoc networks. The main result in the branching process case is a functional equation for the joint probability generating function of flow volumes through a given vertex and in the whole tree. We provide conditions for the existence and uniqueness of solution and a method to compute it using Picard iterations. In the point process case, we provide bounds on flow volumes using the technique of stochastic comparison from the theory of continuous percolation. We use these results to derive a number of random trees' characteristics and discuss their applications to analytical evaluation of the load induced on a network by a multicast session.     

A (Semi)Parametric Functional Coefficient Logarithmic Autoregressive Conditional Duration Model

In this article, we propose a class of logarithmic autoregressive conditional duration (ACD)-type models that accommodates overdispersion, intermittent dynamics, multiple regimes, and asymmetries in financial durations. In particular, our functional coefficient logarithmic autoregressive conditional duration (FC-LACD) model relies on a smooth-transition autoregressive specification. The motivation lies on the fact that the latter yields a universal approximation if one lets the number of regimes grows without bound. After establishing sufficient conditions for strict stationarity, we address model identifiability as well as the asymptotic properties of the quasi-maximum likelihood (QML) estimator for the FC-LACD model with a fixed number of regimes. In addition, we also discuss how to consistently estimate a semiparametric variant of the FC-LACD model that takes the number of regimes to infinity. An empirical illustration indicates that our functional coefficient model is flexible enough to model IBM price durations.     

Geographies of Social Networks: Meetings,Travel and Communications

The past decade has seen striking increases in travel and in communications at‐a‐distance through mobile phone calls, text messaging and emailing. People in prosperous societies are both travelling and communicating more to connect with absent others. People can travel, relocate and migrate and yet still be connected with friends and family members ‘back home’. So, increasingly, people who are near emotionally may be geographically very far away; yet they are only a journey, email or a phone call away. In this article we attempt to examine how such strong ties are spatially distributed and sustained through specific geographies of travel, meetings and communications. How often do strong ties meet, talk at‐at‐distance and write, and to what degree does distance determine regularity? To what extent are communications enhancing and/or substituting for physical travel? We examine in particular to what degree far‐flung ties and emotional networking at‐a‐distance are characteristic of many people other than the transnational ‘elites’ and ‘underprivileged’ migrants. We consider the notion of ‘network capital’.     

Fashions, habits and changing preferences: Simulation of psychological factors affecting market dynamics

Markets can show different types of dynamics, from quiet markets dominated by one or few products, to markets with constant penetration of new and reintroduced products. This paper explores the dynamics of markets from a psychological perspective using a multi-agent simulation model. The behavioural rules of the artificial consumers, the consumats, are based on a conceptual meta-theory from psychology. The artificial consumers have to choose each period between similar products. Products remain in the market as long as they maintain a minimum level of market share, else they will be replaced by a new product. Assuming a population of consumats with different preferences, and social networks, the model simulates adoption of new products for alternative assumptions on behavioural rules. Furthermore, the consequences of changing preferences and the size of social networks are explored. Results show that the behavioural rules that dominate the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in and unstable renewal. Results also show the importance of psychological variables like social networks, preferences and the need for identity to explain the dynamics of markets.     

Symbolic Interactionism and Social Network Analysis: An Uncertain Encounter

The aim of this article is to respond to the question of whether social networks represent a possible terrain of application and investment for interactionist research. The answer to that question is, without a doubt, affirmative. What appears to be truly problematic, if not completely improbable, is that this investment can come about through a “coming together” of symbolic interactionism and social network analysis. The vocational focus that has evolved in the two perspectives, the conceptual frameworks and methods used for the study of social interactions and their interlinking in relational networks, presents aspects of extreme differentiation that render a possible convergence quite difficult.     

Embracing and Resisting Ethnoracial Boundaries: Second‐Generation Immigrant and African‐American Students in a Multicultural University1

The transformation of college campuses related to the growing presence of minority youth and the arrival of second‐generation immigrants offers opportunities for exploring the formation of social and cultural boundaries and ethnoracial identities in local multicultural contexts. Absent from many discussions of the merits of multicultural college settings is specification of the interactional processes and cultural transformations that presumably lie at the heart of diversity payoffs. This project focuses on students from four minority groups, three of whom are second‐generation immigrants, in a racially diverse university, combining focus groups and in‐depth interviews. First, we analyze how the social mixing practices of students congeal into ethnoracial boundaries on campus. We find that two images of multiculturalism (“fragmented pluralism” and “interactive pluralism”) play out simultaneously on this campus. Second, we examine the pathways leading to more insular ethnoracial mixing and toward more heterogeneous social mixing, as well as explore the cultural meanings of these practices in student narratives. We also compare the influence of campus context, student agency, and internal and external group pressures on varying degrees of student satisfaction with their achieved social worlds.     

Social fabric and fear of crime: Considering spatial location and time of day

Criminologists have long noted that social networks play a role in influencing residents' fear of crime, but findings vis a vis the exact nature of that role have been mixed. More social ties may be associated with less fear of crime through their role in collective action, trust, and emotional support, but also with more fear of crime because of their role in the diffusion of information on local crime patterns. In what follows, we suggest temporal and spatial distinctions in how social ties matter for fear of crime with respect to these different mechanisms. Analysis of data from a large scale egocentric network study in Southern California provides evidence for these claims.