A Markov switching analysis of contagion in the EMS

This paper applies the multivariate version of the Forbes and Rigobon (2002) contagion test, as proposed by Dungey et al. (2005a), to detect contagion effects in the Exchange Rate Mechanism (ERM) of the European Monetary System (EMS). Crisis and non-crisis observations are determined endogenously via a Markov-switching vector autoregression (MSVAR). We show that the MSVAR is suitable for this purpose, as it does particularly well in identifying the 11 realignments of the ERM. We examine whether Denmark’s rejection of the Maastricht Treaty and Italy’s competitiveness problems affected other EMS participants and find evidence for contagion.     

基于马尔柯夫分析的计算机预测和决策应用

从DSS应用现状出发,介绍了马尔柯夫分析的定义和数学原理,阐述了马尔柯夫分析的过程和预测的基本步骤,利用Excel设计了进行市场占有率预测的应用模型,并进行了仿真预测和决策分析。测试表明,应用模型简便通用,操作方便,提高了预测的计算精度和效率。     

Small-sample Properties of Panel Spatial Autoregressive Models: Comparison of the Bayesian and Maximum Likelihood Methods

Abstract

This article considers autoregressive (SAR) models. We method to estimate the parameters of likelihood (ML) method. Our Bayesian by the Monte Carlo studies. We found the efficient as the ML estimators.     

Median‐voter Equilibria in the Neoclassical Growth Model under Aggregation*

We study a dynamic version of Meltzer and Richard's median‐voter model where agents differ in wealth. Taxes are proportional to income and are redistributed as equal lump‐sum transfers. Voting occurs every period and each consumer votes for the tax that maximizes his welfare. We characterize time‐consistent Markov‐perfect equilibria twofold. First, restricting utility classes, we show that the economy's aggregate state is mean and median wealth. Second, we derive the median‐voter's first‐order condition interpreting it as a tradeoff between distortions and net wealth transfers. Our method for solving the steady state relies on a polynomial expansion around the steady state.     

MC's for MCMC'ists

We develop a minimum amount of theory of Markov chains at as low a level of abstraction as possible in order to prove two fundamental probability laws for standard Markov chain Monte Carlo algorithms:
1. The law of large numbers explains why the algorithm works: it states that the empirical means calculated from the samples converge towards their "true" expected values, viz. expectations with respect to the invariant distribution of the associated Markov chain (=the target distribution of the simulation).
2. The central limit theorem expresses the deviations of the empirical means from their expected values in terms of asymptotically normally distributed random variables. We also present a formula and an estimator for the associated variance.     

A useful tool for forecasting the Euro-area business cycle phases

Based on a novel extension of existing multivariate Markov-switching models, we provide the reader with a useful tool for analyzing current business conditions and making predictions about the future state of the Euro-area economy in real time. Apart from the Industrial Production Index, we find that the European Commission Industrial Confidence Indicator, which is issued with no delay, is very useful for constructing the real-time predictions.     

本土企业应对跨国公司"全球化链条"的战略选择

跨国公司在全球经济生活中正发挥着越来越重要的作用,而"全球化链条"是确保其竞争优势的一大利器,它在同中国本土企业的竞争中将日益发挥其威力。中国本土企业采取何种战略应对竞争是理论家们讨论最多的话题,本文先对"全球化链条"的优势进行剖析,然后相应提出中国本土企业应对     

Stationary measures for some Markov chain models in ecology and economics

Summary. Let continuous, exists in for x in . Let be an i.i.d. sequence from F and X₀ be a nonnegative random variable independent of . Let be the Markov chain generated by the iteration of random maps by . Such Markov chains arise in population ecology and growth models in economics. This paper studies the existence of nondegenerate stationary measures for {X_n}. A set of necessary conditions and two sets of sufficient conditions are provided. There are some convergence results also. The present paper is a generalization of the work on random logistics maps by Athreya and Dai (2000).Received: 20 March 2002, Revised: 4 December 2002, JEL Classification Numbers: C22, D9.The author wishes to thank Professor Mukul Majumdar and the referees for several useful suggestions.     

基于模块化的企业价值网络及其竞争优势研究

以价值模块化为基础,传统的集合型价值链经过解构、整合和重建形成具有差异化竞争优势的模块化价值链。不同企业的价值模块和模块化价值链在共同的界面标准内交叉连接、融合贯通,形成企业价值网络。企业价值网络集聚各成员企业的优势资源,将各种能力要素协同在一个无形的网络平台上,通过不同组织模块之间的协作、创新和竞争,能够产生新的竞争优势。企业以价值模块化为基础,对自身价值链进行整合,融入企业价值网络,能够分享网络内成员企业的优势资源和技术创新成果,共享模块化经济,增强企业核心竞争力和抗风险能力。模块化时代,企业之间的竞争已经演进为企业价值网络之间的竞争。