移动通信单向收费定价策略研究

随着移动通信业务的飞速发展,其收费模式和定价策略为世界各国所关注。本文从中国电信产业现状出发,对移动通信单向收费定价策略进行研究,结果表明:①网络外部性对移动通信市场有福利增加效果;②产业发展早期,可采取呼叫付费原则发展移动通信;③产业发展后期,可采取分离付费原则增加社会福利。     

Führung aus neuer Perspektive

New perspectives on leadership. Reflecting and constructing realities in the surplus reality of psychodramaThe authors show how the psychodramatic concept of surplus reality can be used as a frame of reference for action-oriented, experiential interventions in leadership coaching. The concept is shown to have four different facets: surplus reality as a term for (1) the intangible dimensions of reality, (2) the non-verbal dimensions of reality, (3) the action space of psychodrama, (4) human imagination. The use of mental imagery and metaphors is shown to be a realization of the surplus reality principle. Case studies and practical hints for leadership coaches illustrate how surplus reality can be used to open up new ways of learning.     

跳过程下的公司证券定价和最优资本结构

由于几何布朗运动不能反映复杂经济背景下的资产价值动态,本文以双指数跳扩散过程作为资产价值过程来研究公司证券定价和最优资本结构问题。本文主要结果是：运用均衡定价的方法给出了公司证券的定价并获得了公司资本价值的解析解。通过比较静态分析揭示了跳风险对企业资本价值、最优资本结构、收益率差价等都具有显著的影响。与几何布朗运动相比,跳风险降低了公司价值和债券价值以及公司最优杠杆率,同时增加了债券的收益率差价和股权价值。     

中国合意城市化率研究

城市化是中国经济发展的必然要求。当经济持续发展到一定阶段,消除农村与城市的差距,实现社会公平,吸收转移掉农业剩余劳动力并保持农业规模不下降时,我们认为中国的城市化便达到一个合意的城市化水平,即合意城市化率。本文将从宏观角度出发,根据历年的统计资料,结合模型分析,得出中国合意城市化率,为 63%左右。更重要的是,我们认为中国下阶段经济增长的关键点是加速城市化进程,达到合意城市化水平。作为本文分析的中间成果,我们在保持农业规模不下降的条件下,根据柯布—道格拉斯生产函数,借助回归分析和二维搜索等数学方法,求出中国农业剩余劳动力数目,为 2.06亿人。     

Strategic Supply Function Competition With Private Information

A finite number of sellers (n) compete in schedules to supply an elastic demand. The cost of each seller is random, with common and private value components, and the seller receives a private signal about it. A Bayesian supply function equilibrium is characterized: The equilibrium is privately revealing and the incentives to rely on private signals are preserved. Supply functions are steeper with higher correlation among the cost parameters. For high (positive) correlation, supply functions are downward sloping, price is above the Cournot level, and as we approach the common value case, price tends to the collusive level. As correlation becomes maximally negative, we approach the competitive outcome. With positive correlation, private information coupled with strategic behavior induces additional distortionary market power above full information levels. Efficiency can be restored with appropriate subsidy schemes or with a precise enough public signal about the common value component. As the market grows large with the number of sellers, the equilibrium becomes price‐taking, bid shading is on the order of 1/n, and the order of magnitude of welfare losses is 1/n². The results extend to inelastic demand, demand uncertainty, and demand schedule competition. A range of applications in product and financial markets is presented.     

The Time Series and Cross‐Section Asymptotics of Dynamic Panel Data Estimators

In this paper we derive the asymptotic properties of within groups (WG), GMM, and LIML estimators for an autoregressive model with random effects when both T and N tend to infinity. GMM and LIML are consistent and asymptotically equivalent to the WG estimator. When T/N→ 0 the fixed T results for GMM and LIML remain valid, but WG, although consistent, has an asymptotic bias in its asymptotic distribution. When T/N tends to a positive constant, the WG, GMM, and LIML estimators exhibit negative asymptotic biases of order 1/T, 1/N, and 1/(2N−T), respectively. In addition, the crude GMM estimator that neglects the autocorrelation in first differenced errors is inconsistent as T/N→c>0, despite being consistent for fixed T. Finally, we discuss the properties of a random effects pseudo MLE with unrestricted initial conditions when both T and N tend to infinity.     

Clustering microarray data using model-based double K-means

The microarray technology allows the measurement of expression levels of thousands of genes simultaneously. The dimension and complexity of gene expression data obtained by microarrays create challenging data analysis and management problems ranging from the analysis of images produced by microarray experiments to biological interpretation of results. Therefore, statistical and computational approaches are beginning to assume a substantial position within the molecular biology area. We consider the problem of simultaneously clustering genes and tissue samples (in general conditions) of a microarray data set. This can be useful for revealing groups of genes involved in the same molecular process as well as groups of conditions where this process takes place. The need of finding a subset of genes and tissue samples defining a homogeneous block had led to the application of double clustering techniques on gene expression data. Here, we focus on an extension of standard K-means to simultaneously cluster observations and features of a data matrix, namely double K-means introduced by Vichi (2000). We introduce this model in a probabilistic framework and discuss the advantages of using this approach. We also develop a coordinate ascent algorithm and test its performance via simulation studies and real data set. Finally, we validate the results obtained on the real data set by building resampling confidence intervals for block centroids.     

Exact likelihood inference for Laplace distribution based on Type-II censored samples

We develop exact inference for the location and scale parameters of the Laplace (double exponential) distribution based on their maximum likelihood estimators from a Type-II censored sample. Based on some pivotal quantities, exact confidence intervals and tests of hypotheses are constructed. Upon conditioning first on the number of observations that are below the population median, exact distributions of the pivotal quantities are expressed as mixtures of linear combinations and of ratios of linear combinations of standard exponential random variables, which facilitates the computation of quantiles of these pivotal quantities. Tables of quantiles are presented for the complete sample case.     

分类数据的计量误差模型

二分类总体单元被错误分类情形下,样本比例是总体比例的有偏估计。给出调整比例估计的两种方法：双样本方法和极大似然法,补充了经典抽样理论比例估计的内容。     

MAXIMUM LIKELIHOOD ESTIMATION FOR A POISSON RATE PARAMETER WITH MISCLASSIFIED COUNTS

This paper proposes a Poisson‐based model that uses both error‐free data and error‐prone data subject to misclassification in the form of false‐negative and false‐positive counts. It derives maximum likelihood estimators (MLEs) for the Poisson rate parameter and the two misclassification parameters — the false‐negative parameter and the false‐positive parameter. It also derives expressions for the information matrix and the asymptotic variances of the MLE for the rate parameter, the MLE for the false‐positive parameter, and the MLE for the false‐negative parameter. Using these expressions the paper analyses the value of the fallible data. It studies characteristics of the new double‐sampling rate estimator via a simulation experiment and applies the new MLE estimators and confidence intervals to a real dataset.