A statistical equilibrium model of competitive firms

We find that the empirical density of firm profit rates, measured as returns on assets, is markedly non-Gaussian and reasonably well described by an exponential power (or Subbotin) distribution. We start from a statistical equilibrium model that leads to a stationary Subbotin density in the presence of complex interactions among competitive heterogeneous firms. To investigate the dynamics of firm profitability, we construct a diffusion process that has the Subbotin distribution as its stationary probability density. This leads to a phenomenologically inspired interpretation of variations in the shape parameter of the Subbotin distribution, which essentially measures the competitive pressure in and across industries. Our findings have profound implications both for the previous literature on the ‘persistence of profits’ as well as for understanding competition as a dynamic process. Our main formal finding is that firms' idiosyncratic efforts and the tendency for competition to equalize profit rates are two sides of the same coin, and that a ratio of these two effects ultimately determines the dispersion of the equilibrium distribution.     

Ordering univariate distributions by entropy and variance

This paper examines the role of variance and entropy in ordering distributions and random prospects. There is no universal relation between entropy and variance orderings of distributions. But we place their relationship in the context of a stronger ordering relation known as dispersion ordering. Further, some conditions are identified under which variance and entropy order similarly when continuous variables are transformed. We also analyze parametric changes which do not disturb the agreement between these rankings. The results are conveniently tabulated in terms of distribution parameters.     

基于熵理论的企业激励模型研究

激励的发生是正熵流与负熵流矛盾运动的过程,产生激励正熵的因素主要有:目标设置不当、组织结构僵化、工作设计过于专业化、奖惩不公平等;产生激励负熵的因素有:设置合理的目标、改革组织结构、重新进行工作设计、公平及时地进行奖惩、营造积极向上的企业文化、引入适度竞争等。这从本质上揭示了企业激励的实质和如何进行改革。     

Inter-Firm and Intra-Firm Efficiency Measures

Intra-firm efficiencyinvolves computing a particular firm's efficiency degree overtime relative to the firm-specific production frontier. Inter-firmefficiency reveals a particular firm's performance over timerelative to the ``best practice frontier' among the set of comparablefirms. These efficiency measures are related by an inter-firmcatch-up component reflecting differences in technology acrossfirms. Those measures are estimated for Dutch pot-plant firmsusing the Generalized Maximum Entropy formalism. The empiricalresults suggest the inter-firm catch-up component is the majordeterminant of inter-firm efficiency.     

基于组织结构熵与耗散结构理论的企业组织结构完善研究

企业组织结构的合理性及混乱程度一般认为是无法量化和衡量的,只能通过组织内部各项定性指标来进行评价。热力学概念熵是揭示系统无序程度的物理定量方法,而企业的系统性、开放性为企业组织结构熵的提出提供了必要条件。在企业管理中引用熵理论,有利于更加直观地了解组织结构合理性问题。通过耗散结构理论对无序、混乱、熵值较高的组织结构引入"负熵"进行改造,降低企业组织结构熵值,使组织结构向有序化方向发展。     

A Paradigm for Masking (Camouflaging) Information

This is an expository paper. Here we propose a decision-theoretic framework for addressing aspects of the confidentiality of information problems in publicly released data. Our basic premise is that the problem needs to be conceptualized by looking at the actions of three agents: a data collector, a legitimate data user, and an intruder. Here we aim to prescribe the actions of the first agent who desires to provide useful information to the second agent, but must protect against possible misuse by the third. The first agent is under the constraint that the released data has to be public to all; this in some societies may not be the case.
A novel aspect of our paper is that all utilities—fundamental to decision making—are in terms of Shannon's information entropy. Thus what gets released is a distribution whose entropy maximizes the expected utility of the first agent. This means that the distribution that gets released will be different from that which generates the collected data. The discrepancy between the two distributions can be assessed via the Kullback–Leibler cross-entropy function. Our proposed strategy therefore boils down to the notion that it is the information content of the data, not the actual data, that gets masked. Current practice of "statistical disclosure limitation" masks the observed data via transformations or cell suppression. These transformations are guided by balancing what are known as "disclosure risks" and "data utility". The entropy indexed utility functions we propose are isomorphic to the above two entities. Thus our approach provides a formal link to that which is currently practiced in statistical disclosure limitation.     

The LIML estimator has finite moments!

The Limited Information Maximum Likelihood estimator of the vector of coefficients of a structural equation in a simultaneous equation model is the vector that defines the linear combination maximizing the effect variance relative to the error variance. If this “eigenvector” solution is normalized by setting a designated coefficient equal to 1, the second-order moment of the estimator may be unbounded. However, the second-order moment is finite if the normalization sets the sample error variance of the linear combination equal to 1.     

GMM estimation of a maximum entropy distribution with interval data

We develop a generalized method of moments (GMM) estimator for the distribution of a variable where summary statistics are available only for intervals of the random variable. Without individual data, one cannot calculate the weighting matrix for the GMM estimator. Instead, we propose a simulated weighting matrix based on a first-step consistent estimate. When the functional form of the underlying distribution is unknown, we estimate it using a simple yet flexible maximum entropy density. Our Monte Carlo simulations show that the proposed maximum entropy density is able to approximate various distributions extremely well. The two-step GMM estimator with a simulated weighting matrix improves the efficiency of the one-step GMM considerably. We use this method to estimate the U.S. income distribution and compare these results with those based on the underlying raw income data.     

Two state capital accumulation with heterogenous products: Disruptive vs. non-disruptive goods

The paper considers the problem of a firm that, while producing a standard product, has the option to introduce an innovative product. The innovative product competes with the standard product and will therefore reduce revenues of the standard product. A distinction is made between innovative products that do or do not become even more relatively appealing as their market share grows (e.g., because of network externalities). It is shown that in the former case, which we call a “disruptive” good, history dependent long run equilibria can occur, which are in line with recent real life economic examples.     

保障房退出机制研究

保障性住房退出机制建设是实现有限资源条件下住房资源优化配置的前提。在有限理性的条件下,通过建立进化博弈模型对退出机制进行均衡分析,设计了有效退出选择模型。结果表明:实现保障性住房的有效退出,关键在于合理制定奖惩金额以增加拖延退出的成本。根据有效退出模型所推导的奖惩金额计算公式,为政府合理制定奖惩标准提供了一种思路。     

基于熵定律的产品造型设计原理探析

现代产品是科技与美的凝结,产品造型是传递功能、传达理念、美学诉求的载体。熵定律是普遍存在于自然界、人类社会、精神领域等一切时空的普遍规律,本文从熵定律的角度,并结合格式塔心理学,对产品造型感性需求的深层心理机制、产品复杂度与审美共鸣、低熵整体观的传达等问题作出了剖析,从中总结出指导设计的一些方法原则。     

辽宁省朝阳市物流发展影响因素的灰关联熵分析

选用了灰关联熵的分析方法对影响朝阳物流发展的因素进行定量分析,通过比较灰关联熵来找出影响朝阳物流发展的主要因素,克服了以往人们主观、定性分析的缺点,为朝阳物流业科学合理的发展提供依据。     

有关GIS的架构与应用

随着现代科学技术的迅猛发展,世界将进入以创新为基础的知识经济时代,科学技术将成为经济发展的最重要的资源和首要的推动力,同时更是全球可持续发展战略的核心。站在知识创新的高度、时代的高度、战略地位的高度,发展GIS成为新世纪全球科技信息化的热点。这篇文章针对GIS的架构、以及实用性来简要探讨GIS的重要性。