Using a Demand System to Estimate Extended Input–Output Multipliers

The interface between household income and expenditure has always been considered to be a key component in the construction of input–output models. However, it can be argued that households are too often treated as if they were just another in dustry in the input–output table. In this paper, we seek to address this problem by developing a new modelling framework in which a micro demand system is used to estim ate the relationship between income and expenditure. This demand system is conjoined with an input–output table for the UK economy, and the system as a whole is solved as a computable general equilibrium model. Comparisons are made between the Jacobian multipliers generated by this model and those derived from a more traditional input–output model in which the income-expenditure linkage is estimated using static coefficients.     

An integrated structural model toward successful continuous improvement activity

This paper provides a different view from Bassent et al.'s (2001) toward a successful continuous improvement (CI) activity. Their concept encourages a business that is resting on its present accomplishments to seek greater gain. However, their behavioral model is not easy to operate for managers. In order to operate CI activity effectively and obtain company-wide involvement for management, we need a system which can meet the current CI status and lead the firm toward the correct road as described by Bessant et al. This system has to be open in the way that it can fit into any organization so that it can easily embed the necessary regenerative input into its physical structure. This system has also to be super in the way that it can successfully lead the organization structure toward the evolutionary route.Thus, we propose an open super system which places a pyramid composed by problem, models and tools, and promotion, at its core. Using Bessant et al.'s five evolutionary levels as a time map, this system can analyze a firm's improvement ability from the presentation of cases and find the proper regenerative input from the failure status. A firm can inject this input into its structure to upgrade its level of capability.Applying this open super system on our previous studies, we derived five improvement levels and the different ability types in each level. From there, we discovered some failure status in each level. We also drew some important perspectives on the injection of regenerative input from failure status, including the promotion of the technique-excellence ability, the value problem, and efficiently solving problem. To help the readers to understand this system better, we give ‘AB two stage’ system as an example to show how to inject regenerative input into the physical structure to fulfill the expectations from different perspectives.     

INTER-REGIONAL TRADE FLOW ESTIMATION THROUGH NON-SURVEY MODELS: AN EMPIRICAL ASSESSMENT

Inter-regional trade estimation has been pointed out as a crucial problem when constructing a multiregional input–output system. Knowledge of inter-regional trade flows, at least of the pooled volume of exports and imports by commodity, is critical in accounting for important spillover and feedback effects deriving from inter-regional linkages. However, in most countries, there are no completely reliable survey-based statistics on inter-regional trade. Thus, this paper intends to evaluate the reasonability of using indirect inter-regional trade estimates, comparing different estimating methods and assessing the sensitivity of the model results. Based on our empirical comparisons we conclude that input–output models are not greatly affected by the insertion of different trade values. Thus, our results support the use of indirect estimates for inter-regional trade, whenever survey-based data are unavailable.     

冲击性负荷对热电厂孤网动态稳定性研究

对某大型钢铁公司自备热电厂供配电系统正常运行期间的测试数据进行分析,结合系统供配电结构及运行方式建立系统SIMULINK仿真模型,研究了该配电系统孤网动态运行时输入功率不平衡导致电网的大幅度波动问题。周期性大容量的冲击负荷会引起系统频率的周期振荡,为此类供配电系统孤网运行可行性分析及存在问题评估提供可靠的理论支撑。     

流数据管理降载技术研究综述

流数据作为一种新的数据形态快速流行，但由于其连续快速不可预测的特点．当输入速率超过系统处理能力时，系统会产生过载。降载是解决该问题的有效途径。本文讨论了流数据管理降载的关键技术，分析了目前有代表性的流数据系统所采用的降载技术．同时给出了降载技术的研究趋势。     

Estimation and decomposition of inefficiency when producers maximize return to the outlay: an application to Norwegian fishing trawlers

This paper deals with estimation of a production technology where endogeneous choice of input and output variables is explicitly recognized. In particular, we assume that producers maximize return to the outlay (RO). For simplicity and tractability we start with a Cobb–Douglas transformation function with multiple inputs and outputs and show how the first-order conditions of RO maximization can be used to derive an estimating equation which is nothing but a partial input productivity equation. This equation does not suffer from the econometric endogeneity problem although the output and input variables are endogenous. First, we consider the case where producers are fully efficient allocatively but technically inefficient. The model is estimated using a single equation stochastic frontier approach. The model is then extended to allow allocative inefficiency and it is estimated as a system using generalized method of moment. Algebraic expressions are derived to decompose the effect of technical and allocative inefficiencies on RO. We also consider translog specifications that are estimated as (1) a single equation frontier model as well as (2) a system. We use a panel of Norwegian fishing trawlers data to estimate the model. Outputs are different species caught while inputs are labor and vessel size. We also control for number of days of operation, age of the vessel and year effects. Empirical results show that the average rate of RO is reduced by about 20 to 30 % due to technical inefficiency. On the other hand, average allocative efficiency is found to be about 78 %. The average overall efficiency is found to be around 60 %.     

可持续发展生产要素价值浅论

本文在传统经济学商品生产要素价值论的基础上,根据现实经济、社会和环境协调一致的可持续发展要求,提出了包括经济、社会、环境广义三要素的可持续发展生产要素的观点.进一步讨论了广义生产三要素的成本投入、价值补偿及其增值问题.同时在理论论述的基础上提出了建立和完善可持续发展生产环境要素投入资金的来源、运用和管理机制.以促使现实可持续发展战略的实现.     

Bayesian Estimation of Prediction Error and Variable Selection in Linear Regression

An important statistical application is the problem of determining an appropriate set of input variables for modelling a response variable. In such an application, candidate models are characterized by which input variables are included in the mean structure. A reasonable approach to gauging the propriety of a candidate model is to define a discrepancy function through the prediction error associated with this model. An optimal set of input variables is then determined by searching for the candidate model that minimizes the prediction error. In this paper, we focus on a Bayesian approach to estimating a discrepancy function based on prediction error in linear regression. It is shown how this approach provides an informative method for quantifying model selection uncertainty.     

我国逆向物流发展问题与对策研究

科学合理的逆向物流策略能够有效降低企业的物流成本,针对我国目前逆向物流存在问题,提出在认识逆向物流的重要性基础上,通过建立有效的逆向物流管理系统,构建循环经济发展的法律体系,加大逆向物流科技投入以及引入第三方逆向物流管理等措施,促进逆向物流健康发展。     

COMPLEMENTARITY IN INPUT–OUTPUT ANALYSIS AND STOCHASTICS

The complementarity between the quantity and value systems of input–output analysis is shown to be the basis of the complementarity problem approach to computable general equilibrium. The numerical superiority of the latter to the linear programming approach facilitates stochastic analysis of input–output scenarios. For the example where Kyoto targets are underachieved to uncertain degrees, confidence intervals are derived for the associated consumption reductions.     

关于220kV线路保护配合的探讨

线路保护是电力系统中不可缺少的装置,对维护变电站电力系统安全有着重要的作用。随着社会电力运行负荷的大幅度增加,对变电站采取综合性的线路保护是电力企业必须要深入研究的问题。线路保护功能的发挥要依赖于各种装置产品的运行,只有按照设计线路的标准要求组合装置且进行模式调试后,才能将线路保护投入到正常的系统使用中。针对这一点,文章以实际案例为研究对象,分析了220 kV线路保护配置的相关问题。     

基于主成分分析-RBF神经网络模型的备件预测研究

备件预测在产品物流保障中占有极其重要的地位,针对现有各种航空备件预测方法精度较低,无法满足实际需求的现状,文章提出了基于主成分分析-RBF神经网络模型的备件预测方法：首先利用主成分分析方法去除原始输入层数据的相关性,以解决RBF神经网络模拟预测备件需求时输入变量过多,网络规模过大导致效率下降的问题．最后选择合适的径向基函数密度训练神经网络。通过结合实例进行分析,取得了较好的效果。     

A polynomial goal programming approach to a class of quality control problems

The traditional quality control approach based on statistical tools has been very useful and effective when output and input qualities can be denned in terms of a single characteristic. However, in process industries such as paper, the output quality is denned in terms of two or more distinct characteristics; hence, reducing the deviation of one output characteristic from its permissible limits could result in forcing other output and/or input characteristics to deviate from their respective limits. Compounding this phenomenon is the fact that most of these industries produce substantial amounts of pollutants whose characteristics are a function of the input and output characteristics. Thus, with increasing costs of waste treatment and stringent pollution standards, there arises a notion of a trade-off between attaining market specified output characteristics and meeting federally regulated pollution standards.In this article a general process quality control problem has been formulated that reflects the above trade-off both in terms of a linear and a polynomial goal programming problem. Major advantages and differences between the two formulations are highlighted and illustrated with a practical example drawn from the paper industry.Three separate cases each with different priorities assigned to the output, pollutant and input characteristics are developed and solved under both formulations. Based on the analysis it is observed that the different solutions that result are contingent on the assumptions concerning the priorities associated with each goal and the manner by which one chooses to incorporate tradeoffs between goals in the objective function. Additionally, it is found that the solutions obtained under polynomial goal programming formulation are more conducive for implementation in practical quality control contexts.     

An Aggregated Regional Economic Input–Output Analysis within a Fuzzy Environment

Abstract

Imprecision within economic input–output frameworks can be a problem, particularly when investigating the characteristics of defined industry sectors. This study undertakes an aggregated regional economic input–output analysis, within a fuzzy environment. The dearth of studies encompassing a fuzzy approach within input–output analysis largely concerns the problematic representation of imprecision. Results pertaining to the fuzzy output multipliers associated with each sector group are described, including possibilistic mean and variance; also identified is a specific ranking of the sector groups. Where appropriate, results are compared with those from a Monte Carlo simulation based stochastic analysis.     

ESTIMATION OF SYMMETRIC INPUT–OUTPUT TABLES: AN EXTENSION TO BOHLIN AND WIDELL

This paper presents two optimisation models for use in the production of symmetric input–output tables (SIOTs) based on data contained within supply-use tables (SUTs). The first model produces commodity-by-commodity SIOTs derived from the selection of appropriate technology assumptions, while the second produces industry-by-industry SIOTs derived through the selection of appropriate sales structure assumptions. Both models address the problem of negative coefficients and also permit the use of rectangular SUTs as base input data. Additionally, this paper explores the development of a ‘comprehensive model’ enabling production of both commodity-by-commodity and industry-by-industry SIOTs that are conceptually and mathematically consistent.     

多源多汇运输系统的多目标规划模型

本文以多目标规划为工具，对多源多汇运输问题进行了探讨，给出了具有普遍意义的建模思想，通过案例分析，证明了这种建模思想与方法的可行性和灵活性     

Price-endogenized Input–Output Model: A General Equilibrium Analysis of the Production Sector of the Japanese Economy

This paper considers a generalization of the open Leontief model, by endogenizing the input coefficients on the basis of the neoclassical multi-sectoral produc-tion function. The adopted production function is of the two-level CES type, which is quite effective for avoiding the multi-collinearity problem. As a result, the estimates obtained are quite stable, satisfying the quasi-concavity conditions of the production function for all the sectors. Comparative statics based on the Jacobian of the excess supply function for each commodity market reveal that, owing to the factor substitution the effect of an increase in the final demand on the level of the production is significantly smaller than that which occurs in the open Leontief model with fixed input coefficients.     

A CYCLING METHOD FOR CONSTRUCTING INPUT–OUTPUT TABLE TIME SERIES FROM INCOMPLETE DATA

There are a number of approaches for constructing time series of input–output tables. Some authors generate an initial estimate for a base year, and then serially estimate tables for subsequent years using the balanced prior-year table as an initial estimate. Others first generate a series of initial estimates for the entire period, and then balance tables in parallel. Current serial methods are affected by sudden leaps in the magnitude of table elements, which occur straight after a period of data unavailability. Current parallel methods require two complete tables for base and final years in the same classification, and therefore do not work under misaligned or incomplete data. We present a new method for constructing input–output table time series that overcomes these problems by averaging over alternate forward and backward sweeps across the time series period. We also solve the problem of hysteresis causing forecast and backcast table estimates to differ.     

Signaalstroomdiagrammen en Markov-ketens

The transient behavior of a simple two-state discrete Markov process can be studied by means of matrix-multiplication and z-transformations.
For linear systems the output is equal to the convolution of the input and the impulse response of the system. By taking z-transforms the convolution can be avoided: the transform of the output is equal to the transform of the input multiplied by the transform of the impulse response of the system.
The signal flow graph method is the transformation of the matrix-method of solving a system of simultaneous equations in a topological method.
The simple two-state discrete Markov process can be represented by such a flow graph and it is shown how to simplify this flow graph step by step. Taking as input the unit-impulse at time zero, the output of this system at time n turns out to be the n-step transition-probability.
The results for the transmission in a network are mentioned (Mason and Zimmermann [8]). With these results it is possible to give at once the n-step transition probability of a system without first simplifying the flow graph.
Building on this result signal flow graphs can be used to determine the chance to be for the first time in a certain state, the average number of times a system is in a certain state and the chance to reach a certain state for the first time before another state of the system has been reached.
Finally the results are extended to continuous Markov processes.