The use of dummy variables to compute predictions,prediction errors,and confidence intervals

This paper presents a method for computing predictions, prediction error variances, and confidence intervals, which can be implemented with any regression program. It demonstrates that a regression estimated for an augmented data set, obtained by (1) combining n sample points with r forecast points, and (2) including r dummy variables (each equalling one only for the corresponding forecast point), will yield r dummy variable coefficients and variances which equal the corresponding prediction errors and prediction error variances. Since most programs lack special routines to calculate these magnitudes, while manual computation is cumbersome, the proposed method is of considerable practical value.     

The use of proxy variables in housing price analysis

This paper presents a reexamination of data used by Berry to study housing prices in Chicago. The detailed data on 275 single-family houses are used to test the proposition that the tax assessment on improvements is a good proxy for the attributes of the houses. It is shown that the test used by Berry is irrelevant for the question of omitted variables bias, and the correct test is presented. It is concluded that the proxy corrects for a bias in the coefficient of percent black population, but increases the negative bias in the coefficient of percent Latino population.     

Employment predictions in social impact assessment: An analysis of some unexplored variables

Social scientists investigating the impacts of energy development are increasingly searching for predictive models of the employment benefits to locals. This issue is of extreme importance not only because of the benefits to locals but because of the issue of local benefits as well as the connection with population growth and boom town development. Unfortunately, some of the recent investigations and predictive models are of little utility as a result of certain analytical and methodological faults, including improper assumptions about local labor supply and local preferences. In addition to the assessment of previous investigations, a framework for predicting local employment impacts is suggested. This framework utilizes characteristics and preferences of the local population.     

Estimating predictions,prediction errors and their standard deviations using constructed variables

Increasing use has been made of predictive tests for assessing model adequacy, but it is sometimes difficult to generate predictions and their standard errors in dynamic or simultaneous equation models. Following earlier suggestions by Salkever and Fuller, this paper shows how the requisite information may be obtained by the use of specially constructed variables in a regression framework. The main use of the method will be in those situations where prediction information is not available as a standard option in econometric packages.     

Performance indicator evaluation for a cloud computing system from QoS viewpoint

With the development of information technology, the cloud computing system (CCS) has become a new paradigm for the business and clients. The system supervisor has to guarantee the CCS keeps a good quality of service (QoS) to satisfy the clients’ requirements. The maintenance action is thus necessary when the CCS falls to a specific state such that it cannot afford enough capacity to meet demand d. In order to measure the service level of a CCS, this paper constructs a network model and proposes a key performance indicator (KPI), where the KPI is utilized to evaluate the probability that the demand can be satisfied under both transmission time and maintenance budget constraints. A method to derive the interval estimation for the KPI is developed. The system supervisor can conduct the sensitive analysis to improve/investigate the most important part in a large CCS afterwards.     

Establishing the use of cloud computing in supply chain management

Despite having various benefits associated with greater information flow in the supply chain, empirical cloud computing research is scarce in the supply chain management domain. This paper explores the managerial perceptions on the use of cloud computing in supply chain management. Specifically, this paper seeks to address: how cloud computing impacts information sharing among supply chain partners, the impact of trust in cloud information sharing and the impact of cloud computing on supply chain performance. Using a multi-method research design we present a combined semi-structured interviews of four different companies in the United States and a survey to analyze and empirically assess our results. Structural equation modeling was used to analyze the results of this study. Our analysis provides empirical support based on managerial perceptions regarding cloud computing, information sharing and supply chain performance. The data provide evidence on the impact of cloud computing in enhancing information sharing. This information sharing through cloud computing appears to positively impact supply chain performance. This paper also provides support on the important role of inter-organizational trust in facilitating the use of cloud computing for information sharing purposes.     

The use of R2 to determine the appropriate transformation of regression variables

It is proved that, under certain conditions, the ‘true’ model, from a set of alternative regression specifications involving different transformations of the same dependent variable, is the formulation for which population R² is highest. This theorem, which requires assumptions of normality, is proved through the use of Hermite polynomials. The paper contains an appendix listing the major properties of these polynomials.     

文本中的会计变量及属性分析

会计文本是会计变量的集成,研究文本中的会计变量特性及其属性有助于对会计变量的设置及属性的说明。探讨会计变量及其属性,以说明不同会计变量及其属性特征描述的合理性,反映不同变量的信息含量。     

The moments of products of quadratic forms in normal variables*

Abstract The expectation of the product of an arbitrary number of quadratic forms in normally distributed variables is derived.     

The psychological and social variables determining education

The object of the paper is to logically integrate in a single frame of reference the studies of the psychological and sociological determinants of achievement and acculturation of the students.

The education or socialization process is defined as the process of social interaction that has as its object the teaching-learning of culture.

The two main instruments used for the analysis of education are a model of social interaction, and, since the characteristics of any social interaction depend upon the way in which the actors in it peform their roles, a model of the performance of any activity.

The model of social interaction, applied to classroom interactions, gives the basis determining the main elements of the roles of teachers and students. The influence that the performance of these roles has on the indoctrination and achievement of the students is studied with the model of the performance of any activity. Finally it is assumed that the levels of achievement and indoctrination attained by the students determines whether or not they remain in the educational system.     

The impact of the number of sellers on quantal response equilibrium predictions in Bertrand oligopolies

This paper studies how increasing the number of sellers in a Bertrand oligopoly with homogenous goods affects the equilibrium price level predicted by logistic quantal response equilibrium (LQRE) and power‐function QRE (PQRE). We show that increasing the number of sellers reduces the average posted price in a PQRE, but can increase the average posted price in an LQRE. Our results indicate that the comparative‐static predictions of QRE (McKelvey & Palfrey, 1995, Games Econ Behav, 10, 6–38) are not necessarily robust to changes of the quantal response function.     

The usefulness of oil price forecasts—Evidence from survey predictions

This paper evaluates survey forecasts for crude oil prices and discusses the implications for decision makers. A novel disaggregated data set incorporating individual forecasts for Brent and Western Texas Intermediate is used. We carry out tests for unbiasedness, sign accuracy, and forecast encompassing, followed by the computation of coefficients for topically oriented trend adjustments and the Theil's U measure. We also control for the forecast horizon finding heterogeneous results. Forecasts are more precise for shorter horizons, but less accurate than the naïve prediction. For longer horizons, topically oriented trend adjustments become more pronounced, but forecasters tend to outperform the naïve predictions.     

The influence of variables of attitude on collective entrepreneurship

In the current global corporate climate that surrounds us, firms would do well to encourage the talent and creativity of their employees in order to achieve success. This is achieved, not by giving priority to individual talent, but by optimizing the collective as a whole and the firm’s activity based on team work and joint effort. Heads of organizations might benefit from creating a favorable context for the birth and growth of collective internal cooperation, which is understood to be the collective ability to create and innovate on the part of the team, the firm or the organization. Having contrasted our hypotheses through research on Spanish firms, we have concluded that job satisfaction and commitment to the team are factors that have a direct and positive effect on collective entrepreneurship.     

Latent variables in econometrics

Unobservable variables in econometrics are represented in one of three ways: by variables contaminated by measurement errors, by proxy variables, or by various manifest indicators and/or causes. This paper contains a discussion of models involving each of these representations, and highlights certain interesting implications that have been insufficiently emphasized or completely unrecognized in the literature.     

依托云计算的移动电子商务模式浅析

云计算是一种依托互联网以虚拟化方式共享资源的计算模式;移动商务是依靠手机、平板电脑等可移动的信息终端实现一系列商品交易活动的新电商模式,云计算的引入解决了移动商务的安全漏洞、成本高昂等瓶颈.本文以“电子外包”思想建立基于“移动云”、“供应链云”的移动商务模式.在此技术背景下,总结了基于云计算的基础设施、平台和软件三项服务方案,详细阐述了移动云存储、信息推荐、轻客户端三项主要应用模式.     

The spatial price equilibrium problem with path variables

Most of the recent literature dealing with the solution of the spatial price equilibrium model has dealt with the arc variable formulation; that is, the situation where the flows on the paths connecting an origin-destination pair in a network with trans-shipment nodes are not explicitly considered. This paper presents a clarification of the main assumption underlying this arc formulation and presents an argument for the need for using a model with path variables in certain applications. After this discussion, a new solution algorithm for the model with path variables is stated and compared against the linear approximation algorithm first proposed by Florian and Los [1] for this problem. Numerical examples are presented which illustrate the features of this new algorithm.     

Using weather ensemble predictions in electricity demand forecasting

Weather forecasts are an important input to many electricity demand forecasting models. This study investigates the use of weather ensemble predictions in electricity demand forecasting for lead times from 1 to 10 days ahead. A weather ensemble prediction consists of 51 scenarios for a weather variable. We use these scenarios to produce 51 scenarios for the weather-related component of electricity demand. The results show that the average of the demand scenarios is a more accurate demand forecast than that produced using traditional weather forecasts. We use the distribution of the demand scenarios to estimate the demand forecast uncertainty. This compares favourably with estimates produced using univariate volatility forecasting methods.     

The expectation of products of quadratic forms in normal variables: the practice

Summary  A table is presented to simplify the computation of the expectation of a product of quadratic forms in normal variables. Some peculiarities of the table are discussed.     

Modeling the accuracy of certain regional predictions

A model is hypothesized specifying forecast error as a function of specific ‘year effects’, particular dates of forecast, and ‘time span effects’, length of projection horizon. Model estimation methodology is presented and empirical application is made to inaccuracies arising in the RAS procedure for projecting bivariate region/industry employment arrays for two sets of regional data. In both applications, the model is found to explain a large proportion of variation in forecast errors, and estimation results permit isolation of pure time effects on deterioration of model accuracy and quantification of relative ‘year effects’.