Missing data and forecasting in multivariate time series: An application of the common components dynamic linear model

Summary The paper deals with missing data and forecasting problems in multivariate time series making use of the Common Components Dynamic Linear Model (DLMCC), presented in Quintana (1985), and West and Harrison (1989). Some results are presented and discussed: exploiting the correlation between series, estimated by the DLMCC, the paper shows as it is possible to update state vector posterior distributions for the unobserved series. This is realized on the base of the updating of the observed series state vectors, for which the usual Kalman filter equations can be applied. An application concerning some Italian private consumption series provides an example of the model capabilities.     

中国各地区市场化进程区位分布的空间效应研究

 本文从空间分析的角度研究各地区市场化进程的空间效应及其对区域经济增长绩效的影响,空间计量经济分析的结果表明市场化进程的空间分布在整个样本区间与GDP、资本和劳动一样呈现出集聚的趋势,区域差异显著,各地区的市场化进程在地理空间上存在显著的自相关关系,证实了各地区市场化进程存在制度溢出效应。因此,在研究各地区市场化进程与经济增长关系时必须考虑其空间效应的影响,基于此结论本文运用空间计量模型测算了各地区市场化进程对经济增长的贡献。结果证实,考虑了空间效应后,市场化进程在1998～2001年阶段对经济增长的贡献约为6.2％,在2002～2005年阶段约为10.8％,这表明了市场化对中国的经济增长起到了重要的作用,而且近年来的贡献愈加显著。     

The coefficient of determination and its adjusted version in linear regression models

This article presents a comparative study of the efficiency properties of the coefficient of determination and its adjusted version in linear regression models when disturbances are not necessarily normal.     

Some subjective bayesian considerations in the selection of models

Some considerations relating to the post-data selection of models are discussed. These include some difficulties with orthodox theory, implementation of the likelihood principle, and Bayesian tests of hypotheses.     

A monte carlo comparison of tests based on the durbin-watson statistic with other autocorrelation tests in dynamic models

This paper examines the sampling properties of a number of serial correlation tests in dynamic linear models which include one or two lags of the dependent variable. Among the tests considered are the Durbin-Watson (DW) bounds test, modified versions of the DW proposed recently by King and Wu and Inder, Durbin's m test, Inder's point optimal test and a Hausman type test. Sampling designs include models with one or two lags of the dependent variable. The m, Hausman, and Inder's tests have the best performance, while Inder's modified DW test appears to be better than the other DW based tests. Results also suggest that tests are less powerful and more sensitive to design parameters in models with higher dynamics, with the DW-based tests being the most sensitive.     

Amemiya's generalized least squares and tests of overidentification in simultaneous equation models with qualitative or limited dependent variables

Amemiya's generalized least squares method for the estimation of simultaneous equation modeis with qualitative or limited dependent variables is known to be efficient relative to many popular two stage estimators. This note points out that test statistics for overidentification restrictions can be obtained as by-products of Amerniya's generalized least squares procedure. Amemiya's procedure is shown to be a minimum chisquare method. The Amemiya procedure is valuable both for efficient estimation and for model evaluation of such models.     

TAPAS: A modular framework to support reuse in scheduling software development

Industrial schedulers try to take into account more and more complex aspects of manufacturing and become, as a consequence, more difficult to use efficiently. We suggest a modular framework for scheduling in order to support the development of schedulers better adapted to the workshop they are used in. An extensive reuse of past developments is made possible by the definition of a powerful, yet generic, data model, together with a fully modular architecture and the use of standards, e.g. CORBA, MMS and STEP. Examples of the first schedulers developed within this framework in an industrial context are shown.     

Product Positioning and Pricing Under Production Cost Considerations*

A framework in a competitive environment is proposed that incorporates production cost and economies of scale in the problem of positioning a product for a market segment. The model facilitates the existence of a Nash equilibrium in prices and product positions. As such, firms can simultaneously choose prices and product positions for the segment. This result improves the traditional theory on equilibria points in prices and product positions where firms choose their product positions first and then set their prices. A sensitivity analysis demonstrates the effects of changes in the unit savings derived from economies of scale or the cost of furnishing a product with its attributes by one firm on the product positions, prices, and profits of all competing firms. More important, the paper examines the effect on prices and profits of competing firms when one of the firms repositions its product closer to the segment's ideal point. It is shown that under certain conditions, the profit of a firm may actually decrease as it redesigns its product closer to the segment's ideal point. These conditions assist management to identify the product design beyond which enhancements of the product would lead to lower profits because of increasing production costs. It is also shown that the price of this firm increases. Past research supports the idea that positioning a brand closer to the ideal point, given fixed product positions of competing firms, would lead to greater buyer preferences and eventually higher profits. The price and profits of the competing firm may increase or decrease. Conditions are derived under which a movement towards the segment's ideal point by one firm would lead to higher profits by the competing firm.     

AN EMPIRICAL ANALYSIS OF THE TAX COURT'S DETERMINATION OF REASONABLE COMPENSATION

The determination of reasonable compensation is one of the most frequently contested issues between the taxpayer and the IRS. The major purpose of this study is to develop a multiple regression model to predict accurately the amount of compensation allowed by the Tax Court as a percent of the amount in dispute between the taxpayer and the IRS. In general, the taxpayer receives favorable treatment in Tax Court when contesting unreasonable compensation payments. The multiple regression model, developed using a stepwise procedure, is a good predictor of the compensation allowed by the court. The overall results have important implications for developing taxpayers' appeal strategies.     

Supplier‐Switching Inertia and Competitive Asymmetry: A Demand‐Side Perspective*

Building on strategic management, operations strategy, and supplier management literatures, this article presents a framework for supplier selection from the demand‐side perspective. We highlight the role of a purchasing firm's switching inertia in the supplier‐selection process and demonstrate the usefulness of our framework for the industrial automation industry. Empirical data for this study was collected from 171 corporate and plant‐level executives in pharmaceutical, chemical, and paper‐and‐pulp manufacturing industries in the United States. A series of Web‐based individually customized discrete choice experiments asked the respondents to either switch to the new supplier or stay with the existing supplier. Based on the results of these experiments, we demonstrate the existence of switching inertia in the supplier‐selection process and discuss the managerial implications for incumbent and challenger supplier firms.