A model of multiple-unit ownership as a diffusion process

This paper develops and tests a new model for multiple-unit adoptions of durable goods based on the diffusion modeling tradition. Multiple-unit adoptions are a major component of sales for many consumer durable product categories. For instance, sales of multiple-unit adoptions for televisions have been higher than both first adoptions and replacement purchases since 1977, while for automobiles, they have represented more than 20% of sales since 1966 in Australia. The structural drivers of multiple-unit adoptions are quite different from either first purchase or replacement purchase. Hence, identifying and modeling the multiple-unit component of sales is important for aggregate sales forecasts. Moreover, consumer requirements for additional units of a product are likely to be considerably different than for the other components of sales (first purchases and replacement purchases). As such, the ratio of the first, multiple, and replacement sales components will strongly influence the product mix requirements of the market.

While forecasting and influencing multiple-unit sales are an important managerial issue, very little attention has been given to multiple-unit ownership in the diffusion modeling literature. The only model available was developed for the purpose of modeling relatively short-term behavior of multiple-unit adoptions, rather than the longer-term pattern of sales. We propose a model of multiple-unit adoptions as a diffusion process.

We apply the model to both color television and automobiles. Analysis of the model's long-term fit and forecasts in these applications provide support for the structure of the new model.     

Asymptotic confidence bands for the estimated autocovariance and autocorrelation functions of vector autoregressive models

This paper provides closed-form formulae for computing the asymptotic covariance matrices of the estimated autocovariance and autocorrelation functions of stable VAR models by means of the delta method. These covariance matrices can be used to construct asymptotic confidence bands for the estimated autocovariance and autocorrelation functions to assess the underlying estimation uncertainty. The usefulness of the formulae for empirical work is illustrated by an application to inflation and output gap data for the U.S. economy indicating the existence of a significant short-run Phillips-curve tradeoff.First version received: November 2002/Final version received: September 2003     

Forecasting UK house prices: A time varying coefficient approach

Previous studies of UK house prices, developed from the demand and supply ofhousing or from the asset market approach have been poor in terms of robustness and ex-post forecasting ability. The UK housing market has suffered a number of structural changes, particularly since the early 1980s with substantial house price increases, financial market deregulation and the removal of mortgage market constraints through competition. Consequently, models which assume that the underlying data-generating process is stable and apply constant parameter techniques tend to suffer in terms of parameter instability. This article uses the Time Varying Coefficient (TVC) methodology where the underlying data-generating process in the UK housing market is treated as unstable. The estimation results of the TVC regression of UK house prices is compared with those obtained from three alternative constant parameter regressions. Comparisons of forecasting performance suggest the TVC regression out-performs forecasts from an Error Correction Mechanism (ECM), Vector Autoregressive (VAR) and an Autoregressive Time Series regression.     

Geometrical Interpretation of the Mean and the Constant in a Box-Jenkins Time Series Model

Certain manuals and computer programs mistakenly identify the mean with the constant in Box-Jenkins time series models. In this paper, it will be shown that (a) the mean and the constant have different values in autoregressive models, and (b) they have an algebraic and graphical relationship.     

贵州乡村生态旅游发展构想

本文论述了贵州乡村生态旅游开发的依据和必要性,分析了贵州乡村生态旅游开发的有利条件和存在的问题,阐述了贵州乡村生态旅游开发应遵循的原则。从旅游资源性质、游客感知方式及运作管理等不同侧面探讨了贵州乡村生态旅游开发的模式,提出了促进贵州乡村生态旅游持续健康发展的措施。     

环境艺术设计“课题制“教学模式实验

本文结合教学实践,就环境艺术设计教学中实施"课题制"教学模式进行了探索,着重对"课题制"教学模式的基本认识和运用进行了论述。     

基于组合权的灰色关联分析在供电企业营销效果综合评价中的应用

在供电企业电力营销效果综合评价中,客观赋权法体现了指标的信息量,而主观赋权法体现了指标的价值量,综合评价应当体现二者的统一.针对电力营销效果评价,提出了基于组合权的灰色关联分析方法.对传统的灰色关联法进行改进,将该方法用于供电企业电力营销效果评价,得到了较好的结果.     

Explaining Real Commercial Rents Using an Error Correction Model with Panel Data

This paper presents rent models for retail and office property in the United Kingdom. Panel data are used covering eleven regions for 29 years, enabling us to overcome the limitations of a relatively short time series. We use an error correction model (ECM) framework to estimate long-run equilibrium relationships and short-term dynamic corrections. The combination of panel data and an ECM is an innovative approach that is still being developed in economics. We construct new supply series that combine infrequent stock data with more frequent construction data. Separate regional models are estimated for retail and office properties. The regions are then combined into a number of panels on the basis of the income and price elasticities in the long-run and short-run models. Unlike previous studies, we find no evidence of a board north–south divide between low growth and high growth regions. Like these studies we do find a London effect: in London, demand elasticities for space with respect to both price (rent) and income are much lower in magnitude. We conclude that, while the economic drivers may vary, there is no evidence of differences in the operation of the regional property markets outside London. Elasticities for retail and office are similar. Our final models are parsimonious with single measures of economic activity and of supply and always support the use of an ECM.