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。     

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.     

Aging and Retirement: Evidence Across Countries

How do demographic factors influence retirement? Using a large cross-country data set, I show that in countries with a larger share of elderly in their population the length of retirement is longer. This result holds true if I control for wealth effects, and when the effective labor force participation rate of the elderly is used instead of the official retirement age. Retirement policies and the social security size are strictly related: a new variable, representing the aggregate relevance of retirement policies, turns out to be significant in explaining the size of social security. Finally, the total amount of social security transfers is positively related with the increase of the elderly population, while in per capita terms this relation is not significant.     

完善公路监理体制确保公路工程质量

分析我国公路工程监理的现状，进一步阐述完善监理制度的必要性，并对监理工作的几个主要的关系进行了分析，巳达到确保工程质量的目的。     

A Semiparametric Method for Valuing Residential Locations: Application to Automated Valuation

This paper is motivated by automated valuation systems, which would benefit from an ability to estimate spatial variation in location value. It develops theory for the local regression model (LRM), a semiparametric approach to estimating a location value surface. There are two parts to the LRM: (1) an ordinary least square (OLS) model to hold constant for interior square footage, land area, bathrooms, and other structural characteristics; and (2) a non-parametric smoother (local polynomial regression, LPR) which calculates location value as a function of latitude and longitude. Several methods are used to consistently estimate both parts of the model. The LRM was fit to geocoded hedonic sales data for six towns in the suburbs of Boston, MA. The estimates yield substantial, significant and plausible spatial patterns in location values. Using the LRM as an exploratory tool, local peaks and valleys in location value identified by the model are close to points identified by the tax assessor, and they are shown to add to the explanatory power of an OLS model. Out-of-sample MSE shows that the LRM with a first-degree polynomial (local linear smoothing) is somewhat better than polynomials of degree zero or degree two. Future applications might use degree zero (the well-known NW estimator) because this is available in popular commercial software. The optimized LRM reduces MSE from the OLS model by between 5 percent and 11 percent while adding information on statistically significant variations in location value.