Bayesian inference in time series models using kernel quasi likelihoods

The paper takes up Bayesian inference in time series models when essentially nothing is known about the distribution of the dependent variable given past realizations or other covariates. It proposes the use of kernel quasi likelihoods upon which formal inference can be based. Gibbs sampling with data augmentation is used to perform the computations related to numerical Bayesian analysis of the model. The method is illustrated with artificial and real data sets.     

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.     

Estimation of the change point of a distribution based on the number of failed test items

This paper discusses the family of life distributions with failure rate functions which decrease initially until a change point and remain constant thereafter. The paper focuses on the estimation for the change point of the failure rate function. While point estimation of the change point of the failure rate function has been discussed by some authors, one can hardly find any existing work on the interval estimation of the change point. In this paper, a method for constructing approximate confidence intervals for the change point is proposed. The proposed approximate confidence intervals are based on the number of failed test items at or before a fixed inspection time. Received: September 1999     

Sectoral Shocks and Metropolitan Employment Growth

In this paper, we study the sources of industry employment growth in each of five metropolitan statistical areas (MSAs). The objective is to understand the relative importance of aggregate disturbances versus local sectoral shocks in generating observed employment fluctuations at the MSA level. The empirical evidence presented in this paper derives from structural vector autoregressions (SVARs), estimated for each of the five MSAs. Estimations use monthly employment data covering nine one-digit industrial categories for the period 1951:1–1999:8, as well as two variables that capture the influences of aggregate (i.e., national) shocks on MSAs. We find that within-MSA industry shocks explain considerably more of the forecast error variance in industry employment growth than do aggregate shocks. Sectoral shocks account for between 87 and 94% of the 36-month-ahead forecast error variance. Among individual local sectors, shocks to MSA-specific government, manufacturing, and service sector employment growth are the predominate sources of variability.     

Minimising emergency response time of ambulances through pre-positioning in Dhaka city,Bangladesh

This study conducted a large-scale survey in Dhaka, Bangladesh; the survey involved 95 major hospitals, more than 3000 emergency room patients, and 2 of the largest ambulance operators. Currently, most ambulances are parked within the vicinity of hospitals and are either dispatched or fetched by the acquaintances of the patient on demand, resulting in lengthy round trips. Reducing the response time of ambulances would certainly improve the emergency service, and pre-positioning of the ambulances could be a solution to reducing the response time. This study used two approaches to address the problem. First, the location-allocation problem was solved to find the optimal number of ambulance locations by maximising the demand coverage. Second, separate location-allocation for the peak and off-peaks, using K-means clustering, was applied to systematically optimise the ambulance positioning in small clusters near demand points. These approaches could substantially improve the existing emergency response time. Distributing ambulances near demand points yielded greater improvements in response time than when the ambulances are stationed near hospitals.     

基于双层规划模型的冷链物流网络多目标优化

针对冷链物流时效性强这一特性,应用软时间窗反映客户满意度,并结合T.T.T理论换算货损成本。在考虑满足客户时间窗的条件下,寻找配送中心建设及操作成本、车辆成本、惩罚成本及货损成本所构成的总成本最小时的最优配送方案,建立冷链物流配送选址及路径优化的双层规划模型,并将改进的遗传算法运用到该模型中,借助Matlab软件对具体实例进行求解,得到最优结果,为冷链物流网络多目标优化问题提供理论依据。     

基于响应时间的供应链协调策略研究

在市场需求价格和响应时间敏感下,本文以一个供应商和一个制造商构成的两级MTO供应链为背景,通过建立供应链收益函数模型,分析响应时间对供应链企业决策的影响。给出了供应商和制造商在分散决策下的最优响应策略,得出了供应链双方在分散决策下无法实现供应链完美协调的结论。而后,对供应链协调问题进行了探讨,发现两部收费制契约在满足一定条件下能够实现供应链完美协调,并通过数值实例对上面的结论进行了释义和说明。     

Incentives and Performance in Real Estate Brokerage

This article has two objectives. One is to offer a theoretical model to study how the difference in commission structures affects the performance of agents at full-commission firms (e.g., RE/MAX agents) relative to other agents. The other is to provide an empirical test of the relative performance of full-commission agents. We predict that in equilibrium the selling price and the expected time it takes to sell a listing through a full-commission agent are the same as they are with a traditional agent. Our theoretical predictions are supported by our empirical results.     

基于时间序列的BP神经网络预测鄂尔多斯市的GDP

国内生产总值(GDP)是制定经济发展战略、规划、年度计划以及各种宏观经济政策的重要依据,研究GDP预测方法具有重要的现实意义。在对鄂尔多斯市GDP数据序列分析的基础上,考虑到BP神经网络可以通过简单非线性函数的复合能够实现对于复杂函数的映射,本文采用BP神经网络方法来预测鄂尔多斯市的GDP,取得了较好的预测效果。     

Timing and Commitment of Environmental Policy,Adoption of New Technology,and Repercussions on R&;D

We investigate the interplay between environmental policy, incentives to adoptnew technology, and repercussions on R&D. We study a model where a monopolistic upstream firm engages in R&D and sells advanced abatement technology to polluting downstream firms. We consider four different timing and commitment regimes of environmental tax and permit policies: ex post taxation (or issuing permits), interim commitment to a tax rate (a quota of permits) after observing R&D success but before adoption, and finally two types of ex antecommitment before R&D activity, one with a unique tax rate (quota of permits), the other one with a menu of tax rates (permit quotas). We study the second best tax and permit policies and rank these with respect to welfare. In particular, we find that commitment to a menu of tax rate dominates all other policy regimes.