高龄人口死亡率预测模型的比较与选择

高龄人口死亡率预测模型是人口预测、养老金成本和债务评估以及长寿风险度量与管理的基础。我国大陆地区高龄人口死亡数据量少、数据波动性大,如何选择适合我国高龄数据特点的死亡率预测模型,是重要的研究课题。本文在归纳总结死亡率预测模型研究进展的基础上,先采用数据较为充分的台湾地区高龄死亡数据,选用Lee-Carter、CBD、贝叶斯分层模型等八种死亡率模型,对模型的拟合效果、预测效果和稳健性做出比较。在此基础上,基于修正和平滑后的我国大陆人口死亡数据,采用CBD模型和贝叶斯分层模型建模和预测。结果显示:贝叶斯分层模型能捕捉我国大陆高龄死亡率数据的历史波动,预测区间能够涵盖全部死亡率的真实值,但预测区间过宽,生存曲线不收敛;相比之下,CBD模型对我国大陆地区高龄死亡率的拟合和预测较好,预测区间和生存曲线合理。在长寿风险度量中,建议采用CBD模型。     

A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations

We study the evolution of U.S. inflation by means of a new noncausal autoregressive model with time‐varying parameters that outperforms the corresponding causal and constant‐parameter noncausal models in terms of fit and forecast accuracy. Our model also beats the unobserved component stochastic volatility (UCSV) model, one of the best‐performing univariate inflation forecasting models, in terms of both point and density forecasts. We also show how the new Keynesian Phillips curve can be estimated based on our noncausal model. Both expected and lagged inflation turn out important, but the former dominates in determining the current inflation.     

A New Approach to Markov-Switching GARCH Models

The use of Markov-switching models to capture the volatilitydynamics of financial time series has grown considerably duringpast years, in part because they give rise to a plausible interpretationof nonlinearities. Nevertheless, GARCH-type models remain ubiquitousin order to allow for nonlinearities associated with time-varyingvolatility. Existing methods of combining the two approachesare unsatisfactory, as they either suffer from severe estimationdifficulties or else their dynamic properties are not well understood.In this article we present a new Markov-switching GARCH modelthat overcomes both of these problems. Dynamic properties arederived and their implications for the volatility process discussed.We argue that the disaggregation of the variance process offeredby the new model is more plausible than in the existing variants.The approach is illustrated with several exchange rate returnseries. The results suggest that a promising volatility modelis an independent switching GARCH process with a possibly skewedconditional mixture density.     

Forecasting and controlling of energy refining process based on multi-factor data barycentre method

A new and useful parameter estimation method is presented, and it is the application to the forecasting and controlling of coal refining process. This method can mostly decrease the errors of the fitting and forecasting results; Moreover, the strict hypotheses in least square method are not necessary in the method, which overcome the shortcoming of least square method and expand the application of multi-factor data barycentre method. Process forecasting and controlling models of coal refining are presented in this paper. From the comparison of multi-factor data barycentre forecasting method with least square method using in fitting and forecasting results of the mathematical model of coal refining process, we can conclude that the multi-factor data barycentre forecasting method is better than traditional least square regression forecasting method.     

The Term Structure as a Predictor of Real Activity and Inflation in the Euro Area: A Reassessment

We study the informational content of the term structure of interest rates on future developments in inflation and real activity for the euro area, explicitly taking into account the possibility of a time-varying risk premium. We put forward a simple adjustment procedure for the term premium based on the rational expectations hypothesis of the term structure and provide evidence that the predictive content of term spreads for future developments in industrial production improves significantly if the adjusted term spread is used. The adjustment also achieves some (less systematic) improvements in the forecasting abilities of the term spread for headline inflation and core inflation. JEL no. E43, E44, E47     

现代物流中的销售预测模型研究

针对销售物流对销售预测的要求，尝试采用改进了的适应指数平滑法，建立短期销售预测模型，并对模型进行验证，同时采用客户调查法和销售物流人员综合意见法，进行同样目的的预测，将各种预测方法得出的结果进行融合，得到最终预测结果。     

Spanish diffusion indexes

We use the Stock-Watson diffusion index methodology to summarize the information contained in a wide set of monthly series (published in the Statistical Bulletin of the Bank of Spain) by means of a reduced number of factors. We find that the first two factors may be used as indicators of the core inflation and the business cycle dynamics of the Spanish economy, respectively. In addition, we study the effects of incorporating large information sets for the analysis of monetary policy. Finally, we show that forecasting prices and output with our factors outperforms other standard alternative forecasting procedures.JEL Classification: E31, E32, E37We are most grateful to Pilar Bengoechea, Ramón María-Dolores, and Javier Vallés for valuable comments. We would like to thank Gabriel Pérez-Quirós and two anonymous referees for constructive suggestions leading to improvements in the content and presentation of the paper. We however stand responsible for any remaining errors and omissions.     

Application of grey model GM(1, 1) to vehicle fatality risk estimation

A mathematical model known as grey model GM(1, 1) has been herewith employed successfully in the estimation of vehicle fatality risk. Its application to the UK and US data sets yields exact predictions that are of high repeatability with characteristics depicting high reliability and efficiency. Another advantage is that these results are obtained without using any assumptions. In the analysis, the model normally deals directly with original data and searches the intrinsic regularity of data. The forecasting accuracy is related to the sample number n in grey model, and the accuracies for smoothed fatality risk predictions are higher than those for short-term predictions. The total time-dependent trends for these cases show very small variability between the real and prediction values, hence showing the theory to be working. For rollover cases, US data sets show that the risk of occupants to experience fatal injuries is decreasing and the fluctuating amplitude is declining. The theory predicted this trend and showed the time-dependent curves for data set and prediction to be in-phase. Another interesting observation that has come from the study is that UK and US experience similar phases in the time-dependent trend of motor vehicle fatality risk despite the different perception of safety between the USA and UK, especially when it comes to occupant usages of restraint systems.     

Forecasting earthquakes and earthquake risk

This paper reviews issues, models, and methodologies arising out of the problems of predicting earthquakes and forecasting earthquake risk. The emphasis is on statistical methods which attempt to quantify the probability of an earthquake occurring within specified time, space, and magnitude windows. One recurring theme is that such probabilities are best developed from models which specify a time-varying conditional intensity (conditional probability per unit time, area or volume, and magnitude interval) for every point in the region under study. The paper comprises three introductory sections, and three substantive sections. The former outline the current state of earthquake prediction, earthquakes and their parameters, and the point process background. The latter cover the estimation of background risk, the estimation of time-varying risk, and some specific examples of models and prediction algorithms. The paper concludes with some brief comments on the links between forecasting earthquakes and other forecasting problems.     

Decision support oriented sales forecasting methods

Forecast accuracy is not always a good criterion by which to evaluate alternative sales forecasting methods. Accurate forecasts do not always lead to desirable management policies. The paper gives two examples of this in practice, one in which short term sales forecasts are used for operational planning purposes, and the other in which long term sales forecasts are used for strategic company planning. In each case the most accurate forecasts do not give the best plans and alternative criteria to accuracy are proposed and shown to perform better. Conclusions are drawn regarding evaluation criteria for alternative sales forecasting methods within a planning context and also regarding the position of the forecasting function within an organisation.