A Hierarchical Forecasting Model for China’s Foreign Trade

Analyzing the underlying characteristics of trade values movements has attracted much attention in the domestic research. However, the proposed understanding of these characteristics is limited by the intrinsic complexity of the imports/exports. Since economic systems are naturally organized by hierarchies, a novel hierarchical model is proposed in this paper to forecast China's foreign trade. First, the foreign trade data are disaggregated from perspectives of trading partners and trading products, forming two independent hierarchical models with total exports and imports as target variables. Second, a bottom-up strategy is applied. All bottom time series are modelled by corresponding control variables according to trading theories. Forecasts for bottom time series are then combined to generate initial forecasts for total exports and imports. Finally, forecasts for total imports and exports from the two hierarchical models, plus a single VECM model are combined to generate final forecasts. Empirical experiments show that this proposed forecasting model approach significantly outperforms benchmark models and produces consistent forecasts for both total imports and exports or detailed items, which helps a lot for analyzing future trading structure evolution and making foreign trade policies.     

Variant population projections for the United Kingdom and its constituent countries

Interest has been growing steadily in understanding the impact of the inherent uncertainty in the national population projections. As a result, the Government Acturay's Department has recently produced the most extensive set of official variant projections ever published in the United Kingdom. These include 'standard' variants based on alternative high and low assumptions for future fertility, life expectancy and net migration and also a number of 'special case scenarios.' All of these variants have been produced at both UK and individual country level. This article describes the full range of variant projections available from the 2000-based national projections and summaries some of the key results for both the UK and the individual countries.     

A Demand Forecasting Method Based on Stochastic Frontier Analysis and Model Average: An Application in Air Travel Demand Forecasting

Demand forecasting is often difficult due to the unobservability of the applicable historical demand series. In this study, the authors propose a demand forecasting method based on stochastic frontier analysis(SFA) models and a model average technique. First, considering model uncertainty,a set of alternative SFA models with various combinations of explanatory variables and distribution assumptions are constructed to estimate demands. Second, an average estimate from the estimated demand values is obtained using a model average technique. Finally, future demand forecasts are achieved, with the average estimates used as historical observations. An empirical application of air travel demand forecasting is implemented. The results of a forecasting performance comparison show that in addition to its ability to estimate demand, the proposed method outperforms other common methods in terms of forecasting passenger traffic.     

Fifty years of United Kingdom national population projections: how accurate have they been?

This article considers the accuracy of the official national population projections made for the UK over the last fifty years The findings take account of the revision to population estimates following the 2001 Census and are largely similar to the findings of a previous review carried out after the 1991 Census. The total population has been projected reasonably accurately but this is largely a chance result of compensating errors in the assumptions of fertility, mortality and net migration. The largest differences between projected and actual populations are for the very young and the very old, while projections of the working age population have been comparatively accurate. Fertility and mortality errors have reduced in more recent projections, while migration errors have grown. However, this may simply reflect the volatility or stability of the respective time-series at the time the projections are made. Changes in estimates of the past and current size of the population (highlighted by the revisions made to population estimates following the 2001 Census) are also shown to play a part in explaining projection error.     

我国通货膨胀与对外经济的半相依自回归模型的研究

对时间序列提出半相依自回归模型的概念 ,并将其应用于我国通货膨胀与对外经济的预测 .预测结果与自回归模型的预测结果进行了比较 .     

Participatory Demographic Scenarios Addressing Uncertainty and Transformative Change in Ethiopia

Projections on future population trends provide important decision support, however are confronted with high uncertainty. In contexts of low data quality, missing and contradicting knowledge on drivers of change, such as in many developing countries, participatory scenarios can support the quality of assumptions needed for quantitative projections. We present a scenario approach designed for contexts of uncertain and missing demographic data and illiteracy, which was successfully tested in three study sites in North-West Ethiopia. The four qualitative scenarios for 2030 supported the inter-subjective definition of assumptions for the calculations, which were again validated by members of the rural communities. We argue that the participation process has resulted in more robust and context-specific projections. The collaborative work on the local drivers of demographic change between science and society provided a valuable space for social learning, so that local stakeholders could identify the need for and scope of local mitigation or adaptation measures to demographic transformation.     

交通需求预测中不确定性的传播分析

交通运输系统是包含许多不确定性因素的复杂大系统，在进行交通需求预测时应充分考虑输入、模型参数等不确定性的影响，以便作出正确决策。本文运用灵敏度分析方法研究社会经济、模型参数的不确定性在四阶段需求预测模型中的传播情况；用弹性系数表示输出对输入、模型参数反应的灵敏程度，并通过一简单网络分析其在短期、长期预测中的变化情况。     

基于贝叶斯网络的编队对地攻击损伤评估研究

随着武器的高科技化、战场环境的复杂化、战斗节奏的加快,战斗损伤评估系统在现代战争中占有越来越重要的地位。针对战场战斗损伤评估信息的多样性、不确定性和模糊性,基于贝叶斯网络易于进行不确定性推理的优点,提出应用贝叶斯网络对对地攻击效果进行分析评价,建立了编队对地攻击损伤评估的贝叶斯网络模型,给出了基于贝叶斯网络的损伤评估的推理决策方法,并且对该方法进行了仿真分析。仿真实例表明,基于贝叶斯网络的损伤评估模型能够提高损伤评估的准确度,而且推理简单,易于实现。     

Artificial Neural Network for Combining Forecasts

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UK national population projections in perspective: how successful compared to those in other European countries?

Compared to population forecasts of other European countries, those made in the United Kingdom during the past 30 years had somewhat larger forecast errors for fertility and smaller errors for mortality. Migration forecasts in the UK were about as accurate as the European average. After controlling for various effects such as relative data volatility both at the time a projection is made and during the period of the projection, there is no indication that recent forecasts in European countries have been more accurate than older ones. Hence population forecasts are intrinsically uncertain, and a forecast for the UK in the form of probability distributions is presented.     

Research on time series mining based on shape concept time warping

Time series is an important kind of complex data, while a growing attention has been paid to mining time series knowledge recently. Typically Euclidean distance measure is used for comparing time series. However, it may be a brittle distance measure because of less robustness. Dynamic time warp is a pattern matching algorithm based on nonlinear dynamic programming technique, however it is computationally expensive and suffered from the local shape variance. A modification algorithm named by shape DTW is presented, which uses linguistic variable concept to describe the slope feather of time series. The concept tree is developed by cloud models theory which integrates randomness and probability of uncertainty, so that it makes conversion between qualitative and quantitive knowledge. Experiments about cluster analysis on the basis of this algorithm, compared with Euclidean measure, are implemented on synthetic control chart time series. The results show that this method has strong robustness to loss of feature data due to piecewise segment preprocessing. Moreover, after the construction of shape concept tree, we can discovery knowledge of time series on different time granularity.     

贝叶斯网络个人信用评估模型

研究了朴素贝叶斯分类器、树增强朴素贝叶斯分类器2种贝叶斯网络信用评估模型的精度,用10层交叉验证在2个真实数据集上对贝叶斯网络信用评分模型进行了测试并与神经网络模型进行了比较.结果表明,贝叶斯网络信用评估模型具有较高的分类精度,在信用评估中具有优势.     

基于数据特征的仿真动态输出验证方法

为了解决考虑不确定性时仿真系统动态输出验证问题,提出一种基于数据特征的仿真系统动态输出验证方法。首先在给出数据特征度量模型集概念的基础上,定义了形状、位置、频谱3方面的差异特征度量模型;然后分别构建仿真系统输出和参考输出的标准序列,建立仿真系统和参考系统动态输出的数据特征矩阵;再者,应用基于核密度估计的改进贝叶斯因子法实现仿真系统动态输出统计特性的一致性度量,从而完成动态输出的验证;最后,通过实例应用对所提方法进行了验证。     

基于FTA仿真的三高气田事故风险概率

高含硫、高压、高产的“三高"气田的钻完井事故概率计算是国内外钻完井事故风险评价中的重点和难点,为全面刻画事故发生机理, 合理计算事故风险概率,针对三高气田钻完井阶段事故风险建立了事故树,结合事故树仿真方法和贝叶斯修正方法提出了三高气田钻完井事故风险概率评估方法,将现有现场统计资料和专家判断相结合,对基本事件失效率及失效概率进行统计推断, 并利用Monte Carlo仿真得到井喷事故及相关事故的失效概率分布. 实证结果表明,该研究方法有效弥补了因样本数据有限和经验判断差异带来的不确定性,可以为三高气田事故风险定量评价提供依据.     

基于模糊概率的多状态贝叶斯网络可靠性分析

利用贝叶斯网络对多状态系统进行可靠性分析时,各根节点不同状态的精确概率难以获得。因此提出了把模糊理论与贝叶斯网络方法相结合,将不同专家给出的根节点各状态发生概率的语言变量转化为三角模糊数,并经过均值化、解模糊和归一化得到不同状态的发生概率的精确值。将其代入多状态贝叶斯网络中,计算叶节点不同状态的发生概率,进而计算各根节点的后验概率及风险增加当量重要度。通过实例分析验证了该方法的可行性。应用该方法能够提高贝叶斯网络处理不确定性问题的能力,使其在解决多状态不确定性系统可靠性和安全性问题时发挥更大的作用。     

基于时变模型平均方法的我国航空客运量预测

机场扩建、政策导向、经济发展等外在因素的变化常常导致航空客运量数据发生结构性改变,其模型的设定也在很大程度上存在不确定性,因此,精准而稳定地预测航空客运量变得十分困难.为了解决以上问题,本文采用了一种时变模型平均方法(TVJMA)(Sun等,2020,2012)对全国Top 5机场的客运量进行了预测研究,该方法在模型平均时基于最小化局部Jackknife准则给出了最优的权重选择,并通过非参数估计,实现了最优权重随时间变化.实证结果表明,本文所采用的TVJMA方法显著优于其它基准模型,包括Hansen和Racine (2012)的Jackknife模型平均(JMA)以及自回归模型(AR),单整自回归移动平均模型(ARIMA),季节性单整自回归移动平均模型(SARIMA)和时变参数模型(TVP)等传统方法.进一步,对不同的预测步长,TVJMA在航空客运量的预测效果同样具有稳健性.因此,TVJMA方法可以有效地降低由于航空客运量的结构性变化和预测模型不确定性等导致的预测风险,进而做出精准而稳定的客运量预测.     

Modelling student age-groups in the subnational population projections for England: an investigation into potential improvements

This article describes research aimed at improving modeling of student age-groups in the ONS subnational population projections for England. A number of data-sources were investigated, and the research focused on Higher Education Statistics Agency data. Although the coverage of HESA data is not sufficient to enable student populations to be projected separately, the data have been used to devise an adjustment method for the student-age population. Both the data and method will be monitored and, if appropriate, used in future projections.     

Endogenous Stackelberg Leadership with Uncertain Information

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基于TVS-MHAR模型金融市场高频多元波动率的预测

本文基于Kalli和Griffin(2011)的时变稀疏模型和多元HAR模型,构建了具有时变稀疏性的多元HAR模型(TVS-MHAR),并利用中国上证综指、沪深300期货和国债期货的五分钟高频数据,对金融市场的已实现波动率矩阵进行预测.本文通过Cholesky转换方法保证预测波动率矩阵的正定性.通过对不同多元波动率模型的预测结果进行数值比较和经济比较,本文发现,本文构建的TVS-MHAR模型无论对于短期预测、中期预测还是长期预测都具有最高的预测精度和最大的投资改善.同时,时变多元波动率模型可以获得比固定参数模型更好的预测效果,高频数据模型比低频数据模型获得更大的投资改善.     

The new subnational population projections model: methodology and projection scenarios

This article describes the most recent process of projecting population at the subnational level in England. It briefly explains the reasons why projecting population at the subnational level is important, describes the model and how it was used to produce the latest set of long-term subnational population projections in England published by the Office for National Statistics (ONS) in 1998. The article then discusses how the model may be applied to answer various 'what-if' questions about future population.