经济预测中原始数据处理方法探讨

经济预测是指在一定经济理论的指导下,以经济发展过程中收集到的统计资料和信息为依据,通过定性分析和定量计算对未来经济系统的发展做出的推测。本文对如何对原始数据进行适当的处理以提高预测精度进行了探讨。     

经济预测中原始数据处理方法探讨

经济预测是指在一定经济理论的指导下,以经济发展过程中收集到的统计资料和信息为依据,通过定性分析和定量计算对未来经济系统的发展做出的推测.本文对如何对原始数据进行适当的处理以提高预测精度进行了探讨.     

黑龙江省经济适用住房价格预测

经济适用住房越来越成为广大人民群众关注的焦点。通过采用灰色系统理论中的灰色预测方法并建立灰色预测供给模型．对影响黑龙江省经济适用住房供给的因素进行定量化分析,进行价格预测。其结论是：黑龙江省降低经济适用房的价格势在必行;灰色预测模型具有较好的预测精度．预测结果可信;这种方法在房地产业具有较好的应用前景。     

利润最大化与财务管理目标

微观经济学对经济现象进行解释和预测,会计学对经济行为的结果进行总结并为经济行为提供参考资料,经济学理论为会计理论的发展提供了基础性的工具和指导。本文通过兑财务管理目标的分析,找出企业价值最大化财务管理目标的合理性及其与利润最大化假设的关联。     

中长期电力负荷预测理论研究

本文首先分析了电力负荷理论中的主成分回归理论与灰色预测理论,其次利用优选组合预测模型,形成中长期电力负荷预测理论模型。优选组合预测模型比主成分回归理论模型与灰色预测理论模型具有更高的精度。     

慎用三大需求定量分析方法

三大需求,即投资需求、消费需求和出口需求.运用三大需求理论来分析经济问题,是经济分析预测中常见的一种方法.特别是近些年来,以三大需求来定量预测经济发展趋势和分析经济现象的有关材料较多,且有将这种方法在应用中日益精确化的倾向(如测算三大需求分别对经济增长的精确贡献度等).但是,这些定量分析得出的结论往往不一,也与实际情况有较大的差距,经不起实践检验,难以为经济工作决策提供正确的参考.我们经过研究认为,造成上述现象的原因,既有理论理解上的偏误,也有应用中主客观方面存在的问题,在目前条件下,分析或预测经济增长趋势,应慎用三大需求理论作为精确度量分析的方法.主要理由有三点:     

对我国股票市场混沌现象的实证分析

自80年代混沌理论运用于经济领域后,对于股票市场的混沌现象研究一直持续至今,并且该领域的争议也持续至今。我国股市在近几年表现出较大波动,本文对这种波动进行混沌现象识别,并作了验证性预测,得出了我国股市不存在混沌现象的结论。     

基于GRA-BiLSTM模型对北京市游客流量的预测方法研究

本文旨在探讨北京市游客流量的预测方法,通过分析相关数据和使用GRA-BiLSTM预测模型进行研究。首先,我们收集了包括经济、社会、人口影响指标关联度进行筛选,同时对比其他预测模型,预测结果表明,该模型具有更高的预测精度。使用该模型对未来的游客流量进行了预测,并评估了预测结果的准确性和可靠性,并且可为相关部门提供有效的决策依据。此研究对于优化旅游资源配置、提升游客体验以及改善城市管理具有重要意义。     

混沌理论与经济预测

混沌理论改变了我们对预测的传统认识,为复杂经济系统的预测提供了新的理论和方法。本文结合混沌理论中的预测概念讨论了混沌对经济预测的影响。     

组合预测系数的确定方法

<正> 一、问题的提出 在经济预测中,对于同一个问题常采用不同的预测方法。衡量一种预测方法的优劣主要取决于其预测精度,不同的预测方法其精度往往也不相同。一般是以预测误差平方和作为评价预测方法优劣的标准,从各种预测方法中选取预测误差平方和最小的那种方法。不同的预测方法从不同角度提炼出样本数据的信息,为了提高预测精度,很自然想到用多种预测方法进行组合预测。组合预测的关键是确定各种预测方法的组合系数,本文提出一种确定最优组合预测系数     

The HWWA econometric model for economic forecasts

Econometric models are often used to forecast economic developments. Does the use of computer-based econometric procedures help sharpen our view of the future or are we blinkered by the supposed ‘precision’ of such models? What problems arise when building national economic models and when these models are used for forecasting purposes? These issues are examined with reference to the HWWA model.     

北京市未来50年人口变动趋势预测研究

根据北京市 2 0 0 8年率先基本实现现代化、2 0 2 0年基本建成现代化国际大都市、2 0 5 0年建成世界一流水平的国际大都市的“新三步走”战略 ,采用国家计划生育委员会开发的中国人口预测软件(CPPS) ,利用北京市第五次人口普查数据 ,以 2 0 0 0年为预测基年 ,分 2 0 0 1— 2 0 0 8年、2 0 0 9— 2 0 2 0年和2 0 2 1— 2 0 5 0年三个阶段 ,设计低、中、高三个方案 ,对未来 5 0年北京市常住人口、户籍人口、外来人口的变动趋势进行预测 ,进而针对首都人口老化问题提出思考与建议。     

Managerial evaluation of sales forecasting effectiveness: A MIMIC modeling approach

A Multiple Indicators and MultIple Causes (MIMIC) model is developed in which managerial evaluations of forecasting effectiveness are modeled as a function of different forecast performance criteria, namely, accuracy, bias, timeliness and cost. The model is estimated using data from a survey of export sales forecasting practices and several hypotheses linking the aforementioned criteria on effectiveness are tested. The findings indicate that evaluations of forecasting effectiveness are equally influenced by short-term accuracy and absence of overestimating bias, while timely delivery of the forecast to management is somewhat less important. Long-term accuracy, underestimation and timing of production of the forecast are not found to impact on effectiveness. Implications of the results for forecasting practice are considered and future research directions identified.     

An innovative regime switching model to forecast Taiwan tourism demand

The tourism industry has become a major part of economic development for many countries. These countries have greatly invested in tourism to attract more tourist arrivals. Hence, the need for more accurate forecasts of tourism demand is important. Various approaches have been applied to forecast tourism demand of different countries. However, tourism demands tend to be imprecise and their trends nonlinear. In addition, there may be drastic changes in the tourism demand time series. To properly handle these problems, this study proposes an innovative forecasting model to detect the regime switching properly and to apply fuzzy time-series model to forecast. The monthly tourist arrivals to Taiwan will be used as forecasting target. The analysis by the proposed model will be validated by the major events as well as previous studies.     

基于多因素分析的区域物流需求径向基函数网络预测

对区域物流需求量进行合理、精确地预测,能为政府部门科学制定物流规划、合理配置物流资源提供决策支持和依据。在对影响区域物流需求的多种因素进行全面分析以及物流需求量指标合理选取的基础上,采用径向基函数神经网络构建区域物流需求量的非线性预测模型,并以四川省相关统计数据为基础,对区域物流需求量进行了预测,取得了满意的预测结果。研究表明:该预测模型较全面地反映了区域物流需求量的变化规律,预测精度较高,泛化能力强,预测结果具有较高的可信性。     

Forecasting the World Economy in the Short Term

(1433) Audrone Jakaitiene and Stephane Dees Forecasting the world economy is a difficult task given the complex interrelationships within and across countries. This paper proposes a number of approaches to forecast short‐term changes in selected world economic variables and aims, first, at ranking various forecasting methods in terms of forecast accuracy and, second, at checking whether methods forecasting directly aggregate variables (direct approaches) outperform methods based on the aggregation of country‐specific forecasts (bottom‐up approaches). Overall, all methods perform better than a simple benchmark for short horizons (up to 3 months ahead). Among the forecasting approaches used, factor models appear to perform the best. Moreover, direct approaches outperform bottom‐up ones for real variables, but not for prices. Finally, when country‐specific forecasts are adjusted to match direct forecasts at the aggregate levels (top‐down approaches), the forecast accuracy is neither improved nor deteriorated (i.e. top‐down and bottom‐up approaches are broadly equivalent in terms of country‐specific forecast accuracy).     

蓝色经济区战略下产业升级与就业调整——基于青岛市产业结构与就业结构的相关性分析

半岛蓝色经济区战略上升为国家战略加快了青岛市产业结构的调整步伐,也为就业结构提供了新的调整和拓展空间。通过建立模型对1988-2010年青岛市产业结构和就业结构数据进行实证分析检验,结合半岛蓝色经济区战略确立的目标进行预测,得出蓝色经济区产业结构升级应坚持:第一产业重点提升水产渔业的发展水平;在依托海洋低耗能、低排放和高效益的第二产业取得突破性发展;加强高等教育、海洋研发作为金融、法律、服务业等第三产业发展的力量源泉。在蓝色经济区建设中,就业结构变动与产业结构变动相互影响,就业结构调整方向预测数值应符合蓝色经济产业升级的需求预测指标。     

Information content of volatility spreads

This study reexamines the determinants of volatility spreads and suggests a new forecast of future volatilities. Contrary to earlier volatility forecasts, the newly introduced forecast is applicable when investors are not risk‐neutral or when underlying returns do not follow a Gaussian probability distribution. This implies that the method is consistent with the presence of risk premia for other risks such as volatility risk. Using S&P 500 index options, we show that the new volatility forecast outperforms other volatility forecasts including risk‐neutral implied volatility and historical volatility in two aspects. First, the new forecast is superior to other estimates in terms of forecasting errors for future realized volatilities. Second, it is an unbiased estimator of future realized volatilities. This is shown using an encompassing regression analysis. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:533–558, 2010     

The importance of demographics in economic analysis: the unusual suspects.

"The proper use of demographic information can add significantly to the ability to analyze and forecast economic activity. With housing, short-run forecasting is difficult and long-term forecasting impossible without considering changing demographic factors. Combining detailed demographic analysis with sound structural econometric modeling of the cyclical factors underlying the demand for and the supply of housing has resulted in significantly more accurate analyses and forecasts of the [U.S.] housing market."     

Solving the problems of new product forecasting

An important consideration in solving the problems of new product forecasting entails distinguishing new product forecasting from the process of forecasting existing products. Particular differences between the two can be identified across the dimensions of data, analytics, forecast, plan, and measurement. For example, new product forecasting features little to no data with which to begin the process, whereas data are available and accessible in forecasting existing products. The minimal data situation requires a qualitative approach that lays out assumptions to provide transparency; in contrast, quantitative techniques are predominantly used when forecasting existing products. Different assumptions help construct a range of new product forecast outcomes on which company contingencies can be planned versus a singular point forecast for an existing product. And the measure of forecast accuracy, which is a common metric in forecasting existing products, must give way to meaningfulness so that the new product forecast is actionable. Recognizing new product forecasting as a cross-functional, company-wide process helps resolve the problems of new product forecasting. While incapable of remedying all problems, a properly understood and organized new product forecasting effort can help the company better prepare, execute, and support a new product launch, affording a greater propensity to achieve new product success.