经济决策定量 第二章Forecasting部分翻译

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管理经济学--生意和经济的预测(1)-文档资料

管理经济学--生意和经济的预测(1)-文档资料
Detrending a series involves regressing each variable in the model on t
The residuals form the detrended series
Basically, the trend has been partialled out
If a series is weakly dependent and is stationary about its trend, we will call it a trend-stationary process
Detrending
Adding a linear trend term to a regression is the same thing as using “detrended” series in a regression
Gives the Expected Direction
Quantitative Forecasting 2.7654 %
Gives the precise Amount
2002 South-Western Publishing
Time-Series Characteristics: Secular Trend and Cyclical Variation in Women’s Clothing Sales
Thus, this weaker form of stationarity requires only that the mean and variance are constant across time, and the covariance just depends on the distance across time

经济决策定量分析翻译

经济决策定量分析翻译

第二章预测未来是企业经济决策的一个基本方面。

未来的销售是经济预测中最重要的变量。

了解销售是预算和规划过程的一个先决条件。

人们开发出各种定量方法来预测变量的未来值,这些方法模型可以划分为三大类:1、利用过去的数据进行预测一个变量的历史模式可以用来识别和预测未来,通过从时间序列数据外推得到这些模式。

2、利用因果模型进行预测找出未知变量与一个或多个已知变量之间的关系。

利用已知变量的值去预测所需的变量值。

3、.利用统计数据进行预测定量陈述法用来表达主观概率判断。

这些方法可以合并预测的实际“击球率”并且能提供一个集体决策的表达式。

第三章定量分析方法在实现成本节约方面做得非常成功的一个商业决策领域是存货控制领域。

这个成功故事的主要原因在于存货代表了整个经济活动的大部分。

仅仅在美国,数千亿美元都是投资在存货上。

由于很大规模的存贮投资,即便存储控制有很小的提高,但也会导致极大的节约。

存储理论始于20世纪20年代,从此经历了几个阶段的发展。

一开始,它有非常简单的几个参数的模型来捕获关键因素。

后来,通过增加更多的参数,这些模型被建立成包含更多的细节。

渐渐地,概率模型在20世纪50年代被研发,用来描述难以预测需求和订货至交货时间的影响。

所有的模型遭遇到一个限制------它们在一段时间内仅仅处理一种产品。

真正的生活存贮人们面临的是管理项目的巨大变化,用充分的相互关系来形成一个管理问题。

在20世纪70年代早期,一个被称为物料需求计划(MRP)的技术开始得到使用。

后来,这个技术没有改变初始的条件,而被改名为制造资源计划(MRPⅡ)。

MRP的中心思想是不能停工待料,使得需要物料是能充分有效地提供。

最初的版本假设对最终产品的决定性需求,对订购数量进行简单的逆向工作,和安排组件与基本元件的提供。

逐渐扩展这些模型使它们更符合实际。

20世纪70年代后期80年代初,另外一场运动兴起改革了生产实践。

被更高利益成本(零库存)和日本一些成功企业的例子的刺激下,准时生产的概念变得流行起来。

经济评价基本术语英汉对照(精选五篇)

经济评价基本术语英汉对照(精选五篇)

经济评价基本术语英汉对照(精选五篇)第一篇:经济评价基本术语英汉对照汉英对照经济评价基本术语备择方案AlternativeOpen 备选方案Option备选方案价值 Option Value备选方案评估 OptionAppraisal标准换算系数 Standard Conversion Factor , SCF补贴 Subsidy 不变价格 Constant Price不可外贸货物 Non-Tradable Goods财务补贴 Financial Subsidy 环境卫生 Environment Sanitation 换算系数 Conversion Factor汇率溢价 Foreign Exchange Premium 或有估价法 Contingent Valuation Method , CVM 货币的时间价值 Time Value of Money机会成本 Opportunity Cost 基准收益率 Hurdle Cut-Off Rate 计算单位 Numeraire加权平均资金成本 Weighted Average Cost of Capital , 年金价值 Annuities Value平均增量财务费用 Average Incremental Financial Cost , AIFC 平均增量成本 Average Incremental Cost , AIC平均增量经济费用Average Incremental Economic Cost , AIEC 评估 Appraisal 评价 Evaluation项目框架 Project Rramework 项目周期 Project Cycle 消费者剩余 Consumer Surplus 效果费用比 Effectiveness Cost Ratio 需求曲线 Demand Price 需求曲线 Demand Curve要求回报率Required Rate of Return, RRR 意愿调差评估法Contingent Valuation 隐含价值法Hedonic Method 财务分析Financial Analysis 财务价格 Financial Price财务净现值 Financial Net Present Value , FNPV 财务可持续性Financial Sustainability财务内部收益率 Financial Internal Rate of Return , FIRR 财务效益 Financial Benefit财务效益费用分析Financial Benefit –Cost Analysis 残值Residual Value偿债备付率Debt Service Coverage Ratio , DSCR 陈诉偏好Stated Preference 成本回收Cost Recovery成本有效性分析Cost Effectiveness Analysis 出口评价Export Parity Price到岸价格Cost , Insurance & Freight , C.I.F 等价年度费用Equivalent Annual Cost非外贸产出和收入Non-Traded Output and Input非外贸货物Non-Traded Goods 费用效果比 Cost Effectiveness Ratio 费用效果分析 Cost Effectiveness Analysis , CEA 费用效益分析Cost Benefit Analysis , CBA 分配分析 Distribution Analysis 福利费用 Welfare Cost福利效益 Welfare Benefit公共产品 Public Goods 供给价Supply Price官方汇率 Official Exchange Rate , OER规模经济 Economies of Scale 国民收入平减指数 GDP Deflator耗减补偿 Depletion Premium 核算单位 Unit of Account环境估价Environment Valuation 环境可持续性Environment SustainabilityWACC价格扭曲Price Distortion价格指数Price Index 交叉补贴CrossProject 无形的 Intangible息税前利润 Earnings Before Interest and Tax , EBIT 显示偏好Revealed Preference 现存价值 Existence Value现金流出(量)Cash Outflow , CO 现金流(量)Cash Flow , CF 现金流入(量)Cash Inflow , CI 现值 Present Value , PV 相对价格作用Relative Price effect 项目备选方案Project Option盈亏价值法 Break – Even Point 影响陈述 Impact Statement影子工作率 Shadow Wage Rate , SWR影子工资系数Shadow Wage Rate Factor , SWRF 影子汇率Shadow Exchange Rate影子汇率系数Shadow Exchange Rate Factor ,SERF 影子价格Shadow Price有项目WithToEquity 资本化价值 Capitalized Value 资本金 Equity资本金净利润率 Return On Equity , ROE 资产负债率 Liability On Asset Ratio , LOAR 资金成本 Resource Cost资金的财务机会成本Financial Opportunity Cost of Capital , FOCC资金的经济机会成本 Economic Opportunity Cost of Capital , EOCC资源成本 Resource Cost总投资收益率 Return On Investment , ROI最低可接受收益率Minimum Acceptable Rate of Return , MARR第二篇:地质年代术语英汉对照stratum 地层stratigraphic correlation 地层对比horizon 层位key bed 标志层barren bed 哑层lacuna 缺失hiatus 间断continuity 连续discontinuity 不连续conformity 整合unconformity 不整合angular unconformity 角度不整合para-unconformity平行不整合geochronologic unit 地质年代单位eon 宙era 代period 纪epoch 世stage 期chron 时chronostratigraphic unit 年代地层单位eonothem 宇erathem 界system 系series 统stage 阶chronozone 时带biostratigraphic unit 生物地层单位biostratigraphic zone 生物地层带lithostratigraphic unit 岩石地层单位group 群formation 组member 段bed 层geochronologic scale 地质年代表Phaneozoic Eon(Eonothem)显生宙(宇)Cainozoic Era(Erathem)新生代(界)Cenozoic Era(Erathem)新生代(界)Quaternary Period(System)第四纪(系)Holocene Epoch(Series)全新世(统)Pleistocene Epoch(Series)更新世(统)Tertiary Period(System)第三纪(系)Neogene Period(System)新第三纪(系)Pliocene Epoch(Series)上新世(统)Miocene Epoch(Series)中新世(统)Paleogene Period(System)老第三纪(系)Oligocene Epoch(Series)渐新世(统)Eocene Epoch(Series)始新世(统)Paleocene Epoch(Series)古新世(统)Mesozoic Era(Erathem)中生代(界)Cretaceous Period(System)白垩纪(系)Jurassic Period(System)侏罗纪(系)triassic Period(System)三叠纪(系)Palaeozoic Era(Erathem)古生代(界)Permian Period(System)二叠纪(系)Carboniferous Period(System)石炭纪(系)DevonianPeriod(System)泥盆纪(系)Silurian Period(System)志留纪(系)Ordovician Period(System)奥陶纪(系)Cambrian Period(System)寒武纪(系)Cryptozoic Eon(Eonothem)隐生宙(宇)Proterozoic Eon(Eonothem)元古宙(宇)Neoproterozoic Era(Erathem)新元古代(界)Sinian Period(System 震旦纪(系)Mesoproterozoic Era(Erathem)中元古代(界)Palaeoproterozoic Era(Erathem)古元古代(界)Archaean Eon(Eonothem)太古宙(宇)Precambrian 前寒武纪第三篇:会计术语英汉对照会计名词术语英汉对照(仅供参考,欢迎指正和补充)account title 会计科目,账户名称 account 账户accounting circle 会计循环accounting entity assumption 会计主体假设accounting period assumption 会计分期假设accounting process 会计流程accounting report 会计报告 accounts payable 应付账款accounts receivable turnover ratio 应收账款周转率accounts receivable 应收账款accrual-basis accounting 应计制会计,权责发生制会计accrued accounting 应计制会计 accrued revenues 应计收入accumulated depreciation 累计折旧 adjusting entries 调整分录administrative expenses 管理费用 advances 预付款aging schedule 账龄分析表allowance for doubtful accounts 坏账准备allowance for returns 备抵销售退回 asset 资产average collection period平均收款期 bad debts expense 坏账费用 balance sheet 资产负债表 bank account 银行存款bank reconciliation银行存款余额调节 bank statement 银行对账单book of original entry 原始分录簿book value 账面价值bookkeeping 簿记business document 业务凭证 calendar year 日历carrying value 账面价值,现存价值cash(net)realizable value 可变现净值 cash advance 预付现金cash count sheet 现金盘点表cash disbursement 现金支出cash discount 现金折扣 cash inflows 现金流入 cash outflows 现金流出 cash over or shot 现金溢缺cash payments journal 现金支出分录簿 cash receipt 现金收入cash receipts journal 现金收入分录簿 cash refund 现金折扣cash register receipt 收款机收据(收银条)cash 现金cash-basis accounting 现金制会计,收付实现制会计 cashier 收银员,出纳chart of accounts 会计科目表 check register 支票登记簿 check 支票claim 索取权、求偿权 claimer 索取者、求偿权人classified balance sheet 分类资产负债表 closing entries 结账分录 closing the book 结账 common stock 普通股 comparability 可比性compensating balances 补偿性余额,补偿性最低存款额compound entry 复合分录conceptual framework 概念框架conservatism 稳健性consistency 一致性contra asset account 资产对销账户,资产备抵账户contra-revenue account 收入抵消账户 corporation 公司correcting entries 更正分录 cost of goods sold 销货成本 cost principle 成本计价原则 credibility 可靠性credit balance 贷方余额 credit(s)贷,贷方current assets 流动资产 current liability 流动负债 current ratio 流动比率current replacement cost 现行重置成本 dealership 代理商debit balance 借方余额 debit(s)借,借方debt to total assets ratio 资产负债率 debt(s)债务decision usefulness 决策有用性 deferrals 递延项目deposit slip 存款单 deposit ticket 存款单deposits in transit 在途存款depreciation expense 折旧费用dishonor(note)拒绝承兑(票据)dividend 股利double-entry system 复式记账法 due date 到期due from sb.应收某人 due from sb.应收某人earnings per share 每股盈余economic entity assumption 经济主体假设 economic event 经济事项electronic funds transfer 电子资金转账 ending balance 期末余额 endorsement 背书 enter 登记 expense 费用expired cost 已耗成本factor 客账经纪商,代理商faithful representation 忠实表述,如实反映 feedback value 反馈价值Financial Accounting Standards Board(FASB)(美国)财务会计准则委员会financial statements 财务报表 finished goods 产成品first-in, first-out(FIFO)先进先出法fiscal year 会计,财政FOB destination 目的地交货 FOB shipping point 寄发地交货 FOB 离岸价格For Deposit Only 仅限转账 freight cost 运费general journal 普通分录簿Generally Accepted Accounting Standards(GAAP)公认会计准则going concern assumption 持续经营假设going-concern assumption 持续经营假设 grace period宽限期 gross profit 毛利guaranteed debt 担保债券 honor(note)承兑(票据)imprest system 定额备用金制度 income from operations 营业利润 income sheet 利润表income summary 损益汇总income tax 所得税intangible assets 无形资产 interim period 中期International Accounting Standards Board(IASB)国际会计准则委员会 inventory count 存货盘点,盘存inventory summary sheets 库存汇总表 inventory turnover 存货周转率 investor 投资者journal 分录簿,日记账journalize 登分录簿,记日记账last-in, first-out(LIFO)后进先出法 lease liability 租赁负债 ledger 分类账 liability 负债liquidity 流动性,变现能力long-term investment 长期投资long-term liability 长期负债lower of cost or market 成本与市价孰低法 market value 市场价值matching principle 匹配原则 materiality 重要性merchandise inventory 库存商品 miscellaneous expense 杂费monetary measurement assumption货币计量假设 monetary unit assumption 货币单位假设 money down 现金,现款 mortgage 抵押借款 net assets 净资产 net income 净收益 neutral 中立性nominal account 虚账户 note payable 应付票据 note(s)附注obligations 承付款项 on account 赊账on demand 见票即付operating expenses 营业费用 operating income 营业利润other expenses and losses 其他费用和损失other revenues and gains 其他收入和利得 outstanding checks 未兑现支票 owed to sb.应付、亏欠某人 paid-in capital 投入资本partnership 合伙企业,合伙制 past-due 逾期,过期未付periodic inventory system 定期盘存制 permanent account 永久性账户perpetual inventory system 永续盘存制 petty cash fund 小额现金基金 postdated check 未到期支票 posting 过账predictive value预测价值 prepaid expenses 预付费用 prepaid insurance 预付保险profit margin percentage 销售利润率profitability 盈利能力promissory note 本票proprietorship 独资企业,业主制purchase invoice 购货发票purchases journal 购货分录簿 raw meterials 原材料 real account 实账户 relevance 相关性 reliability 可靠性remittance advice 汇款通知restrictive endorsement 限制性背书 retailer 零售商retained earnings statement 留存盈余表 retained earnings 留存盈余 return on assets 总资产收益率return on equity 权益收益率,净资产收益率revenue recognition principle 收入确认原则 revenue 收入reversing entries 转会分录 ring up 把款项(金额)记入 sale on credit 赊销,信用销售 sales discount 销售折扣 sales journal 销货分录簿sales return and allowance 销售退回和折让sales slip 销售单scrap value 残值Securities and Exchange Commission(SEC)(美国)证券交易委员会selling expenses 销售费用 service revenue 服务收入 simple entry 简单分录 solvency 偿债能力source document 原始凭证 special journal 特种分录簿specific identification 个别认定法,个别计价法statement of cash flows 现金流量表stockholders’ equity 股东权益 subsidiary ledger 明细分类账 supplies(日常)用品 taxes payable 应付税费temporary account 暂时性账户three-column form of account 三栏式账户time period assumption 会计分期假设 treasurer 财务主管,出纳 trial balance 试算平衡 uncollectable(s)坏账uncollected account expense 坏账费用 unearned revenue 预收收入,未实现收入 unexpired cost 未耗成本 unexpired cost 未耗用成本 verifiable 可核性,可验证性 voucher register 付款凭单登记簿voucher system 付款凭单制度wage payable 应付职工薪酬wholesaler 批发商work in process 在产品work sheet 工作底稿working capital 营运资本 working paper 工作底稿 write-off 冲销第四篇:英汉对照计量经济学术语计量经济学术语A 校正R2(Adjusted R-Squared):多元回归分析中拟合优度的量度,在估计误差的方差时对添加的解释变量用一个自由度来调整。

工程管理专业英语翻译

工程管理专业英语翻译

1.2 Major Types of ConstructionSince most owners are generally interested in acquiring only a specific type of constructed facility, they should be aware of the common industrial practices for the type of construction pertinent to them [1]. Likewise, the construction industry is a conglomeration of quite diverse segments and products. Some owners may procure a constructed facility only once in a long while and tend to look for short term advantages. However ,many owners require periodic acquisition of new facilities and/or rehabilitation of existing facilities. It is to their advantage to keep the construction industry healthy and productive. Collectively, the owners have more power to influence the construction industry than they realize because, by their individual actions, they can provide incentives for innovation, efficiency and quality in construction [2]. It is to the interest of all parties that the owners take an active interest in the construction and exercise beneficial influence on the performance of the industry.In planning for various types of construction, the methods of procuring professional services, awarding construction contracts, and financing the constructed facility can be quite different. For the purpose of discussion, the broad spectrum of constructed facilities may be classified into four major categories, each with its own characteristics.Residential Housing ConstructionResidential housing construction includes single-family houses, multi-family dwellings, and high-rise apartments [3]. During the development and construction of such projects, the developers or sponsors who are familiar with the construction industry usually serve as surrogate owners and take charge, making necessary contractual agreements for design and construction, and arranging the financing and sale of the completed structures [4]. Residential housing designs are usually performed by architects and engineers, and the construction executed by builders who hire subcontractors for the structural, mechanical, electrical and other specialty work. An exception to this pattern is for single-family houses as is shown in Figure 1-2, which may be designed by the builders as well.The residential housing market is heavily affected by general economic conditions, tax laws, and the monetary and fiscal policies of the government. Often, a slight increase in total demand will cause a substantial investment inconstruction, since many housing projects can be started at different locations by different individuals and developers at the same time [5]. Because of the relative ease of entry, at least at the lower end os the market, many new builders are attracted to the residential housing construction. Hence, this market is highly competitive, with potentially high risks as well as high rewards.Figure1-2 Residential Housing Construction (courtesy of caterpillar, Inc) Institutional and Commercial Building Construction Institutional and commercial building construction encomprasses a great variety of project types and sizes, such as schools and universities, medical clinics and hospitals, recreational facilities and sports stadiums, retail chain stores and large shopping centers, warehouse and light manufacturing plants, and skyscrapers for offices and hotels, as is shown in Figure1-3 [6]. The owners of such buildings may or may not be familiar with construction industry practices, but they usually are able to select competent professional consultants and arrange the financing of the constructed facilities themselves. Specialty architects and engineers are often engaged for designing a specific type of building, while the builders or general contractors undertaking such projects may also be specialized in only that type of building.Because of the higher costs and greater sophistication of institutional and commercial buildings in comparison with residential housing, this market segment is shared by fewer competitors [7]. Since the construction of some of these buildings is a long process which once started will take some time to proceed until completion, the demand is less sensitive to general economic conditions than that for speculative housing. Consequently, the owners may confront an oligopoly of general contractors who compete in the same market. In an oligopoly situation, only a limited number of competitors exist, and a firm’s price for services may be based in part on part on its competitive strategies in the local market.Specialized Industrial ConstructionSpecialized industrial construction usually involves very large scale projects, with a high degree of technological complexity, such as oil refineries, steel mills, chemical processing plants and coal-fired or nuclear power plants, as is shown in Figure1-4 [8]. The owners usually are deeply involved in thedevelopment of a project, and prefer to work with designers-builders such that the total time for the completion of the project can be shortened. They also want to pick a team of designers and builders with whom the ownerhas developed good working relations over the years.Figure1-3 Construction of the PPG Building in Pittsburgh, Pennsylvania ( courtesy of PPG Industries, Inc)Figure1-4 Construction of a Benzene Plant in L……( courtesy of Manitowoc Company, Inc)Although the initiation of such projects is also affected by the state of the economy, long range demand forecasting is the most important factor since such projects are capital intensive and require considerable amount of planning and construction time [9].Governmental regulation such as the rulings of the Environmental Protection Agency and the Nuclear Regulatory Commission in the United States can also profoundly influence decisions on these projects.Infrastructure and Heavy ConstructionInfrastructure and heavy construction includes projects such as highways, mass transit systems, tunnels, bridges, pipelines, drainage systems and sewage treatment plants, as is shown in Figure1-5. Most of these projects are publicly owned and therefore financed either through bonds or taxes. This category of construction is characterized by a high degree of mechanization, which has gradually replaced some labor intensive operations.The engineers and builders engaged in infrastructure construction are usually highly specialized since each segment of the market requires different types of skills [10]. However, demands for different segments of infrastructure and heavy construction may shift with saturation in some segments. For example, as the available highway construction projects are declining, some heavy construction contractors quickly move their work force and equipment into the field of mining where jobs are available.Figure1-5 Construction of the Dame Point Bridge in Jacksonville, Florida(courtesy of Mary Lou Maher)Wordsconglomeration 混合物,聚集 infrastructure and heavy construction 重大基础项rehabilitation 修复目建设disincentive 抑制,抑制因素 procure 获得spectrum 波谱,光谱,范围 incentive 动机surrogate 代理,替代 innovation 创新architect 建筑师 residential housing construction 住宅类房fiscal 财政的屋建设entry 进入,编入 take charge 负责clinic 诊所 execute 执行stadium 露天大型体育场 substantial 实质的、重大的sophistication 复杂 recreational 娱乐的construction industry 建筑业 retail 零售high-rise apartments 高层公寓 proceed 开展,进行institution and commercial building segment 部分,份额construction 办公和商业用房建设 single-family house 独户住宅oligopoly 垄断,求过于供 professional consultant 专业咨询人士confront 面对 general contractor 总承包商infrastructure 基础设施 initiation 启动pipeline 管道 strategy 策略specialized industrial construction drainage 排水系统专业化工业项目建设 saturation 饱和Notes[1] 全句可译为:由于大多数业主通常只对获得某种特定类型的建筑物感兴趣,因而他们应当对适合于他们的建设类型的实物有着一定的了解。

预测(Forecasting)

预测(Forecasting)

预测的定义预测(forecasting)是预计未来事件的一门艺术,一门科学。

它包含采集历史数据并用某种数学模型来外推与将来。

它也可以是对未来的主观或直觉的预期。

它还可以是上述的综合,即经由经理良好判断调整的数学模型。

进行预测时,没有一种预测方法会绝对有效。

对一个企业在一种环境下是最好的预测方法,对另一企业或甚至本企业内另一部门却可能完全不适用。

无论使用何种方法进行预测,预测的作用也是有限的,并不是完美无缺。

但是,几乎没有一家企业可以不进行预测而只是等到事情发生时再采取行动,一个好的短期或长期的经营规划取决于对公司产品需求的预测。

[编辑]预测的类型按在规划未来业务方面企业使用可分三种类型的预测:经济预测(economic forecasts)、技术预测(technological forecasts)、需求预测(demand forecasts)。

1、经济预测(economic forecasts),通过预计通货膨胀率、货币供给、房屋开工率及其它有关指标来预测经济周期。

2、技术预测(technological forecasts),即预测会导致产生重要的新产品,从而带动新工厂和设备需求的技术进步。

3、需求预测(demand forecasts),为公司产品或服务需求预测。

这些预测,也叫销售预测,决定公司的生产、生产能力及计划体系,并使公司财务、营销、人事作相应变动。

按它包含的时间跨度来分类,也有三种分类:短期预测、中期预测、长期预测1、短期预测。

短期预测时间跨度最多为1年,而通常少于3个月。

它用于购货、工作安排、所需员工、工作指定和生产水平的计划工作。

2、中期预测。

中期预测的时间跨度通常是从3个月到3年。

它用于销售计划、生产计划和预算、现金预算和分析不同作业方案。

3、长期预测。

长期预测的时间跨度通常为3年及3年以上。

它用于规划新产品、资本支出、生产设备安装或天职,及研究与发展。

中期预测和长期预测与短期预测的区别主要体现在以下三个方面:第一,中长期预测要处理更多的综合性问题并主要为产品、工厂、工序的管理决策提供支持;第二,短期预测采用的方法通常与长期预测采用的方法不同。

forcast指标 -回复

forcast指标 -回复

forcast指标-回复什么是经济预测指标?经济预测指标是用来预测经济趋势和未来经济表现的数据和指标。

这些指标可以包括各种经济数据,如生产总值(GDP)、就业数据、消费者物价指数等。

经济预测指标是政府、学术机构和私人企业用来预测经济增长、通货膨胀、失业率等重要经济指标的关键工具。

为什么需要经济预测指标?经济预测指标对于政府、企业和个人来说都非常重要。

政府需要这些指标来制定经济政策,以促进经济增长、控制通货膨胀、减少失业率等。

企业需要这些指标来预测市场需求和制定战略,以便更好地规划生产和销售。

个人也可以利用这些指标来做出智能的投资决策,减少风险,获得更好的回报。

哪些是常见的经济预测指标?几个常见的经济预测指标包括GDP、CPI、失业率和利率。

GDP是衡量一个国家经济总产出的指标,可以显示经济增长的速度和趋势。

CPI是消费者物价指数,反映价格变动对消费者购买力的影响,可以用来预测通货膨胀。

失业率是用来衡量劳动力市场上的就业情况,通常可以预测经济的健康程度。

利率则是政府或央行设置的利率,对经济和货币市场有重大影响,可以用来预测经济增长和投资状况。

如何使用经济预测指标?使用经济预测指标需要综合考虑各个指标之间的关系和趋势。

首先,需要了解每个指标的定义和影响因素,以及其与其他指标之间的关系。

然后,可以通过观察历史数据和分析趋势来预测将来的经济表现。

此外,重要的是要关注来自政府和其他机构的经济预测报告,以了解专家对经济的观点和预测。

经济预测指标的局限性是什么?尽管经济预测指标对决策和规划非常有帮助,但它们也有一定的局限性。

首先,经济预测本质上是一种推测,无法100准确地预测未来。

其次,经济预测指标只能提供关于经济发展的一部分信息,无法完全反映经济的复杂性和不确定性。

另外,过度依赖经济预测指标可能会导致盲目的决策,忽视其他重要因素的影响。

经济预测指标的重要性和应用尽管经济预测指标存在一定的局限性,但它们仍然是经济决策和规划的重要工具。

BusinessandEconomicForecasting

BusinessandEconomicForecasting
Slide 12
3. Surveys
Common Survey Problems
New Products have no • Sample bias--
historical data -- Surveys
» telephone, magazine
can assess interest in new
• Models differ in accuracy, which is often based on the square root of the average squared forecast error over a series of N forecasts and actual figures
The choice of a particular forecasting method depends on several criteria:
• costs of the forecasting method compared with
its gains
• complexity of the relationships among variables • time period involved • accuracy needed in forecast • the lead time between receiving information and
LAGGING INDICATORS
*Handbook of Cyclical Indicators, 1984
» Prime rate (+12.2)
» Duration of unemployment (+4.4)
Questions
Why are contracts and orders for plant and equipment appropriate leading indicators?

马歇尔经济学原理第二章翻译

马歇尔经济学原理第二章翻译

马歇尔经济学原理第二章翻译【原创实用版】目录1.马歇尔的《经济学原理》概述2.马歇尔《经济学原理》第二章的内容提要3.马歇尔《经济学原理》第二章的翻译版本推荐4.马歇尔《经济学原理》第二章的阅读体验正文马歇尔的《经济学原理》是继亚当·斯密《国富论》之后最重要的经济学著作之一,也是剑桥学派(新古典学派)创始人马歇尔的代表作。

全书名:《经济学原理》(principles,of,economics)。

马歇尔在书中阐述了经济学说,被认为是英国古典政治经济学的继续和发展。

第二章是马歇尔《经济学原理》中的一个重要章节。

本章主要讨论了经济学的基本概念和原理,包括价值、财富、货币、资本、劳动力等方面。

通过对这些概念的阐述,马歇尔为读者建立了一个经济学的基本框架,为后面的章节奠定了基础。

目前,市面上有许多马歇尔《经济学原理》的翻译版本。

其中,曼昆的《经济学原理》翻译版本比较受欢迎。

这个版本写得非常通俗易懂,不像其他作者的那么难懂。

此外,朱志泰翻译的《经济学原理》马歇尔版本也受到了一些读者的喜爱。

这个版本在翻译过程中保留了马歇尔原有的语言风格和表达方式,更适合喜欢原汁原味的读者。

阅读马歇尔《经济学原理》第二章,不仅可以帮助读者理解经济学的基本概念和原理,还可以领略到马歇尔作为一位杰出经济学家的思想魅力。

在阅读过程中,读者可以感受到马歇尔对经济学的深刻理解和独特见解。

同时,通过学习本章内容,读者还可以为后续学习打下坚实的基础。

总之,马歇尔的《经济学原理》第二章是一篇重要的经济学文章,对于学习经济学的人来说是必不可少的。

在众多翻译版本中,曼昆和朱志泰的版本都值得一读。

forecasting

forecasting

Y轴截距
斜率
Y = a + bX
因变量(反应变量) 自变量(解释变量)
线性回归模型 (Linear Regression)
Y
回归方程 Y = a + bX
因变量
X 自变量
预测总是不准确的 Forecast is always wrong!
预测的结果很少能够与实际完全相符; 大多数预测方法假设系统在一段时间内保持稳定;
产品需求数量
第1年
第2年
第3年
第4年
移动平均法(Moving Average)
MA 是一列算术平均值 主要用于数据序列不存在趋势或趋势不明显的情形


通常用于平滑数据波动, 能够反映数据在一段时间内的总体走 势
计算公式: 前n期需求总和 / n
加权移动平均(Weighted Moving Average)
定量预测
用于市场形势稳定或存在大 量历史数据的情形
– 新产品
– 新技术 主要利用决策者的直觉及经 验进行预测 – 如预测商品网络销量
– 已有产品
– 已存在的技术 主要利用数量方法进行预测
– 如预测彩色电视机的销量
定性方法(Qualitative Methods)
各部门主管集体讨论法
时间序列模型
因果模型
移动平均
指数平滑
趋势外推
线性回归
时间序列预测(Time Series)
时间序列即一列均匀分布的数据点 – 数据点可通过观察多个时间周期的反应变量获得 预测仅依赖于过去值 – 过去和当前发挥作用的因素变量在未来将继续施加影响
时间序列预测(Time Series)
周期 (Cycle) 趋势季节 (Season)

学术英语(社科)Unit2二单元原文及翻译

学术英语(社科)Unit2二单元原文及翻译

学术英语(社科)Unit2二单元原文及翻译第一篇:学术英语(社科)Unit2二单元原文及翻译UNIT 2 Economist1.Every field of study has its own language and its own way of thinking.Mathematicians talk about axioms, integrals, and vector spaces.Psychologists talk about ego, id, and cognitive wyers talk about venue, torts, and promissory estoppel.每个研究领域都有它自己的语言和思考方式。

数学家谈论定理、积分以及向量空间。

心理学家谈论自我、本能、以及认知的不一致性。

律师谈论犯罪地点、侵权行为以及约定的禁止翻供。

2.Economics is no different.Supply, demand, elasticity, comparative advantage, consumer surplus, deadweight loss—these terms are part of the economist’s language.In the coming chapters, you will encounter many new terms and some familiar words that economists use in specialized ways.At first, this new language may seem needlessly arcane.But, as you will see, its value lies in its ability to provide you a new and useful way of thinking about the world in which you live.经济学家也一样。

翻译词汇经济学词汇 中英对照

翻译词汇经济学词汇 中英对照

Aaccounting:会计accounting cost :会计成本accounting profit :会计利润adverse selection :逆向选择allocation 配置allocation of resources :资源配置allocative efficiency :配置效率antitrust legislation :反托拉斯法arc elasticity :弧弹性Arrow's impossibility theorem :阿罗不可能定理Assumption :假设asymetric information :非对称性信息average :平均average cost :平均成本average cost pricing :平均成本定价法average fixed cost :平均固定成本average product of capital :资本平均产量average product of labour :劳动平均产量average revenue :平均收益average total cost :平均总成本average variable cost :平均可变成本Bbarriers to entry :进入壁垒base year :基年bilateral monopoly :双边垄断benefit :收益black market :黑市bliss point :极乐点boundary point :边界点break even point :收支相抵点budget :预算budget constraint :预算约束budget line :预算线budget set 预算集Ccapital stock :资本存量capital output ratio :资本产出比率capitalism :资本主义cardinal utility theory :基数效用论cartel :卡特尔ceteris puribus assumption:“其他条件不变”的假设ceteris puribus demand curve :其他因素不变的需求曲线Chamberlin model :张伯伦模型change in demand :需求变化change in quantity demanded :需求量变化change in quantity supplied :供给量变化change in supply :供给变化choice :选择closed set :闭集Coase theorem :科斯定理Cobb—Douglas production function :柯布--道格拉斯生产函数cobweb model :蛛网模型collective bargaining :集体协议工资collusion :合谋command economy :指令经济commodity :商品commodity combination :商品组合commodity market :商品市场commodity space :商品空间common property :公用财产comparative static analysis :比较静态分析compensated budget line :补偿预算线compensated demand function :补偿需求函数compensation principles :补偿原则compensating variation in income :收入补偿变量competition :竞争competitive market :竞争性市场complement goods :互补品complete information :完全信息completeness :完备性condition for efficiency in exchange :交换的最优条件condition for efficiency in production :生产的最优条件concave :凹concave function :凹函数concave preference :凹偏好consistence :一致性constant cost industry :成本不变产业constant returns to scale :规模报酬不变constraints :约束consumer :消费者consumer behavior :消费者行为consumer choice :消费者选择consumer equilibrium :消费者均衡consumer optimization :消费者优化consumer preference :消费者偏好consumer surplus :消费者剩余consumer theory :消费者理论consumption :消费consumption bundle :消费束consumption combination :消费组合consumption possibility curve :消费可能曲线consumption possibility frontier :消费可能性前沿consumption set :消费集consumption space :消费空间continuity :连续性continuous function :连续函数contract curve :契约曲线convex :凸convex function :凸函数convex preference :凸偏好convex set :凸集corporatlon :公司cost :成本cost benefit analysis :成本收益分cost function :成本函数cost minimization :成本极小化Cournot equilihrium :古诺均衡Cournot model :古诺模型Cross—price elasticity :交叉价格弹性Ddead—weights loss :重负损失decreasing cost industry :成本递减产业decreasing returns to scale :规模报酬递减deduction :演绎法demand :需求demand curve :需求曲线demand elasticity :需求弹性demand function :需求函数demand price :需求价格demand schedule :需求表depreciation :折旧derivative :导数derive demand :派生需求difference equation :差分方程differential equation :微分方程differentiated good :差异商品differentiated oligoply :差异寡头diminishing marginal substitution :边际替代率递减diminishing marginal return :收益递减diminishing marginal utility :边际效用递减direct approach :直接法direct taxes :直接税discounting :贴税、折扣diseconomies of scale :规模不经济disequilibrium :非均衡distribution :分配division of labour :劳动分工distribution theory of marginal productivity :边际生产率分配论duoupoly :双头垄断、双寡duality :对偶durable goods :耐用品dynamic analysis :动态分析dynamic models :动态模型EEconomic agents :经济行为者economic cost :经济成本economic efficiency :经济效率economic goods :经济物品economic man :经济人economic mode :经济模型economic profit :经济利润economic region of production :生产的经济区域economic regulation :经济调节economic rent :经济租金exchange :交换economics :经济学exchange efficiency :交换效率economy :经济exchange contract curve :交换契约曲线economy of scale :规模经济Edgeworth box diagram :埃奇沃思图exclusion :排斥性、排他性Edgeworth contract curve :埃奇沃思契约线Edgeworth model :埃奇沃思模型efficiency :效率,效益efficiency parameter :效率参数elasticity :弹性elasticity of substitution :替代弹性endogenous variable :内生变量endowment :禀赋endowment of resources :资源禀赋Engel curve :恩格尔曲线entrepreneur :企业家entrepreneurship :企业家才能entry barriers :进入壁垒entry/exit decision :进出决策envolope curve :包络线equilibrium :均衡equilibrium condition :均衡条件equilibrium price :均衡价格equilibrium quantity :均衡产量eqity :公平equivalent variation in income :收入等价变量excess—capacity theorem :过度生产能力定理excess supply :过度供给exchange :交换exchange contract curve :交换契约曲线exclusion :排斥性、排他性exclusion principle :排他性原则existence :存在性existence of general equilibrium :总体均衡的存在性exogenous variables :外生变量expansion paths :扩展径expectation :期望expected utility :期望效用expected value :期望值expenditure :支出explicit cost :显性成本external benefit :外部收益external cost :外部成本external economy :外部经济external diseconomy :外部不经济externalities :外部性FFactor :要素factor demand :要素需求factor market :要素市场factors of production :生产要素factor substitution :要素替代factor supply :要素供给fallacy of composition :合成谬误final goods :最终产品firm :企业firms’demand curve for labor :企业劳动需求曲线firm supply curve :企业供给曲线first-degree price discrimination :第一级价格歧视first—order condition :一阶条件fixed costs :固定成本fixed input :固定投入fixed proportions production function :固定比例的生产函数flow :流量fluctuation :波动for whom to produce :为谁生产free entry :自由进入free goods :自由品,免费品free mobility of resources :资源自由流动free rider :搭便车,免费搭车function :函数future value :未来值Ggame theory :对策论、博弈论general equilibrium :总体均衡general goods :一般商品Giffen goods :吉芬晶收入补偿需求曲线Giffen's Paradox :吉芬之谜Gini coefficient :吉尼系数goldenrule :黄金规则goods :货物government failure :政府失败government regulation :政府调控grand utility possibility curve :总效用可能曲线grand utility possibility frontier :总效用可能前沿Hheterogeneous product :异质产品Hicks—kaldor welfare criterion :希克斯一卡尔多福利标准homogeneity :齐次性homogeneous demand function :齐次需求函数homogeneous product :同质产品homogeneous production function :齐次生产函数horizontal summation :水平和household :家庭how to produce :如何生产human capital :人力资本hypothesis :假说Iidentity :恒等式imperfect competion :不完全竞争implicitcost :隐性成本income :收入income compensated demand curve :收入补偿需求曲线income constraint :收入约束income consumption curve :收入消费曲线income distribution :收入分配income effect :收入效应income elasticity of demand :需求收入弹性increasing cost industry :成本递增产业increasing returns to scale :规模报酬递增inefficiency :缺乏效率index number :指数indifference :无差异indifference curve :无差异曲线indifference map :无差异族indifference relation :无差异关系indifference set :无差异集indirect approach :间接法individual analysis :个量分析individual demand curve :个人需求曲线individual demand function :个人需求函数induced variable :引致变量induction :归纳法industry :产业industry equilibrium :产业均衡industry supply curve :产业供给曲线inelastic :缺乏弹性的inferior goods :劣品inflection point :拐点information :信息information cost :信息成本initial condition :初始条件initial endowment :初始禀赋innovation :创新input :投入input—output :投入—产出institution :制度institutional economics :制度经济学insurance :保险intercept :截距interest :利息interest rate :利息率intermediate goods :中间产品internatization of externalities :外部性内部化invention :发明inverse demand function :逆需求函数investment :投资invisible hand :看不见的手isocost line :等成本线,isoprofit curve :等利润曲线isoquant curve :等产量曲线isoquant map :等产量族Kkinded—demand curve :弯折的需求曲线Llabour :劳动labour demand :劳动需求labour supply :劳动供给labour theory of value :劳动价值论labour unions :工会laissez faire :自由放任Lagrangian function :拉格朗日函数Lagrangian multiplier :拉格朗乘数,land :土地law :法则law of demand and supply :供需法law of diminishing marginal utility :边际效用递减法则law of diminishing marginal rate of substitution:边际替代率递减法则law of diminishing marginal rate of technical substitution :边际技术替代率law of increasing cost :成本递增法则law of one price :单一价格法则leader—follower model :领导者--跟随者模型least—cost combination of inputs :最低成本的投入组合leisure :闲暇Leontief production function :列昂节夫生产函数licenses :许可证linear demand function :线性需求函数linear homogeneity :线性齐次性linear homogeneous production function :线性齐次生产函数long run :长期long run average cost :长期平均成本long run equilibrium :长期均衡long run industry supply curve :长期产业供给曲线long run marginal cost :长期边际成本long run total cost :长期总成本Lorenz curve :洛伦兹曲线loss minimization :损失极小化1ump sum tax :一次性征税luxury :奢侈品Mmacroeconomics :宏观经济学marginal :边际的marginal benefit :边际收益marginal cost :边际成本marginal cost pricing :边际成本定价marginal cost of factor :边际要素成本marginal physical productivity :实际实物生产率marginal product :边际产量marginal product of capital :资本的边际产量marginal product of 1abour :劳动的边际产量marginal productivity :边际生产率marginal rate of substitution :边替代率marginal rate of transformation边际转换率marginal returns :边际回报marginal revenue :边际收益marginal revenue product :边际收益产品marginal revolution :边际革命marginal social benefit :社会边际收益marginal social cost :社会边际成本marginal utility :边际效用marginal value products :边际价值产品market :市场market clearance :市场结清,市场洗清market demand :市场需求market economy :市场经济market equilibrium :市场均衡market failure :市场失败market mechanism :市场机制market structure :市场结构market separation :市场分割market regulation :市场调节market share :市场份额markup pricing :加减定价法Marshallian demand function :马歇尔需求函数maximization :极大化microeconomics :微观经济学minimum wage :最低工资misallocation of resources :资源误置mixed economy :混合经济model :模型money :货币monopolistic competition :垄断竞争monopolistic exploitation :垄断剥削monopoly :垄断,卖方垄断monopoly equilibrium :垄断均衡monopoly pricing :垄断定价monopoly regulation :垄断调控monopoly rents :垄断租金monopsony :买方垄断NNash equilibrium :纳什均衡Natural monopoly :自然垄断Natural resources :自然资源Necessary condition :必要条件necessities :必需品net demand :净需求nonconvex preference :非凸性偏好nonconvexity :非凸性nonexclusion :非排斥性nonlinear pricing :非线性定价nonrivalry :非对抗性nonprice competition :非价格竞争nonsatiation :非饱和性non--zero—sum game :非零和对策normal goods :正常品normal profit :正常利润normative economics :规范经济学Oobjective function :目标函数oligopoly :寡头垄断oligopoly market :寡头市场oligopoly model :寡头模型opportunity cost :机会成本optimal choice :最佳选择optimal consumption bundle :消费束perfect elasticity :完全有弹性optimal resource allocation :最佳资源配置optimal scale :最佳规模optimal solution :最优解optimization :优化ordering of optimization(social) preference :(社会)偏好排序ordinal utility :序数效用ordinary goods :一般品output :产量、产出output elasticity :产出弹性output maximization 产出极大化Pparameter :参数Pareto criterion :帕累托标准Pareto efficiency :帕累托效率Pareto improvement :帕累托改进Pareto optimality :帕累托优化Pareto set :帕累托集partial derivative :偏导数partial equilibrium :局部均衡patent :专利pay off matrix :收益矩阵、支付矩阵perceived demand curve :感觉到的需求曲线perfect competition :完全竞争perfect complement :完全互补品perfect monopoly :完全垄断perfect price discrimination :完全价格歧视perfect substitution :完全替代品perfect inelasticity :完全无弹性perfectly elastic :完全有弹性perfectly inelastic :完全无弹性plant size :工厂规模point elasticity :点弹性post Hoc Fallacy :后此谬误prediction :预测preference :偏好preference relation :偏好关系present value :现值price :价格price adjustment model :价格调整模型price ceiling :最高限价price consumption curve :价格费曲线price control :价格管制price difference :价格差别price discrimination :价格歧视price elasticity of demand :需求价格弹性price elasticity of supply :供给价格弹性price floor :最低限价price maker :价格制定者price rigidity :价格刚性price seeker :价格搜求者price taker :价格接受者price tax :从价税private benefit :私人收益principal—agent issues :委托--代理问题private cost :私人成本private goods :私人用品private property :私人财产producer equilibrium :生产者均衡producer theory :生产者理论product :产品product transformation curve :产品转换曲线product differentiation :产品差异product group :产品集团production :生产production contract curve :生产契约曲线production efficiency :生产效率production function :生产函数production possibility curve :生产可能性曲线productivity :生产率productivity of capital :资本生产率productivity of labor :劳动生产率profit :利润profit function :利润函数profit maximization :利润极大化property rights :产权property rights economics :产权经济学proposition :定理proportional demand curve :成比例的需求曲线public benefits :公共收益public choice :公共选择public goods :公共商品pure competition :纯粹竞争rivalry :对抗性、竞争pure exchange :纯交换pure monopoly :纯粹垄断Qquantity—adjustment model :数量调整模型quantity tax :从量税quasi—rent :准租金Rrate of product transformation :产品转换率rationality :理性reaction function :反应函数regulation :调节,调控relative price 相对价格rent :租金rent control :规模报酬rent seeking :寻租rent seeking economics :寻租经济学resource :资源resource allocation :资源配置returns :报酬、回报returns to scale :规模报酬revealed preference :显示性偏好revenue :收益revenue curve :收益曲线revenue function :收益函数revenue maximization :收益极大化ridge line :脊线risk :风险Ssatiation :饱和,满足saving :储蓄scarcity :稀缺性law of scarcity :稀缺法则second—degree price discrimination :二级价格歧视second derivative :--阶导数second—order condition :二阶条件service :劳务set :集shadow prices :影子价格short—run :短期short—run cost curve :短期成本曲线short—run equilibrium :短期均衡short—run supply curve :短期供给曲线shut down decision :关闭决策shortage 短缺shut down point :关闭点single price monopoly :单一定价垄断slope :斜率social benefit :社会收益social cost :社会成本social indifference curve :社会无差异曲线social preference :社会偏好social security :社会保障social welfare function :社会福利函数socialism :社会主义solution :解space :空间stability :稳定性stable equilibrium :稳定的均衡Stackelberg model :斯塔克尔贝格模型static analysis :静态分析stock :存量stock market :股票市场strategy :策略subsidy :津贴substitutes :替代品substitution effect :替代效应substitution parameter :替代参数sufficient condition :充分条件supply :供给supply curve :供给曲线supply function :供给函数supply schedule :供给表Sweezy model :斯威齐模型symmetry :对称性symmetry of information :信息对称Ttangency :相切taste :兴致technical efficiency :技术效率technological constraints ;技术约束technological progress :技术进步technology :技术third—degree price discrimination :第**价格歧视total cost :总成本total effect :总效应total expenditure :总支出total fixed cost :总固定成本total product :总产量total revenue :总收益total utility :总效用total variable cost :总可变成本traditional economy :传统经济transitivity :传递性transaction cost :交易费用Uuncertainty :不确定性uniqueness :唯一性unit elasticity :单位弹性unstable equilibrium :不稳定均衡utility :效用utility function :效用函数utility index :效用指数utility maximization :效用极大化utility possibility curve :效用可能性曲线utility possibility frontier :效用可能性前沿Vvalue :价值value judge :价值判断value of marginal product :边际产量价值variable cost :可变成本variable input :可变投入variables :变量vector :向量visible hand :看得见的手vulgur economics :庸俗经济学Wwage :工资wage rate :工资率Walras general equilibrium :瓦尔拉斯总体均衡Walras's law :瓦尔拉斯法则Wants :需要Welfare criterion :福利标准Welfare economics :福利经学Welfare loss triangle :福利损失三角形welfare maximization :福利极大化Zzero cost :零成本zero elasticity :零弹性zero homogeneity :零阶齐次性zero economic profit :零利润。

[英语考试]考研笔译常用词汇_经济

[英语考试]考研笔译常用词汇_经济

accumulated earnings 积累收益a circular economy 循环经济a convenient method of payment 方便的付款方式an economic boom 经济兴旺an economic depression (slump, recession) 经济萎缩an economic takeoff 经济起飞anti-dumping measures 反倾销措施assets depreciation range 资产折旧幅度balance the two-way trade 保持双边贸易的平衡bonded/free trade area 保税区bonded warehouse 保税仓库bottleneck restrictions 瓶颈制约break regional blockades and trade monopolies 打破地区封锁和待业垄断capital market 资本市场cargo handling capacity 货物吞吐量commission/brokerage 佣金commodity economy 商品经济confessional/favorable terms 优惠条件cost and benefit analysis 成本收益分析cost-of-living index 生活费指数cross-border takeover 跨国并购currencydepreciation/appreciation 通货贬值/升值current account balance sheet 流动资产负债表current asset losses in suspense 待处理流动资产损失current debt ratio 流动负债比率current fund employment rate 流动资金占有率current liability 流动负债current tangible assets 有形流动资产domestic funds 国内配套资金earning capacity 盈利能力E-commerce/E-business 电子商务economic aggregate 经济总量economic efficiency 经济效益economic growth point 经济增长点economic indicators 经济指标economic measure 经济手段economic strength 经济实力economy of scale 规模经济efficiency in operation 经营效率emerging market economy 新兴市场经济equity capital transaction 产权资本转让equity earnings 参股收益;股本盈利equity investment 股本投资equity ownership 资本所有权excessive consumption 超前消费export-oriented/outward-looking economy 外向型经济是extensive/intensive operation 粗放/集约经营fair trading practice 公平贸易行为financing channels 融资渠道fixed-assets accounting 固定资产核算fluctuate in line with market conditions随行就市foreign exchange-earning enterprise 创汇型企业foreign exchange market 外汇市场foreign investment in actual use 实际利用外资general retail price index 社会零售物价总指数generous pension and healthcare plans 优厚的养老金和医疗卫生保障green power 财力;金钱gross foreign export value 外贸出口总额gross output value of industry and agriculture 工农业总产值guidance plan 指导性计划2-hour economic zone 两小时经济圈import/export quota 进出口配额in a period of transition 在过渡时期income tax return 所得税申报表income to net worth ratio 净值收益率industrial policy 产业政策industrialredeployment/relocation 产业转移inflation-proof bank savings 保值储蓄investment in fixed assets 固定资产投资investment portfolio 投资组合invisible trade 无形贸易ironclad job protection 铁饭碗knowledge economy 知识经济letters patent/certificate of patent 专利证书low-profit era 微利时代macro-economic control 宏观调控maintenance of value 保值majority shareholding 占有多数股权managerial decision-making process 管理决策程序managerial know-how 管理专门知识mandatory plan 指令性计划margins desired 期望的毛利market demand price 市场需求价格marketing channel 销售渠道,市场渠道market regulation 市场调节market value method 市价法medium-sized enterprise 中型企业merchandise inventory 商品库存mild inflation 温和通货膨胀negative growth 负增长non-core business 非主营业务non-performing loan 不良贷款outbound/overseas investment 海外投资petrol chemistry 石油化工property right market 产权市场public financing rate 财政purchasing power parity 购买力平价法qualitative analysis 定性分析quality guarantee 质量保证quantitative analysis 定量分析rate of return on equity 股本收益率risk investment/ venture capital 风险投资seller’s market 卖方市场social benefits/returns 社会效益start-up company 新兴企业state revenue 财政收入sub-prime crisis 次贷危机tax reduction and exemption 减免税收the globalization of capital 资本的全球化the Great Depression 经济大萧条The Internet of Things 物联网the law of demand/supply 需求/供应定律the linkage system between the US dollar and the HK dollar 港币的联系汇率制the primary/secondary/tertiary industry (the service sector) 第一/第二/第三产业the real economy 实体经济the sub-prime mortgage market 房产次贷抵押市场tighten the money supply 紧缩银根total volume of retail sales of consumer goods 社会消费品零售总额total volume of retail sales 社会商品零售总额trade barrier 贸易障碍trademark registration 商标注册Lower export demand and reduced foreign direct investment are more likely to hit urban jobs harder.出口需求下降和外国直接投资的减少,更有可能使城市就业形势更为严峻。

商务英语翻译第2章 翻译方法

商务英语翻译第2章 翻译方法

第二章翻译方法第一节增译法BrainstormingTranslate the following into Chinese1.After climbing a great hill, one only finds that there are many more to climb. 登上高山后,你会发现还有更多的山峰等着你去超越。

2.Money won’t create success, the freedom to make it will.创造成功,靠的不是金钱,而是拥有创造成功的自由。

3.Reading makes a full man; conference a ready man; writing an exact man.读书使人充实;讨论使人机智,写作使人缜密。

4.We won’t attack unless attacked.人不犯我,我不犯人。

5.She was more royal than the royals.她比皇家成员更有皇家气质。

Part V Practical trainingTranslate the following English sentences into Chinese1. The manager’s report summarized the achievement made in industry, agriculture and foreign trade.经理的报告总结了在工业、农业以及外贸三个方面取得的成就。

2. I’ve been to John’s company twice.我曾经去过约翰的公司两次。

3. A computer will help us a lot for the analysis job.如果我们用一台电脑来做这个分析,则会事半功倍。

4. Unless informed, we shall not make copies.除非贵方通知我们,否则我们不会制作副本。

经济学最全词典 中英对照

经济学最全词典 中英对照

经济学词典提供经济学词典.向他致敬!Ability-to-pay principle(of taxation)(税收的)支付能力原则按照纳税人支付能力确定纳税负担的原则。

纳税人支付能力依据其收人或财富来衡量。

这一原则并不说明某经济状况较好的人到底该比别人多负担多少。

Absolute advantage(in international trade)(国际贸易中的)绝对优势A国所具有的比B国能更加有效地(即单位投入的产出水平比较高等)生产某种商品的能力。

这种优势并不意味着A国必然能将该商品成功地出口到B国。

因为B国还可能有一种我们所说的比较优势或曰比较利益(comparative advantage)。

Accelerator principle 加速原理解释产出率变动同方向地引致投资需求变动的理论。

Actual,cyc1ical,and structual budget 实际预算、周期预算和结构预算实际预算的赤字或盈余指的是某年份实际记录的赤字或盈余。

实际预算可划分成结构预算和周期预算。

结构预算假定经济在潜在产出水平上运行,并据此测算该经济条件下的政府税入、支出和赤字等指标。

周期预算基于所预测的商业周期(及其经济波动)对预算的影响。

Adaptive expectations 适应性预期见预期(expectations)。

Adjustable peg 可调整钉住一种(固定)汇率制度。

在该制度下,各国货币对其他货币保持一种固定的或曰“钉住的”汇率。

当某些基本因素发生变动、原先汇率失去合理依据的时候,这种汇率便不时地趋于凋整。

在1944-1971年期间,世界各主要货币都普遍实行这种制度,称为“布雷顿森林体系”。

Administered(or inflexible)prices 管理(或非浮动)价格特指某类价格的术语。

按照有关规定,这类价格在某一段时间内、在若干种交易中能够维持不变。

(见价格浮动,price flexibility)Adverse selection 逆向选择一种市场不灵。

大学生实用行业英语1-3单元英语翻译

大学生实用行业英语1-3单元英语翻译

第一单元市场营销我们把市场营销看作是交易,把营销人员看成是管理交易的人。

从远古时期开始,人们一直在进行交易,以物易物,以物换服务,或以服务换服务。

市场营销或许是这样开始的:一个洞穴人发现自己有太多肉,但没有新鲜的蔬菜。

于是就和一个有蔬菜没有肉的人做交易。

一次简单的交易。

这么多肉换了这么多蔬菜。

这个洞穴人都很开心,因为两人都以自己的东西换得价值相等的东西。

随着时间的推移,越来越多的人住在一起,形成村落,交易变得更加复杂。

一个人以修屋顶来换取鸡和鸡蛋。

然后,他也许用部分的鸡蛋去换面包师傅的面包。

也有人可能帮人磨刀来交换让别人整修他的花园。

两人都是交换服务,而不是商品。

市场营销或许是这样开始的:一个洞穴人发现自己有太多肉,但没有新鲜的蔬菜。

于是就和一个有蔬菜没有肉的人做交易。

一次简单的交易。

这么多肉换了这么多蔬菜。

这两个洞穴人都很开心,因为两人都以自己的东西换得价值相等的东西。

随着时间的推移,越来越多的人住在一起,形成村落,交易变得更加复杂。

一个人以修屋顶来换取鸡和鸡蛋。

然后,他也许用部分的鸡蛋去换面包师傅的面包。

也有人可能帮人磨刀来交换让别人整修他的花园。

两人都是交换服务,而不是商品。

欲望是人类的需要所采取的文化和个性的形式。

食物是一个人的需要,而他的欲望是得到一个大汉堡。

得到购买力的支持时,欲望成为需求。

那些最棒的营销公司会下大工夫去了解顾客的需要、欲望和需求。

市场供给——产品、服务和体验市场提供产品、服务、信息、体验的组合体来满足人们的需要和欲望。

市场供给包括产品和服务。

服务——所销售的是一种无形的活动或利益,且不会导致所有权的变化。

营销短视症是指公司过度重视自己的产品,而忽视潜在的顾客需要。

顾客价值和满意度各种市场供给形成顾客价值和满意度,顾客据此来判断是否购买。

满意的顾客会再次购买,并告诉别人他们的好经验。

不满意的顾客转投竞争对手,向他人贬低该产品。

顾客价值和顾客满意度是开发和管理顾客关系的关键组成部分。

经济决策第一章终极翻译

经济决策第一章终极翻译

第一章:经济决策定量方法简介在过去的30年里,管理决策领域发生了巨大的变化,这一巨大变化的出现主要是由于定量方法和计算机的普遍应用。

能利用这些定量方法解决的经济问题越来越多,在企业的各个职能领域都能发现成功应用定量方法的案例,这些职能领域可以从营销到生产、财务和人力资源。

这里的企业可以覆盖全部重要的产业。

定量方法确实可以普遍地应用于管理决策之中。

无论个人或集团,在教育、专业技术领域及各种组织中都有着广泛的应用。

这里的组织也包括政府和非营利性机构。

历史上一些经典的案例将展示定量方法在解决各种实际问题时是多么的有用。

二十世纪五十年代后期,美国海军面临着用北极星弹道导弹武装其核潜艇部队的巨大任务。

一种被称为PERT(计划评审技术)的定量方法被用于制定作业计划,并且用来协调和控制成千上万个承包商的整体效果。

银行经常使用定量分析来决定在一个星期里的不同时间内需要多少前台服务员,所以能够平衡员工的工作负荷,同时客户可以在可容忍的时间里排队。

一个国际石油公司投资数亿美元在波斯弯建设一个港口以服务于油轮。

设计多个方案并对这些方案进行多年的模拟,以确定各个方案未来利润的估计值。

通过计算机模拟,选择在一个可接受的风险水平下,能够提供最大投资汇报率的方案作为决策方案。

在国际通信领域,卫星扮演着日益重要的角色。

1971年,RCA公司决定进入通信卫星领域的私人市场。

可以在许多不同领域得以应用的各种定量方法被用来评价各个备选方案,以推荐最优策略。

本书主要关注的是只能适应所描述环境或相似环境的特定技术。

这些定量方法可以大体上归类于管理科学,管理科学是商业学、经济学、统计学、数学和一些其他学科相互融合的产物,它所形成的符合实际的结果能够帮助管理者进行决策。

作为一个研究领域,这些定量方法经常被称为运筹学。

无论把它称为什么,其实管理科学和运筹学都是利用数学知识解决最优方案的选择问题。

许多情形都能构造数学模型,因此各个备选方案可以按照某一数量尺度进行排序。

外文翻译--电力负荷预测方法:决策工具

外文翻译--电力负荷预测方法:决策工具

附录3Electric load forecasting methods: Tools for decisionmakingHeiko Hahn, Silja Meyer-Nieberg *, Stefan PicklFakult für Informatik, Universitat der Bundeswehr, 85577 Neubiberg, Germany AbstractFor decision makers in the electricity sector, the decision process is complex with several different levelsthat have to be taken into consideration. These comprise for instance the planning of facilities and anoptimal day-to-day operation of the power plant. These decisions address widely differenttime-horizonsand aspects of the system. For accomplishing these tasks load forecasts are very important. Therefore,finding an appropriate approach and model is at core of the decision process. Due to the deregulationof energy markets, load forecasting has gained even more importance. In this article, we give an overviewover the various models and methods used to predict future load demands.2009 Elsevier B.V. All rights reserved.1. Load forecasts in deregulated marketsDecision making in the energy sector has to be based on accurateforecasts of the load demand. Therefore, load forecasts areimportant tools in the energy sector. Forecasts of different timehorizonsand different accuracy are needed for the operation ofplants and of the complex power syste m itself: The ‘‘system responsefollows closely the load requirement” (Kyriakides and Polycarpou, 2007, p. 392). The decision maker is faced with a multitudeof decision problems on different time-scales as well as on differenthierarchies of the power system: These problems comprisefor instance the determination of an optimal secure scheduling ofunit commitment and energy allocation. But decisions do not havemade only with respect to the day-to-day operation of the powersystem but also with respect to investment decisions on new facilitiesbased on the anticipation of future energy demands. For bothends, reliable forecasts are needed. The deregulation of energymarkets has increased the need for accurate forecasts even more(see e.g. Feinberg and Genethliou, 2005; Kyriakides and Polycarpou,2007). To participate in the market, a player needs an accurateestimate howmuch energy is needed at a certain time. On theone hand, an underestimation of the energy demand by a suppliermay lead to high operational costs because the additional demandhas to be met by procuring energy in the market. An overestimationon the other hand wastes scarce resources (see e.g. Tzafestasand Tzafestas, 2001; Feinberg and Genethliou, 2005; Kyriakidesand Polycarpou, 2007). Furthermore, demand is one of the mainfactors for pricing. LoadDue to the highimportance of accurate load forecasting, the history of this fieldis quite long: A 1987 survey paper (Gross and Galiana, 1987) listsan impressive number of publications devoted to load analysisand forecasting – reaching back as far as 1966 (Heinemann et al.,1966). Up to now, various approaches have been introduced. Theycan be grouped into two main classes: Models and methods whichfollow a more classical approach, i.e., which apply concepts stemmingfrom time series and regression analysis and methods whichbelong to the fields of Artificial and Computational Intelligence.This paper gives a short survey over models and methods forload forecasting. Further survey and review papers are for exampleKyriakides and Polycarpou (2007), Feinberg and Genethliou (2005),Tzafestas and Tzafestas (2001) and Hippert et al. (2001).2. Short-term, medium-term and long-term forecastsAs we have seen, forecasts are made for various purposes: theday-to-day operation of the power system (e.g. Kyriakides andPolycarpou, 2007) requires the prediction of the load for a dayahead whereas the decision whether to undertake major structuralinvestments requires a far longer prediction horizon. Forecasts canbe distinguished therefore firstly by the time-horizon or the leadtime: short-term load forecasts (STLF) usually aim to predict theload up to one-week ahead (Kyriakides and Polycarpou, 2007).Frequently, the term very short-term load forecast is used forforecasts with a time-horizon of less than 24 hours (see Yang,2006, p. 7). Up to now, the main focus in load forecasting has beenon STLF since it is an important tool in the day-to-day operation ofutility systems (see e.g. Gonzalez-Romera et al., 2006). Morerecently with the deregulation of energy markets, more and moreattention is also paid to load forecasts with a greater time-horizon,i.e., medium-term load forecasts. As stated in (Gonzalez-Romeraet al., 2006), medium-term load forecasts enables companies toestimate the load demand for a longer time interval which helpsthem for example in the negotiation of contracts with other companies.Medium-term load forecasts (MTLF) are from one weekto one year. Forecasts aiming at load prediction for more than ayear ahead are usually termed long-term load forecasts (LTLF)(see e.g. Feinberg and Genethliou, 2005). As stated in Kyriakidesand Polycarpou (2007) the time-horizon in LTLF is usually 20 yearsalthough longer lead times of 25–30 years can be found. The differencesin lead times have consequences for the models and methodsapplied and for the input data available and selected. The load demandis influenced by numerous factors – ranging from weatherconditions over seasonal effects to socio-economic factors. Whichinput data has to be selected usually depends on the task and dataat hand. The decision maker, therefore, is not only faced with thetask of selecting an appropriate model type but also with determiningimportant external factors. Both tasks usually depend oneach other. Some general observations can be made, however.conditions whether weather-dependent factors havea significant influence on the prediction. There is a common agreementthat the air temperature is the most important weather influence(see e.g. Hippert et al., 2001; Feinberg and Genethliou, 2005).This was already recognized in the 1930s (Hippert et al., 2001).Generally, the demand is high on cold days which can be attributedto electric heating. Similarly on hot days, the increased usage ofair-conditioning generates a higher demand of energy. In manycountries, this results in aU-shaped and clearly non-linear responsefunction of the load towards the temperature (Hippertet al., 2001). However, the exact shape of the curve depends onthe region, the climatic conditions and of course on the consumers’behavior. Additionally, the designated time-horizon and the availabilityof the datadetermine the input variables. As mentioned in (Tayloret al., 2006) univariate models are standard for very short-termload forecasts for up to 6 hours ahead. Furthermore, it should benoted that sometimes obtaining accurate weather forecasts maybe difficult. Therefore, univariate models are also applied for longerlead times (Taylor et al., 2006; Soares and Souza, 2006).In Kyriakides and Polycarpou (2007) three main groups of inputdata forshort-term load forecasts are identified: seasonal inputvariables, weather forecast variables, and historical load data(Kyriakides and Polycarpou, 2007). Short-term load forecasts usuallyaim at providing the daily, hourly, or half-hourly load and thepeak load (day, week) (see e.g. Tzafestas and Tzafestas, 2001)although even smaller time intervals occur. Forecasting the loadprofile, i.e., the load of the next 24 hours, is also a main target(Tzafestas and Tzafestas, 2001; Hippert et al., 2001).Medium-term load forecasts usually incorporate several additionalinfluences - especially demographic and economic factors.These forecasts often provide the daily peak and average load,although hourly loads are also sometimes given, e.g. Bruhns et al.(2005). In the case of long-term load forecasts, even more indicatorsfor the demographic and economic development have to be takeninto account (Kyriakides and Polycarpou, 2007). These are forinstance thepopulation growth and the gross domestic product.Long-term load forecasting usually aims at predicting the annualload and the peak load (Kyriakides and Polycarpou, 2007).The time series of the loads itself has generally three seasonalcycles: anintra-daily cycle (the daily load curve or the load profile),a weekly cycle, and a yearly seasonal cycle. The weekly cycle usuallyshows two main groups:week-days and weekends. Due toindustrial demand, the load tends to be higher during week-days.The weekend tends to influence the neighboring days so that Mondaysand Fridays are often treated separately. Saturday is also often found to show a different load profile than Sunday. However, theexact weekly pattern depends on the particular region under considerationand furthermore on the season (Hippert et al., 2001).Additionally ‘‘regular” exceptional cases can beTheseexceptional days depend on the calendar date which is also commonlyconsidered as a very important information. Several approaches,however, neglect these exceptional cases (e.g. Hippertet al., 2005; Taylor and McSharry, in press). One of the reasonsfor this is that there are typically only few data available whichcould be used to estimate the model parameters for these day -types. Concerning the seasonal data patterns, different approaches arefollowed.Generally, local and global approaches can be distinguished.Local approaches apply distinct models for each identifiedfeature: for instance a model for each distinct day-type or a hour.However, this may lead towards problems if the data basis is notsufficiently large (Hippert et al., 2001). Therefore, in severalapproachesa single monolithic model is build and the informationis encoded in the input data.3. Models and methodsThis section gives an overview over various approaches for loadforecasting. Many of them are developed for STLF although MTLFhas gained importance which is especially due to the deregulationof electricity markets. The dominance of STLF-methods is also reflectedin the survey papers (Hippert et al.,2001;Tzafestas andTzafestas, 2001; Feinberg and Genethliou, 2005; Kyriakides andPolycarpou, 2007). Only Feinberg and Genethliou (2005) includedan overview over MTLF and LTLF-methods whereas the remaindersfocused on short-term load forecasts. Our own non-exhaustive surveyof over 100 papers shows a similar composition.There are various approaches applied to load forecasting(Kyriakides andPolycarpou, 2007; Feinberg and Genethliou,2005; Taylor and McSharry, in press; Hippert et al., 2001; Tzafestasand Tzafestas, 2001). These range fromregression-based approachesover time-series approaches towards artificial neural networksand expert systems. In the following, a short overview oversome of the models and methods is given. The error measure mostfrequently used to assess the performance of a model – at least inthe literature found – is the mean absolute percentage error(MAPE) defined by 1100Tt t t MAPE y y T ==-∑with t y the real value atpoint t and ty the forecast. 3.1. Classical time series and regression methodsStatistical approaches require an explicit mathematical modelwhich gives the relationship between load and several input factors.Several classical models are applied for load forecasting, forexample regression-based methods, time series methods, statespace models and Kalman-filtering. In the following, we focus on regression-based and time series models.3.1.1. Regression-based modelsRegression models are quite common in load forecasting(Kyriakides andexternal factors, for instanceweather and calendar information or customer types (Feinbergand Genethliou, 2005). Mainly, linear regression is used – theinfluence of the temperature is usually modeled non-linearly,however.Regression methods are relatively easy to implement.A further advantage is that the relationship between input andoutput variables is easy to comprehend. Regression models alsoallow relatively easy performance assessments (see e.g. Bruhnset al., 2005). As reported in Kyriakides and Polycarpou (2007),there may be inherentproblems in identifying the correct model,though, which are due to the complex non-linear relationship betweenthe load and the influencing factors. Further drawbacks arereported in Kyriakides and Polycarpou (2007). In thefollowing,two examples are presented. Many more approaches appear inthe literature – for example regression models based on localpolynomial regression for STLF (Zivanovic, 2001), non-parametricregression (Charytoniuk et al.,1998), or robust regression methods(Jin et al., 2004). A description of furtherregression-based approachescan be found in Kyriakides and Polycarpou (2007) andFeinberg and Genethliou (2005).Hor et al. developed a multiple regression model and analyzedthe impact of weather variables on the load demand for Englandand Wales (Hor et al., 2005). They used data from 1989 to 1995for model training and from 1996 to 2003 for testing the accuracy.Their aim was to provide an accurate model for a long-term predictionof the monthly demand. The regression model was basedon two types of input variables: weather-dependent factors, i.e.,temperature, wind speed W V , rainfall r M , relative humidity Hr ,and hours of sunshine Ms andsocio-economic factors, i.e., theGross Domestic Product. Further socio-economic factors, for instancethe population growth, were eliminated. First of all, theyanalyzed the relationship between load and temperature andfound anon-linear dependence. In order to cope with this non-linearityseveral derived variables: heating degree days (HDD), coolingdegree days (CDD), and enthalpy latent days (ELD) wereintroduced. The last variable takes the influence of humidity onair-conditioning into account. Three linear regression modelswere finally proposed: model 1 includes the CDD, HDD, and theELD0123456.A w s rE CDD HDD ELD V M M ααααααα=++++++(1) Model 2 substitutes these values with the raw temperature and relativehumidity while model 3 differs by model 1 only by a substitutionof the ELD with therelative humidity. All models were thenadjusted to take socio-economic factors into account. Model 1 and3 were found to perform best with mean absolute percentage errors(MAPE) of 1.98% and 2.1% – although model 2 is alsorelatively goodwith a MAPE of 2.69%.Bruhns et al. (2005) presenteda non-linear regression model forMTLF. Their model is devoted to an hourly prediction of the load.The load was decomposed into a weather-dependent i Phc andweather-independent part i Pc ,i i i i i Gaussian (Bruhnset al., 2005). The weather-independent part coverestrends,seasonalbehavior, and calendar effects. The weather-dependent partis assumed to be mainly influenced by the temperature and thecloud cover. The relationship between temperature and load is fittedby a non-linear model differentiatingbetween a heating part(temperature above a certain threshold) and a cooling part (temperaturebelow a certain threshold) of the weather sensitive partof the load. The temperature does not enter the equations directly.First of all, it is exponentially smoothed to reflect the inertia tovariations inbuildings (Bruhns et al., 2005). Afterwards, it is averagedagain with the observed temperature and – in the case of theheating part – with the cloud cover. Thisreflects the assumptionthat there is a mixed response to the temperature observed andto the temperature felt inside buildings (Bruhns et al., 2005). Thisaggregated temperature then enters the threshold function.Fortheweather-independent part of the load a product of two Fourierseries was used. The first depended on the hour, the second on theday-type. The authors do not report the MAPE but the scale-dependentrootmean squared error (RMSE). However, they note that thepredecessor of their model which applied one Fourier seriesdepending on the hour already achieved a MAPE of 2% for yearahead forecasts (known weather) and 1.5% for day ahead forecasts(Bruhns et al., 2005).3.1.2. Time-series approachesTime-series approaches (Box and Jenkins, 1970) are among theoldest methods applied in load forecasting. They can be distinguishedon several levels. First of all, there are univariate (Tayloret al., 2006; Taylor and McSharry, in press ) and multivariatemethods. The former are usually used for very short-termloadforecasts whereas the latter are applied for all time-horizons.The time series is usually assumed to be linear. It should be noted,though, that the assumption of linearity usually does not comprisethe influence of the temperature. In this case, there appearsto be an unanimous agreement that the non-linearity of thisrelationshiphas to be preserved in the model (Moral-Carcedo andVicens-Otero, 2005). Several authors apply non-linear models(Hor et al., 2006).A very simple class is the so-called autoregressive movingaverage or ARMA models(Brockwell and Davis, 1991). In short, astationary process ()0t t X ≥is called anARMA(p,q)-process if 11p qt k t k t m t q k m X X Z Z φθ--==-=+∑∑ (2)holds. The process ()t Z must be white noise with zero mean andconstantstandarddeviation σThe main steps consist of determiningthe order p of theautoregressive (AR)-part and q of the movingaverage (MA)-part and ofestimating the coefficients (Brockwell andDavis, 1991). Common approaches for the estimation of the coefficientsuse Maximum-Likelihood or variants of leastnoise. However, in Huang and Shih (2003) an ARMA-modeling procedurefor STLF was presented which also allows for non-Gaussiannoise. In the following, let B denote the lag or backshift operator, i.e.,1.t t BX X -=Setting ()11p k k k B B φ-Φ=-∑ and ()11q m m m B B θ-Θ=+∑,(2) can bewritten shortly as ()()t t B X B Z Φ=Θ.In Huang et al. (2005) an ARMAX-model ()()()()t t B L t B Z B U Φ=Θ+ψ with ()1km m m B B ψ=ψ=∑and exogenous variable t U forone-day and one-week ahead hourly load forecasts for four exampleseasons in 1998 was presented. Theexogenous variable in thecase denoted the temperature. Instead of the classical algorithmsto determine the model and to estimate the coefficients, particleswarm optimization (PSO) (Eberhart and Kennedy, 1995) was appliedto determine both the order of the model and the coefficients.Particle swarm optimization is a so-called swarm-based optimizationmethod and belongs to the class ofComputational Intelligence(CI) methods.The ARMA-model can be extended to so-called autoregressiveintegrated moving average (ARIMA) models. This model types usesdifferencing in order to cope with non-stationarity. An ARIMA(p,d,q)-model is thus()()()1d t t B B X B Z Φ-=Θ. The parameterd is required to be an integer. Themodels above are univariate linearmodels most often used for short-term load forecasts. As mentionedin Taylor et al. (2006), univariate ARIMA-models are oftenused as sophisticated benchmark models in STLF.Amjady used a modified ARIMA-model to predict the hourlyload demand and the daily peak loads in STFL (Amjady, 2001).His modified ARIMA-models takes not only past loads but alsoestimates of past loads into account. The estimates were providedby experienced human experts. Thus, in a sense the modelincorporates human knowledge. First of all, Amjady identifiedfourdifferent day-types in the load data of the Iranian nationalgrid: Saturday, Sunday to Wednesday, Thursday and Friday andpublic holidays. These models were separated again into modelsfor hot days (average temperature above 23 degrees) and colddays. In total, 16 models were used. The parameters wereestimatedusing data from 1996 to 1997 from the Iranian nationalgrid and tested on data for 1998. The MAPE of the models rangedfrom 1.48% (Sunday to Wednesday, hot) to 1.99% (public holidays,cold).The ARIMA/ARMA-models can be extended to take seasonalityinto account. Several models have been developed for this task.For example, in Espinoza et al. (2005) a periodic autoregressivemodel (PAR) was used of order p,11,,t s s t s p t p s t y C y y φφε--=++++ (3)(see Espinoza et al., 2005) to represent the periodic dynamics of theseries. The parameters are allowed to vary across the NS seasons. In Espinoza et al. (2005) aload curves whereas the monthlyand weekly seasonality was coveredbyintroducing dummyvariables.Taylor et al. (2006) and Taylor and McSharry (in press) presentedacomparison of several univariate methods for short-termload forecasting. They analyzed four main models and two benchmarkfunctions. The models chosen were double seasonal ARIMA(with-in day and with-in week cycle), exponential smoothing fordouble seasonality, artificial neural network, and a regressionmethod with principal component analysis (PCA) (Taylor et al.,2006). The exponential smoothing method adapted by the authorsis an extension of the classical seasonal Holt-Winter smoothingmethod to incorporate two seasonal cycles()()12111t t t t t s t S y S S T D W αα----=+-+ (4) ()()111t t t t T S S T γγ--=-+- (5)()121t t t s t t s y D D S W δδ--=+- (6) ()211t t t s t t s y W w W S D ω--=+- (7) ()()()()()121121t t k t t t t s k t s s t t s t s y k S kT D W y S T D W φ--+-+---=++-+ (8)(see Taylor et al., 2006). The variables t s and t T denote thesmoothed level and trend;t D and tW are seasonal indices (intradayand intra-week) and ()t y k is the forecast at t k +from the startingpoint t (Taylor et al., 2006). The greek parameters (except φ) arethe smoothing parameters to be determined. The parameter φ is anadjustment for first-order autocorrelation.The comparison was based on two time series: the hourly demandfor Rio de Janeiro in 1996 (30 weeks, 5th May 1996–30th November 1996) and thehalf-hourly demand for England andWales in 2000 (30 weeks, 27th March –22nd October). Several errormeasures were considered, however, only the MAPE was reportedsince the other error measures lead to similar results.The exponential smoothing method emerged as the bestapproach.In Taylor and McSharry (in press) the study was extended toan evaluation of six univariate methods based on the electricitydemand of ten European countries. Again, the double seasonalexponential smoothing method was found to lead to the best results – with a MAPE below 2% even for the longest lead time of24 hours. As it can be seen, time series based approaches are verycommon. However, several drawbacks are reported. As regression-based approachestime-series approaches may suffer fromnumerical instabilities (Huang and Shih,3.2. Artificial intelligence and computational intelligence methodsComputational intelligence is a relatively new research field.The expression computational intelligence is commonly used to referto the fields of fuzzysystems, artificial neural networks (ANN),evolutionary computation, and swarm intelligence. Of these fields,neural networks are the subtype which is most often applied inload forecasting.3.2.1. Neural networksNeural networks are modeled after the basic working principleof human brains. They consist of several neurons. A neuron receivesinformation over its inputnodes and aggregates the information.Afterwards, it determines its activation and propagatesits response over the output node to other neurons. Neuralnetworksare very frequently applied for load forecasting (see e.g.Hippertet al. (2001) for a survey). As stated in Hippert et al. (2005), in1998 a software based on neural networks technology was used byover 30 US electric utilities. Several subtypes of neural networksexist (see e.g. Bishop, 1995). In load forecasting, for example, radialbasis function networks (Ranaweera et al., 1995;Gonzalez-Romeraet al., 2006), self-organizing maps (Becalli et al., 2004) for clusteringand recurrent neural networks (Senjyu et al., 2004; Tran et al.,2006) are used. However, feed-forward neural networks (or multilayerperceptron) are the subtype which is most often applied(Hippert et al., 2001, 2005;Gonzalez-Romera et al., 2006; Becalliet al., 2004; Ringwood et al., 2001). A feed-forward network consistsof several successive layers of neurons with one input layer,several hidden layers, and an output layer. The neuronsareconnectedusing weight vectors and neither feedback norinterlayerconnectionsexist. A neuron i thus takes the output of its kinputneurons, computes theweighted sum, subtracts a so-calledbias hi and applies the activation function a (), i.e.,()1ni ik k i k y a w x θ==-∑.The basic learning or weight-adjustingprocedureis back-propagation (a form of steepest descent) which propagatesthe error backwards and adjusts the weightsaccordingly(Bishop, 1995). Frequently, only one hidden layer is used (seeforinstance Becalli et al. (2004), Fidalgo et al. (2007) and Hippertet al. (2005)). Hippert et al. (2005) provided a comparisonof large neural networks (neural networks with a large numberof neurons and weights) with several classical approaches. Theclassical approaches ranged from naive forecasting methods oversmoothing filters and combination of smoothing filters with linearregression. Furthermore, hybrids of smoothing filters andneural networks were considered. The task was to forecast the24 hours load profile based on data from a local utility inRio de Janeiro. Used for building, testing, and validating the forecastmodel were the hourly loads and thetemperature from April1996 to December 1997. Hippert et al. (2005) found large neuralnetworks to perform best – not only with the smallest MAPE(2.35–2.65%) but also with acan be seen as competitivewith other models as far as the forecasting of load profiles isconcerned.4. ConclusionsLoad forecasting is very important for decision processes in theelectricity sector. In this paper, we have given an overview overcommonly used input variables and forecast targets. Afterwards,we presented several classes of models and methods. Several recenttrends can be identified: Support vector regression hasemerged as a relatively new and competitive method for load forecasting.Furthermore, more and more attention is focused on hybridapproaches.Load forecasting is not only important to provide accurate estimatesfor the operating of the power system but also as a basis forenergy transactions and decision making in energy markets. Theaccuracy of forecasts is a very crucial factor: A decision maker inthe energy sector has the need of accurate forecasts since mostof the decisions are necessarily based on forecasts of future demands.One of the first decisions to be made is therefore the selectionof an appropriate model. This depends on the problem and thesituation currently under consideration. Therefore, no general recommendationscan be given.AcknowledgementThe authors wish to thank especially the anonymous reviewer #1 for hishelpful comments附录4电力负荷预测方法:决策工具摘要对于电力部门的决策者来说,决策过程是复杂的,必须考虑不同的标准。

第3章-需求预测

第3章-需求预测
第二轮:把第一轮收到的意见进行综合整理, “反馈”给每个专家,要求他们澄清自己的观点, 提出更加明确的意见,要求专家回答。
第三轮:把第二轮收到的意见进行整理,“再反 馈”给每个专家。
德尔菲预测示意图
预测问题 意见反馈(1、2、……n)
预测组 织者
信息资料
专家们
反馈(1)
整理(1)
反馈(2) 整理(2)
• 德尔菲是古希腊的地名。相传希腊神在此降伏妖龙, 后人用德尔菲比喻神的高超预见能力。后来的不少 预言家,都曾先后在此发表演说,提出种种预言。 从此德尔菲就成为专家提出语言的名词。
Delphi 法
第一轮:把调查表发给各个专家,要求他们对调 查表中提出的问题一一做出回答。在规定时间内 专家意见收回。
• 销售人员意见综合法首先由企业领导根据经营的 需要,向全部销售人员介绍预测的市场形势,提 供有关资料确定预测期限;然后销售人员根据企 业要求提出各自的预测方案;最后进行综合分析 判断,确定企业的销售预测值。
• 销售人员意见综合法对短期市场预测效果较好。
• 实例分析
销售 员
销售预测值(百万元)
一事悲 乐观 事件 般 件 观 预测 概率 预 概 预
n
xi
x
x n1 t1
n
n+1期的的预测值
t 1 234
② 适用范围:短期的水平型数据模式。
注:当各期增长量基本相同时,也可借用(若线性, 增长率呈现水平变动规律)。
2、加权平均
▪依据:不同时期的历史数据对未来的影响是不同的。
▪特点:此法对上述事实有一个合理的处理。
x ① 预测模型:
n 1 xi wi wi
3.1.1 预测及其作用(续)
• 预测的作用

forecast用法 -回复

forecast用法 -回复

forecast用法-回复‘’forecast用法‘’预测是人们理解和处理不确定性的一种常见方法。

无论是在经济学、气象学、金融领域还是其他各种领域,预测都起到了非常重要的作用。

在本文中,我们将深入探讨“预测”一词的用法,并解释其在不同领域中的应用。

首先,让我们来定义什么是预测。

预测指的是对未来事件或情况的可能结果进行推测。

这可以通过对现有数据和趋势的分析、数学模型的建立以及专家对话的方式来实现。

预测通常具有一定的不确定性,因为未来是无法精确预测的,但是通过使用可用的信息和分析方法,我们可以增加对未来事件的了解。

在经济学领域,预测扮演着至关重要的角色。

政府、企业和个人都需要根据未来的经济趋势做出决策。

中央银行可以利用通货膨胀率、国内生产总值(GDP)和就业率等因素来预测经济的未来发展。

企业可以通过预测市场需求和销售趋势来制定生产计划和销售策略。

个人也可以通过对未来经济状况的预测来做出投资决策,例如购买股票、房产或其他投资工具。

在气象学领域,预测对于准确预报天气状况至关重要。

气象学家使用大气数据、卫星图像和气象模型等信息来预测未来几天或几周的天气状况。

这对于农民来说尤其重要,因为他们需要根据天气预测来计划农作物的种植和收获时间。

此外,天气预报还对航空和航海等行业的安全也具有重要意义。

金融领域是另一个需要预测的重要领域。

股票市场、货币市场和商品市场等金融市场的价格波动不仅影响企业和投资者的利润,还对整个经济产生重大影响。

分析师使用各种技术指标和基本分析来预测未来市场走势。

投资者可以根据这些预测来制定投资策略,以获得更好的回报。

此外,预测在科学领域中也有着重要的应用。

疾病的传播、环境变化和人口增长等问题都需要预测来制定解决方案。

科学家使用数学模型、实验数据和统计分析来预测未来的趋势和结果。

这些预测对于政府官员和决策者来说都是重要的参考,可以帮助他们采取正确的行动。

最后,预测也在日常生活中发挥着作用。

我们经常使用天气预报来选择适当的衣物和活动。

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经济决策定量第二章Forecasting部分翻译
Forecasting the future is a fundamental aspect of business decision making.Future sale is the most important variable in business forecasts.Knowledge about sales is a prerequisite to the budgetary and planning process.
预测未来是企业制定决策的一个基本方面。

未来的销售是在业务预测中最重要的变量。

有关销售知识是预算和规划过程的一个先决条件。

1.Forecasting using past data
The historical patterns of a variable are identified and projected into the future.These patterns are abtained through extrapolation from time series data.
1.用过去的数据预测
一个变量的历史模式可以用来识别和预测未来。

这些模式是通过外推法从时间序列数据。

2-Forecasting using causal models
A relationship is found between the unknown variable and one or more other known variables. The values of the known variables are then used to predict the value of the variable of interest.
2.用因果模型预测
可以从未知的变量与一个或多个已知的变量发现数值关系。

使用已知变量的值然后用于预测的所需的变量值。

3.Forecasting using judgment
Quantitative representations are used to express judgments in terms of subjective probabilities. These methods can incorporate the forecaster’s actual “batting average”and may provide a way to express collective judements.
In this chapter,we will survey the forecasting methods commonly used in each of these three categories.
3.主观判断来预测
定量表示法用来表达主观概率判断。

这些方法可以纳入预测者的实际平均成功率,而且可能会提供一个表达集体决策的方法。

在这一章,我们将研究以上三个模型中常用的预测方法。

A time series is a numerical sequence in which individual values are generated at regular intervals of time. The goal of time series analysis is to identify the swings and fluctuations of a time series and then to sort them into various categories by the arithmetic manipulation of the numerical values abtained.
时间序列是其中的单个值产生规律的间隔时间的数值序列。

时间序列分析的目标是找出波动和波动的时间序列,然后把它们划分为各种类别由数值导出的算术操作。

Several models can be used to characterize time series.The classical model used by economists provides the clearest explanation of the four components of time series variation, which are secular trend,cyclical movement,seasonal fluctuation,and irregular variation.These components can be related to the forecast variable by mathematical equations.The forecast variable is denoted b the symbol Y t , where the subscript t refers to a period of time.
几种模型可以用于时间序列的特点。

经济学家们所使用的经典模型提供了清晰的解释的四个组成部分的时间系列变异,即长期趋势、周期性运动、季节性波动和不规则变化。

这些组件可以与有关的预测变量的数学方程。

预测的变量用公式Yt表示,下标t 在这里指的是一段时间。

The classical time series model originally used by economics combines the four components of time series variation,
Yt=Tt * Ct *St * It
经济学家最初所用的典型时间序列模型包括以下四个部分。

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