Monthly Review on Price Indices

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金融词汇缩写

CPI Consumer Price IndexPPI Producer Price IndexJVC joint venture company 合资公司K. D. knocked down 拆散K. D. knocked down price 成交价格L. B. letter book 书信备查簿LB licensed bank 许可银行L.& D. loans and discounts 放款及贴现Li. liability 负债LI letter of interest (intent) 意向书lifo (LIFO) last in, first out 后进先出法L. I. P. (LIP) life insurance policy 人寿保险单LIRCs low interest rate currencies 低利率货币L/M list of materials 材料清单LMT local mean time 当地标准时间LRP limited recourse project 有限追索工程LRPF limited recourse project financing 有限追索工程融资i. s. lump sum 一次付款总额i. s. t. local standard time 当地标准时间LT long term 长期Ltd. limited 有限〔公司〕m million 百万M matured bond 到期的债券M&A merger & acquisition 兼并收购MA my account 本人帐户Mat. maturity 到期日Max., max maximum 最大量M. B. memorandum book 备忘录MBB mortgage-backed bonds 抵押支持的债券MBO management by objectives 目标管理M/C marginal credit 信贷限额m/c metallic currency 金属货币MCA mutual currency account 共同货币帐户MCP mixed credit program 混合信贷方案M/d months after deposit 出票后......月M. D. maturity date 到期日M. D. (M/D) memorandum of deposit 存款(放〕单M. D. malicious damage 恶意损坏mdse. merchandise 商品MEI marginal efficiency of investment 投资的边际效率mem. memorandum 备忘录MERM multilateral exchange rate model 多边汇率模型M. F. mutual funds 共同基金MF mezzanine financing 过渡融资mfg. manufacturing 制造的MFN most favoured nations 最惠国mfrs. manufacturers 制造商mg milligram 毫克M/I marine insurance 海险micro one millionth part 百万分之一min minimum 最低值、最小量MIP monthly investment plan 月度投资方案mks. marks 商标mkt. market 市场MLR minimum lending rate 最低贷款利率MLTG medium-and-long-term guarantee 中长期担保M. M. money market 货币市场MMDA money market deposit account 货币市场存款帐户MMI major market index 主要市场指数MNC multinational corporation 跨〔多〕国公司MNE multinational enterprise 跨国公司MO (M. O.) money order 汇票MOS management operating system 经营管理制度Mos. months 月MP market price 市价M/P months after payment 付款后......月MPC marginal propensity to consume 边际消费倾向Mrge.(mtg. ) mortgage 抵押MRJ materials requisition journal 领料日记帐MRO maintenance, repair and operation 维护、修理及操作MRP manufacturer's recommended price 厂商推荐价格MRP material requirement planning 原料需求方案MRP monthly report of progress 进度月报MT medium term 中期M/T mail transfer 信汇mthly monthly 每月MTI medium-term insurance 中期保险MTN medium-term note 中期票据MTU metric unit 米制单位n. net 净值N. A. net assets 净资产n. a not available 暂缺NC no charge 免费N/C net capital 净资本n. d. no date 无日期N. D. net debt 净债务n. d. non-delivery 未能到达ND next day delivery 第二天交割NDA net domestic asset 国内资产净值N.E. net earnings 净收益n. e. no effects 无效n. e. not enough 缺乏negb. negotiable 可转让的、可流通的Neg. Inst., N. I. negotiable instruments 流通票据nego. negotiate 谈判N. E. S. not elsewhere specified 未另作说明net. p. net proceeds 净收入N/F no fund 无存款NFD no fixed date 无固定日期NFS not for sale 非卖品N. G. net gain 纯收益NH not held 不追索委托N. I. net income 净收益N. I. net interest 净利息NIAT net income after tax 税后净收益NIFO next in, first out 次进先出法nil nothing 无NIM net interest margin 净息差NIT negative income tax 负所得税N. L. net loss 净损失NL no load 无佣金n. m. nautical mile 海里NM no marks 无标记N. N. no name 无签名NNP net national product 国民生产净值NO. (no.) number 编号、号数no a/c no account 无此帐户NOP net open position 净开头寸NOW a/c negotiable order of withdrawal 可转让存单帐户N/P net profit 净利NP no protest 免作拒付证书N. P. notes payable 应付票据NPC nominal protection coefficient 名义保护系数NPL non-performing loan 不良贷款NPV method net present value method 净现值法N. Q. A. net quick assets 速动资产净额NQB no qualified bidders 无合格投标人NR no rated 〔信用〕未分等级N/R no responsibility 无责任N. R. notes receivable 应收票据N. S. F. (NSF) no sufficient fund 存款缺乏NSF check no sufficient fund check 存款缺乏支票nt. wt. net weight 净重NTA net tangible assets 有形资产净值NTBs non-tariffs barriers 非关税壁垒ntl no time lost 立即NTS not to scale 不按比例NU name unknown 无名N. W. net worth 净值NWC net working capital 净流动资本NX not exceeding 不超过N. Y. net yield 净收益NZ$ New Zealand dollar 新西兰元o order 订单o. (O.) offer 发盘、报价OA open account 赊帐、往来帐o/a on account of 记入......帐户o. a. overall 全面的、综合的OAAS operational accounting and analysis system 经营会计分析制OB other budgetary 其他预算O. B. ordinary business 普通业务O. B. (O/B) order book 订货簿OB/OS index overbought/oversold index 超买超卖指数OBV on-balance volume 持平数量法o. c. over charge 收费过多OC open cover 预约保险o/d, o. d.,(O. D.) overdrawn 透支OD overdraft 透支O/d on demand 见票即付O. E. (o. e. ) omission excepted 遗漏除外O. F. ocean freight 海运费OFC open for cover 预约保险O. G. ordinary goods 中等品O. G. L. Open General License 不限额进口许可证OI original issue 原始发行OII overseas investment insurance 海外投资保险ok. all correct 全部正确o. m. s. output per manshift 每人每班产量O. P. old price 原价格O. P. open policy 不定额保险单opp opposite 对方opt. optional 可选择的ord. ordinary 普通的OS out of stock 无现货O/s outstanding 未清偿、未收回的O. T. overtime 加班OTC over-the -counter market 市场外交易市场OV A overhead variance analysis 间接费用差异分析OW offer wanted 寻购启示OWE optimum working efficiency 最正确工作效率oz ounce(s) 盎司ozws. otherwise 否那么p penny; pence; per 便士；便士；每P paid this year 该年〔红利〕已付p. pint 品托〔1/8加仑〕P.A. particular average; power of attorney 单独海损；委托书P.A. personal account; private account 个人账户、私人账户p.a., per ann. per annum 每年P&A professional and administrative 职业的和管理的P&I clause protection and indemnity clause 保障与赔偿条款P&L profit and loss 盈亏，损益P/A payment of arrival 货到付款P/C price catalog; price current 价格目录；现行价格P/E price/earning 市盈率P/H pier-to-house 从码头到仓库P/N promissory note 期票，本票P/P posted price (股票等)的牌价PAC put and call 卖出和买入期权pat. patent 专利PAYE pay as you earn 所得税预扣法PAYE pay as you enter 进入时支付PBT profit before taxation 税前利润per pro. per procurationem 〔拉丁〕由...代理PF project finance 工程融资PFD preferred stock 优先股pk peck 配克〔1/4蒲式耳〕PMO postal money order 邮政汇票P.O.C. port of call 寄航港，停靠地P.O.D. place of delivery 交货地点P.O.D. port of destination; port of discharge 目的港；卸货港P.O.R. payable on receipt 货到付款P.P. payback period 〔投资的〕回收期P.P.I. policy proof of interest 凭保证单证明的保险利益POE port of entry 报关港口POP advertising point-of-purchase advertising 购物点广告POR pay on return 收益PR payment received 付款收讫PS postscript 又及PV par value; present value 面值；现值q. quarto 四开，四开本Q. quantity 数量QB qualified buyers 合格的购置者QC quality control 质量控制QI quarterly index 季度指数qr. quarter 四分之一，一刻钟QT questioned trade 有问题交易QTIB Qualified Terminal Interest Property Trust 附带可终止权益的财产信托quad. quadruplicate 一式四份中的一份quotn. quotation 报价q.v. quod vide (which see) 参阅q.y. query 查核R option not traded 没有进行交易的期权R. response; registered; return 答复；已注册；收益r. rate; rupee; ruble 比率；卢比；卢布RAD research and development 研究和开发RAM diverse annuity mortgage 逆向年金抵押RAN revenue anticipation note 收入预期债券R&A rail and air 铁路及航空运输R&D research and development 研究与开发R&T rail and truck 铁路及卡车运输R&W rail and water 铁路及水路运输R/A refer to acceptor 洽询〔汇票〕承兑人R/D refer to drawer 〔银行〕洽询出票人RB regular budget 经常预算RCA relative comparative advantage 相比照拟优势RCMM registered competitive market maker 注册的竞争市场自营商rcvd. received 已收到r.d. running days=consecutive days 连续日RDTC registered deposit taking company 注册接受存款公司Re. subject 主题re. with reference to 关于RECEIVED B/L received for shipment bill of lading 待装云提单REER real effective exchange rate 实效汇率ref. referee; reference; refer(red) 仲裁者；裁判；参考；呈递REO real estate owned 拥有的不动产REP import replacement 进口替代REP Office representative office 代办处，代表处REPO, repu, RP Repurchase Agreement 再回购协议req. requisition 要货单，请求REVOLVER revolving letter of credit 循环信用证REWR read and write 读和写RIEs recognized investment exchanges 认可的投资交易〔所〕Rl roll 卷RLB restricted license bank 有限制牌照银行RM remittance 汇款rm room 房间RMB RENMINBI 人民币，中国货币RMS Royal Mail Steamer 皇家邮轮RMSD Royal Mail Special Delivery 皇家邮政专递RMT Rail and Maritime Transport Union 铁路海运联盟ROA return on asset 资产回报率ROC return on capital 资本收益率ROE return on equity 股本回报率ROI return on investment 投资收益ROP registered option principal 记名期权本金ro-ro roll-on/roll-off vessel 滚装船ROS return on sales 销售收益率RPB Recognized Professional Body 认可职业〔投资〕机构RPI retail price index 零售物价指数RPM resale price maintenance 零售价格维持措施〔方案〕rpt. repeat 重复RRP Reverse Repurchase Agreement 逆回购协议RSL rate sensitive liability 利率敏感性债务RSVP please reply 请回复RT Royalty Trust 特权信托RTM registered trade mark 注册商标Rto ratio 比率RTO round trip operation 往返作业RTS rate of technical substitution 技术替代率RTW right to work 工作权利RUF revolving underwriting facility 循环式包销安排RYL referring to your letter 参照你方来信RYT referring to your telex 参照你方电传S no option offered 无期权出售S split or stock divided 拆股或股息S signed 已签字s second; shilling 秒；第二；先令SA semi-annual payment 半年支付SA South Africa 南非SAA special arbitrage account 特别套作账户SAB special assessment bond 特别估价债券sae stamped addressed envelope 已贴邮票、写好地址的信封SAFE State Administration of Foreign Exchange 国家外汇管理局SAIC State Administration for Industry and Commerce 〔中国〕国家工商行政管理局SAP Statement of Auditing Procedure 【审计程序汇编】SAR Special Administrative Region 特别行政区SAS Statement of Auditing Standard 【审计准那么汇编】SASE self-addressed stamped envelope 邮资已付有回邮地址的信封SAT (China) State Administration of Taxation 〔中国〕国家税务局SATCOM satellite communication 卫星通讯SB short bill 短期国库券；短期汇票SB sales book; saving bond; savings bank 售货簿；储蓄债券；储蓄银行SBC Swiss Bank Corp. 瑞士银行公司SBIC Small Business Investment Corporation 小企业投资公司SBIP small business insurance policy 小型企业保险单SBLI Savings Bank Life Insurance 储蓄银行人寿保险SBN Standard Book Number 标准图书号SC sales contract 销售合同sc scilicet namely 即SC supplier credit 卖方信贷SCF supplier credit finance 卖方信贷融资Sch schilling 〔奥地利〕先令SCIRR special CIRR 特别商业参考利率SCL security characteristic line 证券特征线SCORE special claim on residual equity 对剩余财产净值的特别要求权SD standard deduction 标准扣除额SDB special district bond 特区债券SDBL sight draft, bill of lading attached 即期汇票，附带提货单SDH synchronous digital hierarchy 同步数字系统SDR straight discount rate 直线贴现率SDRs special drawing rights 特别提款权SE shareholders' equity 股东产权SE Stock Exchange 股票交易所SEA Single European Act 【单一欧洲法案】SEAF Stock Exchange Automatic Exchange Facility 股票交易所自动交易措施SEATO Southeast Asia Treaty Organization 东南亚公约组织sec second(ary); secretary 第二，次级；秘书sect. section 局部Sen senator 参议院Sept. September 九月SET selective employment tax 单一税率工资税sextuplicate 〔文件〕一式六份中的一份SEC special economic zone 经济特区SF sinking fund 偿债基金Sfr Swiss Frank 瑞士法郎SFS Summary Financial Statements 财务报表概要sgd. signed 已签署SHEX Sundays and holidays excepted 星期日和假日除外SHINC Sundays and holidays included 星期日和假日包括在内shpd. shipped 已装运shpg. shipping 正装运shpt. shipment 装运，船货SI Statutory Instrument; System of Units 有效立法；国际量制SIC Standard Industrial Classification 标准产业分类SIP structured insurance products 结构保险产品SITC Standard International Trade Classification 国际贸易标准分类sk sack 袋，包SKD separate knock-known 局部散件SLC standby LC 备用信用证SMA special miscellaneous account 特别杂项账户SMEs small and medium-sized enterprises 中小型企业SMI Swiss Market Index 瑞士市场指数SML security market line 证券市场线SMTP supplemental medium term policy 辅助中期保险SN stock number 股票编号Snafu Situation Normal, All Fouled Up 情况还是一样，只是都乱了SOE state-owned enterprises 国有企业SOF State Ownership Fund 国家所有权基金sola sola bill, sola draft, sola of exchange 〔拉丁〕单张汇票sov. sovereign 金镑=20先令SOYD sum of the year's digits method 年数加总折旧法spec. specification 规格；尺寸SPF spare parts financing 零部件融资SPQR small profits, quick returns 薄利多销SPS special purpose securities 特设证券Sq. square 平方；结清SRM standard repair manual 标准维修手册SRP Salary Reduction Plan 薪水折扣方案SRT Spousal Remainder Trust 配偶幸存者信托ss semis, one half 一半SS social security 社会福利ST short term 短期ST special treatment (listed stock) 特别措施〔对有问题的上市股票〕St. Dft. sight draft 即期汇票STB special tax bond 特别税债务STIP short-term insurance policy 短期保险单sub subscription; substitute 订阅，签署，捐助；代替Sun Sunday 星期日sund. sundries 杂货，杂费sup. supply 供给，供货t time; temperature 时间；温度T. ton; tare 吨；包装重量，皮重TA telegraphic address=cable address 电报挂号TA total asset 全部资产，资产TA trade acceptance 商业承兑票据TA transfer agent 过户转账代理人TAB tax anticipation bill 〔美国〕预期抵税国库券TACPF tied aid capital projects fund 援助联系的资本工程基金TAF tied aid financing 援助性融资TAL traffic and accident loss 〔保险〕交通和意外事故损失TB treasury bond, treasury bill 国库券，国库债券T.B. trial balance 试算表t.b.a. to be advised; to be agreed; to be announced; to be arranged 待通知；待同意；待宣布；待安排t.b.d. to be determined 待〔决定〕TBD policy to be declared policy 预保单，待报保险单TBV trust borrower vehicle 信托借。

99FED财政报告

For use at11:00a.m.,E.D.T.ThursdayJuly22,1999Board of Governors of the Federal Reserve SystemMonetary Policy Report to the CongressPursuant to theFull Employment and Balanced Growth Act of1978 July22,1999Letter of TransmittalBOARD OF GOVERNORS OF THEFEDERAL RESERVE SYSTEMWashington,D.C.,July22,1999THE PRESIDENT OF THE SENATETHE SPEAKER OF THE HOUSE OF REPRESENTATIVESThe Board of Governors is pleased to submit its Monetary Policy Report to the Congress,pursuant to the Full Employment and Balanced Growth Act of1978.Sincerely,Alan Greenspan,ChairmanTable of ContentsPage Monetary Policy and the Economic Outlook1 Economic and Financial Developments in19994Monetary Policy Report to the CongressReport submitted to the Congress on July22,1999, pursuant to the Full Employment and Balanced Growth Act of1978M ONETARY P OLICY AND THE E CONOMICO UTLOOKThe U.S.economy has continued to perform well in 1999.The ongoing economic expansion has moved into a near-record ninth year,with real output expand-ing vigorously,the unemployment rate hovering around lows last seen in1970,and underlying trends in inﬂation remaining subdued.Responding to the availability of new technologies at increasingly attractive prices,ﬁrms have been investing heavily in new capital equipment;this investment has boosted productivity and living standards while holding down the rise in costs and prices.Two of the major threats faced by the economy in late1998—economic downturns in many foreign nations and turmoil inﬁnancial markets around the world—receded over theﬁrst half of this year.Eco-nomic conditions overseas improved on a broad front. In Asia,activity picked up in the emerging-market economies that had been battered by theﬁnancial crises of1997.The Brazilian economy—Latin America’s largest—exhibited a great deal of resil-ience with support from the international community, in the wake of the devaluation and subsequentﬂoat-ing of the real in January.These developments,along with the considerable easing of monetary policy in late1998and early1999in a number of regions, including Europe,Japan,and the United States,fos-tered a markedly better tone in the world’sﬁnancial markets.On balance,U.S.equity prices rose substan-tially,and in credit markets,risk spreads receded toward more typical levels.Issuance of private debt securities ballooned in late1998and early1999,in part making up for borrowing that was postponed when markets were disrupted.As these potentially contractionary forces dissi-pated,the risk of higher inﬂation in the United States resurfaced as the greatest concern for monetary pol-icy.Although underlying inﬂation trends generally remained quiescent,oil prices rose sharply,other commodity prices trended up,and prices of non-oil imports fell less rapidly,raising overall inﬂation rates. Despite improvements in technology and business processes that have yielded striking gains in efﬁ-ciency,the robust growth of aggregate demand, fueled by rising equity wealth and readily available credit,produced even tighter labor markets in theﬁrst half of1999than in the second half of1998.If this trend were to continue,labor compensation would begin climbing increasingly faster than warranted by productivity growth and put upward pressure on prices.Moreover,the Federal Open Market Commit-tee(FOMC)was concerned that as economic activity abroad strengthened,theﬁrming of commodity and other prices might also foster a less favorable inﬂa-tion environment.To gain some greater assurance that the good inﬂation performance of the economy would continue,the Committee decided at its June meeting to reverse a portion of the easing undertaken last fall when globalﬁnancial markets were dis-rupted;the Committee’s target for the overnight fed-eral funds rate,a key indicator of money market conditions,was raised from43⁄4percent to5percent. Monetary Policy,Financial Markets,and the Economy over the First Half of1999The FOMC met in February and March against the backdrop of continued rapid expansion of the U.S. economy.Demand was strong,employment growth was brisk,and labor markets were tight.Nonetheless, price inﬂation was still low,held in check by a sub-stantial gain in productivity,ample manufacturing capacity,and low inﬂation expectations.Activity was supported by a further settling down ofﬁnancial markets in theﬁrst quarter after a period of considerable turmoil in the late summer and fall of 1998.In that earlier period,which followed Russia’s moratorium on a substantial portion of its debt pay-ments in mid-August,the normal functioning of U.S.ﬁnancial markets had been impaired as investors cut back sharply their credit risk exposures and market liquidity dried up.The Federal Reserve responded to these developments by trimming its target for the overnight federal funds rate by75basis points in three steps.In early1999,the devaluation and subse-quentﬂoating of the Brazilian real in mid-Januaryheightened concerns for a while,but market condi-tions overall improved considerably.At its February and March meetings,the FOMC left the stance of monetary policy unchanged.The Committee expected that the growth of output might well slow sufﬁciently to bring production into close enough alignment with the economy’s enhanced potential to forestall the emergence of a trend of ris-ing inﬂation.Although domestic demand was still increasing rapidly,it was anticipated to moderate over time in response to the buildup of large stocks of business equipment,housing units,and durable goods and more restrained expansion in wealth in the absence of appreciable further increases in equity prices.Furthermore,the FOMC,after taking account of the near-term effects of the rise in crude oil prices,saw few signs that cost and price inﬂation was in the process of picking up.The unusual combination of very high labor resource utilization and sustained low inﬂation suggested considerable uncertainty about the relationship between output and prices.In this envi-ronment,the Committee concluded that it could wait for additional information about the balance of risks to the economic expansion.By the time of the May FOMC meeting,demand was still showing considerable forward momentum,and growth in economic activity still appeared to be running in excess of the rate of increase of the economy’s long-run capacity to expand output.Bor-rowers’heavy demands for credit were being met on relatively favorable terms,and wealth was further boosted by rapidly rising equity prices.Also,the economic and ﬁnancial outlook for many emerging-market countries was brighter.Trends in inﬂation were still subdued,although consumer prices—even apart from a big jump in energy prices—were reported to have registered a sizable rise in April.At its May meeting,the FOMC believed that these developments tilted the risks toward further robust growth that would exert additional pressure on already taut labor markets and ultimately show through to inﬂation.Moreover,a turnaround in oil and other commodity markets meant that prices of these goods would no longer be holding down inﬂa-tion,as they had over the past year.Yet,the economy to date had shown a remarkable ability to accommo-date increases in demand without generating greater underlying inﬂation trends,as the continued growth of labor productivity had helped to contain cost pres-sures.The uncertainty about the prospects for prices,demand pressures,and productivity was large,and the Committee decided to defer any policy action.However,in light of its increased concern about the outlook for inﬂation,the Committee adopted an asymmetric directive tilted toward a possible ﬁrm-ing of policy.The Committee also wanted to inform the public of this signiﬁcant revision in its view,and it announced a change in the directive immediately after the meeting.The announcement was the ﬁrst under the Committee’s policy of announcing changes in the tilt of the domestic directive when it wants to communicate a major shift in its view about the balance of risks to the economy or the likely direction of its future actions.In the time leading up to the FOMC’s June meet-ing,economic activity in the United States continued to move forward at a brisk pace,and prospects in a number of foreign economies showed additional bor markets tightened slightly fur-ther.The federal funds rate,however,remained atSelected interest rates45672/53/255/207/28/199/3011/1212/162/43/315/197/18/189/2910/1511/1712/222/33/305/186/30199719981999Note.The data are daily.Vertical lines indicate the days on which the Federal Reserve announced a monetary policy action.The dates on the horizon-tal axis are those on which either the FOMC held a scheduled meeting or a policy action was st observations are for July 19,1999.2Monetary Policy Report to the Congress July 1999the lower level established in November1998,when the Committee took its last of three steps to counter severeﬁnancial market strains.With those strains largely gone,the Committee believed that the time had come to reverse some of that accommodation, and it raised the targeted overnight federal funds rate 25basis points,to5percent.Looking ahead,the Committee expected demand to remain strong,but it also noted the possibility that a further pickup in productivity could allow the economy to accommo-date this demand for some time without added inﬂa-tionary pressure.In light of these conﬂicting forces in the economy,the FOMC returned to a symmetric directive.Nonetheless,with labor markets already tight,the Committee recognized that it needed to stay especially alert to signs that inﬂationary forces were emerging that could prove inimical to the economic expansion.Economic Projections for1999and2000The members of the Board of Governors and the Federal Reserve Bank presidents see good prospects for sustained,solid economic expansion through next year.For this year,the central tendency of their forecasts of growth of real gross domestic product is 31⁄2percent to33⁄4percent,measured as the change between the fourth quarters of1998and1999.For 2000,the forecasts of real GDP are mainly in the21⁄2percent to3percent range.With this pace of expansion,the civilian unemployment rate is expected to remain close to the recent41⁄4percent level over the next six quarters.The increases in income and wealth that have bolstered consumer demand over theﬁrst half of this year and the desire to invest in new high-technology equipment that has boosted business demand during the same period should continue to stimulate spend-ing over the quarters ahead.However,several factors are expected to exert some restraint on the economy’s momentum by next year.With purchases of durable goods by both consumers and businesses having risen still further and running at high levels,the stocks of such goods probably are rising more rapidly than is likely to be desired in the longer run,and the growth of spending should moderate.The increase in market interest rates should help to damp spending as well.And unless the extraordinary gains in equity prices of the past few years are extended, the impetus to spending from increases in wealth will diminish.Federal Reserve policymakers believe that this year’s rise in the consumer price index(CPI)will be larger than that in1998,largely because of the rebound in retail energy prices that has already occurred.Crude oil prices have moved up sharply, reversing the decline posted in1998and leading to a jump in the CPI this spring.For next year,the FOMC participants expect the increase in the CPI to remain around this year’s pace,with a central tendency of 2percent to21⁄2percent.Futures market quotes sug-gest that the prevailing expectation is that the rebound in oil prices has run its course now,and ample industrial capacity and productivity gains may help limit inﬂationary pressures in coming months as well. With labor utilization very high,though,and demand still strong,signiﬁcant risks remain even after the recent policyﬁrming that economic andﬁnancial conditions may turn out to be inconsistent with keep-ing costs and prices from escalating.Although interest rates currently are a bit higher than anticipated in the economic assumptions under-lying the budget projections in the Administration’s Mid-Session Review,there is no apparent tension between the Administration’s plans and the Fed-eral Reserve policymakers’views.In fact,Federal Reserve ofﬁcials project somewhat faster growth in real GDP and slightly lower unemployment rates into 2000than the Administration does,while the Admin-istration’s projections for inﬂation are within the Federal Reserve’s central tendencies.1.Economic projections for1999and2000PercentIndicatorFederal Reserve governorsand Reserve Bank presidentsAdministration1Range Centraltendency1999Change,fourth quarterto fourth quarter2Nominal GDP...........43⁄4–51⁄25–51⁄2 4.8Real GDP...............31⁄4–431⁄2–33⁄4 3.2Consumer price index3..13⁄4–21⁄221⁄4–21⁄2 2.4Average level,fourth quarterCivilian unemploymentrate................4–41⁄24–41⁄4 4.32000Change,fourth quarterto fourth quarter2Nominal GDP...........4–51⁄44–5 4.2Real GDP...............2–31⁄221⁄2–3 2.1Consumer price index3..11⁄2–23⁄42–21⁄2 2.4Average level,fourth quarterCivilian unemploymentrate................4–41⁄241⁄4–41⁄2 4.71.From the Mid-Session Review of the budget.2.Change from average for fourth quarter of previous year to average forfourth quarter of year indicated.3.All urban consumers.Board of Governors of the Federal Reserve System3Money and Debt Ranges for1999and2000At its meeting in late June,the FOMC reafﬁrmed the ranges for1999growth of money and debt that it had established in February:1percent to5percent for M2,2percent to6percent for M3,and3percent to 7percent for debt of the domestic nonﬁnancial sec-tors.The FOMC set the same ranges for2000on a provisional basis.As has been the case since the mid-1990s,the FOMC views the ranges for money growth as bench-marks for growth under conditions of price stability and the historically typical relationship between money and nominal income.The disruption of the historically typical pattern of the velocities of M2 and M3(the ratio of nominal GDP to the aggregates) during the1990s implies that the Committee cannot establish,with any conﬁdence,speciﬁc target ranges for expected money growth for a given year that will be consistent with the economic performance that it desires.However,persistently fast or slow money growth can accompany,or even precede,deviations from desirable economic outcomes.Thus,the behav-ior of the monetary aggregates,evaluated in the con-text of otherﬁnancial and nonﬁnancial indicators, will continue to be of interest to Committee members in their policy deliberations.The velocities of M2and M3declined again in the ﬁrst half of this year,albeit more slowly than in1998. The Committee’s easing of monetary policy in the fall of1998contributed to the decline,but only to a modest extent.It is not clear what other factors led to the drop,although the considerable increase in wealth relative to income resulting from the substantial gains in equity prices over the past few years may have played a role.Investors could be rebalancing their portfolios,which have become skewed toward equi-ties,by reallocating some wealth to other assets, including those in M2.Even if the velocities of M2and M3were to return to their historically typical patterns over the balance of1999and in2000,M2and M3likely would be at the upper bounds of,or above,their longer-term price-stability ranges in both years,given the Com-mittee’s projections of nominal GDP growth.This relatively rapid expansion in nominal income reﬂects faster expected growth in productivity than when the price-stability ranges were established in the mid-1990s and inﬂation that is still in excess of price stability.The more rapid increase in productivity,if it persists for a while and is sufﬁciently large,might in the future suggest an upward adjustment to the money ranges consistent with price stability.However,con-siderable uncertainty attends the trend in productiv-ity,and the Committee chose not to adjust the ranges at its most recent meeting.Debt of the nonﬁnancial sectors has expanded at roughly the same pace as nominal income this year—its typical pattern.Given the stability of this relation-ship,the Committee selected a growth range for the debt aggregate that encompasses its expectations for debt growth in both years.The Committee expects growth in nominal income to slow in2000,and with it,debt growth.Nonetheless,growth of this aggregate is projected to remain within the range of3percent to 7percent.E CONOMIC ANDF INANCIAL D EVELOPMENTSIN1999The economy has continued to grow rapidly so far this year.Real gross domestic product rose more than 4percent at an annual rate in theﬁrst quarter of1999, and available data point to another signiﬁcant gain in the second quarter.1The rise in activity has been 1.Allﬁgures from the national income and product accounts cited here are subject to change in the quinquennial benchmark revisions slated for this fall.2.Ranges for growth of monetary and debt aggregatesPercentAggregate19981999Provisional for2000M2............1–51–51–5M3............2–62–62–6 Debt...........3–73–73–7Note.Change from average for fourth quarter of preceding year to averagefor fourth quarter of year indicated.Change in realGDP 1994199519961997199819990–+ 2 4Note.In this chart and in subsequent charts that show the components ofreal GDP,changes are measured from theﬁnal quarter of the previous period totheﬁnal quarter of the period indicated.4Monetary Policy Report to the Congress July1999brisk enough to produce further substantial growth of employment and a reduction in the unemployment rate to 41⁄4percent.Growth in output has been driven by strong domestic demand,which in turn has been supported by further increases in equity prices,by the continuing salutary effects of government saving and inﬂows of foreign investment on the cost of capital,and by more smoothly functioning ﬁnancial markets as the turbulence that marked the latter part of 1998subsided.Against the background of the easing of monetary policy last fall and continuing robust economic activity,investors became more willing to advance funds to businesses;risk spreads have receded and corporate debt issuance has been brisk.Inﬂation developments were mixed over the ﬁrst half of the year.The consumer price index increased more rapidly owing to a sharp rebound in energy prices.Nevertheless,price inﬂation outside of the energy area generally remained subdued despite the slight further tightening of labor markets,as sizable gains in labor productivity and ample industrial capacity held down price increases.The Household SectorConsumer SpendingReal personal consumption expenditures surged 63⁄4percent at an annual rate in the ﬁrst quarter,and more recent data point to a sizable further advance in the second quarter.The underlying fundamentals for the household sector have remained extremely favor-able.Real incomes have continued to rise briskly with strong growth of employment and real wages,and consumers have beneﬁted from substantial gains in wealth.Not surprisingly,consumer conﬁdence—as measured,for example,by the University of Michigan Survey Research Center (SRC)and Con-ference Board surveys—has remained quite upbeat in this environment.Growth of consumer spending in the ﬁrst quarter was strong in all expenditure categories.Outlays for durable goods rose sharply,reﬂecting sizable increases in spending on electronic equipment (espe-cially computers)and on a wide range of other goods,including household furnishings.Purchases of cars and light trucks remained at a high level,supported by declining relative prices as well as by the funda-mentals that have buoyed consumer spending more generally.Outlays for nondurable goods were also robust,reﬂecting in part a sharp increase in expendi-tures for apparel.Finally,spending on services climbed steeply as well early this year,paced by sizable increases in spending on recreation and bro-kerage services.In the second quarter,consumers apparently boosted their purchases of motor vehicles further.In all,real personal consumption expendi-tures rose at more than a 4percent annual rate in April and May,an increase that is below the ﬁrst-quarter pace but is still quite rapid by historical standards.Real disposable income increased at an annual rate of 31⁄2percent in the ﬁrst quarter,with the strong labor market generating marked increases in wages and salaries.Even so,income grew less rapidly than expenditures,and the personal saving rate declined further;indeed,by May the saving rate had moved below negative 1percent.Much of the decline in the saving rate in recent years can be explained by the sharp rise in household net worth relative to dispos-able income that is associated with the appreciationChange in real income and consumption1994199519961997199819990–+2468Percent, annual rateWealth and saving4561978198219861990199419980–+24681012Note.The wealth-to-income ratio is the ratio of net worth of households to disposable personal income.Board of Governors of the Federal Reserve System 5of households’stock market assets since 1995.This rise in wealth has given households the wherewithal to spend at levels beyond what current incomes would otherwise allow.As share values moved up further in the ﬁrst half of this year,the wealth-to-income ratio continued to edge higher despite the absence of saving out of disposable income.Residential InvestmentHousing activity remained robust in the ﬁrst half of this year.In the single-family sector,positive funda-mentals and unseasonably good weather helped boost starts to a pace of 1.39million units in the ﬁrst quarter—the highest level of activity in twenty years.This extremely strong level of building activity strained the availability of labor and some materials;as a result,builders had trouble achieving the usual seasonal increase in the second quarter,and starts edged off to a still-high pace of 1.31million units.Home sales moderated in the spring:Sales of both new and existing homes were off some in May from their earlier peaks,and consumers’perceptions of homebuying conditions as measured by the Michigan SRC survey have declined from the very high marks recorded in late 1998and early this year.Nonethe-less,demand has remained quite robust,even in the face of a backup in mortgage interest rates:Builders’evaluations of new home sales remained very high at mid-year,and mortgage applications for home pur-chases showed strength into July.With strong demand pushing up against limited capacity,home prices have risen substantially,although evidence is mixed as to whether the rate of increase is picking up.The quality-adjusted price of new homes rose 5percent over the four quartersended in 1999:Q1,up from 31⁄4percent over the preceding four-quarter period.The repeat sales index of existing home prices also rose about 5percent between 1998:Q1and 1999:Q1,but this series posted even larger increases in the year-earlier period.On the cost side,tight supplies have led to rising prices for some building materials;prices of plywood,lum-ber,gypsum wallboard,and insulation have all moved up sharply over the past twelve months.In addition,hourly compensation costs have been rising relatively rapidly in the construction sector.Starts of multifamily units surged to 384,000at an annual rate in the ﬁrst quarter and ran at a pace a bit under 300,000units in the second quarter.As in the single-family sector,demand has been supported by strong fundamentals,builders have been faced with tight supplies of some materials,and prices have been rising briskly:Indeed,apartment property values have been increasing at around a 10percent annual rate for three years now.Household FinanceIn addition to rising wealth and rapid income growth,the strong expenditures of households on housing and consumer goods over the ﬁrst half of 1999were encouraged by the decline in interest rates in the latter part of 1998.Households borrowed heavily to ﬁnance spending.Their debt expanded at a 91⁄2per-cent annual rate in the ﬁrst quarter,up from the 83⁄4percent pace over 1998,and preliminary data for the second quarter indicate continued robust growth.Mortgage borrowing,fueled by the vigorous housing market and favorable mortgage interest rates,was particularly brisk in the ﬁrst quarter,with mortgage debt rising at an annual rate of 10percent.In the second quarter,mortgage rates moved up consider-ably,but preliminary data indicate that borrowing was still substantial.Consumer credit growth accelerated in the ﬁrst half of 1999.It expanded at about an 8percent annual rate compared with 51⁄2percent for all of 1998.The growth of nonrevolving credit picked up,reﬂecting brisk sales and attractive ﬁnancing rates for automo-biles and other consumer durable goods.The expan-sion of revolving credit,which includes credit card loans,slowed a bit from its pace in 1998.Households apparently have not encountered added difﬁculties meeting the payments associated with their greater indebtedness,as measures of household ﬁnancial stress improved a bit on balance in the ﬁrst quarter.Personal bankruptcies dropped off consid-erably,although part of the decline may reﬂectPrivate housing starts198819901992199419961998.4.81.2Millions of units, annual rateSingle-familyMultifamilyQ2Q26Monetary Policy Report to the Congress July 1999the aftermath of a surge in ﬁlings in late 1998that occurred in response to pending legislation that would limit the ability of certain debtors to obtain forgiveness of their obligations.Delinquency rates on several types of household loans edged lower.Delin-quency and charge-off rates on credit card debt moved down from their 1997peaks but remained at historically high rates.A number of banks continued to tighten credit card lending standards this year,as indicated by banks’responses to Federal Reserve surveys.The Business SectorFixed InvestmentReal business ﬁxed investment appears to have posted another huge increase over the ﬁrst half of1999.Investment spending continued to be driven by buoyant expectations of sales prospects as well as by rapidly declining prices of computers and other high-tech equipment.In recent quarters,spend-ing also may have been boosted by the desire to upgrade computer equipment in advance of the roll-over to the year 2000.Real investment has been rising rapidly for several years now;indeed,the average increase of 10percent annually over the past ﬁve years represents the most rapid sustained expan-sion of investment in more than thirty years.Although a growing portion of this investment has gone to cover depreciation on purchases of short-lived equipment,the investment boom has led to a notable upgrading and expansion of the capital stock and in many cases has embodied new technologies.These factors likely have been important in the na-tion’s improved productivity performance over the past few years.Real outlays for producers’durable equipment increased at an annual rate of 91⁄2percent in the ﬁrst quarter of the year,after having surged nearly 17per-cent last year,and may well have re-accelerated in the second quarter.Outlays on communications equipment were especially robust in the ﬁrst quarter,driven by the ongoing effort by telecommunications companies to upgrade their networks to provide a full range of voice and data transmission services.Purchases of computers and other information pro-cessing equipment were also up notably in the ﬁrst quarter,albeit below last year’s phenomenal spending pace,and shipments of computers surged again in April and May.Shipments of aircraft to domestic carriers apparently soared in the second quarter,and business spending on motor vehicles,including medium and heavy trucks as well as light vehicles,has remained extremely strong as well.Real business spending for nonresidential struc-tures has been much less robust than for equipment,and spending trends have varied greatly across sec-tors of the market.Real spending on ofﬁce buildings and lodging facilities has been increasing impres-sively,while spending on institutional and industrial structures has been declining—the last reﬂecting ample capacity in the manufacturing sector.In the ﬁrst quarter of this year,overall spending on struc-tures was reported in the national income and product accounts to have moved up at a solid 53⁄4percent annual rate,reﬂecting a further sharp increase in spending on ofﬁce buildings and lodging facilities.However,revised source data indicate a somewhat smaller ﬁrst-quarter increase in nonresidential con-struction and also point to a slowing in activity in April and May from the ﬁrst-quarter pace.Delinquency rates on household loans1988199019921994199619982345PercentCredit card accounts at banksAuto loans at domestic auto ﬁnance companiesMortgagesQ1Q1Q1Note.The data are quarterly.Source.Data on credit card delinquencies are from bank Call Reports;data on auto loan delinquencies are from the Big Three automakers;data on mort-gage delinquencies are from the Mortgage Bankers Association.Change in real business ﬁxedinvestment0–+1020Percent, annual rateBoard of Governors of the Federal Reserve System 7。

外贸函电-价格与反还盘

我们要告诉你方，我们的报价已为你处的其他客户所接受，而且已有大量成交。数月来，许许多多的询价单源源而来。
We wish to inform you that our price has been
accepted by other buyers in your city, at which
substantial business has been done, and that
III. Specimen Letters (2)
希望贵方重新考虑这一优惠价格，早日来电订货，以便我们确认。
We hope you will consider it and cable us your order for our confirmation at your earliest convenience.
level.
我们的价格订得合理。
IV. Useful Expressions
(4) We are unable to accept your offer as other suppliers have offered us more favorable terms. 我们不能接受你们的报价，因为其他供应商向我们提出更优惠的价格。
IV. Useful Expressions
(2)
Your
counter-offer
is
not
in
keeping with the current market.
你方的还盘与现行市价不符。
IV. Useful Expressions
(3) Our price is fixed at a reasonable
III. Specimen Letters (1)

报价实盘英语作文模板

报价实盘英语作文模板英文回答：Quotation Strategy Paper。

Executive Summary。

This quotation strategy paper outlines our comprehensive approach to quoting and competitively pricing our products and services. The paper covers market research, competitor analysis, and our internal processes for developing and issuing quotations. By adhering to these strategies, we aim to maximize revenue, retain customers, and maintain a competitive edge in the marketplace.Market Research and Competitor Analysis。

In-depth market research is crucial to understandingthe competitive landscape and customer needs. We conduct thorough research to identify our target customers, analyzetheir purchasing patterns, and determine the prevailing market prices.Similarly, comprehensive competitor analysis helps us benchmark our pricing and quotation strategies against industry leaders. We monitor their pricing, terms and conditions, and value propositions to stay informed and make informed decisions.Internal Quotation Process。

What’s happening to China’s GDP statistics,China Economic Review

What is happening to China’s GDP statistics?Thomas G.RAWSKI*Department of Economics,University of Pittsburgh,Pittsburgh,P A 15260,USAAbstractThis paper argues that official Chinese statistics contain major exaggerations of real output growth beginning in 1998.The standard data contain numerous inconsistencies.Chinese commentaries castigate widespread falsification at lower levels and question the authenticity of figures emanating from the central statistical authorities.The author speculates that cumulative GDP growth during 1997/2001was no more than one-third of official claims,and possibly much smaller.D 2002Elsevier Science Inc.All rights reserved.Keywords:China;Growth;Falsification;Statistics1.IntroductionDuring a May 2001conversation with several Chinese economists in Beijing,I expressed doubt that China’s recent GDP statistics reflect actual economic performance.Without missing a beat,a Chinese colleague said,‘‘Nobody believes recent GDP statistics.’’According to the New York Times ,‘‘many economists say the country’s real economic growth rate is,at most,half of that reported’’(Smith,2001).What is going on?I believe that,beginning with 1998,standard GDP data contain exaggerations that extend far beyond the technical difficulties addressed in recent studies (e.g.,Maddison,1998;Meng &Wang,2000;Ren,1997).This comment focuses on three matters:quantitative inconsistencies,qualitative information from Chinese commentaries,and suggestions about the possible magnitude of overstatement.1043-951X/02/$–see front matter D 2002Elsevier Science Inc.All rights reserved.PII:S 1043-951X (01)00062-1*Tel.:+1-412-648-7062;fax:+1-412-648-1793.E-mail address :tgrawski@ (T.G.Rawski).China Economic Review 12(2001)347–3542.Quantitative inconsistenciesOfficial figures for recent GDP growth appear in the top row of Table 1.The yearbook figures imply that real GDP grew by 24.7%between 1997and 2000.During the same 3years,energy consumption dropped by 12.8%.The implied reduction of 30%in unit energy consumption over 3years seems implausible,despite the rapid growth of computer manufac-ture and other activities with low unit energy consumption.Rapid growth of energy efficiency is not a hallmark of China’s economy:in 1997/1998,for example,the efficiency of energy conversion in producing thermal electricity,coke,and refined oil products all declined,and the ‘‘total efficiency of energy conversion’’was no better than the average for 1983/1984(China Statistical Yearbook ,2000,pp.55and 246;China Statistical Abstract ,2001pp.7and 130).International comparisons highlight the implausibility of recent Chinese growth claims.Table 2presents capsule summaries of several Asian economies during comparably short time periods going back to the 1950s.China’s recent official growth story is an obvious misfit:in every other instance,including China’s own experience 10years earlier,substantial GDP growth coincided with increased energy use,higher employment,and rising consumer prices.Returning to recent Chinese data,the clash between output and energy trends is only one of many unlikely elements.The figures for 1997/1998bristle with inconsistencies.Could farm output increase in all but one province despite floods that rank among China’s top 10natural disasters of the 20th century?1Could industrial production rise 10.75%even though only 14of 94major products achieved double-digit growth and 53suffered declining physical output?2Could investment spending jump 13.9%even though steel consumption and cement output rose by less than 5%?3Skeptical Chinese analysts point to many such puzzles (e.g.,Meng,1999).4Subsequent figures seem equally dubious.Data on consumption,which Chinese accounts identify as ‘‘a major driving force in the rapid development of the economy,’’are especially problematic (GDP Growth,2000,p.1).Table 3compares national data on retail sales growth with survey figures showing changes in per capita outlays by urban and rural households.With one exception,5national figures for retail sales grow 1Agricultural output data are from China Statistical Yearbook (1999,p.382).For the classification of the 1998floods among the top 10natural disasters of the 20th century,see Zhongguo tongji (China Statistics ,no.8,1999,p.38).2Industrial output value and physical commodity output for 1997/1998are from China Statistical Yearbook (1999,pp.424and 445–446).3Investment spending and cement output from China Statistical Yearbook (1999,pp.183and 446);increased steel consumption of ‘‘about 4%’’from Zhongguo wujia (China Price,no.3,1999,p.8).4For further examples,see Meng (1999).5The exception is the figure showing that that rural per capita cash expenditure on consumption rose by 12.2%during 1999/2000.This result is inconsistent with reports that rural per capita net income rose by only1.9%during 1999/2000(China Statistical Abstract ,2001,p.96).There is also an internal inconsistency in the source,which shows a drop in per capita cash outlay of RMB 197.7or 8.4%during 1999/2000together with increases of RMB 80and RMB 140.1in expenditure on production and on consumption respectively (China Monthly Indicators ,2001,pp.88–89).T.G.Rawski /China Economic Review 12(2001)347–354348more rapidly than per capita expenditure figures shown in household budgets.The difference is far too large to attribute to population growth,which is approximately 1%per year.A further difficulty is that,particularly in rural areas,retail sales rise more rapidly than household income,implying an increase in the average propensity to consume —i.e.,the share of consumption spending in household income.However,recent studies find a declining trend in the average propensity to consume among both urban and rural households through 1998(Tao,2000;Zhang,2000);subsequent reports indicating that ‘‘moderate income growth has intensified people’s tendency to save money’’(Bing,2001)point to a continuing Table 2Episodes of growth in Asian economies,1957–2001(cumulative percentage change)Cumulative change inJapan,1957/1961Taiwan,1967/1971Korea,1977/1981China,1987/1991China,1997/2001Real GDPOfficial52.849.721.631.834.5Alternate0.4/11.4Energy consumption40.185.233.619.8À5.5Employment4.617.09.423.20.8Consumer prices 10.620.6111.746.6À2.3Sources:Japan:Ohkawa and Shinohara (1979,pp.282,389,393)and .jp/english/1431.htm (Table 9-20);Taiwan:Statistical Yearbook of the Republic of China for 1982(1983,p.103,employment,and p.209,power consumption)and .tw;Korea:www.nso.go.kr/eng;Chinese data for 1987/1991are from China Statistical Yearbook (2000,pp.55,118,239,and 289);data for 1997/2001are from Table 1.Table 1Chinese GDP and related data,official and alternate figures,1998–2001(percentage change)1998199920002001Cumulative growth (1998–2001)Real GDPOfficial7.87.18.07.934.5AlternateÀ2.0/+2.0À2.5/+2.0 2.0/3.0 3.0/4.00.4/11.4a Energy useÀ6.4À7.8 1.1 1.1À5.5Urban formal employment2.3 1.6 1.2 1.20.8Consumer price index À0.8À1.40.4À0.5À2.3Figures for 2001cover only the first two quarters.The cumulative growth calculations assume no change for the second half of 2001.Alternate figures are author’s guesses —see text.Sources:Data for 1997–2000are from China Statistical Yearbook (2000,p.21,official real GDP,and p.118,urban employment)and from China Statistical Abstract (2001,p.130,energy,and p.84,prices).Figures for 2000/2001are from China Monthly Indicators,vol.16(2001,July,pp.14,15,32,and 70).The energy data for 2000/2001refer to production rather than consumption.a Endpoints of cumulative growth range based on low and high annual growth figures.T.G.Rawski /China Economic Review 12(2001)347–354349decline in the ratio of consumption spending to income —the exact opposite of what the retail sales data imply.rmation from Chinese commentariesBeginning in 1998,Chinese analysts complain that the statistics system has become enmeshed in a ‘‘wind of falsification and embellishment’’[jiabao fukuafeng ].ExtensiveTable 3Growth of retail sales and per capita income and expenditure,1997–2001(percentage change,nominal amounts)1998199920002001Cumulative growth (1997–2001a )Aggregate retail sales6.8 6.89.710.338.0Urban dataRetail sales7.17.110.611.641.6Per capita aIncome5.27.97.36.730.0Living expense3.4 6.58.24.624.6Rural dataRetail salesCounty5.2 5.78.39.331.6Below county7.0 6.68.37.432.7Per capita aNet income3.4 2.2 1.9À7.5À0.4Cash outlaySeries A0.8À0.9À8.5À6.8À14.8Series BÀ1.5À1.5À0.7À6.8À10.2Cash outlay for consumptionSeries A0.2 1.412.2 6.621.5Series B À1.7À0.8 5.9 6.610.1Figures for 2001cover only the first one or two quarters.Calculated values for cumulative growth assume no change for the remainder of 2001.Sources:Data for retail sales are from China Monthly Indicators,vol.16(2001,July,p.34).Urban income data for 1997/2000are from China Statistical Abstract (2001,p.94)and measure total income.The figures for 2000/2001are from China Monthly Indicators,vol.16(2001,July,p.88)and cover two quarters of 2001and refer to disposable income.Rural income data for 1997/2000are from China Statistical Abstract (2001,p.100)and measure net income.The figures for 2000/2001are from China Monthly Indicators,vol.16(2001,July,p.88)and measure cash income and cover only the first quarter of 2001.Urban outlays for living expenses from China Statistical Abstract (2001,p.93)and (for the first half of 2001)from China Monthly Indicators,vol.16(2001,July,p.81).Rural cash outlay and cash outlay for consumption:Series A is from China Monthly Indicators,vol.16(2001,July,pp.88–89).Series B is from China Statistical Abstract (2001,p.98,for 1997/2000);the figure for 2000/2001is taken from Series A.a Indicates data from household surveys.T.G.Rawski /China Economic Review 12(2001)347–354350T.G.Rawski/China Economic Review12(2001)347–354351 commentary in Chinese sources,including many specific and detailed accounts,6leaves no room to doubt that intentional falsification of economic performance indicators is common-place throughout the business community and at every level of government.The result is ‘‘universal falsification of statistics,as a‘statistical bubble’works its way up through the system,and provides mistaken reportage to the decision-making levels’’(Meng,1999,p.78). Premier Zhu Rongji complained in March2000that‘‘falsification and exaggeration are rampant’’(Nation Moves Boldly Forward,2000,p.5).Starting in1998,the National Bureau of Statistics(NBS)has rejected provincial data on economic growth,which it dismisses as‘‘cooked local figures’’(Xu,1999).Despite recent efforts to create statistical networks that bypass local,and provincial governments,the Bureau lacks the capacity to collect data outside normal information channels,particularly since survey research remains subject to interference from lower-level officials(e.g.,Hu,Chen,& Zhou,2000,p.24).Chinese policy discussions often ignore the official growth scenario.A July2001 account cites Wu Jinglian’s view that‘‘China has reversed its downward momentum in economic growth,which started in1997’’(Factors Favour Economy in Latter6Months, 2001).An August2001summary of views on fiscal policy notes that deficit spending ‘‘was introduced in1998to overcome insufficient domestic demand and dwindling exports,’’and then observes that because‘‘the economy has been revived,some economists say that the positive policy should be weakened’’(Jia,2001,p.1).But official projections show that growth in the‘‘revived’’economy of1999/2001is slower than in1997and no greater than in the endangered economy of1998.These(and other) texts suggest that prominent Chinese economists base their analysis on private maps of recent trends that differ substantially from the official picture sketched in Table1.In addition,many Chinese accounts directly contradict official figures.For example:‘‘Per capita income in urban and rural areas continued to fall in the first quarter of this year’’(Wang,1999).‘‘In October(1999),66per cent of[apparently urban]consumers said their household incomes had either remained unchanged or had decreased during the previous12 months’’(Bu,1999).‘‘In recent years,rural incomes have gone down year by year[zhunian xiajiang]’’(Wang,2000).4.Toward an alternate view of recent GDP growthSince abandoning provincial growth reports,the NBS has offered no public explanation of how its central office derives the figures that serve as official estimates of China’s national growth.Pressure to affirm official growth targets overwhelms local and provincial statistical bureaus,Chinese economic analysts,and even international bankers and market researchers whose firms pursue business ties with Chinese government agencies.Can we believe that the central offices of the NBS remain untouched by these circumstances?6For further examples and discussion,see Rawski(2001a,2001b).For readers who share this author’s discomfort with the official data,analysis of recent economic trends must begin by exploring alternatives to the official figures in Table 1.The size and diversity of China’s economy pose formidable obstacles to any such effort.7Nonetheless,China’s civil aviation industry offers a starting point for reassessing recent GDP growth.Airline travel appeals to a high-income clientele.Since rising inequality is a prominent feature of China’s economy in the 1990s (e.g.,Xu &Zou,2000),income growth among the airlines’prosperous clientele surely exceeded the norm,probably by a large margin.A fierce price war slashed ticket prices during 1998.8Airlines routinely offered discounts of 30–40%to travelers on domestic routes.With customers’incomes rising and ticket prices plunging,passenger traffic should have grown well ahead of disposable income and aggregate consumption,the largest components of aggregate income and expenditure.Yet the data for 1997/1998show that passenger miles rose by only 2.2%on domestic routes and 3.4%overall.9In the absence of major shifts in the structure of GDP,the elementary economics of demand and consumption points to 2.2%as a generous upper bound for overall real growth during 1997/1998.Declining energy use,output reductions in many branches of industry,mass layoffs,widespread excess capacity,inventory accumulations,and the impact of major floods make this a far more plausible measure of 1997/1998GDP growth than the official figure of 7.8%.And 2.2%is an upper bound.The actual result could have been far lower,perhaps even negative.The (entirely plausible)qualitative picture presented in Chinese reports indicates that GDP growth declined slightly in 1998/1999and improved thereafter.The continuation of excess supply,downward price pressure,near-zero employment creation,widespread excess capacity,inventory build-up,and large-scale accumulation of idle bank deposits indicate that real growth remains well below the 7%level needed to absorb new urban labor force entrants (Ge,1999).These considerations underline the proposed alternate figures for GDP growth shown in Table 1.These figures represent little more than guesses about China’s recent GDP performance.They are not firmly grounded in empirical data.But unlike the official figures,the alternate series does seem consistent with Chinese policy discussions and with official data on changes in employment,prices,and energy consumption.Official performance measures for recent years imply that China’s economy has entered an unprecedented interlude that combines high-speed growth with declining energy use,9Note that both the number of overseas travelers arriving in China and China’s income from international tourism increased during 1997/1998,although more slowly than in prior years (Zhongguo tongji [China Statistics ],no.11,2000,p.48).8In February 1999,‘‘the CAAC [Civil Aviation Administration of China]and the State Development Planning Commission issued an urgent circular that put a halt to selling domestic air tickets at unreasonable discount prices’’(Zhao,1999).7Commenting on an earlier paper (Rawski,2001a),an NBS official said something like:‘‘If you believe that we at NBS cannot measure China’s GDP,what makes you think you can do better?’’T.G.Rawski /China Economic Review 12(2001)347–354352T.G.Rawski/China Economic Review12(2001)347–354353 falling prices,minimal employment growth,widespread excess supply,rampant over-capacity,low expectations,and large-scale pump-priming.Even though recent growth claims defy economic logic and clash with a broad array of credible information from Chinese sources,economists both within and outside China have continued the long-standing practice of routinely adopting official figures.This‘‘business as usual’’approach is a recipe for bad policy and flawed research.The alternative is to hypothesize that the NBS has run afoul of the same political pressures that have caused local authorities to become‘‘obsessed with...GDP growth rates—the leading criteria for evaluating cadre performance’’(Gilley,2001,p.18),to conclude that official data showing7–8%real GDP growth for recent years reflect official objectives rather than economic outcomes,and to continue the search for alternate figures that can provide a realistic appraisal of China’s recent economic performance. ReferencesBing,L.(2001,February13).Deposits up as income growth slows.China Daily,1.Bu,R.(1999,December6).Increased renting expected.China Daily Business Weekly,6.China monthly economic indicators,vol.16.(2001,July).Beijing:National Bureau of Statistics.Factors favour economy in latter6months.(2001,July30).China Daily,4.GDP growth expected to reach8per cent.(2000,November24).China Daily,1.Ge,Y.(1999).Fangfan he huajie shehui fengxian—1999—nian Zhongguo jiuye zhengce xuanzi(Prevent and resolve social risk—China’s employment policy choices for1999).Beijing:Development Research Center. Gilley,B.(2001,July12).Breaking barriers.Far Eastern Economic Review,14–19.Hu,S.,Chen,X.,&Zhou,H.(2000).On rural statistics.Zhongguo tongji(China Statistics)(6),24–26.Jia,H.(2001,August7–13).Rethink on fiscal policy.China Daily Business Weekly,1and24.Maddison,A.(1998).Chinese economic performance in the long run.Paris:OECD.Meng,L.(1999).Analysis of economic conditions and policies during the past several years.Gaige(Reform)(3), 73–82.Meng,L.,&Wang,X.(2000).An estimate of the reliability of statistical data on China’s economic growth.Jingji yanjiu(Economic Research)(10),3–13.Nation moves boldly forward.China Daily(2000,March6),5.Ohkawa,K.,&Shinohara,M.(Eds.)(1979).Patterns of Japanese economic development:a quantitative appraisal.New Haven,CT:Yale University Press.Rawski,T.G.(2001a,January–February).China by the numbers:how reform has affected China’s economic statistics.China Perspectives(also available from /~tgrawski/papers2000)(33),25–34. Rawski,T.G.(2001b).China’s GDP statistics:a case of caveat lector?Available at:/~tgrawski/ papers2001.Abbreviated version published as The credibility gap:China’s recent GDP statistics.China Economic Quarterly,5.1,18–22.Ren,R.(1997).China’s economic performance in international perspective.Paris:OECD.Smith,C.S.(2001,July18).China reports7.8%growth in economy.New York Times,W1.Taiwan,Yearbook.(1983).Zhonghua minguo71—nian tongji tiyao(Statistical yearbook of the Republic of China for1982).Taipei:Xingzheng yuan zhuji chu.Tao,C.(2000).Influence of widening income disparities on the operation of China’s economy.Jiage lilun yu shijian(Price Theory and Practice)(10),13–14.Wang,C.(1999,April29).State to bolster demand.China Daily,1.Wang,X.(2000).Analysis of the current economic situation.Caimao jingji(Finance and Trade Economics)(4), 5–10.Xu,B.(1999,February 15).Statisticians seek reliability.China Daily Business Weekly ,1.Xu,L.C.,&Zou,H.(2000).Explaining the changes of income distribution in China.China Economic Review ,11(2),149–170.Zhang,P.(2000).Income differentials,interest rate,and consumption.Caimao jingji (Finance and Trade Economics)(8),16–22.Zhao,H.(1999,August 18).Aviation sector to make profit.China Daily ,2.Zhongguo tongji nianjian 1999(China statistical yearbook 1999).Beijing:Zhongguo tongji chubanshe.Zhongguo tongji nianjian 2000(China statistical yearbook 2000).Beijing:Zhongguo tongji chubanshe.Zhongguo tongji zhaiyao 2001(China statistical abstract 2001.)Beijing:Zhongguo tongji chubanshe.T.G.Rawski /China Economic Review 12(2001)347–354354。

商务英语谈判unit 6 Price Bargaining[精]

Our counteroffer is in line with the international price. If you can accept, we shall persuade our customers to place orders with you.
9.按这个价格，我们不能说服用户购买你们的产品。 We are not in a position to purchase our end-users to
Unit 6 Price Bargaining
9. We hope we could conclude business with you at something near our level. 我们希望以接近我们的价格水平与你方达成此笔交易。
10. I’m afraid we will have to call the whole deal off if you still insist on your original quotation. 如果你们仍然坚持你们原先的报价，恐怕我们只好取消整笔交易了。
Unit 6 Price Bargaining
IV. Keys to Exercises
1. Translate the following sentences into Chinese
1. It would be very difficult for us to push any sales if we buy it at this price. 如果我们以这个价格购买，我们促销产品将会非常困难。
2. Your price is much higher than we expected.
3. The price of your goods is about 15% higher than that of other manufactures.

ch07SECURITY-MARKET INDICATOR SERIES(投资学,赖利)

Factors in Constructing Market Indexes
The sample of firms to include

What is the intended population that the sample is to represent? How large a sample is needed for the index to be representative? Should the weighting system be based on price, total firm value, or equally weighted? How should the values of the index be reported and tracked (arithmetic or geometric mean)?
Sample used is limited

30 non-randomly selected blue-chip stocks are not representative of the 1800 NYSE listed stocks Similar to assuming an investment of one share per stock Places more weight on higher-priced stocks rather than those with higher market values Introduces a downward bias in DJIA by reducing weight of growing companies whose stock splits
Chapter 7 Questions

企业降成本规则

General Guidelines and Rules - v1.0 May 29th, 2008
Workstream Members and their Roles/Responsibilities (1/3)
Not a hyerarchical report
Local Local Leaders Leaders
Workstream Workstream Leader Leader Sponsor Sponsor 支持者 General Manager (Site) Team Team Members Members Local Local Coordinators Coordinators
PMO
Source: PMO
Recommend. PMP
• PP impact of workstream globally • ICS Impact • Net impact • Plan for 2009
Local coordinators
Team members (Global and local)
• Contact/involve additional resources (within his/her specific areas) to • PP impact of schedule/progress in a project implementation workstream • Prepare and present analyses assigned to him/her individually and with its globally sub-team help • ICS Impact • Identify additional opportunities to generate EOP/FCF impact • Net impact • Participate in the jour-fix plant meetings and in the related problem-solving • Plan for 2009 sessions

论文写作与研究第4章文秋芳著

PROCEDURES FOR REVIEWING THE LITERATURE
Beginning researchers often feel overwhelmed once they enter the library because of the vast amount of materials surrounding them. This section recommend to you a set of procedures which can help you reviewing the literature effectively.
Constructing a working bibliography
What is working bibliography? A tentative list of references for the preparation of reviewing literature. It serves two purpose. Firstly, it can be used as a blueprint to guide your review of the literature. Secondly,It can be taken as a resource bank from which you construct the section of references for your thesis in the end.
There are 4 main kinds of sources for locating reference.① Indices ②unpublished papers ③Journals ④Books
4.1.1Indices

高二英语经济指数单选题50题

高二英语经济指数单选题50题1. The _____ measures the market value of all final goods and services produced within a country in a given period.A. GDPB. CPIC. PPID. PMI答案：A。

解析：GDP（国内生产总值）是衡量一个国家在一定时期内生产的所有最终商品和服务的市场价值的指标，这是GDP的基本定义。

选项B，CPI 消费者物价指数）主要衡量消费者购买一篮子商品和服务的价格变化。

选项C，PPI（生产者物价指数）反映生产环节价格水平。

选项D，PMI（采购经理人指数）反映制造业或服务业的商业活动情况。

2. Which economic index is mainly used to reflect the inflation rate at the consumer level?A. GDPB. CPIC. PPID. PMI答案：B。

解析：CPI是主要用于反映消费者层面通货膨胀率的经济指数。

通货膨胀意味着物价的普遍上涨，CPI通过追踪一篮子消费者商品和服务的价格变化来衡量这种上涨程度。

选项A的GDP是关于生产的价值衡量。

选项C的PPI侧重于生产环节价格。

选项D 的PMI是关于商业活动的指数。

3. China's GDP growth rate has been stable in recent years. GDP stands for _____.A. Gross Domestic ProductB. General Domestic ProductC. Grand Domestic ProductD. Global Domestic Product答案：A。

解析：GDP的全称是Gross Domestic Product（国内生产总值）。

这是固定的经济术语表达。

上调产品价格英语作文

上调产品价格英语作文标题，The Impact of Price Adjustments on Products。

In today's global market, the adjustment of product prices plays a crucial role in shaping consumer behavior, market competition, and overall economic dynamics. Understanding the implications of such adjustments is essential for businesses, consumers, and policymakers alike. This essay explores the various aspects of priceadjustments on products, analyzing their effects ondifferent stakeholders and the broader economy.Firstly, price adjustments influence consumerpurchasing decisions. When prices decrease, consumers may perceive products as more affordable, leading to increased demand and higher sales volumes. Conversely, priceincreases may deter consumers, causing a decline in demand and sales. For example, during promotional periods or sales events, discounted prices often attract more customers, stimulating purchasing activity. On the other hand, suddenprice hikes may lead consumers to seek alternative products or delay their purchases, affecting businesses' revenue streams.Moreover, price adjustments impact market competition. In highly competitive industries, pricing strategies are crucial for companies to gain a competitive edge. Lowering prices can help businesses attract more customers and gain market share, while raising prices may signal product differentiation or quality improvements. However, excessive price competition can lead to price wars, where companies continuously lower prices to undercut rivals, ultimately eroding profitability for all players involved. Therefore, strategic price adjustments are essential for companies to maintain their competitive positions while ensuring sustainable profits.Furthermore, price adjustments have broader economic implications. Inflationary pressures, changes in production costs, and shifts in consumer preferences can all influence price dynamics. Central banks closely monitor inflation rates and consumer price indices to gauge economic healthand adjust monetary policies accordingly. When prices rise persistently, central banks may raise interest rates tocurb inflation, which can impact borrowing costs for businesses and consumers. Conversely, deflationarypressures may prompt central banks to implement expansionary monetary policies to stimulate spending and investment.Additionally, price adjustments can affect income distribution and societal welfare. Lower prices may benefit consumers, particularly those with limited purchasing power, by making essential goods more affordable. However, price reductions may also lead to lower revenues for producers, potentially impacting wages and employment in affected industries. Conversely, price increases may boostprofitability for businesses but can burden consumers, especially if wages do not keep pace with rising costs. Policymakers often face the challenge of balancing the interests of consumers and producers while promotingoverall economic stability and social equity.In conclusion, price adjustments on products havemultifaceted effects on consumers, businesses, and the economy as a whole. Understanding the dynamics of pricing mechanisms is crucial for stakeholders to make informed decisions and navigate market uncertainties effectively. By analyzing the impact of price adjustments from various perspectives, policymakers can develop strategies to promote sustainable economic growth, enhance market competition, and improve societal welfare.This essay draws on various examples and analyses to illustrate the complex interplay between price adjustments and their consequences, providing valuable insights into the dynamics of modern markets. As businesses continue to adapt to evolving consumer demands and competitive pressures, strategic pricing strategies will remain essential for driving growth and maintaining profitability in an increasingly dynamic global economy.。

Commodity Prices, Monetary Policy, and Inflationw

POLICY CORNERCommodity Prices,Monetary Policy,and Inﬂation wJOSE ´DE GREGORIO nDuring the second half of the 2000s,the world experienced a rapid and substantial rise in commodity prices.This shock posed complex challenges for monetary policy,in particular because of the signiﬁcant increase in food and energy prices,and the repercussions they had on aggregate inﬂation measures.This paper discusses the role of commodity price shocks (CPS)in monetary policy in the light of recent episodes of such shocks.It begins by discussing whether monetary policy should target core or headline inﬂation,and what should be the role of CPS in setting interest rates.It is argued that there are good reasons to focus on headline inﬂation,as most central banks actually do.Although core inﬂation provides a good indicator of underlying inﬂation pressures,the evolution of commodity prices should not be overlooked,because of pervasive second-round effects.This paper reviews the evidence on the rise of inﬂation across countries and reports that food inﬂation,more than energy inﬂation,has relevant propagation effects on core inﬂation.This ﬁnding is particularly important in emerging market economies,where the share of food in the consumer basket is signiﬁcant.The evidence also shows that countries that had lower inﬂation during the run up of commodity prices before the globalw Prepared for the Conference on Policy Responses to Commodity Price Movements ,organized by the IMF and the Central Bank of Turkey,April 2012.Part of this paper was written while the author was a visiting scholar at the Research department of the IMF,and he is very grateful for its hospitality.The author is also very grateful for discussions with and suggestions from Larry Ball,Pierre Olivier Gourinchas,Thomas Helbling and Ayhan Kose,and conference participants,as well as for the valuable comments and assistance from Felipe Labbe ´.n Jose De Gregorio is professor at the Economics Department of the Universidad de Chile.He was governor of the Central Bank of Chile,and previously served as Minister of Economy,Mining and Energy.IMF Economic Review Vol.60,No.4&2012International Monetary FundCOMMODITY PRICES,MONETARY POLICY,AND INFLATIONcrisis had more inﬂation in the subsequent rise after the global crisis,suggesting that part of the precrisis inﬂationary success may have been because of repressed inﬂation.This paper also discusses other factors that may explain different inﬂationary performances across countries.[JEL E31,E5,E61]IMF Economic Review(2012)60,600–633.doi:10.1057/imfer.2012.15; published online9October2012T he inﬂationary consequences of rising commodity prices have representeda key challenge for monetary policy.Rising commodity prices result in rising inﬂation,but at the same time it can have different implications on output and income depending on whether the country is an exporter or importer of commodities.For the purposes of this paper I will consider an economy that is a net importer of commodities,and local demand for the commodity is signiﬁcant.This commodity may be an intermediate input,such as oil,or aﬁnal good,such as gasoline or food.Therefore,a commodity price shock(CPS)is an inﬂation shock and has negative effects on income at the same time.I will not focus on natural resource abundant economies,where the rise in commodity prices represents mainly a positive wealth effect,in particular when the fraction of the production of the commodity consumed at home is small.1 Considering countries that are abundant in natural resources that are not consumed domestically would add additional channels,which can be treated separately.For example,a CPS generates mostly a wealth effect,with effects on the exchange rate and aggregate demand.The issue becomes how to manage monetary andﬁscal policy to smooth the CPS.2In this paper I focus on managing monetary policy when confronting commodity price inﬂation shocks.Let us consider,for example,the case of oil.Inﬂation rises through the direct effects on gasoline prices and indirectly through a rise in costs.In addition,an oil price shock is analogous to a negative productivity shock. Therefore inﬂation rises and output slows down.Although in principle one could think that the implications for monetary policy are ambiguous,they are not.Some degree of accommodation may be needed,and this depends on the output effects,and on the size and duration of the shock,but the direction of monetary policy is to reduce the monetary impulse.3 The inﬂationary effect of an oil price shock calls for a tightening of monetary policy.The effects on activity also calls for tightening,since the effects on output are mostly a fall in full-employment output,since the energy shock is equivalent to a negative productivity shock,and hence the output gap increases,4inducing further inﬂation pressures.Atﬁrst sight, this prescription may look somewhat counterintuitive.Indeed,a negative1This is,for example,the case of soy beans in Argentina,copper in Chile,or oil in Nigeria.2For details on managing the copper price boom in Chile,see De Gregorio and Labbe (2011).3See,for example,Medina and Soto(2005)and Batini and Tereanu(2010).601output shock should reduce inﬂation pressures.However,an oil price shock represents a shock to full employment output ,reducing the output gap and generating inﬂation beyond its direct effects.However,there are some caveats to this conclusion.As I discuss later on,there are mitigating demand effects,which could be very important in the case of a food price shock,since the commodity price boom may result in a decline in the terms of trade and national income.In addition,a credible inﬂation-targeting regime may need a much smaller response when facing transitory supply shocks,and indeed as I document in this paper,the fact that the recent oil shocks have had small effects on inﬂation and activity hinges to a large extent on the conduct of monetary policy geared toward price stability.The recent experience with CPS has been very signiﬁcant.In the mid-2000s all commodity prices started rising sharply (Figure 1).The initial reaction in policy and academic circles was how to react to a transitory CPS.In this case,there were good reasons to think that a short-lived price shock should not require decisive policy reaction.However,the reality turned out to be quite modity prices kept rising to unprecedented levels and the change was much more persistent.Only at the peak of the subprime crisis,late 2008,commodity prices suffered a major reversal,but even in a world that had not fully recovered from the crisis,commodity prices rose again.The magnitude and persistence of high commodity prices were not expected some years ago,and hence,it is not appropriate to conduct monetary policy under the assumption that the shock is temporary.Today it is better to work with the assumption that there has been a persistent change in the relative price of commodities.Economies must adjust to these new relative prices,but during the adjustment monetary policy must prevent increases in inﬂation that may end up being too costly to revert.ExcessiveFigure modity Prices20406080100120C u r r e n t U S DI n d e x 2000=100, c u r r e n t U S D Non-energy commoditiesWTI oil price Source:World Bank,GEM Data.The shaded areas correspond to the two-year booms.Jose´De Gregorio 602COMMODITY PRICES,MONETARY POLICY,AND INFLATION propagation feeds back into prices through indexation and rising inﬂationary expectations.A key issue on the impact of a commodity price boom is on its sources. Historically,many shocks,in particular oil price shocks,have been related to supply disruptions.Hence,they have tended to produce high inﬂation and falling output.This time,however,its source has been rising world demand for commodities,especially from emerging markets.Indeed,the rise in commodity prices can be interpreted as an increase in the world relative prices of food and energy,which have been particularly strong in countries with a high share of consumption in food and energy.This is consistent with the overall view that the commodity price boom came with an increase in world inﬂation and without serious recessionary effects,despite those stemming from the globalﬁnancial crisis.An additional factor that has ameliorated the negative output effects of rising commodity prices has been the fact that most emerging markets are exporters of some commodity,and hence,this has resulted in an improvement in emerging markets’terms of trade.This has clearly been the case in most Latin American countries.These two commodity price booms have resulted in higher inﬂation,and the purpose of this paper is to analyze some relevant issues from the standpoint of monetary policy.For analytical purposes,I will deﬁne two commodity price booms,one ranging from the third quarter of2006to the third quarter of2008, and the other from the third quarter of2009to the third quarter of2011.The reason to deﬁne both time spans this way was to have equally sized episodes (nine quarters),which should facilitate comparisons.CPS result in an increase in food and energy inﬂation.They are mechanically passed on to headline inﬂation.The magnitude of these effects depends on the weight of each component in the CPI.But in addition,there are the so-called second round effects,which refer to the indirect impact on other prices,through cost-push or demand-pull pressures.Figures2and3 show the correlation between food and energy inﬂation with headline and core inﬂation for a sample of34countries in both episodes.5It is interest-ing to note that in most countries there was a signiﬁcant increase in food and energy inﬂation,varying across countries and episodes.The simple correlation shows that the rise in food and energy prices had effects on headline inﬂation.The increase in food prices also had important second-round effects, which,as theﬁgures show,are already affecting core inﬂation two quarters into the shock.The second-round effects of energy are weaker,in particular during the second episode.This is consistent with the evidence—discussed 4The output gap is the difference between current output and full-employment output,so an increase in the gap means an increase in economic activity.5The sample is based on data availability at the MEI-OECD database.The advantage of these data is that classiﬁcation is the same across countries,but it only includes OECD countries.The data are available at /index.aspx?DatasetCode= MEI_PRICES.603later—on the relevance of food vis-a-vis energy in the propagation of inﬂation.The paper follows in two main sections.Section I is devoted to an analytical discussion on commodity prices and monetary policy.In the ﬁrst part I take on the issue of whether the inﬂation target should be set in terms of core or headline inﬂation,and regardless of the target,how monetary policy must react to rising commodity price inﬂation.Despite the fact that core inﬂation is a better measure of underlying inﬂation pressures,setting up the target in terms of headline inﬂation is desirable and it is the usual practice of central banks.In addition,ignoring the developments of headline inﬂation may lead to underestimation of future inﬂation when hit by long-lasting CPS.Then,I present a simpliﬁed model to discuss the channels through which commodity prices affect the economy and their implications for monetary policy.I distinguish the direct impact on inﬂation,and the impacts on full-employment output and aggregate demand.In Section II of the paper I look at the empirical evidence of the two episodes of commodity price booms.It reviews the literature on second-round effects and propagation,and presents new evidence on the relevance of food and energy in the propagation of inﬂation.The evidence shows that Figure 2.Change in Inﬂation:2006:Q3-2008:Q3Source:MEI-OECD data.Note:“Delta inﬂation”denotes the change in inﬂation (“top”-“bottom”)during episode.Jose´De Gregorio 604energy has very limited second-round effects,while those of food are much more important.The paper concludes in Section III with some ﬁnal remarks.modity Prices and Monetary PolicyIn this section I will discuss the role that CPS play on monetary policy.I will look at this issue in the context of an inﬂation-targeting central bank,which makes the price stability goal explicit by communicating a numerical inﬂation target.However,the points raised here could also be applied to all central banks with a clear mandate of price stability.In this framework I will assume that the central bank has an inﬂation target,deﬁned over some range of tolerance and a policy horizon.The policy horizon is the time period within which the central bank plans to correct deviations from the target.Since the central bank has to conduct monetary policy to achieve the target in the future,in order to fulﬁll the target on average over time,a key variable is the forecast that the central bank makes about the future path of inﬂation.Indeed,the central bank should pursue a policy that ensures that forecast inﬂation reaches the target in the policy horizon.Then,in practice the central bank has as an intermediate target its forecast inﬂation at the policy horizon.Figure 3.Change in Inﬂation:2009:Q3-2011:Q3Source:MEI-OECD data.Note:“Delta inﬂation”denotes the change in inﬂation (“top”-“bottom”)during MODITY PRICES,MONETARY POLICY,AND INFLATION605Jose´De GregorioBefore proceeding with a review of the literature and policy discussion I will discuss a couple of analytical points regarding policy evaluation exercises.Most of them are done in the context of dynamic stochastic general equilibrium(DSGE)models,and the structure is a sticky price model along the lines of the new-Keynesian models of policy evaluation(Galıand Gertler, 2007).In order to perform the policy evaluation,these models maximize welfare,which is typically the utility of the representative consumer.Then, the maximization of the welfare function can be converted,to a second-order approximation,to the traditional minimization of a quadratic loss function that depends on deviations of inﬂation(p)from its target( p),and deviations of output from the full-employment output level(output gap,y- y).6The speciﬁc inﬂation rate that enters the loss function should be the index to target.However,if the quadratic loss function is assumed rather than derived from the consumers’utility function,the index to target becomes an assumption rather than an implication of the model.But even when the loss function is derived from a welfare function,the approximation is very speciﬁc to the model’s assumptions,and evaluating different and more general environments is what the recent analytical work has done.Another,different,issue is how to conduct monetary policy in order to achieve the target,regardless of whether this is based on core or headline inﬂation.In general,the instrument to conduct monetary policy is the interest rate,and hence the question would be:how must interest rates react to CPS? Indeed this question has led to heated debate over whether a central bank that targets headline inﬂation should pay more attention to developments in headline or core inﬂation.7As aﬁrst approximation we can think that the central bank determines the interest rate according to some feedback rule,by which a given state of the economy implies a certain monetary policy stance.This rule should be consistent with the target.The Taylor rule is the most widely known among feedback rules,and adjusts the interest rate to the output gap and inﬂation deviations from the target.More elaborated rules also include other observed variables as well as the inﬂation forecast some periods ahead.For example, a central bank with a horizon of two years may use inﬂation one year or 18months ahead in the policy rule.Inﬂation forecast two years ahead should be equal to the target,so it should not enter the rule.Most standard models for policy evaluation consider different feedback policy rules,and then evaluate their relative performance in terms of welfare. In the context of this paper,the purpose would be to compare rules that use core inﬂation with rules that use headline inﬂation.However,this strategy has some limitations.First,the number of potential rules is unlimited,and indeed it is likely that a linear combination of the rules being examined may 6For a derivation of this approximation,see Woodford(2003)and Galı(2008).7See,for example,the debate between Paul Krugman and Lorenzo Bin Smaghi reported in Lenza and Reichlin(2011).606COMMODITY PRICES,MONETARY POLICY,AND INFLATIONbe superior.And second,central banks do not operate following mechanical rules.Rules,such as the Taylor rule,are a reduced form to interpret the behavior of monetary policy,even to calibrate models in central banks, but do not represent actual decision-making in central banks,nor optimal monetary policy.An optimal rule should be an interest rate path that maximizes welfare,and this can be better approximated with a path for the interest rate that ensures that the inﬂation forecast at the policy horizon equals the inﬂation target(Svensson,1999;Woodford,2007).In this context, monetary policy should react to all variables and shocks that affect the inﬂation forecast,which should equal the inﬂation target at the policy horizon.8In the remainder of this section I will look at the two separate questions of which index should be targeted,and how should monetary policy react to CPS.More concretely,the two questions with a summary of the answers are:What price index should a central bank target?Although initially the theory emphasized the use of a core price measure as a target,it seems more reasonable to use the headline measure,especially in inﬂation-targeting economies.More recent analytical developments show the advantages of targeting headline inﬂation.Should monetary policy respond to CPS?Regardless of the index used to target inﬂation,monetary policy should respond to CPS to stabilize prices,but the strength of the response depends on the characteristics of the economy as well as those of the speciﬁc shock.Nevertheless,core inﬂation is one of the best measures to evaluate the underlying inﬂation pressures.9What Price Index Should Central Banks Target?Academic research has learned a lot from actual policymaking in inﬂation-targeting countries,but has also had a profound impact on how monetary policy is conducted.Indeed,today most inﬂation-targeting central banks use DSGE models to evaluate policies,produce forecasts,and simulate the economy when facing different shocks.However,an area where deﬁnite prescriptions have been rather elusive and sometime at odds with the facts is on the relevant price index to deﬁne the inﬂation target.Some recent research isﬁnding more justiﬁcation for the current conduct of central banks, which usually aims to target headline CPI.Before analyzing the actual 8This type of models can also be used to deﬁne the optimal monetary policy strategy,for example,whether a strict inﬂation target is preferable,but in this discussion I will focus on ﬂexible inﬂation target regimes.9Indeed,in Spanish the translation of“core inﬂation”is“inﬂacio n subyacente”(underlying)rather than“inﬂacio n central.”607Jose´De Gregorioconduct of central banks,it is useful to start with the lessons taught by the academic literature.First of all,it is useful to clarify what I mean by core inﬂation.There are many different measures for core inﬂation.Measures differ signiﬁcantly across countries and they tend to be tailored to the reality of each particular case.The simplest one is just to exclude some goods that may have highly volatile prices,such as perishable foods.These goods may be affected by seasonal patterns or sudden and short-lived shocks.Of course,central banks should not pay attention to a spike in a price of one particular food item, which usually is reverted over a short period of time.However,given developments of recent years,it is more interesting and relevant to focus on the rate of inﬂation excluding energy and food.Within OECD countries inﬂation excluding food and energy ranges from60percent in the case of Poland,where food weighs24percent and energy16,to 84in the United States,with food and energy being about8percent of the CPI each.10The share of food is even higher in lower-income countries. In countries like Indonesia and the Philippines the share of food is about 40percent.The theoretical argument to target core inﬂation is relatively simple. Suppose there is set of goods whose prices are fullyﬂexible,while the rest of the prices are sticky.Stabilizing fully sticky price inﬂation will lead to no distortions in relative prices and full output stabilization.This point was formally shown in Aoki(2001).However,this result is very particular to the model,especially since there are no lags in monetary policy and no transaction frictions.More important,this framework has no second-round effects from shocks in theﬂexible price sector to sticky price inﬂation.In this case,targeting core inﬂation,deﬁned as the one that includes only sticky prices,is optimal.Indeed,Walsh(2011)argues that the justiﬁcation for focusing on core inﬂation relies on the idea that headline and core inﬂation have the same long-run mean,and noncore inﬂation has no long-run effects on core inﬂation.And this is the key assumption that is not warranted by theory and evidence,in particular in emerging market economies where food and energy account for a large fraction of the consumer basket.In the particular case of energy,theﬁrst thing that comes to mind is that it is a key intermediate good,and hence,a rise in oil prices should have an impact on the sticky price sector,so stabilizing headline inﬂation may prevent excessive second-round effects.In the case of food,three aspects deserve mention.First,many food products,for example grains,are intermediate inputs.Second,although agricultural commodities have deep world markets, there are enough distribution costs to make difﬁcult to think of those goods 10There are differences in the reported weights across different sources,which may be due to the exact index being used or the date when the weight is reported.Here I use2010weights for national CPI according to MEI-OECD.608COMMODITY PRICES,MONETARY POLICY,AND INFLATIONas having fullyﬂexible prices.Indeed,distribution costs have been one of the main reasons why there is only partial pass-through from exchange rates to domestic prices(Burnstein,Eichembaum,and Rebelo,2005).Finally,food prices are very important in the consumer basket of many emerging markets, so they may also have signiﬁcant effects on wage pressures,which also impinge on the overall price level.For all of these reasons,it is not clear that there is a case for ignoring commodity prices in the central bank target.The original work of Aoki(2001)has been extended in several dimensions to more realistic setups,such as the work by Huang and Zheng (2005)and Bodenstein,Erceg,and Guerrieri(2008).Theﬁrst paper assumes that all goods are produced in two stages,and both are characterized by sticky prices.Intermediate good prices are approximated by the PPI,while ﬁnal goods by the CPI.Given the feedback across sectors,the authors conclude that a reasonable rule should take into account both CPI and PPI inﬂation.Bodenstein,Erceg,and Guerrieri(2008)in turn analyze the case of energy as an input,and conclude that following a transitory energy shock,policies that react to forecast headline inﬂation rather than core inﬂation generate higher output and core inﬂation volatility.This paper, however,looks at a20percent shock in energy prices,which reverts to less than a half of it in theﬁrst year,much different to what we have seen in recent episodes.The assumption that imported prices are subject to pricing-to-market, something more realistic than assuming PPP,has been analyzed by Okano (2007).The paper shows the superiority of targeting CPI rather than PPI, as a proxy to inﬂation excluding commodities,when stabilizing output and inﬂation.There may be many other reasons that are likely to result in recommending targeting CPI over core CPI,such as the existence of wage stickiness,which may also generate second-round effects difﬁcult to unwind.A pervasive stickiness in countries with a history of high inﬂation is wage indexation to past CPI.Campolmi(2012)has analyzed the implications of wage stickiness and has shown that this feature allows rationalizing CPI inﬂation targeting.More recent research with a particular focus on emerging market economies has shown that food is a signiﬁcant component of their consumer baskets,much more than in industrialized countries.In a model where there are credit market frictions,namely that a fraction of consumers have no access to credit,Anand and Prasad(2010)show that the central bank should target headline rather than core inﬂation because of the distributional effects and the spillover from commodity prices to aggregate demand.In a related work,Catao and Chang(2010),based on the persistence of food inﬂation and the fact that food inﬂation is a good predictor of world inﬂation,show that targeting headline inﬂation is welfare superior.Their result is based on the fact that the share of food in the consumer basket of emerging markets is much higher than the world average,which may result in a food shock appreciating the currency and deteriorating the terms of609trade.A key novelty in this work is that the authors assume that the shock to food prices is persistent.In discussing optimal monetary policy for commodity exporting countries,Frankel(2010)has proposed targeting the domestic-currency price of exports,as a more moderate alternative to targeting the PPI. This would be similar to core inﬂation targeting,since monetary policy would not react to the prices of imported commodities,and all the comments I have made on core inﬂation targeting are still valid under this proposal. Although my focus is on commodity importers,this proposal has the additional problem that for commodity exporters,where the commodity has no relevant domestic consumption,monetary policy would cause excessive exchange-rateﬂuctuations.A CPS induces a currency appreciation,which under export price targeting would be reinforced by monetary policy tightening,with all the concerns around issues such a Dutch disease and currency appreciation.As I discuss in the next section,terms-of-trade shocks that affect aggregate demand require changes in the monetary policy stance under headline inﬂation targeting,but this response would be less aggressive than the one implied by export price targeting.Although there may be a case for targeting core inﬂation,it is interesting to note that26out of the27economies following formal inﬂation-targeting regimes use headline inﬂation(Hammond,2012).Moreover,there have been some changes in the index used to deﬁne the target,and all of these moves have been drifting away from core inﬂation targeting to headline inﬂation targeting.11This is the case of the Korean Republic,which moved from targeting core to headline inﬂation.Only the Central Bank of Thailand targets core inﬂation,but they are in a transition to targeting headline inﬂation.In the minutes of the monetary policy meeting of March they state: In regard to the monetary policy target for2012,the MPC[MonetaryPolicy Committee]viewed that the proposal to adopt headline inﬂation(annual average headline inﬂation of3.071.5percent per annum)asa monetary policy target remained ap propriate.In the long run,thiswould help enhance the effectiveness of monetary policy communicationand strengthen the anchoring of inﬂation expectations.The Ministry ofFinance and related agencies,after discussing the matter in accordancewith the cabinet resolution,agreed in principle on the adoption ofthe new target,but suggested the postponement of the change(y)Inorder to ensure a smooth transition,the MPC agreed to postpone theadoption of the new monetary policy target to a more ap propriatetime and retained the current target(quarterly average core inﬂationof0.5–3.0percent)for this year.11There are some countries that exclude the mortgage components and taxes from the index to target,in order to isolate inﬂation from monetary andﬁscal policy measures.This has been the case during some time in South Africa,Sweden,and the United Kingdom.The discussion in this section does not address those issues,but as the indices have been harmonized,most countries have eliminated those corrections,which in the past created sharp swings in headline inﬂation.610。

工程管理专业英语词汇

CMC—construction management contractor建設專案管理承包商
CAD—computer aided design電腦輔助設計
CPA--Certified public accounting特許公共會計師
AIA—American institute of architects美國建築師協會
Net future value淨終值
Numerous alternative plans眾多的備選方案
Network diagrams網路計畫圖
O
Overlap搭接，交疊on-site現場
Operation and maintenance managers運行與維護經理
On-site Installation現場安裝
Cost exposure附加成本
Critical path method關鍵線路法
Construction yard施工現場
D
detailed engineering design詳細的工程設計
design methodology設計方法
detailed design詳細設計
drilling and blasting鑽孔和爆破
The feasibility study report可行性研究報告
The state of economy經濟狀況
Turnkey project/contract交鑰匙工程/合同
Top-down design自上而下的設計
Technical feasibility技術可行性
Tangible asset有形資產
PERT—program evaluation and review technology計畫評審技術

企业对员工的月度绩效考核评估表Monthly Review Version1

月度目标：
How Employeeperformed against Objectives
员工根据目标设定的表现如何：
Objectives to be achieved for nextmonth
下一月度需要完成的目标：
Business Objectives & Reference Point /绩效目标及衡量标准[Your individual objectives should align with department objectives & strategies[你的绩效目标应与公司/部门的目标和战略相一致]
B
High Performer良好
在规定的时间内，达到或超过期望，提供高质量工作的员工Achieves an exceeds expectations and Objectives set within the required timeframe, high quality work rate
C
Average Performer一般
1,
2,
3,
4,
[Were the desired outcomes exceeded, met or not achieved? Please give specific examples]
[超过、达到、未完成预定目标？请列举具体事例]
1,
2,
3,
4,
Outline the Objectives you plan to achieve during the next quarter
Key Strengths /主要优势
Key Development Needs /主要改进方面
[ng performance competencies /绩效能力提升]

月度效应

Journal Of Financial And Strategic DecisionsVolume 8 Number 1 Spring 1995THE MONTHLY EFFECT IN INTERNATIONAL STOCK MARKETS:EVIDENCE AND IMPLICATIONSDenis O. Boudreaux*AbstractA monthly effect has been reported in several international stock markets. This study investigatedseven countries’ stock markets that have not been studied thoroughly. Three of the seven countries’markets had a monthly effect. An inverted monthly effect was found in a Pacific basin market. It was alsodetermined that the January effect, although significant, was not capable of explaining the presence ofmonthly effect where they exist.INTRODUCTIONCapital market efficiency has been a popular topic for teaching and empirical research since Fama [3, 4] described the theoretical analysis of market efficiency (Efficient Market Hypotheses). Subsequent to the Fama studies a great deal of research was devoted to investigating the randomness of stock price movements for the purpose of demonstrating the efficiency of capital markets. More recently, however researchers have demonstrated market inefficiency by identifying systematic variations in stock returns. Some of the more important systematic variations, or anomalies as they are referred to are Value Line’s investment recommendations, the small firm effect and extra-ordinary returns related to the time or the calendar effect.The existence of calendar or time anomalies is a contradiction to the weak form of the Efficient Market Hypothesis (EMH). The weak form of the EMH states that the market is efficient in past price and volume information and stock movements cannot be predicted using this historic information. This form infers that stock returns are time invariant, that is, there is no identifiable short-term time based pattern. The existence of seasonality or monthly effects in domestic and international markets suggests a market inefficiency, in that investors should be able to earn abnormal rates of return incommensurate with the degree of risk. For a complete explanation of the characteristics of each efficient market form see any modern investments text (Francis 1993).The purpose of this study is to investigate the existence of a monthly pattern or monthly effect in investment returns for seven different countries’ stock market indexes. In this study the investigation of the monthly effect is extended by examining the return patterns of markets that have not been thoroughly investigated. The countries being studied are Denmark, France, Germany, Norway, Singapore/Malaysia, Spain and Switzerland. The results of this study and others like it should have important implications for financial managers, financial counselors and investors interested in international diversification. Its relevance lies in the direct bearing of its results on the timing and nature of investment decisions.PRIOR RESEARCHStudies in time efficiency have found seasonality (January Effect), day of the week effect and intra-monthly patterns in both domestic markets and international markets. In the United States, stock returns in the first month of the year have been statistically different (larger) from the other months (Rozeff and Kinney 1976). Some *University of Southwestern Louisiana1516Journal Of Financial And Strategic Decisionsexcellent studies have been performed, and seasonal influences found, in specific international markets: in Australian markets (Officer 1975); in Italian capital markets (Barone 1990); evidence in the United Kingdom (Lewis 1989); in Canadian stock prices (Tinic, Barone-Adesi and West 1990) and in the Tokyo Stock Exchange (Aggarwal, Rao and Hiraki 1990). Significant seasonality in major industrial foreign countries were found using both non-parametric and parametric tests (Gultekin and Gultekin 1983).Additionally, empirical investigations have provided convincing evidence that there are day-of-the-week (week-end effect) effects in United States stock returns. Mondays average returns have been found to be negative (Smirlock and Starks 1986). A week-end effect in the return distributions of several foreign countries was also identified (Jaffe and Westerfield 1985). Studies have also been done to determine if there is an intra-monthly anomaly. Ariel [2] documents a monthly pattern in United States stock index returns. Stocks were found to earn a positive average return in the beginning and during the first half of calendar months and zero average returns during the second half. A weak monthly effect has also been observed in foreign countries (Jaffe and Westerfield 1989). Australia, United Kingdom and Canada had patterns consistent with Ariel’s findings in the United States. Japan, however, had a inverse effect. There remains a need in our fast changing global economy for a study of the monthly effect for international markets for which analyses are incomplete.METHODOLOGY AND RESULTSSeasonality as well as the monthly effect is more easily detected in market indexes or large stock portfolios than in individual share prices (Officer 1975). Stock market returns in this study are computed from the indexes reported by Morgan Stanley Capital International Perspective (CIP). CIP is published by Capital International, S.A., headquartered in Geneva, Switzerland. These indexes are performance measurement bench marks for global stock markets and are generally accepted performance measurements. The CIP indexes represent approximately 65 percent of the total market value of all shares traded in the countries.CIP indexes are market-weighted averages without dividends yields. They report closing prices in local currencies. The weighing scheme of an index may effect the results of empirical studies. Analysis performed with data that uses equal weights indicate statistically significant seasonality in U.S. capital markets (Rozeff and Kinney 1976). Equal weighing schemes place a greater weight on small firms than a market weighted approach. Considerable analyses have been performed to investigate the inverse relationship between firm size and stock returns. Domestic studies have linked much of the January effect to the small firm (Kiem 1983). International studies have found that small firms achieve higher rates of return than large companies, with this effect being particularly evident in the month of January (Aggarwal, Rao and Hiraki 1990). For distinguished work on the “January Effect” see Tinic & West [16]. Therefore, utilization of an equal-weighing index in performing statistical analyses will magnify anomalies related to small firms.In the following analysis it is assumed that stock prices or returns within each yearly account follow a geometrical random walk, that is:Equation 1Return t = ln (Index t / Index t-1) = a + u twhere:Return t is the continuously compounded rate of change in the stock index. Index t is the stock market index at time t, a is a constant value and u t is a normal random variable with a mean of zero. This of course implies that the average rate of change of a stock index is equal for every month of the year.The sample parameters are the CIP reported index values for the time periods studied covering the period from March 4, 1978 through December 30 1992, reported in local currencies for the seven countries. The returns are computed as percent change in the price index. Letting P i,t denote the price index of stock i at time t, then:The Monthly Effect In International Stock Markets: Evidence And Implications17 Equation 2R i,t = (P i,t) - (P i,t-1) * (1 / P i,t-1)where:P i,t is the price of the ith index at time t. In the calculation of returns, t represents two distinct time periods, t1 is the index value after the first four trading days and t2 is the second to last trading day of the month. To allow comparison with Ariel [2] and Jaffe and Westerfield’s [9] work, the last trading day of each month is included in the next month’s return. Only five days were used to capture the early month returns because past research has found that the monthly effect is traceable to large returns occurring very early in the month.Table 1 shows the average returns for the two time periods studied and for each country. The monthly effect means that the returns are larger in the beginning of the month than for the middle or end of the month. The results indicate a monthly effect similar to that found in previous research. Average returns were largest for t1 for all of the countries except for Singapore/Malaysia which was reversed. Jaffe and Westerfield [9] had found a reversed monthly effect for another Pacific basin market, Japan. A paired t-test is used to test if there is a difference in mean returns. The null hypothesis of the monthly effect is:HO: t1 = t2or the returns for the five day period representing the beginning of the month is equal to the returns of the rest of the month.HA: t1≠ t2A positive monthly return was found to exist at the .05 level of significance in the Denmark, Germany and Norway stock markets. A significant negative effect was found in the Singapore/Malaysia market at the .01 level.TABLE 1Difference In MeansAverage Return Beginning OfMonth Average ReturnRemaining OfMonthPairedt-StatisticDenmark 1.0232(4.136).1363(4.182) 1.97*France.8974(3.892).0823(4.013) 1.52Germany 1.3613(4.117).2348(3.392) 2.11*Norway 1.0061(4.112).1222(4.086) 1.99*Sin/Mal.0451(2.913)1.0120(2.672)-2.41**Spain.9133(3.114).2716(3.022) 1.61Switzerland 1.0107(3.641).3416(3.717) 1.43*Significant at the .05 level. **Significant at the .01 level.Journal Of Financial And Strategic Decisions 18The monthly effect is also tested using a regression model similar to that used by Jaffe and Westerfield (1989): Equation 3R t -ρ R t-1 = a(1-p) + B(D t -ρD t-1) + e twhere:R t is the stock index return, D t is a dummy variable taking the value of 1 for t1 and 0 for t2. Because stock index returns are serially correlated the regression equation takes the first difference and ρ is the first order serial correlation coefficient of the error terms. The procedure is the Cochrane-Orcutt method. The regression model tests the difference between mean returns for the beginning of the month and at the end of the month. A second regression model was estimated adding the middle of the month in addition to the end of the month (both were given zeroes as the dummy variables) but the results were consistent with the first regression model so it is not reported. The related statistics and the coefficient t values are presented in Table 2. The results are consistent with those in Table 1. A monthly effect is present in the same markets and Singapore/Malaysia had a inverse monthly effect.TABLE 2Regression Model To Test Difference In MeansραB TotalRSQRegressionRSQDenmark.216.00018.00095(1.941)*.0036.0721France.281.000023.00083(1.583).0028.1231Germany.231.00011.00101(2.117)*.0018.0823Norway.225.00026.00162(1.821)*.0031.0141Sin/Mal.118.00021-.00032(-2.361)**.0008.0117Spain.127.00017.00039(1.543).0011.0237Switzerland.134.00032.00082(1.52).0009.0234t-statistics are reported in parentheses*Significant at the .05 level**Significant at the .01 levelThe question remains as to whether the presence of a monthly effect is either confounded or manifested by the January effect. The overall large early month returns may be do to the excess returns earned in January. It is well documented that much of the January effect is traceable to large returns occurring early in the month (Keim 1983, Reinganum 1983). To test whether the monthly effect is no more than the January effect, return patterns were examined with January excluded. Results of the analysis are shown in Table 3. The mean overall returns for all markets were diminished, as expected. However, a positive monthly effect was still present and significant at the .05 level in the German and Danish markets but not the Norway market. The paired t, again was the appropriateThe Monthly Effect In International Stock Markets: Evidence And Implications19 test. The Singapore/Malaysia market, again, exhibited a significant negative effect (at .01) although the January effect was a significant component of the overall monthly effects, the remaining monthly effect in two markets which had significant overall monthly effects was still significant even with January observations removed.TABLE 3Difference In MeansJanuary ExcludedAverage Return Beginning OfMonth Average ReturnRemaining OfMonthPairedt-StatisticDenmark.9771(3.993).2341(3.893) 1.88*France.8115(3.164).0992(3.885) 1.77Germany 1.1120(3.998).3083(4.002) 2.21*Norway.9921(3.897).0833(3.653) 1.88*Sin/Mal.0452(2.887)1.001(2.441)-2.21**Spain.8124(3.006).3550(2.985) 1.55Switzerland 1.0100(3.212).3412(3.440) 1.93**Significant at the .05 level.**Significant at the .01 level.Possible explanations for the monthly effect include the dividend effect, economic and political announcements dates concentrated in one part of the month and large market declines occurred during late October of the study period. However, previous research has found a monthly effect for a time period that excluded 1987’s crash. Further analysis of these and other markets is warranted.SUMMARY AND CONCLUSIONSIt is well documented that there is a week-end effect, a January effect and a monthly effect in U.S. stocks. There is strong evidence of a week-end effect and a January effect in foreign stock markets. Australia and Canada were found to have significant positive monthly effects, while Japan’s market had a negative monthly effect. This research extended Jaffe and Westerfield’s results by investigating the monthly effect in markets in Denmark, France, Germany, Norway, Singapore/Malaysia, Spain and Switzerland. An end of the month effect was found in the Danish, Norwegian and German markets. An inverted (negative effect) was found in the Pacific basin market of Singapore/Malaysia. It was also determined that the January effect, although significant, was not capable of explaining the presence of monthly effects were they exist.20Journal Of Financial And Strategic DecisionsREFERENCES[1]Aggarwal, Raj, Ramesh P. Rao and Takto Hiraki, “Regularities in Tokyo Stock Exchange Security Returns:P/E, Size and Seasonal Influences,” Journal of Financial Research, Vol. 13, Fall 1990, pp. 249-263.[2] Ariel, Robert A., “A Monthly Effect in Stock Returns,” Journal of Financial Economics, Vol. 18, March1987, pp. 161-174.[3] Fama, Eugene F., “The Behavior of Stock Market Prices,” Journal of Business, Vol 38, January 1955, pp 34-105.[4]Fama, Eugene F., “Efficient Capital Markets: A Review of Theory & Empirical Work,” Journal of Finance,1970, pp. 383-417.[5]Francis, Jack C., Management of Investments, New York: McGraw-Hill, 1993.[6] Gultekin, Mustafa N., and N. Bulent Gultekin, “Stock Market Seasonality: International Evidence,” Journalof Financial Economics, Vol. 12, 1983, pp. 469-482.[7]Jaffe, Jeffery, and Randolph Westerfield, “The Week-End Effect in Common Stock Returns: TheInternational Evidence,” Journal of Finance, Vol. 40, June 1985, pp. 433-454.[8]Jaffe, Jeffrey F., Randolph Westerfield and Christopher M., “A Twist on The Monday Effect in Stock Prices:Evidence from the U.S. and Foreign Stock Markets,” Journal of Banking and Finance, Vol. 13, 1989, pp.641-650.[9]Jaffe, Jeffrey and Randolph Westerfield, “Is There a Monthly Effect In Stock Market Returns?: Evidencefrom Foreign Countries,” Journal of Banking and Finance, Vol. 13, 1989, pp. 237-244.[10]Keim, Donald R. “Size Related Anomalies and Stock Return Seasonality: Further Empirical Evidence,”Journal of Financial Economics, Vol. 12, 1993, pp. 13-32.[11]Lewis, Mario, “Stock Market Anomalies: A Re-Assessment Based On The U.K. Evidence,” Journal ofBanking and Finance, Vol. 13, 1989, pp. 675-696.[12]Officer, R.R., “Seasonality in Australian Capital Markets: Market Efficiency and Empirical Issues,”Journal of Financial Economics, Vol. 2, March 1975, pp. 29-52.[13]Reinganum, Marc R., “The Anomalous Stock Market Behavior of Small Firms in January: Empirical Testsfor Tax-Loss Effects,” Journal of Financial Economics, Vol 12, 1983, pp. 89-104.[14]Rozeff, Michael S., and William R. Kinney, “Capital Market Seasonality: The Case of Stock MarketReturns,” Journal of Financial Economics, Vol. 3, October 1976, pp. 376-402.[15]Smirlock, Michael, and Laura Starks, “Day of the Week and Intraday Effects in Stock Returns,” Journal ofFinancial Economics, Vol. 17, 1986, pp. 197-210.[16]Tinic, Seha M., and Richard R. West, “Risk and Return: January and the Rest of the Year,” Journal ofFinancial Economics, Vol. 13, December 1984, pp. 561-574.[17]Tinic, Seha M., Giovanni Barone-Adesi and Richard R. West, “Seasonality in Canadian Stock Prices: A Testof the ‘Tax-Loss Selling’ Hypothesis,” Journal of Financial and Quantitative Analysis, Vol. 22, 1987, pp.51-64.。

MBO&KPI目标管理与关键绩效指标法

Dir. & Dept. P Preliminary Goal Setting Dept. P Strategic Action Plan
Phase 2
Business Plan
Capacity/Competency build up • Know how/Technology Mgmt. & Develop • System /Process • Knowledge System (EDMS=Electronics Document Management System,.FMEA..) Value creation (Project execution/mgmt. Coordination) Strategic action trade off (Priority)
MBO & KPI
目标管理与关键绩效指标法
AGEDA
第一部分 :基础知识基础知识
第二部分 :作业程序作业程序
2.1 2.2 2.3 2.4 準年度計劃與MBO制定作業流程 KPI運用重點說明目標卡及KPI實例說明 MBO & KPI review及評核標
第三部分 :各組實例演各
練
第一部分：第一部分：基础知识
MBO=KPI, MBO=kpi1+kpi2+kpi3+……
第二部分：第二部分：作业程序
2.1 年度計劃與MBO制定作業流程 2.2 KPI運用重點說明 2.3 目標卡及KPI實例說明 2.4 MBO & KPI review 及評核標準
Vision KPI Golden Triangle Goal Strategy
BU HEAD
KPI (MONTHLY& QUARTERLY) ( 6.6)

国际经济学(双语)-第1章

International Economics
Chapter 1
Classical Theories of International Trade
Chapter 1 Classical Theories of International Trade

1.1 Mercantilism 1.2 Trade Based on Absolute Advantage: Adam Smith 1.3 Trade Based on Comparative Advantage: David Ricardo 1.4 Comparative Advantage and Opportunity Cost 1.5 Comparative Advantage with More Than Two Commodities and Countries 1.6 Theory of Reciprocal Demand 1.7 Offer Curve and Terms of Trade

Two assumptions, within each country:
Labor
is the only factor of production and is homogeneous (i.e. of one quality). The cost or price of a good depends exclusively upon the amount of labor required to produce it.
1.3 Trade Based on Comparative Advantage: David Ricardo

An Example of Comparative Advantage

Investor Sentiment and the Cross-Section of Stock Returns

Investor sentiment and the cross-section of stock returnsMALCOLM BAKER and JEFFREY WURGLER∗ABSTRACTWe study how investor sentiment affects the cross-section of stock returns. We predict that a wave of investor sentiment disproportionately affects securities whose valuations are highly subjective and are difficult to arbitrage. We find that when beginning-of-period proxies for investor sentiment are low, subsequent returns are relatively high on small stocks, young stocks, high volatility stocks, unprofitable stocks, non-dividend-paying stocks, extreme-growth stocks, and distressed stocks, suggesting that such stocks are relatively underpriced in low-sentiment states. When sentiment is high, on the other hand, the patterns largely reverse, suggesting that these categories of stocks are relatively overpriced in high-sentiment states.∗ Baker is at the Harvard Business School and National Bureau of Economic Research; Wurgler is at the NYU Stern School of Business and the National Bureau of Economic Research. We thank an anonymous referee, Rob Stambaugh (the editor), Ned Elton, Wayne Ferson, Xavier Gabaix, Marty Gruber, Lisa Kramer, Owen Lamont, Martin Lettau, Anthony Lynch, Jay Shanken, Meir Statman, Sheridan Titman, and Jeremy Stein for helpful comments, as well as participants of conferences or seminars at Baruch College, Boston College, Chicago Quantitative Alliance, Emory University, the Federal Reserve Bank of New York, Harvard University, Indiana University, Michigan State University, NBER, Norwegian School of Economics and Business, Norwegian School of Management, New York University, Stockholm School of Economics, Tulane University, University of Amsterdam, University of British Columbia, University of Illinois, University of Kentucky, University of Michigan, University of Notre Dame, University of Texas, and University of Wisconsin. We gratefully acknowledge financial support from the Q Group and the Division of Research of the Harvard Business School.Classical finance theory leaves no role for investor sentiment. In this theory, most investors are rational and diversify to optimize the statistical properties of their portfolios. Competition among them leads to an equilibrium in which prices equal the rationally discounted value of expected cash flows, and in which the cross-section of expected returns depends only on the cross-section of systematic risks.1 Even if some investors are irrational, classical theory argues, their demands are offset by arbitrageurs with no significant impact on prices.In this paper, we present evidence that investor sentiment may have significant effects on the cross-section of stock prices. We start with simple theoretical predictions. Because a mispricing is the result of an uninformed demand shock in the presence of a binding arbitrage constraint, a broad-based wave of sentiment is predicted to have cross-sectional effects, not simply to raise or lower all prices equally, when sentiment-based demands vary across stocks or when arbitrage constraints vary across stocks. In practice, these two distinct channels lead to quite similar predictions, because stocks that are likely to be most sensitive to speculative demand – those with highly subjective valuations – also tend to be the riskiest and costliest to arbitrage. Concretely, then, theory suggests two distinct channels through which the stocks of newer, smaller, highly volatile firms, firms in distress or with extreme growth potential, firms without dividends, and firms with like characteristics, are expected to be relatively more affected by shifts in investor sentiment.To investigate this prediction empirically, and to get a more tangible sense of the intrinsically elusive concept of investor sentiment, we start with a summary of rises and falls in U.S. market sentiment from 1961 through the Internet bubble. This summary is based on anecdotal accounts and by its nature can only be a suggestive, ex-post characterization of fluctuations in sentiment. Nonetheless, its basic message appears broadly consistent with our theoretical predictions, and suggests that more rigorous tests are warranted.Our main empirical approach is as follows. Because cross-sectional patterns of sentiment-driven mispricing would be difficult to identify directly, we look for the hypothesized patterns in subsequent stock returns that appear when one conditions on proxies for beginning-of-period investor sentiment. The idea is that conditional cross-sectional patterns in subsequent returns may represent the initial patterns of mispricing correcting themselves over time. For example, low future returns on young firms relative to old firms, conditional on high values for proxies for beginning-of-period sentiment, would be consistent with young firms being relatively overvalued ex ante. As usual, we are mindful of the joint hypothesis problem that any predictability patterns we find actually reflect compensation for systematic risks.The first step is to gather proxies for investor sentiment to use as time series conditioning variables. There are no perfect and/or uncontroversial proxies for investor sentiment, so our approach is necessarily practical. We consider a number of proxies suggested in recent work and form them into a composite sentiment index based on their first principal component. To reduce the likelihood that these proxies are connected to systematic risks, we also form an index based on sentiment proxies that have been orthogonalized to several macroeconomic conditions. The sentiment indexes visibly line up with historical accounts of bubbles and crashes.We then test how the cross-section of subsequent stock returns varies with beginning-of-period sentiment. We use monthly stock returns between 1963 and 2001. We start by simply sorting firm-month observations according to the level of sentiment, first, and then the decile rank of a given firm characteristic, second. We find that when sentiment is low (below sample average), small stocks earn particularly high subsequent returns, but when sentiment is high (above average), there is no size effect at all. Conditional patterns are even sharper when sorting on other characteristics. When sentiment is low subsequent returns are higher on very young (or newly listed) stocks than older stocks, high-return volatility than low-return volatility stocks, unprofitable stocks than profitable ones, and nonpayers than dividend payers. When sentiment ishigh, these patterns completely reverse. In other words, several characteristics that do not have any unconditional predictive power actually display sign-flipping predictive ability, in the hypothesized directions, once one conditions on sentiment. These are our most striking findings. Although earlier data is not as rich, most of these patterns are also apparent in a sample that covers 1935 through 1961.The sorts also suggest that sentiment affects extreme growth and distressed firms in similar ways. Note that when stocks are sorted into deciles by sales growth, book-to-market, or external financing activity, growth and distress firms tend to lie at opposing extremes, with more “stable” firms in middle deciles. We find that when sentiment is low, the subsequent returns on stocks at both extremes are especially high relative to their unconditional average, while stocks in middle deciles are less affected by sentiment. (The result is not statistically significant for book-to-market, however.) This U-shaped pattern in conditional difference of returns also appears broadly consistent with theoretical predictions: both extreme-growth and distressed firms have relatively subjective valuations and are relatively hard to arbitrage, and so should be expected to be most affected by sentiment. Again, note that this intriguing conditional pattern would be averaged away in an unconditional study.After confirming these patterns with a regression approach, we turn to the classical alternative explanation that they simply reflect a complex pattern of compensation for systematic risk. For instance, it would require either time variation in rational, market-wide risk premia or time variation in the cross-sectional pattern of risk, i.e., beta loadings. The results cast doubt on these notions. We test the second possibility directly and find no link between the patterns in predictability and patterns in betas with market returns or consumption growth. If risk is not changing over time, then the first possibility requires not just time-variation in risk premia but changes in sign. Put simply, it would require that in half of our sample period (when sentiment is relatively low), that older, less volatile, profitable, dividend-paying firms actually require a riskpremium over very young, highly volatile, unprofitable, nonpayers. This is counterintuitive. Other results also suggest that systematic risk is at best a partial explanation.The results challenge the classical view of the cross-section of stock prices. In doing so, it builds on several recent themes. In particular, our results complement earlier work that sentiment also helps to explain the time series of returns (Kothari and Shanken (1997), Neal and Wheatley (1998), Shiller (1981, 2000), and Baker and Wurgler (2000)). Campbell and Cochrane (2000), Wachter (2000), Lettau and Ludvigson (2001), and Menzly, Santos, and Veronesi (2004) examine the effects of conditional systematic risks; we condition on sentiment. Daniel and Titman (1997) test a characteristics-based model for the cross-section of expected returns; we extend their specification and provide it with a specific, conditional motivation. Shleifer (2000) surveys early work on sentiment and limited arbitrage, two key ingredients here. Barberis and Shleifer (2003), Barberis, Shleifer, and Wurgler (2005), and Peng and Xiong (2004) discuss category-level trading, and Fama and French (1993) document comovement of stocks of similar sizes and book-to-market ratios; uninformed demand shocks for categories of stocks with similar characteristics are central to our results. Finally, we extend and unify known relationships among sentiment, IPOs, and small stock returns (Lee, Shleifer, and Thaler (1991), Swaminathan (1996), and Neal and Wheatley (1998)).Section I discusses theoretical predictions. Section II provides a qualitative history of recent speculative episodes. Section III describes the empirical hypotheses and the data, and the main empirical tests are contained in Section IV. Section V concludes.I. Theoretical effects of sentiment on the cross-sectionA mispricing is the result of an uninformed demand shock and a limit on arbitrage. One can therefore think of two distinct channels through which investor sentiment, as defined moreprecisely below, might affect the cross-section of stock prices. In the first channel, sentimental demand shocks vary in the cross-section, while arbitrage limits are constant. In the second, the difficulty of arbitrage varies across stocks but sentiment is generic. We discuss these in turn.A. Cross-sectional variation in sentimentOne possible definition of investor sentiment is the propensity to speculate.2 Under this definition, sentiment drives the relative demand for speculative investments, and so causes cross-sectional effects even if arbitrage forces are the same across stocks.What makes some stocks more vulnerable to broad shifts in the propensity to speculate? Perhaps the main factor is the subjectivity of their valuations. For instance, consider a canonical young, unprofitable, extreme-growth potential stock. The lack of an earnings history combined with the presence of apparently unlimited growth opportunities allows unsophisticated investors to defend, with equal plausibility, a wide spectrum of valuations, from much too low to much too high, as suits their sentiment. In a bubble period, when the propensity to speculate is apparently high, this profile of characteristics also allows investment bankers (or swindlers) to further argue for the high end of valuations. By contrast, the value of a firm with a long earnings history, tangible assets, and stable dividends is much less subjective, and so its stock is likely to be less affected by fluctuations in the propensity to speculate.3This channel suggests how variation in the propensity to speculate may generally affect the cross-section, but not how sentimental investors actually choose stocks. We suggest that they simply demand stocks that have the bundle of salient characteristics that is compatible with their sentiment.4 That is, those with a low propensity to speculate may demand profitable, dividend-paying stocks not because profitability and dividends are correlated with some unobservable firm property that defines safety to the investor, but precisely because the salient characteristics “profitability” and “dividends” are used to infer safety.5 Likewise, the salient characteristics “noearnings,” “young age,” and “no dividends” mark the stock as speculative. Casual observation suggests that such an investment process may be a more accurate description of how typical investors pick stocks than the process outlined by Markowitz (1959), in which investors view individual securities purely in terms of their statistical properties.variation in arbitrageB. Cross-sectionalInvestor sentiment might also be reasonably defined as optimism or pessimism about stocks in general. Indiscriminate waves of sentiment still affect the cross-section, however, if arbitrage forces are relatively weaker in a subset of stocks.This channel is better understood than the cross-sectional variation in sentiment channel.A body of theoretical and empirical research shows that arbitrage tends to be particularly risky and costly for young, small, unprofitable extreme-growth or distressed stocks. Their high idiosyncratic risk makes relative-value arbitrage especially risky (Wurgler and Zhuravskaya (2002)). They tend to be more costly to trade (Amihud and Mendelsohn (1986)) and particularly expensive, sometimes impossible, to sell short (D’Avolio (2002), Geczy, Musto, and Reed (2002), Jones and Lamont (2002), Duffie, Garleanu, and Pedersen (2002), Lamont and Thaler (2003), and Mitchell, Pulvino, and Stafford (2002)). Further, their lower liquidity also exposes would-be arbitrageurs to predatory attacks (Brunnermeier and Pedersen (2004)).Note that, in practice, the same stocks that are the hardest to arbitrage also tend to be the most difficult to value. So although for expositional purposes we have outlined the two channels separately, they are likely to have overlapping effects. And while this makes them difficult to distinguish empirically, it only strengthens the predictions about what region of the cross-section are most affected by sentiment. Indeed, the two channels can reinforce each other. For example, the fact that investors can convince themselves of a wide range of valuations in some regions ofthe cross-section is a noise-trader risk that further deters short-horizon arbitrageurs (De Long et al. (1990) and Shleifer and Vishny (1997)).6II.An anecdotal history of investor sentiment, 1961 to 2002Here we briefly summarize the most prominent U.S. stock market bubbles between 1961 to 2002 (matching the period of our main data). The reader eager to see results may skip this section, but it is useful for three reasons. First, despite great interest in the effects of investor sentiment, the academic literature does not contain even the most basic, ex-post characterization of most of the recent speculative episodes. Second, a knowledge of the rough timing of these episodes allow us to make a preliminary judgment about the accuracy of the quantitative proxies for sentiment that we develop later. Third, the discussion sheds some initial, albeit anecdotal light on the plausibility of our theoretical predictions.Our brief history of sentiment is distilled from several sources. Kindleberger (2001) draws general lessons from bubbles and crashes over the past few hundred years, while Brown (1991), Dreman (1979), Graham (1973), Malkiel (1990, 1999), Shiller (2000), and Siegel (1998) focus more specifically on recent U.S. stock market episodes. We take each of these accounts with a grain of salt, and emphasize only themes that appear repeatedly.We start in 1961, a year in which Graham (1973), Malkiel (1990) and Brown (1991) note a high demand for small, young, growth stocks. Dreman (1979, p. 70) confirms their accounts. Malkiel writes of a “new-issue mania” that was concentrated on new “tronics” firms. “… The tronics boom came back to earth in 1962. The tailspin started early in the year and exploded in a horrendous selling wave … Growth stocks took the brunt of the decline, falling much further than the general market” (p. 54 - 57).The next bubble develops in 1967 and 1968. Brown writes that “scores of franchisers, computer firms, and mobile home manufactures seemed to promise overnight wealth. … [while] quality was pretty much forgotten” (p. 90). Malkiel and Dreman also note this pattern—a focus on firms with strong earnings growth or potential, and an avoidance of “the major industrial giants, ‘buggywhip companies,’ as they were sometimes contemptuously called” (Dreman 1979, p. 74-75). Another characteristic apparently out of favor was dividends. According to the New York Times, “during the speculative market of the late 1960’s many brokers told customers that it didn’t matter whether a company paid a dividend—just so long as its stock kept going up” (9/13/1976). But “after 1968, as it became clear that capital losses were possible, investors came to value dividends” (10/7/1999). In summarizing the performance of stocks from the end of 1968 through August 1971, Graham (1973) writes: “[our] comparative results undoubtedly reflect the tendency of smaller issues of inferior quality to be relatively overvalued in bull markets, and not only to suffer more serious declines than the stronger issues in the ensuing price collapse, but also to delay their full recovery—in many cases indefinitely” (p. 212).Anecdotal accounts invariably describe the early 1970’s as a bear market, with sentiment at a low level. However, a set of established, large, stable, consistently profitable stocks known as the “nifty fifty” enjoyed notably high valuations. Brown, Malkiel, and Siegel (1998) each highlight this episode. Siegel writes, “All of these stocks had proven growth records, continual increases in dividends … and high market capitalization” (p. 106). Note that this speculative episode is a mirror image of those described above (and below). They center on small, young, unprofitable growth stocks in periods of high sentiment, while the nifty fifty episode appears to be a bubble in a set of firms with an opposite set of characteristics (old, large, and continuous earnings and dividend growth) and happens in a period of low sentiment.The late 1970’s through mid-1980’s are described as a period of generally high sentiment, perhaps associated with Reagan-era optimism, and saw a series of speculativeepisodes. Dreman describes a bubble in gambling issues in 1977 and 1978. Ritter (1984) studies the hot issue market of 1980, finding greater initial returns on IPOs of natural resource start-ups than on larger, mature, profitable offerings. Of 1983, Malkiel (p. 74-75) writes that “the high-technology new-issue boom of the first half of 1983 was an almost perfect replica of the 1960’s episodes … The bubble appears to have burst early in the second half of 1983 … the carnage in the small company and new-issue markets was truly catastrophic.” Brown confirms this account. Of the mid-1980’s, Malkiel writes that “What electronics was to the 1960’s, biotechnology became to the 1980’s. … new issues of biotech companies were eagerly gobbled up. … having positive sales and earnings was actually considered a drawback” (p. 77-79). But by 1987 and 1988, “market sentiment had changed from an acceptance of an exciting story … to a desire to stay closer to earth with low-multiple stocks that actually pay dividends” (p. 79).The late-1990’s bubble in technology stocks is familiar. By all accounts, investor sentiment was broadly high before the bubble started to burst in 2000. Cochrane (2003) and Ofek and Richardson (2002) offer ex post perspectives on the bubble, while Asness et al. (2000) and Chan, Karceski, and Lakonishok (2000) were arguing even before the crash that late-1990’s growth stock valuations were difficult to ascribe to rationally expected earnings growth. Malkiel draws parallels to episodes in the 1960’s, 1970’s, and 1980’s, and Shiller (2000) compares the Internet bubble to the late 1920’s. As in earlier speculative episodes that occurred in high sentiment periods, demand for dividend payers seems to have been low (New York Times, 1/6/1998). Ljungqvist and Wilhelm (2003) find that 80% of 1999 and 2000 IPOs had negative earnings per share and that the median age of 1999 IPOs was 4 years. This contrasts with an average age of over 9 years just prior to the emergence of the bubble, and of over 12 years by 2001 and 2002 (Ritter, 2003).These anecdotes suggest some regular patterns in the effect of investor sentiment on the cross-section. For instance, canonical extreme-growth stocks seem to be especially prone tobubbles (and subsequent crashes), consistent with the observation that they are more appealing to speculators and optimists and at the same time hard to arbitrage. The “nifty fifty” bubble is a notable exception. However, anecdotal accounts suggest that this bubble occurred in a period of broadly low sentiment, so it may still be consistent with the cross-sectional prediction that an increase in sentiment increases the relative price of stocks that are most subjective to value and hardest to arbitrage. We now turn to formal tests of this prediction.III. Empirical approach and dataA. Empirical approachTheory and historical anecdote both suggest that sentiment may cause systematic patterns of mispricing. Because mispricing is hard to identify directly, however, our approach is to look for systematic patterns of correction of mispricing. For example, a pattern in which returns on young and unprofitable growth firms are (on average) especially low when beginning-of-period sentiment is estimated to be high may represent the correction of a bubble in growth stocks.More specifically, to identify sentiment-driven changes in cross-sectional predictability patterns, we need to control for two more basic effects: the generic impact of investor sentiment on all stocks and the generic impact of characteristics across all time periods. Thus, our analysis is organized loosely around the following predictive specification:[]11211111''−−−−−+++=it t it t it t T T a a R E x b x b (1) where i indexes firms, t is time, x is a vector of characteristics, and T is a proxy for sentiment. a 1 picks up the generic effect of sentiment and b 1 the generic effect of characteristics. Our interest centers on b 2. The null is that b 2 is zero or, more precisely, that any nonzero effect is rational compensation for systematic risk. The alternative is that b 2 is nonzero and reveals cross-sectionalpatterns in sentiment-driven mispricing. Eq. (1) is a “conditional characteristics model” because it adds conditional terms to the characteristics model of Daniel and Titman (1997).B. Characteristics and returnsThe firm-level data is from the merged CRSP-Compustat database. The sample includes all common stock (share codes 10 and 11) between 1962 through 2001. Following Fama and French (1992), we match accounting data for fiscal year-ends in calendar year t-1 to (monthly) returns from July t through June t+1, and we use their variable definitions when possible.Table 1 shows summary statistics. Panel A summarizes returns variables. Following common practice, momentum MOM is defined as the cumulative raw return for the eleven-month period from 12 through two months prior to the observation return. Because momentum is not mentioned as a salient characteristic in historical anecdote, nor does theory suggest a direct connection between momentum and the difficulty of valuation or arbitrage, we use momentum merely as a control variable, to establish the robustness of other patterns.The remaining panels summarize the firm and security characteristics that we consider. The previous sections’ discussions point us directly to several variables. To that list, we add a few more characteristics that, by introspection, seem likely to be salient to investors. Overall, we roughly group characteristics as pertaining to firm size and age, profitability, dividends, asset tangibility, and growth opportunities and/or distress.Size and age characteristics include market equity ME from June of year t, measured as price times shares outstanding from CRSP. ME is matched to monthly returns from July of year t through June of year t+1. Age is the number of years since the firm’s first appearance on CRSP, measured to the nearest month.7Sigma is the standard deviation of monthly returns over the twelve months ending in June of year t. If there are at least nine returns to estimate it, Sigma is then matched to monthly returns from July of year t through June of year t+1. While historicalanecdote doesn’t identify stock volatility itself as a salient investment characteristic, it seems likely to serve as a good proxy for both the difficulty of valuation and of arbitrage.[TABLE 1 HERE]Profitability characteristics include the return on equity E+/BE, which is positive for profitable firms and zero for unprofitable firms. Earnings (E)is income before extraordinary items (Item 18) plus income statement deferred taxes (Item 50) minus preferred dividends (Item19), if earnings are positive; book equity (BE)is shareholders equity (Item 60) plus balance sheetdeferred taxes (Item 35). E>0is a dummy variable for profitability that takes the value one for profitable firms and zero for unprofitable firms.Dividend characteristics include dividends to equity D/BE, which is dividends per share at the ex date (Item 26) times Compustat shares outstanding (Item 25) divided by book equity.D>0 is a dummy for positive dividends per share by the ex date. The decline in the percentage offirms that pay dividends noted by Fama and French (2001) is apparent.Asset tangibility characteristics are measured by property, plant and equipment (Item 7) over assets PPE/A and research and development expense over assets (Item 46) RD/A. The referee suggests that asset tangibility may proxy for the difficulty of valuation. One concern is the coverage of the R&D variable. We do not consider this variable prior to 1972, because FASB did not require R&D to be expensed until 1974 and Compustat coverage prior to 1972 is very poor. Also, even in recent years less than half of the sample reports positive R&D.Characteristics indicating growth opportunities, distress, or both include book-to-market equity BE/ME, whose elements are defined above. External finance EF/A is the change in assets (Item 6) minus the change in retained earnings (Item 36) divided by assets. Sales growth (GS) is the change in net sales (Item 12) divided by prior-year net sales. Sales growth GS/10 is the decile of the firm’s sales growth in the prior year relative to NYSE firms’ decile breakpoints.As we shall see, one must understand the multidimensional nature of the growth and distress variables in order to understand how they interact with sentiment. In particular, book-to-market wears at least three hats: high values may indicate distress; low values may indicate high growth opportunities; and, as a scaled-price variable, book-to-market is also a generic valuation indicator, varying with any source of mispricing or rational expected returns. Sales growth and external finance wear at least two hats: low values (which are negative) may indicate distress; high values may reflect growth opportunities. Further, to the extent that market timing motives drive external finance, EF/A also serves as a generic misvaluation indicator.All explanatory variables are Winsorized each year at their 0.5 and 99.5 percentiles. Finally, in Panels C through F, the accounting data for fiscal years ending in calendar year t-1 are matched to monthly returns from July of year t through June of year t+1.sentimentC. InvestorPrior work suggests a number of proxies for sentiment to use as time-series conditioning variables. There are no definitive or uncontroversial measures, however. We form a composite index of sentiment. It is based on the common variation in six underlying proxies for sentiment: the closed-end fund discount, NYSE share turnover, the number and average first-day returns on IPOs, the equity share in new issues, and the dividend premium. The sentiment proxies are measured annually from 1962 to 2001. We first introduce each one of them, and then discuss how they are formed into overall sentiment indexes.The closed-end fund discount CEFD is the average difference between the NAV of closed-end stock fund shares and their market prices. Prior work suggests that CEFD is inversely related to sentiment. Zweig (1973) uses it to forecast reversion in Dow Jones stocks, and Lee, Shleifer, and Thaler (1991) argue that sentiment is behind various features of closed-end fund discounts. We take the value-weighted average discount on closed-end stock funds for 1962。

Econ 2nd semester, 1st monthly

10th Grade Economics S level 1st Monthly Exam Review Sheet.GDP: Gross Domestic Product, the dollar value of all ﬁnal goods and services produced within a country’s borders in a given year.Intermediate goods: Goods used in the production of the ﬁnal goods.Durable goods: Goods that last for a relatively long time, such as refrigerators, cars, and DVD players.Nondurable goods: Goods that lsat a short period of time, such as food, light bulbs. Nominal GDP: GDP measured in current prices.Real GDP: GDP expresses in constant, or unchanging prices.Real GDP per capita: Real GDP divided by the total populationGNP: gross national product, the annual income earned by U.S owned ﬁrms and US citizens.Depreciation: The loss of the value of capital equipment that results from normal wear and tearNet National Product: A measure of the net output for one year or the output made after the adjustment for depreciation.Price Level: The average of all prices in the economyAggregate Supply:The amount of goods and services in the economy available at all possible price levels.Aggregate Demand: The amount of goods and services in the economy that will be purchased at all possible price levels.Business Cycle: A period of macroeconomic expansion followed by a period of contraction.Expansion: A period of economic growth as measured by a rise in real GDP Contraction: A period of economic decline marked by falling real GDPRecession: A prolonged economic contractionDepression: A recession that is especially long and severePeak: The height of an economic expansion, when real GDP stops rising.Trough: The lowest point in an economic contraction, when real GDP stops falling. Capital Deepening: Process of increasing the amount of capital per workerSaving: Income not used for consumptionSavings Rate: The proportion of disposable income that is savedTechnological Progress: An increase in efﬁciency gained by producing more output without using more inputs.Frictional unemployment: Unemployment that occurs when people take time to ﬁnd a job Seasonal Unemployment: Unemployment that occurs as result of harvest schedules or vacations, or when industries slow or shut down for a seasonStructural Unemployment: Unemployment that occurs when workers skills do not match the jobs that are available.Cyclical Unemployment: Unemployment that rises during economic downturns and falls when the economy improves.Census: An ofﬁcial count of the populationUnemployment Rate: The percentage of the nations labor force that is unemployed.Full Unemployment: The level of employment reached when there is no cyclical unemployment.Underemployed: Working at job for which one is overqualiﬁed or working part time when full time work is desired.Discouraged Worker: A person who wants a job but has given up looking.Inﬂation: A general increase in pricesPurchasing Power: The ability to purchase goods and servicesPrice Index: A measurement that shows how the average price of a standard group of goods changes over time.CPI: A price index determined by measuring the price of a standard group of goods meant to represent the “market basket” of a typical urban consumer.Market Basket: A representative collection of goods and services.Inﬂation Rate: The percentage rate of change in price level over timeCore Inﬂation Rate: The rate of inﬂation excluding the effects of food and energy prices. Hyperinﬂation: Inﬂation that is out of controlQuantity Theory: Theory that too much money in the economy causes inﬂation.Demand-pull Theory: Theory that inﬂation occurs when demand for goods and services exceeds existing supplies.Cost-push Theory: Theory that inﬂation occurs when producers raise prices in order to meet increased costs.Wage-price Spiral: The process by which rising wages cause higher prices, and higher prices cause higher wages.Fixed Income: Income that does not increase even when prices go upDeﬂation:A sustained drop in the price level.1) GDP is the estimated value of the country’s production and services, within its boundaries by its nationals and foreigners, whereas GNP calculates the total worth of production and services by its land or foreign land.2)Final goods are products in the form sold to consumers where as intermediate goodsare used in the production of the ﬁnal goods.3)Durable goods for a long period of time, where as nondurable goods last for relativelyshort period of time.4)The Government uses the price of the base year to establish a set of constant price,therefore, they don’t get a GDP that is increasing because output remains the same but the price rises. They use the price from the ﬁrst year where the output and price is the ﬁrst years.5)The loss of the value of capital equipment that results from normal wear and tear. Thecost to repair these products decrease the value of the product.6) We can simply use the price of the present year to calculate the nominal GDP, or usingthe base years price where the price is constant to calculate the real GDP.7) Aggregate supply raises the price level, leading to an increase of all the prices of thegoods and services. Higher price leading to more proﬁt along with an increase in GDP.Aggregate demand lowers the price level causing more demand power and the amount of goods consumed increases and rise the GDP.8) Expansion --> Peak --> Contraction --> Trough9)Recession represents a prolonged economic contraction, whereas depression is a moreserious version of recession, where it is long and severe.10) They are mainly caused by business investment, interest rates and credits,consumer expectations and external shocks. Companies may invest heavily on their products while economy is expanding, or may cut back the investment, leading to a lower price level and GDP, leading to unemployment, lower sales and production. When interest rates are low, companies are more willing to borrow money for investments, but they are not likely to do so when the interest rate is high. Fear of a weak economy from the consumers may lead to a lack of spending and towards saving, lower the GDP and economy. However, if consumers are expecting an increasing economy, they would buy more and push up the economy. External shocks are unpredictable, for example, lack of oil supply, wars etc. There are also positive external shocks like discovery of newelements, or a good season etc.11) They measure it to ﬁnd out the nation’s standard of living, as long as Real GDP isrising faster than the population, then so will the standard of living. Economists can see how the standard of living changes over time by comparing the real GDP per capita from two periods. Also to compare the economy of two nations.12) Patents issue rights for the company to produce the product. It can help companies torecover the cost of research by earning proﬁts before its competitors are allowed to copy new products.13) Frictional Unemployment is when people don’t have a job currently because they arespending time to ﬁnd their preferred job for themselves. Structural Unemployment occurs when worker’s skill no longer meet their jobs. These following reasons could be the reason for the unemployment : a development of new technology, a discovery of new resources, changes in consumer demand, globalization, lack of education. Also Cyclical Unemployment is an unemployment that will occur in a healthy economy, there will always be up and downs within a economy, therefore causing people to lose their jobs during the troughs and recessions.14) (Number of people unemployed / number of people in the civilian force) x10015) The CPI is calculated by determining the price of a “market basket” which representsthe collections of basic goods and services, government can then compare the prices of these goods with the price from the past seeing how the price has changed.16) Inﬂation rate is the percentage rate of change in price level over time.(CPI Year A - CPI Year B) / CPI Year B x 100 CPI = Updated Cost / Base Period Cost x 10017) Inﬂation could lead to purchasing power, where people can’t use the same amount ofmoney to buy the some value worth of goods or services. The income can also be eroded, many would raise their income to meet the inﬂation rate, but not everyone gets to raise their income. The inﬂation can also affect the interest rate, where it has to keep up with the inﬂation all the time. A huge part of the interest rate depends on the inﬂation rate, sometimes, people may even lost money if the inﬂation rate is too high.AD/ AS model :Business Cycle:。