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Financial·Wealth：周道E-mail：*******************2012年上市公司一季度业绩预告（5）88第14期1111第14期2011年上市公司主要财务数据一览（11）责任编辑：周道E-mail ：Financial ·89:赵迪E-mail:*****************Financial·Wealth分析师一致预期大幅调高个股统计截止日：2012-4-05排名股票代码简称2011年一致预期2011年一致预期净利调整变动4周变化率(%)2012年一致预期2012年一致预期净利调整变动4周变化率(%)所属行业2011年EPS2011年PE2012年EPS2012年PE1000419通程控股0.4812.2359.40.3815.36 3.65零售业2000883湖北能源0.2523.7817.510.3617.01 6.26电力3300022吉峰农机0.2340.2911.590.3427.799.53零售业4600485中创信测0.1561.188.210.4222.25 4.51技术硬件与设备5300245天玑科技0.8826.787.13 1.219.71 4.09软件与服务6600208新湖中宝0.2714.64 6.530.3610.92 6.62房地产7600428中远航运0.1144.73 5.580.1532.47 4.84运输8600366宁波韵升 1.1915.85 5.38 1.2714.847.57仪器仪表9600352浙江龙盛0.6110.31 4.580.748.559.88原材料10000830鲁西化工0.3117.66 4.480.4312.6523.66原材料11600572康恩贝0.420.76 4.340.4817.3112.55制药与生物科技12002128露天煤业 1.1213.03 4.23 1.2211.997能源13600240华业地产0.7413.34 3.68 1.18.93 3.19房地产14601028玉龙股份0.5317.43 3.420.6913.44 4.43原材料15002005德豪润达0.6925.15 3.23 1.0416.648.91耐用消费品与服装1、为保证数据的有效性仅选取沪深300下的股票作为选股样本，以2011年一致预期净利润调整变动4周变化率排名。

热阻值计算公式20110810

传热系数：
传热系数以往称总传热系数。国家现行标准规范统一定名为传热系数。传热系数K值，是指在稳定传热条件下，围护结构两侧空气温差为 1 度 (K ， ℃ ) ， 1 小时内通过1平方米面积传递的热量，单位是瓦/平方米•度 (W/ ㎡ • K ，此处 K 可用 ℃ 代替)。
热工计算：
1、围护结构热阻的计算
单层结构热阻：
R=δ/λ
式中： δ—材料层厚度(m)
λ—材料导热系数 [W/(m.k)]
多层结构热阻：
R=R1+R2+----Rn= δ 1/ λ1+δ2/λ2+----+δn/λn
式中 : R1 、 R2 、 ---Rn —各层材料热阻(m.k/w)
δ 1 、 δ 2 、 --- δ n — 各层材料厚度(m)
3、围护结构传热系数计算
K=1/ R0 式中: R0—围护结构传
热阻外墙受周边热桥影响条件
下，其平均传热系数的计算
Km=(KpFp+Kb1Fb1+Kb2Fb2+ Kb3Fb3 )/( Fp + Fb1+Fb2+Fb3) 式中:
Km — 外墙的平均传热系数[W/(m.k)]
Kp — 外墙主体部位传热系数[W/(m.k)]
Kb1、Kb2、Kb3—外墙周边热桥部位的传热系数 [W/(m.k)]
Fp — 外墙主体部位的面积
Fb1、Fb2、Fb3—外墙周边热桥部位的面积 4、单一材料热工计算运算式
①厚度δ(m) = 热阻值 R(m.k/w) * 导热系数 λ [W/(m.k)] ② 热阻值 R(m.k/w) = 1 / 传热系数K [W/(㎡•K)] ③厚度δ(m) = 导热系数λ [W/(m.k)] / 传热系数 K [W/(㎡•K)] 5、围护结构设计厚度的计算

中山大学中标基金

56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
21272289 21272290 21272291 21272292 21273007 21273290 21274166 21274167 21274168 21275168 21276288 21276289 21276290 21277176 21277177 21277178 31200179
2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2016-12-31 2015-12-31
80 80 80 80 78 80 80 80 80 83 82 80 80 80 80 78 23
2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1 2013-1-1
巫瑞波毛宗万吴明娒王静朱新海邱立勤叶保辉刘高峰刘岚万一千黄世亮
中山大学中山大学中山大学中山大学中山大学中山大学中山大学中山大学中山大学中山大学中山大学
B030204 B0104 B0101 B010201 B020101 B020104 B020201 B020202 B020403 B020403 B020601

2012md

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973计划2011-2012年项目清单

附件：973计划2011-2012年项目清单项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2011CB012800多时空脉冲强磁场成形制造基础研究李亮华中科技大学教育部2011CB012900 新型能源装备中大型锻件均质化热制造的科学基础李建国上海交通大学上海市科学技术委员会教育部2011CB013000激光微纳制造新方法和尺度极限基础研究姜澜北京理工大学工业和信息化部2011CB013100 高性能LED制造与装备中的关键基础问题研究刘岩深圳清华大学研究院深圳市科技工贸和信息化委员会2011CB013200 空间光学先进制造基础理论及关键技术研究李圣怡中国人民解放军国防科学技术大学中国人民解放军国防科学技术大学2011CB013300 人体运动功能重建的生机电一体化科学基础朱向阳上海交通大学上海市科学技术委员会教育部2011CB013400机械装备再制造的基础科学问题张洪潮大连理工大学教育部2011CB013500 大型水利水电工程高陡边坡全生命周期性能演化与安全控制周创兵武汉大学教育部湖北省科学技术厅2011CB013600 近海重大交通工程地震破坏机理及全寿命性能设计与控制杜修力广州大学广东省科学技术厅中国地震局—1—项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2011CB013700深海工程结构的极端环境作用与全寿命服役安全滕斌大连理工大学教育部2011CB013800 城市轨道交通地下结构性能演化与感控基础理论朱合华同济大学上海市科学技术委员会教育部2012CB113900 主要蔬菜重要品质性状形成的遗传机理与分子改良黄三文中国农业科学院蔬菜花卉研究所农业部2012CB114000主要粮食作物重大病害控制的基础研究彭友良中国农业大学教育部2012CB114100害虫暴发成灾的遗传与行为机理康乐中国科学院动物研究所中国科学院2012CB114200作物应答盐碱胁迫的分子调控机理郭岩中国农业大学教育部2012CB114300作物水分高效利用机理与调控的基础研究宋纯鹏河南大学河南省科学技术厅2012CB114400 海水养殖动物主要病毒性疫病爆发机理与免疫防治的基础研究宋林生中国科学院海洋研究所山东省科学技术厅中国科学院2012CB114500木材形成的调控机制研究卢孟柱中国林业科学研究院国家林业局2012CB114600 家蚕关键品质性状分子解析及分子育种基础研究夏庆友西南大学重庆市科学技术委员会教育部2012CB214700 中国南方古生界页岩气赋存富集机理和资源潜力评价肖贤明中国科学院广州地球化学研究所中国科学院—2—项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2012CB214800 中国早古生代海相碳酸盐岩层系大型油气田形成机理与分布规律刘文汇中国石油化工股份有限公司石油勘探开发研究院中国石油化工集团公司2012CB214900低品质煤大规模提质利用的基础研究刘炯天中国矿业大学江苏省科学技术厅2012CB215000 绿色低碳导向的高效炼油过程基础研究卢春喜中国石油大学（北京）中国石油天然气集团公司2012CB215100大规模风力发电并网基础科学问题研究袁小明华中科技大学教育部2012CB215200 智能电网中大规模新能源电力安全高效利用基础研究刘吉臻华北电力大学教育部2012CB215300 草本能源植物培育及化学催化制备先进液体燃料的基础研究马隆龙中国科学院广州能源研究所中国科学院广东省科学技术厅2012CB215400碳基燃料固体氧化物燃料电池体系基础研究韩敏芳中国矿业大学（北京）教育部2012CB215500 基于贵金属替代的新型动力燃料电池关键技术和理论基础研究孙公权中国科学院大连化学物理研究所中国科学院2012CB315600 新型宽带大动态毫米波器件及应用中的微波光子学基础研究郑小平清华大学教育部2012CB315700 面向宽带泛在接入的微波光子器件与集成系统基础研究纪越峰北京邮电大学教育部2012CB315800 面向服务的未来互联网体系结构与机制研究刘韵洁中国科学院计算技术研究所中国科学院—3—项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2012CB315900 可重构信息通信基础网络体系研究兰巨龙中国人民解放军信息工程大学河南省科学技术厅2012CB316000能效与资源优化的超蜂窝移动通信系统基础研究牛志升清华大学教育部2012CB316100 高移动性宽带无线通信网络重点理论基础研究范平志西南交通大学教育部四川省科学技术厅2012CB316200海量信息可用性基础理论与关键技术研究李建中哈尔滨工业大学工业和信息化部2012CB316300面向公共安全的社会感知数据处理谭铁牛中国科学院自动化研究所中国科学院2012CB316400 面向公共安全的跨媒体计算理论与方法庄越挺浙江大学教育部浙江省科学技术厅2012CB316500基于新一代测序的生物信息学理论与方法张学工清华大学教育部2012CB416600 华北克拉通前寒武纪重大地质事件与成矿翟明国中国科学院地质与地球物理研究所中国科学院2012CB416700华夏地块中生代陆壳再造与巨量金属成矿蒋少涌南京大学教育部2012CB416800 我国富铁矿形成机制与预测研究张招崇中国地质科学院矿产资源研究所国土资源部2012CB416900 我国主要人工林生态系统结构、功能与调控研究朱教君中国科学院沈阳应用生态研究所中国科学院—4—项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2012CB417000 长江中游通江湖泊江湖关系演变及环境生态效应与调控杨桂山中国科学院南京地理与湖泊研究所水利部中国科学院2012CB417100 典型流域陆地生态系统-大气碳氮气体交换关键过程、规律与调控原理郑循华中国科学院大气物理研究所中国科学院2012CB417200 我国持续性重大天气异常形成机理与预测理论和方法研究翟盘茂中国气象科学研究院中国气象局2012CB417300 西南印度洋洋中脊热液成矿过程与硫化物矿区预测周怀阳同济大学教育部上海市科学技术委员会2012CB417400 热带太平洋海洋环流与暖池的结构特征、变异机理和气候效应王凡中国科学院海洋研究所中国科学院山东省科学技术厅2012CB517500脂代谢紊乱导致脂肪肝及高脂血症发生的机制管又飞北京大学教育部2012CB517600 常见肾小球疾病发病机制及其早期诊断刘志红中国人民解放军南京军区南京总医院中国人民解放军总后勤部卫生部江苏省科学技术厅2012CB517700慢性肾脏病进展的机制研究侯凡凡南方医科大学广东省科学技术厅2012CB517800 环境代谢因素致高血压机制及其干预措施的研究祝之明中国人民解放军第三军医大学中国人民解放军总后勤部卫生部重庆市科学技术委员会2012CB517900 儿童孤独症的遗传基础及其致病的机制研究夏昆中南大学湖南省科学技术厅教育部—5—项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2012CB518000 重大心血管疾病相关GPCR新药物靶点的基础研究肖瑞平北京大学教育部2012CB518100 严重创伤重要组织器官修复再生的细胞与分子机制研究付小兵中国人民解放军总医院中国人民解放军总后勤部卫生部2012CB518200 高原低氧环境的快速习服与长期适应机制研究范明中国人民解放军军事医学科学院基础医学研究所中国人民解放军总后勤部卫生部2012CB518300 前列腺癌分子机制与干预的研究孙颖浩中国人民解放军第二军医大学中国人民解放军总后勤部卫生部上海市科学技术委员会2012CB518400 治疗心血管疾病有效方剂组分配伍规律研究张伯礼天津中医药大学国家中医药管理局天津市科学技术委员会2012CB518500 经穴效应循经特异性规律及关键影响因素基础研究梁繁荣成都中医药大学国家中医药管理局四川省科学技术厅2012CB518600 基于微血管病变性疾病的营卫“由络以通、交会生化”研究吴以岭河北以岭医药研究院有限公司国家中医药管理局河北省科学技术厅2012CB518700 重要病原菌与宿主相互作用分子机制的研究戈宝学同济大学教育部上海市科学技术委员会2012CB518800 动物重要病原菌功能基因组与分子致病机理研究周锐华中农业大学教育部湖北省科学技术厅2012CB518900病毒与细胞相互作用导致炎症的基础研究吴建国武汉大学教育部—6—项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2012CB519000 重要病毒持续性感染形成和维持的分子机制研究袁正宏复旦大学教育部上海市科学技术委员会2012CB619100 新型医用材料的功能化设计及生物适配基础科学问题研究王迎军华南理工大学教育部2012CB619200 高性能近红外InGaAs探测材料基础研究及其航天应用验证龚海梅中国科学院上海技术物理研究所中国科学院上海市科学技术委员会2012CB619300 全组分可调III族氮化物半导体光电功能材料及其器件应用沈波北京大学教育部2012CB619400铁性智能材料的高性能化研究任晓兵西安交通大学教育部2012CB619500 航空高性能铝合金材料的基础研究张新明中南大学湖南省科学技术厅教育部2012CB619600 先进金属基复合材料制备科学基础张荻上海交通大学上海市科学技术委员会2012CB719700城市高层建筑重大火灾防控关键基础问题研究孙金华中国科学技术大学中国科学院公安部2012CB719800 城市固体废弃物填埋孕育环境灾害与可持续防控的基础研究陈云敏浙江大学教育部浙江省科学技术厅2012CB719900 高分辨率遥感数据精处理和空间信息智能转化的理论与方法单杰武汉大学教育部2012CB720000行星表面精确着陆导航与制导控制问题研究崔平远北京理工大学工业和信息化部—7—项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2012CB720100 大型客机座舱内空气环境控制的关键科学问题研究陈清焰天津大学教育部天津市科学技术委员会2012CB720200大型客机主要气动噪声机理及先进控制方法研究孙晓峰北京航空航天大学工业和信息化部2012CB720300 乙炔法聚氯乙烯生产过程的高效、节能、减排科学基础张金利石河子大学新疆生产建设兵团科学技术局2012CB720400钢铁生产过程高效节能基础研究张欣欣北京科技大学教育部2012CB720500 化工过程物质与能量高效利用的集成优化基础研究钱锋浙江大学教育部浙江省科学技术厅2012CB720600基于核酸的重大疾病诊断新策略和新技术研究周翔武汉大学教育部2012CB720700 中国语言相关脑功能区与语言障碍的关键科学问题研究谭力海香港大学深圳研究院深圳市科技工贸和信息化委员会2012CB720800 食品加工过程安全控制理论与技术的基础研究陈坚江南大学教育部江苏省科学技术厅2012CB720900 脆弱性硅酸盐质文化遗产保护关键科学与技术基础研究罗宏杰中国科学院上海硅酸盐研究所上海市科学技术委员会中国科学院国家文物局2012CB721000微生物药物创新与优产的人工合成体系冯雁上海交通大学教育部—8—项目编号项目名称项目首席科学家项目第一承担单位项目依托部门2012CB721100 新功能人造生物器件的构建与集成赵国屏中科院上海生科院中国科学院上海市科学技术委员会2012CB821200 空间合作目标运动再现中跨尺度控制的前沿数学问题贾英民北京航空航天大学工业和信息化部2012CB821300 光频标关键物理问题与技术实现高克林中国科学院武汉物理与数学研究所中国科学院2012CB821400 高通量中子散射在凝聚态物质磁相互作用方面的前沿研究戴鹏程中国科学院物理研究所中国科学院2012CB821500 高分子非晶液-固转变的基本问题研究安立佳中国科学院长春应用化学研究所中国科学院2012CB821600 若干重要元素的有机化学前沿周其林南开大学教育部天津市科学技术委员会2012CB821700有机分子基框架多孔材料的前沿研究苏成勇中山大学教育部2012CB821800 射电波段的前沿天体物理课题及FAST早期科学研究李菂中国科学院国家天文台中国科学院2012CB821900 四亿年以来中国陆地生物群演变及其与环境的关系周忠和中国科学院古脊椎动物与古人类研究所中国科学院2012CB822000晚中生代温室地球气候-环境演变王成善中国地质大学（北京）教育部2012CB822100肿瘤的糖化学生物学前沿研究叶新山北京大学教育部—9—。

丽水市人民政府关于公布丽水市2011－2012年度社会科学优秀成果获奖名单的通知

丽水市人民政府关于公布丽水市2011－2012年度社会科学优秀成果获奖名单的通知
文章属性
•【制定机关】丽水市人民政府
•【公布日期】2014.01.09
•【字号】丽政发[2014]1号
•【施行日期】2014.01.09
•【效力等级】地方规范性文件
•【时效性】现行有效
•【主题分类】基础研究与科研基地
正文
丽水市人民政府关于公布丽水市2011－2012年度社会科学优
秀成果获奖名单的通知
（丽政发〔2014〕1号）
各县（市、区）人民政府，市政府直属各单位：
经丽水市社会科学优秀成果评选委员会组织评定，《抗日战争时期浙江省会云和细菌战调研纪实》等100项科研成果，分别被评为丽水市2011-2012年度社会科学优秀成果一、二、三等奖。

现予以公布。

丽水市人民政府
2014年1月9日丽水市2011-2012年度社会科学优秀成果获奖名单
（共100项）。

七年级12月月考英语试题

本卷分为第Ⅰ卷（选择题）和第Ⅱ卷（非选择题）两部分。

全卷共 4页，第Ⅰ卷 1 至2页，第Ⅱ卷3至4页。

共120分。

第Ⅰ卷（选择题，共90分）温馨提示：1、答第Ⅰ卷前，考生务必把自己的姓名、考号、考试科目用2B铅笔涂写在答题卡上。

2、每小题选出答案后，用2B铅笔把答题卡上对应题号涂黑。

如需改动，用橡皮擦干净后，再选涂其它答案。

不能答在试题卷上。

3、考试结束后，将本试题卷带走妥善保管，答题卡交回。

第一部分听力测试（20小题，20分）一、听句子，选择选择与其内容相符的图片。

每个句子读一遍。

1.A B C2.A B C3.A B C4.A B C5.A B C二、听句子，选择正确的答语。

每个句子读一遍。

6. A. Yes, she does. B. Yes, he does. C. No, she doesn’t.7. A. They are good. B. It’s yellow. C. They are red.8. A. Carrots. B. Pears. C. Eggs.9. A. OK. B. My brother likes it. C. You like it.10. A. Hats. B. Hamburgers. C. Soccer.三、听对话，选择正确的答案。

对话读两遍。

11. What does the woman like?A. She likes apples very much.B. She likes oranges very much.C. She likes bananas very much.12. Does her father like broccoli?A. No, he doesn’t.B. Yes, he likes it a lot.C. Yes, he likes it a little.13. What do they like for dinner?A. They like eggs, salad and fruit.B. They like vegetables and ice cream.C. They like chicken, tomatoes and French fries.14. What does Jane’s brother like playing?A. Soccer.B. Basketball.C. Tennis.15. Who likes French fries?A. Bob.B. Lily.C. Bob and Lily.四、听短文，选择正确的答案。

CBA2011-2012赛季常规赛国内运动员与外援技术运用能力对比分析

Comparative Analysis on Technology Proficiency between Domestic Players and Foreign Aid in CBA 2011--2012 Regular Season
作者：宣暄[1]
作者机构： [1]安庆师范学院体育学院,安徽安庆246133
出版物刊名：中国体育科技
页码： 52-56页
年卷期： 2013年第2期
主题词： CBA;常规赛;国内运动员;外籍运动员;技术运用
摘要：CBA2011-2012赛季常规赛引进高水平的外援不仅提高了联赛的竞技水平，而且，增强了比赛的观赏性。

运用录像观察、数理统计和逻辑分析等方法，对CBA2011-2012赛季常规赛国内运动员与外援技术运用进行统计分析。

研究认为，本赛季常规赛国内运动员与外籍运动员在上场时间、进攻效率、快攻、助攻、抢断、得分、篮板球、犯规方面呈显著性差异，为CBA联赛在外援的引入和国内运动员的培养提供了理论参考。

Bpvsqan2012考研时间

三十
5还有308天
2月小
6还有307天
惊蛰
7还有306天
初三
8还有305天
妇女节
9还有304天
初五
10还有303天
初六
11还有302天
初七
12还有301天
植树节
13还有300天
初九
考研倒计时300天
14还有299天
初十
15还有298天
消费者权益日
16还有297天
十二
17还有296天
十三
18还有295天
处暑
24还有136天
廿五
25还有135天
廿六
26还有134天
廿七
27还有133天
廿八
28还有132天
廿九
29还有131天
8月小
30还有130天
初二
31还有129天
初三
书山有路，勤为径
学海无涯，苦作舟
2012考研日历
2011年9月
周日
周一
周二
周三
周四
周五
周六
危险、怀疑和否定之海，围绕着人们小小的岛屿，
Time will pierce the surface or youth, will be on the beauty of the ditch dug a shallow groove ; Jane will eat rare!A born beauty, anything to escape his sickle sweep
21还有63天
廿八
22还有62天
除夕
23还有61天
春节
1月大
24距复试还有60天
初二
复试倒计时60天

(技术规范标准)现代图书情报技术参考文献著录规范

《现代图书情报技术》参考文献著录规范参考文献的规范使用，既体现科研论文的严谨态度，也是对前人研究成果的尊重。

为规范参考文献的使用要求，本刊严格执行国家标准《文后参考文献著录规则》，归纳总结如下。

1著录格式1.1参考文献类型及其标志(见下表)1.2一般性著录要求（1）著者英文名统一采用“姓+名简称”形式，首字母大写。

如：Piggot T M，Sandhu R。

（2） 3个以下（含3个）著者全部著录，“,”分隔。

著者超过3个，只著录前3个，后加“等”或者“et al”。

（3）参考文献每个著录项之间用“.”分隔。

（4）英文文献对文题名及刊名著录时，文题名及刊名所有单词首字母大写，其他全部小写，刊名用斜体标识。

以下对各种参考文献的著录格式分别给出详细的解释，红色标注部分为任选项，有则提供。

请作者参考应用：表2 不常用参考文献2注意事项（1）公开出版物:参考文献必须是公开出版物（不少于6个）。

如引用非公开出版物，请采用脚注形式。

（2）时效性：参考文献尽可能选用较新的文献，一般来说近三年内的参考文献的数量至少应该占50%-80%。

（3）充分标注:文中凡涉及引用或者参考他人成果（包括定义、公式、方法、数据、图表、历史事件等），全部要进行标注，采用上角标形式，如“[1]”；当文中一处引用多篇文献时，可标注为“[1，3，5]”或者“[2，5-9]”的形式；文末列出的所有参考文献都需在文中进行标注，不可漏标。

（4）合理标注：参考文献标注位置须与此处正文内容直接相关，标注在引用内容的结束标点前，尽量不标注在章节的大标题上。

（5）顺序编码制：采用顺序著录法，即参考文献在文中的标注按序出现。

如，文献[4]的首次标注位置不能先于[3]的首次标注，当然[3]可以重复标注。

（6）著录唯一性：同一参考文献在文中可重复引用多次，文末只著录一次。

比如，著录时不要出现“[4] 同[1]”的字样。

(Chung-Hua Shen Meng-Wen Wu)The Effects of Bank Market Share on Profits It’s Not Just the Bank

The Effects of Bank Market Share on Profits: It’s Not Just Bank Size that MattersChung-Hua Shen*& Meng-Wen Wu*** National Taiwan University，** National Chengchi UniversityAbout the AuthorsChung-Hua Shen, Department of Finance, National Taiwan University, Phone: 886-2-33611087, Fax: 886-2-33611087, E-mail:chshen01@.twMeng-Wen Wu, Department of Money and Banking, National Chengchi University, Phone: 886-6-3120366, E-mail:g1352509@.twThe Effects of Bank Market Share on Profits: It’s Not Just Bank Size that MattersAbstract This paper investigates whether market share affects profits in the banking industry, a phenomenon that we refer to here as the market share effect. Earlier empirical studies have reported mixed results on this issue but mostly use single country data. We employ data for 44 countries from 1998-2004 to investigate this issue. Furthermore, we postulate five institutional factors--structure, efficiency, regulations, government governance and the wealth of a country--to investigate whether any of them could magnify or mitigate the market share effect. Our results show that while structure moderately fuels the market share effect, efficiency does so to a much greater extent. Regulations on different banking activities generate mixed results. Sound government governance is beneficial to escalates the effect and the wealth of a country strengthens the effect, albeit only modestlyKeywords: Market Share, Bank Concentration, Efficiency, Entry BarrierJEL:D43, G21, G28, G38,I IntroductionStudies as to whether bank market shares have a positive effect on bank profits have been engulfed in controversy. In their seminal work, Buzzell, Gale, Bradley and Sultan (1975) identified 37 factors that could affect a company’s profits, and among the most important is market share.1Brouthers, Hastenbury and V en’s (1998) survey of the factors behind mergers and acquisitions supports this view. And, the report of the Group of Ten (2001, p. 101) also stresses that size is the greatest motivation for mergers, reporting that “although mergers and tie-ups seen thus far may not have an obvious strategic goal, the general conclusion is that “bigger is better”.2In Europe, it can be readily noted that the market shares of the three largest banks have all been on the rise, which suggests that market share is considered critical, even though the reason is controversial (Dymski 1999, Deutsche Bank Research 2004). In Asia, particularly since the 1997 Asian crisis, governments have either forced or encouraged1The report is “Profit Impact of Market Strategies (OIMS)” of the Marketing Science Institute, Harvard Business School.2Based on interviews with bankers, they report that, “Interviewees all agreed that the motives for consolidation are affected by the size of the financial institutions involved.”banks to merge for the purpose of becoming larger. Chong, Liu and Tan (2006), for example, report that Bank Negara Malaysia (Malaysia’s central bank) announced a scheme to force the consolidation of the country’s 58 financial institutions into 10 anchor banks, and they point out that “The main objective of the forced merger scheme was to create bigger banks”. Along similar lines, in 2004, the Taiwan government announced that the goal of its second bank policy reform was to have at least three very large banks, each with a market share exceeding 10%, for a total share of more than 30%.3Simply put, market share is customarily deemed a crucial factor affecting bank profits.While the argument that a larger market share can generate greater profits is widely accepted in the practical field and among authorities, academic empirical research results have been far from conclusive. Solid evidence in support of the notion above can be found in discussing the validity of the hypothesis of structure-conduct-performance (SCP) versus the efficiency-structure (ES) in the earlier period, with the structure proxied by the concentration ratio and the efficiency by the market structure. In this regard, Smirlock (1985) and Evanoff and Fortier (1988), for example, found that market share is positively related to profit. Similarly, using the data of banks in Italy, Belgium, France, Holland and Spain, Molyneux and Forbes (1995) attested to a positive relationship between market share and profits. Berger (1995), slightly recently, argued that any comparison between SCP and ES without taking into account real efficiency estimators may be misspecified. By using the U.S. data, he regarded the concentration ratio and market share as market power, and into the regression, he added two efficiency measures, X-efficiency (Xeff) and scale efficiency (Seff), and his results were still in support of the positive relationship between market share and profit. Similar findings were obtained using European data (Goldberg and Rai, 1996).But it cannot be overlooked that conflicting results providing evidence that smaller market-share or middle-size banks which have better profits have also been reported. Berger and Hannan (1998) proposed the quiet life hypothesis which argues3For more information on Taiwan’s second phase of financial reform, readers are referred to/News/taiwan/archives/2007/05/24/2003362231that managers of large banks tend to opt for an easy way of life and do not pursue profit-maximization because they face little competition. Employing UK banks as their sample, Kosmidou, Pasiouras, Doumpos and Zopounidis (2003) find that smaller banks have economies of scale (EOS) and superior profits. Vennet (1998) found that, unlike large banks with assets greater than 1,000 billion euros, European banks with assets of less than 10 billion euros show evidence of EOS. Other studies of scale economy have also found that the average cost curve in banking has a relatively flat U-shape, with medium-sized banks being slightly more scale efficient. (Mester 1987, Clark 1988, Humphrey 1990, Berger, Hunter, and Timme 1993).Further complicating the issue, still other empirical results have shown that the market shares of banks are not at all related to profits. Using bank data for Switzerland, West Germany and New York, Leo (1984) did not find any significant relationship between market shares and profits. Eichengreen and Gibson (2001) employ Greek bank data, Claeys and V ander Vennet (2003) use European bank data, and Bourke (1989) and Molyneux and Forbes (1995) use the largest banks of 12 European countries, but none find any evidence that the two are related.Given the absence of a broad-based consensus, the purpose of this paper is to break the logjam concerning the relationship between market share and profits, which we refer to as the market share effect hereafter. By most accounts, one of the reasons for the mixed results can be attributed to the different samples that have been used. As Leo (1994) pointed out, the true relation between market share and performance can best be explored by adopting cross-country data. He himself, however, adopted data of only three countries seemingly because of data unavailability. To investigate this issue, this paper improves upon Leo’s efforts by using bank data from 44 countries.The use of cross-country data allows for a more profound, more complete understanding of the reasons for the mixed results since we are able to investigate whether the unique “institutional factors” of individual countries matter or not. This paper proposes five “institutional factors”to investigate which ones could conceivably strengthen or weaken the effects of market share on profits, and therefore, better account for the mixed results. The first two institutional factors are based on theconcepts of SCP and ES that are respectively proxied by the concentration ratio and efficiency.4We hypothesize that the effects of market share are enhanced in more concentrated markets or when banks are more efficient. Worth noting here is that the purpose of this paper is not to examine the validity of SCP vis-à-vis ES per se as typically done in the literature.The remaining three institutional factors here are government governance (hereafter governance), bank restrictions and country wealth, which are often found to strengthen or weaken the relations between financial variables and performance, especially in cross-country studies. For example, Shen and Chang (2005), in a related but slightly different study, found that good governance do have influence on the effect of bank restrictions on performance. Shen and Lee (2006) find that not only governance but also income and region can affect the relationship between growth and financial development. Berger, Demirgüç-Kunt, Levine and Haubrich (2004) maintain that indicators for regulation, entry restrictions and other legal impediments to bank competition have important effects on the relation between banks and economic growth. These five institutional factors are accounted for in details in the next section.Two caveats must be pointed out. The terms ‘large market shares’ and ‘large’are used interchangeably throughout this paper. We recognize that the two underlying concepts are not completely the same. A bank with large market share is usually a large bank but a large bank does not necessarily have a large market share. For example, when a country has many banks, a large bank may not have a large share, such as in the case of the U.S.5Thus, we are cautious in interpreting our results when confusion arises. Next, because of the large number of countries, our estimations may suffer from heteroscedasticity of countries. We have difficulty in using the conventional econometric methods, such as fixed or random effects to remove it owing to the missing data, which causes the panel data to be unbalanced. Thus, we add regional dummies to mitigate this impact.4The proxy for efficiency has a long history. Initially, efficiency was proxied by market shares (Smirlock 1985, and Evanoff and Fortier 1988), but later on, it came to be proxied by Xeff and Seff (Berger, 1995). This paper first uses cost/income as the proxy for efficiecy measure and thus uses Xeff and Seff as the robust testing.5We are told that the market share of each bank is restricted to be less than 10% in U.S.The remainder of the paper is organized as follows. Section 2 discusses the five financial institutional factors affecting the relationship between market share and profits. Section 3 presents the econometric model we employ. Section 4 provides the descriptions and sources of the data. Section 5 highlights the empirical analysis of the relationship between market share and profits and shows how it is affected by the five financial institutional factors. Section 6 concludes.2. Financial Institutional Factors2.1 Structure: Concentration Enhancing EffectWe first hypothesize that banks with a large market share are more effective in terms of making a higher profit in a more concentrated market, which we refer to as the concentration enhancing effect. The SCP hypothesis argues that when the concentration ratio increases, banks have greater monopoly power to affect the deposit and loan rates and therefore earn profits. As a case in point, Berger and Hannan (1989) used U.S. data and confirmed that banks in more concentrated markets charge higher rates on small- and medium-sized enterprise loans and pay lower rates on retail deposits. This however stands in contrast to the results of Goldberg and Rai (1996) who found the opposite results when using European data. Gale (1972) divided his sample into high- and low-concentration markets and concluded that large banks in concentrated markets have greater power to affect price. These conflicting empirical evidence are thus worth more studies by using more sample countries. Smirlock’s (1985) study was similar to ours since it considered the interaction terms of market share and concentration ratio6, but it used market share as proxy for efficiency. Smirlock (1985), however, did not employ cross-country data and therefore did not make use ofinstitutional differences.Structure typically refers to the concentration ratio of deposits or the loans of the first three (i.e., k=3) largest banks, which is denoted as CR3. But we also attempt other k=4 and 5.6Smirlock (1985) used the interaction terms of market share and concentration ratio to indirectly test whether the finding-- market concentration has no effect on bank profitability once market share is properly considered-- is due to a potential relationship between market share and monopoly rent- sharing.2.2 Efficiency: Efficiency Enhancing EffectThe efficiency enhancing effect that we introduce here, suggests that the efficiency of bank efficiency can fuel the effect of market shares on profits. This assertion is based on the ES hypothesis that the efficiency of a bank first increases its profitability and then augments its market shares. Berger (1995) used U.S. data and Goldberg and Rai (1996) used European country data and empirically showed that bank efficiency can increase profits. And, in other studies, though they did not use banks as their sample, Lambson (1987) and Hay and Liu (1997) showed that in a competitive market, the efficiency of firms could affect their market share, and subsequently their profits.Two approaches have been used to measure efficiency. The first one involves adopting cost/income. Given his skepticism about the measure of X-efficiency,7 V ennet (2002) adopts the cost/income measure to investigate the efficiency of European banks. He, like most Wall Street analysts and regulators, view this indicator as the key measure of bank efficiency. Also, see Demirgüç-Kunt, Laeven and Levine (2004) for the similar application. The second one is the X-efficiency and Scale-efficiency, which are obtained by estimating a cost function, where the former is the measure of efficiency relative to its peer banks and the latter is a measure of that bank’s own economies of scale (Berger, 1993, 1995). In their survey of 113 papers, Berger and Humphrey (1997) reported that large banks exhibit more about Xeff and less about Seff, which simply means that large banks can still increase profits by improving X-efficiency but are uneasy go gain profits by expanding the scale.This paper first uses cost/income to proxy the efficiency of banks because of its wide acceptance as the measure and the easy calculation. Then, we estimate the cost function of our 44 sample countries to obtain Xeff and Seff that we employ to test for robustness.2.3 Regulation: Uncertain EffectRegulations are a double-edged sword; on the one hand, they deter large banks 7He argues that the standard error of' the estimates from the cost function are not accounted for in the subsequent profit regression.from partaking in tremendously risky activities and protect them from default. In this sense, they enhance the positive effects of large size banks on profits. On the other hand, regulations limit large banks from optimizing their business, such as in highly diversified activities that would otherwise increase risk. In this case, the restrictions mitigate the positive effects of large size banks. Godlewski (2006) supports the former argument, and by contrast, Francisco (2004) holds that banks in countries with stricter regulations have a lower charter value, which ironically enough increases their incentive to adopt risk-laden policies. In short, whether greater restrictions are beneficial to banks may in effect depend on the actual type of regulation.With this in mind, we consider two types of regulatory restrictions. The first set comprises restrictions on banking activities in securities (Restrict_S), insurance(Restrict_I) and real restate (Restrict_E). These three indices measure the degree of regulatory restrictiveness on each activity based on a range of 1 to 4, with a larger number representing greater restrictiveness. That is, the higher the number, the more restrictive the regulation of country is. It is important to note that it is not easy to predict a priori the effects of these restrictions on bank performance, as explained above. For example, Shen and Chang (2005) find that restrictions on securities and insurance reduce banking profits but that restrictions on real estate have the opposite effect. They contend that this is largely because of the high risk of real estate during their sample period; Countries with tighter restrictions on real estate were able to insulate their banks from investing in these falling markets, thus shielding them from bad loans and allowing them to make higher profits. Briefly stated then, the effects of the degree of regulatory restrictiveness in securities (Restrict_S), insurance (Restrict_I) and real restate (Restrict_E) on bank profits are uncertain.In the second type of regulatory restrictions is the entrance restrictions, but they too are at the center of contradictory opinions. One is the view that new entries could be a hindrance to the market, which means that allowing foreign banks or a new local bank to be established increases competition in the market and thus shrinks the profits of existing large banks. Gilbert (1984) shares this view, claiming that when there is unrestricted entry into banking markets, the pricing of banking services mustbe influenced by the threat of entry by firms not already in the market, irrespective of the existing structure of the market. Thus, large banks tend not to monopolize the local market and their monopoly power decreases when the entrance threshold level is low. Evanoff and Fortier (1988) found strong support for the argument that market share matters when markets are characterized with significant entry barriers. The second view--that new entries could be beneficial to the market -- is based on the premise that the entrance of foreign banks increases efficiency and the competitiveness and this on the grounds that they are threatened or can learn more management and governance skills from the new entries. In a similar vein, Berger et al. (2000) propose the global advantage hypothesis that posits that some efficiently managed foreign institutions are able to overcome cross-border disadvantages and operate more efficiently than domestic institutions by disseminating their superior managerial skills or best-practice policies and procedures over more resources, thereby lowering costs. Lensink and Hermes (2004) also maintain that foreign bank entry may lead to positive spill-over effects.8Micco, Panizza and Yanez’s (2004) results provide solid evidence to support this view; they contend that in developing countries, the entry of foreign banks plays an invaluable role by prompting domestic banks to become more efficient in terms of overhead costs and spreads.In the present study, we consider two entrance restrictions, as suggested by Barth et al., (2006). The first pertains to limitations on foreign bank entry/ownership (EntryFor), which measures whether foreign banks are allowed to own domestic banks and whether foreign banks are allowed to partake in a country’s banking industry. Its range is from 0 to 3, with a higher value indicative of greater ease for and fewer restrictions on a foreign bank. The second type of restriction is related to requirements (EntryReq) with respect to various types of legal submissions for a local bank to obtain a banking license. It represents the ease with which a foreign bank can set up as a new local bank and ranges from 0 to 8, where a higher value denote greater8Lensink and Hermes (2004) advocate that, first of all, foreign banks may introduce new financial services and that this may motivate domestic banks to also develop such new services, thereby improving the overall efficiency of financial intermediation in the domestic financial system. Moreover, foreign banks may introduce modern and more efficient banking techniques that are new to domestic banks. These up-to-date banking techniques may be copied. Additionally, foreign banks may help to improve the management of domestic banks, especially if foreign banks directly participate in the management of those domestic banks -- for example, in the case of a joint-venture or take-over.difficulty. The expected sign is uncertain2.4 Government Governance: Governance Enhancing EffectSound government governance is expected to enhance the effect of market shares in that better government governance permits banks to fully devote their time and skills, and this is what we refer to here as the governance enhancing effect. Good governance, which comprises a lower degree of corruption, better law and order, and a more effective legal systemdo indeed reduce transaction costs, strengthen trust and encourage economic agents to become fully committed. Good governance is often found to enhance the relationship between some economic forces. To cite a few examples, it enhances the positive relationship between financial deepening and economic growth (Shen and Lee 2006), reduces the negative effect of restrictions on banking activities in securities (Shen and Chang 2005), and it mitigated the consequences of the Asian financial crisis (Mitton 2002). We hypothesize that good government governance can increase the effects of market shares.9Our three governance indices are the protection of investor (Protect_I), the protection of creditor (Protect_C) and the efficiency of law (LawEff), which are taken from La Porta, Lopez-de-Silanes, Shleifer, and Vishny (hereafter LLSV) (1998). As for the first of these, investors may be better protected when dividend rights are tightly linked to voting rights. We use anti-director rights as the proxy because shareholders exercise their power by voting for directors. In the case of the second governance index, proxied by creditor rights, which are more complex than shareholder rights because the most basic creditor right is the right to repossess and then liquidate or keep collateral and to have a say in reorganization should a loan be in default. As regards the third one, the efficiency of law can serve as a substitute for weak rules since active and well-operated courts can step in and rescue investors should they ever be abused by managers. We use the product of the efficiency of the judicial system and the rule of law as the proxy here. It is expected that a country with a good governance index should have more creditability and less corruption, which9Beck, Demirgüç-Kunt, and Maksimovic (2005) find that firms that operate in underdeveloped systems with higher levels of corruption are affected by all types of hindrance to a greater extent than firms operating in countries with less corruption.may or may not improve banks ’ performance when these banks are restricted with regard to engaging in various activities.2.5 Wealth of Countries: Rich Country EffectA large bank in a rich country tends to have more opportunity to sell its products, which we refer to here as the rich country effect . Neely and Wheelock (1997) found that in the U.S., banks earn higher profits in areas with high GDP per capita. Grigorian and Manole (2002) support this view, claiming that large banks in rich countries earn higher profits by virtue of their superior skills and greater efficiency. Thus, we expect that when a country is more prosperous, it intensifies the effects of market share on profits. We use GDP per capita (GDPper) as the proxy for the wealth of countries.3. Econometric ModelOur model is expressed as follows:kit it kit kit kit kit εααααα+++++=GDPgrow StateOwn L/D MS ROA 43210, (1)Region Z 2101βββα++= (2) whereZ = [Structure, Efficiency, Regulation, Governance, Income ]where k =1,…,K ,N i ,...,1=, T t ,...,1=, and K =1,877 is the number of banks used in this paper, N = 44 is the number of countries, and T =7 is the sample period. The dependent variable, ROA, is the proxy for bank profit, MS is the market share of bank assets, L/D is the ratio of loans over deposits, StateOwn is the shares owned by government and GDPgrow is the GDP growth rate.The five financial institutional factors are summarized in Z: Structure is proxied by the concentration ratio of the three largest banks (CR3) based on deposits; Efficiency is first proxied by Costs / Income, then proxied by Xeff and Seff in our robustness testing; Regulation includes restrictions on banking activity and entry barriers; the former is proxied by restrictions on securities (Restrict_S), on insurance(Restrict_I) and on real estate (Restrict_E); the latter is proxied by limitations on foreign bank entry/ownership (EntryFor) and entry into banking requirements (EntryReq); Governance includes the protection of investor (Protect_I), proxied by anti-director rights, the protection of creditor (Protect_C), proxied by creditor rights, and the efficiency of law (LawEff), proxied by the product of rule of law and efficiency of judicial system; and Income is proxied by GDP per capita (GDPper). Our regional dummy (Region) is catchall variables that are used to control the remaining heterogeneity, including European (Euro for short), North American, Latin American (Latin for short), Asian, and African.We refer to Equation (1) as the basic model and Equations (1) and (2) simultaneously as the extended model. In the basic model, we study whether the α, has a positive or negative effect on bank profit or not. Then, we coefficient of MS,1investigate whether the institutional factors could affectα. The missing data in our1sample cause our panel to be unbalanced, which makes the estimation of the model using the fixed or random effects of the panel difficult. For this reason, we use the simple ordinary least squares (OLS) with White heteroscedasticy errors and weighted least squares (WLS).4. Sources of the Data and Basic StatisticsOur sample banks are taken from 44 countries, where 25 are high-income countries, 8 upper-middle income countries, 7 lower-middle income countries and 4 low-income countries.10The total number of banks is 1,877 banks, comprising commercial banks, saving banks and cooperative banks. The bank financial statement data are primarily based on consolidated data, but unconsolidated data are used when consolidated data are not available. The sample covers the 1998-2004 period.The data used in this study are obtained from a number of different sources. The10The high-income countries comprise Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Hong Kong, Ireland, Israel, Italy, Japan, Korea, the Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, the United Kingdom and the U.S.A.; the upper middle-income countries are Argentina, Chile, Malaysia, Mexico, South Africa, Taiwan, Turkey and Uruguay; the lower middle-income countries include Brazil, Colombia, Egypt, Peru, the Philippines, Sri Lanka and Thailand; and the low-income countries are India, Kenya, Nigeria and Pakistan.financial variables, i.e. ROA, MS, Cost/Income, L/D and StateOwn, are taken from the Bankscope data set, published by Fitch-IBCA Ltd, and it contains annual balance sheet data for a wide variety of banks;the macro variables GDPper and GDPgrow are taken from the World Development Index (WDI), published by the World Bank; the regulation variables, i.e. restrictions on banking activities and on entry are taken from Barth et al. (2006); and the governance variables, i.e. Protect_I and Protect_C and LawEff, are taken from LLSV. See Table 1 for the definitions and sources of the variables.Table 2 presents the basic statistics of the above variables for the 44 countries. The average values of the dependent variable, ROA, are given in the first column. For all countries, the average is 0.746,and the highest value is for Nigeria (2.019%), followed by Brazil (1.838%) and Kenya (1.782%). The lowest value falls on Thailand (–1.415%) that is just slightly ahead of Uruguay (–0.723%) and Korea (–0.239%).In the second column, MS (market share) shows an average of 3.249%. The three highest ratios are found in Finland (11.722%), New Zealand (11.191%) and Singapore (10.141%), whereas the lowest, in an ascending order, are in the U.S.A.(0.222%), Germany (0.2777%) and Japan (0.296%). The general trend is that MS is greater in Nordic countries and smaller in countries with a large number of banks. The three countries with the highest L/D ratios are South Africa (418.2%), Denmark (323.807%) and Portugal (300.8%), while those with the lowest are Turkey (39.273%), Nigeria (43.5%) and Pakistan (48.6%). As expected, the lending ratios of high-income countries are higher than those of low-income countries.Table 3 reports the basic statistics of market structure (CR3), bank efficiency (Cost/Income), regulation (Restrict_S, Restrict_I, Restrict_R, Entry For, and EntryReq) and economic development (GDPper). The three countries with the highest CR3 are Finland (78.8%), Singapore (66.8%) and Sri Lanka (64.7%), whereas the three with the lowest values are the U.S.A. (12.7%), Japan (18.3%) and Italy (24.8%). The countries with the highest and lowest CR3 are slightly overlapped with those of MS. Reported in the next three columns are the three restrictions on bank activities, the 1998 - 2004 scores of which we average. The averages of Resrict_S, Restrict_E。

FTC纪念册.pdf

2012FIRST科技挑战赛02 04 06 07 08 16 18 20 22 24 26 27 28 30 32 34 37 38裴钢校长寄语：该活动的创办宗旨与同济大学倡导并正在推动的“卓越工程师”培养目标一致，就是要培养学生的创新意识、动手能力和团队合作精神。

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目前，我国要从“中国制造”走向“中国创造”、“中国设计”，在这一进程中，作为把人才培养作为第一要素的大学大有可为，也必须有为。

0203赛前Before the competition 0405First科技挑战赛日程安排表面试3月3日,星期六 15支中国团队到达评审会议( draw lots to determine the order )机器人检查开始( )练习场开放配备 FCS 系统9 Panel A T eam 1T eam 4T eam 7T eam 10T eam 13Panel B T eam 2T eam 5T eam 8T eam 11T eam 14Panel C T eam 3T eam 6T eam T eam 12T eam 15中国团队参观同济大学嘉定校区12支国际团队到达评审会议( draw lots to determine the order )T eam 16 T eam 17 T eam 18 T eam 19 T eam 20 T eam 21 T ea m 22 T eam 23 T eam 24 T eam 25T eam 26 T eam 27机器人检查结束 FCS 系统关闭练习场关闭（不配备FCS 系统)3月日，4星期日Registration begins 评审会议机器人检查开始练习赛评审面试 (如果需要的话)Assemble Opening Ceremonies participant s开幕式资格赛 Judges visit teams inPit AreaSet up lunchesLunch break for all12:30 pm 12:45 pm 13:00 pm1:00 pm 1:20 pm 1:40 pm 2:00 pm 2:20 pm 2:40 pm 3:00 pm 3:30 pm 3:45 pm 4:00 pm 4:20 pm 4:40 pm 5:00 pm 5:30 pm 8:00 pm7:30 am 7:45 am 9:00am 9:30am 9:50 am 11:00 am 12:30 pm7:30 am 7:45 am 8:45 am 9:30 am9:50 am 12:30 pm 0706FIRST 以及FIRST 科技挑战赛项目简介“……要创造一个世界，在这个世界里，人们赞美科学与技术，年轻人梦想成为科学与技术领域的英雄。

The Long and Short of Quality Ladders

NBER WORKING PAPER SERIESTHE LONG AND SHORT (OF) QUALITY LADDERSAmit KhandelwalWorking Paper 15178/papers/w15178NATIONAL BUREAU OF ECONOMIC RESEARCH1050 Massachusetts AvenueCambridge, MA 02138July 2009I am especially grateful to my dissertation committee, Irene Brambilla, Penny Goldberg and Peter Schott, for guidance and support. I have benefited from conversations with Steve Berry, Ray Fisman, Juan Carlos Hallak, David Hummels, Kala Krishna, Chris Ksoll, Frank Limbrock, Alex Mcquoid, Nina Pavcnik, Siddharth Sharma, Gustavo Soares, Robert Staiger, Catherine Thomas, Daniel Trefler, Chris Udry, Eric Verhoogen, David Weinstein, Jeffrey Weinstein, and various seminar participants. Special thanks also to Amalavoyal Chari. All errors are my own. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.© 2009 by Amit Khandelwal. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.The Long and Short (of) Quality LaddersAmit KhandelwalNBER Working Paper No. 15178July 2009JEL No. F1,F15,F16ABSTRACTPrices are typically used as proxies for countries' export quality. I relax this strong assumption by exploiting both price and quantity information to estimate the quality of products exported to the U.S. Higher quality is assigned to products with higher market shares conditional on price. The estimated qualities reveal substantial heterogeneity in product markets' scope for quality differentiation, or their "quality ladders.'' I use this variation to explain the heterogeneous impact of low-wage competition on U.S. manufacturing employment and output. Markets characterized by relatively shorter quality ladders are associated with larger employment and output declines resulting from low-wage competition. Amit KhandelwalGraduate School of BusinessColumbia UniversityUris Hall 606, 3022 BroadwayNew York, NY 10027and NBERak2796@The Long and Short(of)Quality Ladders∗Amit Khandelwal†Columbia Business School&NBERFirst Draft:November2006This Version:July2009AbstractPrices are typically used as proxies for countries’export quality.I relax this strong assumption by exploiting both price and quantity information to estimate the quality of products exported to the U.S.Higher quality is assigned to products with higher market shares conditional on price.The estimatedqualities reveal substantial heterogeneity in product markets’scope for quality diﬀerentiation,or their“quality ladders.”I use this variation to explain the heterogeneous impact of low-wage competition onU.S.manufacturing employment and output.Markets characterized by relatively shorter quality laddersare associated with larger employment and output declines resulting from low-wage competition. Keywords:Quality Ladders;Low Wage Competition;Quality Specialization;Product DiﬀerentiationJEL Classiﬁcation:F1,F15,F161IntroductionThe quality of products manufactured by countries aﬀects many economic outcomes in international and development economics.Past studies have consistently found that product quality inﬂuences cross-border trade;richer countries consume and export higher quality products than developing countries.1The ability ∗I am especially grateful to my dissertation committee,Irene Brambilla,Penny Goldberg and Peter Schott,for guidance and support.I have beneﬁted from conversations with Steve Berry,Ray Fisman,Juan Carlos Hallak,David Hummels,Kala Krishna, Chris Ksoll,Frank Limbrock,Alex Mcquoid,Nina Pavcnik,Siddharth Sharma,Gustavo Soares,Robert Staiger,Catherine Thomas,Daniel Treﬂer,Chris Udry,Eric Verhoogen,David Weinstein,Jeﬀrey Weinstein,and various seminar participants. Special thanks also to Amalavoyal Chari.All errors are my own.†Uris Hall,Room606,3022Broadway,New York,NY10027,email:ak2796@,website: /faculty/akhandelwal/.1Support for the demand-side explanation,initially posited by Linder(1961),has been shown by Hallak(2006)and Verhoogen (2008).Studies by Hummels and Klenow(2005)and Schott(2004)provide systematic evidence that richer countries exportof developing countries to transition from low-quality to high-quality products is therefore seen by some as a necessary(but certainly not a suﬃcient)condition for export success and,ultimately,economic development.2 In addition,quality upgrading features prominently in current debates about the role of international trade in driving wage inequality.But while this research suggests a positive association between quality upgrading and income per capita,Verhoogen(2008)and Goldberg and Pavcnik(2007)argue that quality upgrading also aﬀects the variance of the income distribution through changes in the relative demand for skilled labor. Quality specialization may therefore partly explain why inequality has risen in developing countries following trade liberalizations,in contrast to Stolper-Samuelson predictions.Diﬀerences in the quality space may also aﬀect how closely countries’products compete with one another and therefore have implications for the impact of trade on industry employment and output Leamer(2006).These studies stress the importance of understanding why product quality varies across countries and over time,and how it is inﬂuenced by policy.The challenge faced by this literature is that product quality is unobserved.Research in the international trade literature has attempted to deal with this problem by using prices(or unit values)to proxy for quality.This approach,while convenient,requires strong assumptions since prices could reﬂect not just quality,but also variations in manufacturing costs.For example,in1999, the U.S.imported Malaysian and Portuguese women’s trousers(HS6204624020)at unit values(inclusive of transportation and tariﬀduties)of$146and$371,respectively.If prices are assumed to proxy perfectly for quality,Malaysian trousers would possess about half the quality of Portuguese trousers.However,the annual wage in the apparel sector for Malaysia and Portugal was$3,100and$5,700,respectively(UNIDO, 2005).So the diﬀerence in unit values may instead be a reﬂection of these diﬀerent factor prices.Why would a consumer ever purchase expensive Portuguese trousers if they,in fact,possess lower quality?One explanation is that a fraction of consumers have a preference for the horizontal attributes of Portuguese trousers(for instance,the cut or color patterns).Indeed,U.S.consumers imported more than82,000dozens of Malaysian trousers compared to only865dozens from Portugal.Idiosyncratic preferences for products’horizontal attributes can therefore break the direct mapping from prices to quality that has been traditionally assumed.This paper estimates the quality of U.S.imports using a procedure that relaxes the strong quality-equals-price assumption.The quality measures are derived from a nested logit demand system,based on Berry(1994),that embeds preferences for both horizontal and vertical attributes.3Quality is the vertical higher quality products.Baldwin and Harrigan(2007),Hallak and Sivadasan(2009),Kugler and Verhoogen(2008)and Johnson (2009)also document the role of product quality in inﬂuencing production and trade patterns.2Kremer(1993)provides microeconomic foundations for the quality production function and its implications for economic development(see also Verhoogen(2008)and Kugler and Verhoogen(2008)).Endogenous growth models that highlight the importance of product quality include Grossman and Helpman(1991).Hausmann and Rodrik(2003),Rodrik(2006)and Hidalgo et al.(2007)highlight the importance of export quality for economic performance.3Other studies within international trade that use a nested logit structure include Goldberg(1995)and Irwin and Pavcnikcomponent of the estimated model and captures the mean valuation that U.S.consumers attach to an im-ported product.The procedure utilizes both unit value and quantity information to infer quality and has a straightforward intuition:conditional on price,imports with higher market shares are assigned higher quality.Importantly,the procedure requires no special data beyond what is readily available in standard disaggregate trade data.It is also easy to implement;here,I estimate separate demand curves for approxi-mately hundreds of manufacturing industries.Moreover,the procedure recovers quality at theﬁnest level of product aggregation available(for the U.S.data,this is the ten-digit HS level).4The inferred qualities indicate that developed countries export higher quality products relative to developing countries.Thisﬁnding is consistent with Schott(2004)who uses unit values to proxy for quality.However,the estimates also reveal substantial heterogeneity in product markets’scope for quality diﬀerentiation,or quality ladders,which I measure as the range of qualities within the product market.In markets with a larger scope for quality diﬀerentiation,or a“long”quality ladder,unit values are relatively more correlated with the estimated qualities.In these markets,prices appear to be appropriate proxies for quality.In contrast,prices appear to be less appropriate proxies for quality in markets with a narrow range of estimated qualities(“short”ladder markets).This provides suggestive evidence that expensive imports in short-ladder markets coexist with cheaper rivals due to horizontal product diﬀerentiation.That is,although the average U.S.consumer attaches a low valuation to the expensive import,there is a fraction of consumers who still value the product.This heterogeneity underscores the drawback in invoking the quality-equals-price assumption,particularly for products characterized by short quality ladders.I use this heterogeneity in ladder lengths to demonstrate that quality specialization has important implications for the bor market.The public’s fear of globalization is often rooted in the vulnerability or, to use Edward Leamer’s terminology,the contestability of jobs.According to Leamer,the contestable jobs are those where“wages in Los Angeles are set in Shanghai”(Leamer(2006),p.5).A recent study by Bernard, Jensen,and Schott(2006)provides evidence that the probability of U.S.plant survival and employment growth are negatively associated with an industry’s exposure to import penetration,particularly from low-wage countries.5However,while low-wage competition negatively aﬀects output and employment growth, the impact is heterogenous across industries.For instance,between1980and the mid-1990s,electronics (SIC36)experienced greater low-wage import penetration than fabricated metals(SIC34)but experienced (2004)although these papers do not focus on the quality of imported products.4An alternative procedure developed by Hallak and Schott(2007)relies on the similar intuition to infer countries’export quality to the U.S.,but their methodology prevents estimating quality at theﬁnest level of disaggregation due to data limitations.5Other studies studying the negative relationships between trade and employment include Sachs and Shatz(1994),Free-man and Katz(1991)and Revenga(1992).Bernard,Jensen,and Schott(2006)explicitly connect the relationship between employment and trade with low-wage countries,deﬁned as nations with less than5percent of U.S.per capita GDP.I use their deﬁnition of low-wage countries in this paper(see Table1).a smaller employment decline.6Using a simple model developed in Section2,I demonstrate that the impact of low-wage competition on U.S.industries will vary with its quality ladder.My argument is related to a body of research that reject standard model predictions of factor price equalization(FPE).7These studies show that if countries inhabit diﬀerent cones of(quality)diversiﬁcation,with developing countries exporting low-quality products,then developed countries will be insulated from movements of wages in developing countries.However,if markets vary in their scope for quality diﬀerentiation,developed countries will experience heterogeneity in their exposure to developing countries.In long-ladder markets,developed countries can insulate themselves from the South by using comparative advantage factors(e.g.,skill,capital and/or technology)to specialize atop the quality ladder.In short-ladder markets,however,developed countries will be directly exposed to Southern competition because quality upgrading is infeasible.Thus,a market’s scope for vertical diﬀerentiation is important for understanding Leamer’s notion of contestable jobs.Iﬁnd robust support for this hypothesis by matching U.S.industry data and import competition to quality ladders constructed from the estimated qualities.Consistent with Bernard et al.(2006),Iﬁnd that industry employment is negatively associated with import penetration,particularly from low-wage countries. However,the empirical results conﬁrm that import penetration has a weaker impact on employment in industries with long quality ladders:a ten percentage point increase in low-wage penetration is associated with a6percent employment decline in an industry characterized by an average quality ladder length.A similar increase in competition in a long-ladder industry(one standard deviation above the mean)results in only a1.4percent employment decline.Diﬀerential impacts on industry output are similar.Importantly,the impact of import competition on short and long-ladder industries is similar in magnitude to the diﬀerential impact on low and high capital-intensive industries.In other words,even after controlling for the diﬀerential impact through traditional channels,such as capital and skill intensities(see Sachs and Shatz(1994)and Bernard et al.(2006)),the quality ladder remains an important determinant of an industry’s vulnerability to low-wage competition.Moreover,the heterogenous eﬀect is not precisely captured if one simply uses variations in unit values.These results complement the literature studying the relationship between quality specialization and labor markets.But while existing studies focus predominantly on developing countries(see Goldberg and Pavcnik(2007),Verhoogen(2008),Kaplan and Verhoogen(2005)),the evidence here suggests that quality specialization is also important for developed countries.Quality ladders may therefore help identify those markets that are likely to be contested by competition from low-wage countries.6One potential explanation is diﬀerences in capital intensity,but in1980,electronics was less capital intensive than fabricated metals.Indeed,this paper oﬀers evidence that capital intensity only partly explains the heterogeneity in U.S.employment outcomes due to import competition.7For instance,see Leamer(1987)and Schott(2003).The remainder of the paper is organized as follows.Section2oﬀers a simple model to illustrate that exposure to low-wage competition is greater in markets with short quality ladders.In Section3,I discuss the approach used to infer quality from trade data.The data and quality estimation results are presented in Section4.Section5applies the quality estimates to test the implications of quality specialization for U.S. employment.I conclude in Section6.2A Model of Contestable JobsThis section develops a simple model that delivers two comparative static results.First,the impact of foreign competition on domestic market shares is larger from low-wage countries.Second,the impact will depend on the market’s quality ladder length.I then use the empirical quality measures derived in Section3to assess the predictions of the model.The model is partial equilibrium and analyzesﬁrms in two regions,North(N)and South(S),where the Southernﬁrms freely export to the North.The wages in each country are determined by an outside sector and are therefore treated as exogenous:w N>w S.Each region has J homogenousﬁrms that compete by manufacturing horizontally and vertically distinct varieties.Following Krugman(1980)and Melitz(2003), horizontal diﬀerentiation is costless so in equilibrium,allﬁrms produce horizontally distinct varieties.But as in Flam and Helpman(1987),vertical(e.g.,quality)diﬀerentiation depends on a Ricardian-type comparative advantage given by region c’s technology,Z c.I assume that Northernﬁrms have access to better technology than the South:Z N>Z S.Firm j uses this technology to manufacture a variety subject to a marginal cost function that is increasing with quality(λj):w c+λ2j,for c∈{N,S}.82Z cThe consumers who live in the North have discrete choice preferences.Consumer n observes the domestic and Southern varieties and chooses the variety j that provides her with the highest indirect utility,V nj=θλj−αp j+ nj.(1) Quality is deﬁned as an attribute whose valuation is agreed upon by all consumers:holding pricesﬁxed, all consumers would prefer higher quality objects.The vertical component can be interpreted as the clarity or sharpness of a television screen or it can reﬂect the perceived quality that results from advertising.In either case,quality represents any attribute that enhances consumers’willingness-to-pay for a variety.An alternative interpretation is thatλrepresents a shift parameter in the variety’s demand schedule:holding price p jﬁxed,demand shifts out when the quality improves(Sutton,1991).The empirical identiﬁcation of quality relies on this latter intuition.The parameterθreﬂects the consumers’valuation for quality and,as shown below,represents a proxy for the market’s quality ladder in the model.8One can think of this marginal cost function as arising from aﬁxed-proportions technology that combines labor and capital (with the rental rate on capital being implicitly treated as one).in the proportion1toλ22ZHorizontal product diﬀerentiation is introduced in(1)through the consumer-variety-speciﬁc term, nj.Following standard practice in the discrete choice literature, nj is assumed to be distributed i.i.d. type-I extreme value.Unlike the vertical attribute,the horizontal attribute has the property that some people prefer it while others do not and on average,it provides zero utility.9Denote the mean valuation for variety j asδj≡θλj−αp j.Under the distributional assumption,the market share of variety j is given by the familiar logit formulam j=eδjkeδk.(2)Aﬁrm from region c maximizes proﬁts in the Northern market by choosing price and quality bysolving the following problemmaxp j,λjp j−w c−λ2j2Z ceδjkeδk(3)The market is characterized by monopolistic competition with a suﬃciently large number ofﬁrms that no oneﬁrm can inﬂuence the market equilibrium prices and qualities.The optimal price charged by variety j is therefore10p∗j=1α+w c+λ∗2j2Z c,∀j∈c(4)Under this pricing rule,ﬁrms charge a markup(1α)over their marginal cost.The optimal quality choice equates the marginal beneﬁt of choosing quality to its marginal cost:λ∗j=θZ cα,∀j∈c(5)Equations(4)and(5)indicate that allﬁrms within a region choose the same price and quality(but recall that allﬁrms diﬀerentiate their varieties in the(costless)horizontal dimension).I therefore drop the subscript j and index the representativeﬁrm’s choice in each region by N or S.Note also that the market share in(2) simpliﬁes to m c=eδcJ(eδN+eδS),c∈{N,S}and the aggregate market share in each region is M c=Jm c.The optimal price and quality choice imply that the mean valuation consumers attach to the representativeﬁrm in region c isδ∗c≡θλ∗c−αp∗c=θ2Z c2α−αw c−1,c∈{N,S}.(6)The Northernﬁrms manufacture the higher quality varieties since Z N>Z S.11Below,I verify that more advanced countries indeed export higher quality products using the newly proposed quality measures 9For example,comfort is a quality attribute since,ceteris paribus,all consumers prefer more comfort to less.An article of clothing’s fashion or style is a horizontal attribute since at equal prices,not all consumers would purchase the same style(e.g., stripes versus solids).10If aﬁrm takes into account the impact of its decision on the denominator in(2),the optimal price is given by p∗j=1α(1−m j)+w c+λ∗2j2Z c.As discussed in Anderson et al.(1992),monopolistic competition assumes there are a suﬃciently largenumber of varieties so that the market share of any one variety is negligible.The optimal price is therefore given by(4).11Since quality is a monotonic function of technology,prices are suﬃcient statistics for quality in this model.However,if Z N=Z S,all qualities would be identical,but the North would charge higher prices because of higher manufacturing costs. Thus,empirically,prices alone may confound diﬀerences in quality and quality-adjusted manufacturing costs.which provides a justiﬁcation for this assumption.These higher quality Northernﬁrms will also have larger market shares ifθ2(Z N−Z S)>α(w N−w S),(7)since this implies thatδ∗N >δ∗S.This condition in(7)holds if consumers’valuation for quality is suﬃcientlyhigh or the North’s technological prowess is suﬃcient to overcome its disadvantage in manufacturing costs. This assumption is consistent with substantial theoretical and empirical work arguing that higher quality, or more productive,ﬁrms have higher output(and market shares).12I deﬁne the market’s quality ladder as the diﬀerence between the highest and lowest quality(Gross-man and Helpman,1991).As discussed below,the empirical measures cannot separately identifyλfrom the consumers’valuation for quality(θ).I therefore deﬁne the market’s quality ladder asLadder(θ)≡θλ∗N−θλ∗S=θ2α(Z N−Z S).(8)The market’s quality ladder can be indexed byθand so as the valuation for quality increases,the quality ladder increases,or lengthens.The scope for quality diﬀerentiation will therefore vary according the con-sumers’valuations for quality in each market.13Moreover,as the quality ladder increases,the market sharegains are disproportionately distributed to the manufacturers of the higher quality(∂δ∗N∂θ>∂δ∗S∂θ).This simple model abstracts away from the endogenous“lengthening”of the ladder that may occur in a long-run equilibrium with technological progress or shifts in consumer preferences.Instead,I assume that the quality ladder isﬁxed which may be appropriate in the short to medium run and mitigate endogeneity concerns in the empirical analysis by assigning a market’s quality ladder its initial length.This assumption is consistent with the data which reports a persistence between a market’s initial ladder length and itsﬁnal period length.That is,on average,markets with initially“short”ladders are not“long”by the end of the sample,implying that the quality ladder length is an intrinsic attribute of a market characterizing its scope for quality diﬀerentiation.14I can now analyze how the aggregate Northern market share changes with Southern wages,and how this impact varies according to a market’s quality ladder length.Theﬁrst result shows that the North loses market share as Southern manufacturing wages decline:∂M NS =−M N M S∂δ∗SS>0(9)since∂δ∗SS=−α.(10)12For instance,see Melitz(2003)and Bernard et al.(2007).13The ladder length could also vary by changing Z N and the predictions of the model do not change.Hence,the contestable jobs hypothesis does not hinge on the source of the market’s scope for quality diﬀerentiation.14A market’s intrinsic scope for quality diﬀerentiation is closely related to escalation principle developed in Sutton(1998).Thus,Southernﬁrms become more competitive as its manufacturing costs falls and this gain comes at the expense of lower market shares for the Northernﬁrms.This comparative static is quite intuitive and is supported by existing empirical evidence.For instance,Bernard et al.(2006)show that output and employment for U.S.plants are negatively associated with import competition,but the impact is much larger when import competition originates from countries with less than5%of U.S.per capita GDP.Importantly,this model adds quality diﬀerentiation to show that the intensity of competition within a market depends on the quality ladder length.In particular,while(9)indicates that the North’s market share falls as Southern wages decline,it suﬀers a smaller loss in markets characterized by longer quality ladders(highθmarkets).This is seen by diﬀerentiating(9)with respect toθ:∂2M N ∂w S∂θ=−∂2δ∗S∂w S∂θM N M S+∂δ∗S∂w SM N∂M S∂θ+M S∂M N∂θ=−∂δ∗S∂w SM N M2S−M2N M S∂δ∗N∂θ−∂δ∗S∂θ=∂δ∗S∂w SM N M S(M N−M S)∂δ∗N∂θ−∂δ∗S∂θ=−θM N M S(M N−M S)(Z N−Z S)<0,(11)since M N>M S.This derivative shows that in long-ladder markets(highθ),the sensitivity of Northern market shares to Southern competitiveness is reduced.As a result,a decrease in the South’s wage results in a smaller decline of the North’s market share in long ladders.The model shows that trading with the South can generate a diﬀerential impact on two markets that are otherwise identical but vary according in their quality ladders.This result is related to more general models of international trade that predict a breakdown of FPE when countries are fully specialized in production.In contrast to a single-cone equilibrium,where endowments are such that all countries produce all goods,the conditions required for factor price equalization are not met in multi-cone equilibrium because countries specialize in varieties tailored to their endowments.15Schott(2004)has extended this analysis to within product specialization where endowment diﬀerences cause countries to specialize in diﬀerent segments of a product’s quality ladder.The model here sharpens this analysis by arguing that the scope for quality specialization varies across markets.3Empirical ImplementationThis section describes the procedure that infers quality using price and quantity information from standard disaggregate trade data.The estimated qualities are then used to verify predictions from the model.15For evidence in favor of the hypothesis that countries inhabit multiple cones of diversiﬁcation,see Leamer(1987),Davis and Weinstein(2001)and Schott(2003).The methodology is based on the nested logit framework by Berry(1994).The nested logit has the advantage over the logit in(1)because it partially relaxes the independence of irrelevant alternatives(IIA) property by allowing for more plausible correlation structures among consumer preferences.To understand why this is important,suppose a consumer is choosing between a Japanese wool shirt and an Italian cotton shirt.If a Chinese cotton shirt enters the market,a logit or CES framework would predict that the market shares for both imports would fall by the same percent.However,we might expect the Italian cotton shirt’s market share to adjust more than the Japanese shirt because the Chinese shirt is also cotton.The nested logit allows for more appropriate substitution patterns by placing varieties into appropriate nests.In order to delineate the nests,I rely on the structure of the U.S.trade data.Feenstra et al.(2002) have compiled U.S.import data which containﬁve-digit SITC industries that have been mapped to ten-digit HS products denoted by h.The products serve as the nests.An import from country c within a product is called a variety.I model consumer preferences for a single industry and therefore suppress industry subscripts.Fol-lowing Berry(1994),consumer n has preferences for country c’s import into HS product h(e.g.,variety ch) at time t.The consumer purchases the one variety that provides her with the highest indirect utility,given byV ncht=λ1,ch+λ2,t+λ3,cht−αp cht+Hh=1µnht d ch+(1−σ) ncht.(12)Quality is deﬁned asλ1,ch+λ2,t+λ3,cht since it reﬂects the valuation for variety ch that is common across consumers(notice that these terms are not subscripted by n).This quality term is decomposed into three components.Theﬁrst term,λ1,ch,is the time-invariant valuation that the consumer attaches to variety ch. The second term,λ2,t,captures for secular time trends common across all varieties.Theλ3,cht term is a variety-time deviation from theﬁxed eﬀect that is observed by the consumer but not the econometrician.This last term is potentially correlated with the variety’s c.i.f.unit value,p cht.The horizontal component of the model is captured by the random component, Hh=1µnht d ch+(1−σ) ncht.The logit error ncht is assumed to be distributed Type-I extreme value and explains why a variety that is expensive and has low quality is ever purchased.The former term interacts the common valuation that consumer n places on all varieties within product h,µnht,with a dummy variable d ch that takes a value of1if country c’s export lies in product h.This term generates the nest structure because if allows consumer n’s preferences to be more correlated for varieties within product h than for varieties across products.16 An“outside”variety completes the demand system.The purpose of the outside variety is to allow16As discussed in Berry(1994),Cardell(1997)has shown that the distribution of Hh=1µnht d ch is the unique distributionsuch that if is distributed extreme value,then the sum is also distributed type-I extreme value.The degree of within nest correlation is controlled byσ∈(0,1].Asσapproaches one,the correlation in consumer tastes for varieties within a nest approaches one and asσtends to zero,the nested logit converges to the standard logit model.。

2012年与2011年考试大纲对比析

Valuation and Risk Models
Study session Level II Market Risk Measurement and Management Credit Risk Measurement and Management Operational and Integrated Risk Management Risk Management and Investment Management Current Issues in Financial Markets
• Pricing and factors that affect it
• Uses in hedging and hedging strategies
• Uses in hedging and hedging strategies
• Delivery options
• Delivery options
1、书的版本做了更新，相应章节的号码也有所变化，但内容未变。
2、去掉了“ Dale F. Gray, Robert C. Merton and Zvi Bodie, “Contingent Claims Approach to Measuring and Managing Sovereign Credit Risk,” Journal of Investment Management, Vol. 5, No. 4 (2007).” ，这部分主要对应考点中的“Contingent Claims ”。
• Chapter 11.Binomial Trees
• Chapter 12.Binomial Trees
• Chapter 13.The Black-Scholes-Merton • Chapter 14.The Black-Scholes-Merton

七年级英语上册第一次月考调研检测试题2

A B C D E 七年级英语试题Ⅰ.听力部分。

（30分） A) 听字母，选出与其内容相符的图片。

（5分） 1. 2. 3. 4. 5. B) 选出你所听到的字母。

（5分）（）6. A. Mm B. Ll C. Ff （）7. A. Ii B. Ee C. Aa （）8. A. Ww B. Gg C. Jj （）9. A. Kk B. Hh C. Bb （）10.A. Vv B. Pp C. Zz C) 听句子，选出你听到的单词。

（10分）（）11.A. meet B. are C. is ( ) 12.A. Mr. Li B. Miss Li C. Miss Wang ( )13.A. are B. too C. Canada ( ) 14.A.from B. who C. they ( )15.A. then B. they C. he D) 听句子，选出你听到的句子的最佳应答语。

（10分） ( ) 16. A. Fine , thanks. B. How do you do? C. How are you? ( ) 17. A. Good morning! B. Good afternoon! C. Thank you. ( ) 18. A. That ’s OK B. Hello! C. I ’m fine, thanks. ( ) 19.A. I ’m fine B. Nice to see you, too. C. How do you do? ( ) 20.A. Bye B. Hello! C. Thanks. Ⅱ按字母表的顺序写出所给字母的左邻右舍。

（大小写要与所给字母保持一致）（10分） 1. 2. 3. 4. 5. Ⅲ.在四线三格中规范地写出下列标志中你所见到字母的大小写形式。

D r g Q Y1 2 3 4 5 1. 2. 3. 4. 5. Ⅳ.单项选择题。