第4讲--需求分析与需求估计.ppt

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1、LOGO第四讲第四讲 需求分析与需求估计需求分析与需求估计主要内容主要内容一 需求关系二 需求的价格弹性三 需求的收入弹性四 需求的交叉弹性五 弹性在管理决策中的应用六 需求估计的市场研究方法七需求函数的统计估计经济分析与决策经济分析与决策n 需求分析n 生产和成本分析n 产品、定价和产出量决策n 资本支出分析经济、政治与社会环境经济、政治与社会环境n经营状况（趋势、周期和季节性影响）n要素市场状况（资本、劳动和原材料）n竞争者反应与策略性反应n组织架构与规则限制现金流量现金流量风险风险厂商价值厂商价值（股东的财富）（股东的财富）Health Care&CigarettesvRaising c

2、igarette taxes reduces smokingIn Canada,$4 for a pack of cigarettes reduced smoking 38%in a decadevBut cigarette taxes also helps fund health care initiativesThe issue then,should we find a tax rate that maximizes tax revenues?Or a tax rate that reduces smoking?一、需求关系一、需求关系n 需求表、需求曲线与需求函数需求表、需求曲线与需求

3、函数。n 消费者的基本问题消费者的基本问题花得起的条件下最大化效用花得起的条件下最大化效用需求函数需求函数。n 价格变化引起需求量的变化价格变化引起需求量的变化。收入效应；替代效应。n 耐用品与非耐用品n 对生产者的派生需求。vReasons that price and quantity are negatively related include:income effect-as the price of a good declines,the consumer can purchase more of all goods since his or her real income incr

4、eased.substitution effect-as the price declines,the good becomes relatively cheaper.A rational consumer maximizes satisfaction by reorganizing consumption until the marginal utility in each good per dollar is equal:二、需求的价格弹性二、需求的价格弹性n需求的决定因素厂商是否可控？这些因素变化对需求量的影响有多大？定量！n 案例案例3-1两种不同机制：两种不同机制：Ford&Pizz

5、ahut。n 价格弹性价格弹性 Price ElasticityED=%change in Q/%change in PShortcut notation:ED=%Q/%PA percentage change from 100 to 150 is 50%A percentage change from 150 to 100 is-33%For arc elasticities,we use the average as the base,as in 100 to 150 is+50/125=40%,and 150 to 100 is-40%Arc Price Elasticity-avera

6、ges over the two pointsDarc priceelasticityED=DQ/(Q1+Q2)/2DP/(P1+P2)/2Average priceAverage quantity二、需求的价格弹性二、需求的价格弹性n 计算实例1P63李维斯牛仔裤的需求弹性。n 计算实例2P63NBA公司索价。n 案例案例3-2麦肯电讯麦肯电讯。n 价格与收益的关系价格与收益的关系 表表3-4。图。图3-2。当需求弹性绝对值当需求弹性绝对值1时，价格上升（下降）将造成消时，价格上升（下降）将造成消费者的总支出的的减少（增加）。费者的总支出的的减少（增加）。当需求弹性绝对值当需求弹性绝对值=1

7、时，价格上升（下降）将造成消时，价格上升（下降）将造成消费者的总支出的的不变。费者的总支出的的不变。If ED=-1,unit elasticIf ED -1,inelastic,e.g.,-0.43If ED 1）。n 奢侈品一般具有高收入弹性，必需品具有低收入弹性If EY 0,then it is a normal or income superior goodsome goods are Luxuries:EY 1 with a high income elasticitysome goods are Necessities:EY 0；互补品互补品EX Critical-t,then

8、REJECT Ho.We say that its significant!vThe estimated t=(b-0)/bvThe critical t is:Large Samples,critical t2N 30Small Samples,critical t is on Students t Distribution,page B-3 at end of book,usually column 0.05.D.F.=#observations,minus number of independent variables,minus one.N 2.306,so we reject the

9、 null hypothesis.vWe informally say,that promotional expenses(X)is“significant.”Correlation CoefficientvWe would expect more promotional expenditures to be associated with more sales at Sherwin-Williams.vA measure of that association is the correlation coefficient,r.vIf r=0,there is no correlation.I

10、f r=1,the correlation is perfect and positive.The other extreme is r=-1,which is negative.r=-1r=+1r=0Y Y Y X X XCoefficient of Determination:R2vR-square is the percentage of the variation in dependent variable that is explained vR2=Yt-Yt 2 /Yt-Yt 2=SSR/SSTvAs more variables are included,R-square ris

11、esvAdjusted R-square,however,can decline_XY_YYt Yt predicted Association and CausationvRegressions indicate association,but beware of jumping to the conclusion of causationvSuppose you collect data on the number of swimmers at a beach and the temperature and find:vTemperature=61+.04 Swimmers,and R2=

12、.88.Surely the temperature and the number of swimmers is positively related,but we do not believe that more swimmers CAUSED the temperature to rise.Furthermore,there may be other factors that determine the relationship,for example the presence of rain or whether or not it is a weekend or weekday.vEd

13、ucation may lead to more income,and also more income may lead to more education.The direction of causation is often unclear.But the association is very strong.Multiple Linear RegressionvMost economic relationships involve several variables.We can include more independent variables into the regressio

14、n.vTo do this,we must have more observations(N)than the number of independent variables,and no exact linear relationships among the independent variables.vAt Sherwin-Williams,besides promotional expenses,different regions charge different selling prices(SellPrice)and have different levels of disposa

15、ble income(DispInc)vThe next slide gives the output of a multiple linear regression,multiple,because there are three independent variablesFigure 4.9Dep var:Sales(Y)N=10 R-squared=.790Adjusted R2=.684 Standard Error of Estimate=17.417VariableCoefficient Std error T PConstant310.245 95.075 3.263 .017P

16、romotion .008 0.204 0.038 .971SellPrice-12.202 4.582 -2.663 .037DispInc 2.677 3.160 0.847 .429Interpreting Multiple Regression OutputvWrite the result as an equation:Sales=310.245+.008 Promotion-12.202 SellPrice+2.677 DispIncvDoes the result make economic sense?As promotion expense rises,so does sal

17、es.That makes sense.As the selling price rises,so does sales.Yes,thats reasonable.As disposable income rises in a region,so does sales.Yup.Thats reasonable.vIs the coefficient on the selling price statistically significant?The estimated t value is given in Figure 4.9 to be-2.663The critical t value,

18、with 6(which is 10 3 1)degrees of freedom in table B2 is 2.447Therefore|-2.663|2.447,so reject the null hypothesis,and assert that the selling price is significant!n案例案例3-5飞跃北大西洋旅行的需求估计飞跃北大西洋旅行的需求估计J.M.Cigliano估计了估计了19651978美国与欧洲之间的空中美国与欧洲之间的空中旅行需求：旅行需求：n案例案例3-6公共交通与城市拥挤公共交通与城市拥挤北京北京广州等大城市城市拥护现象突出。广州等大城市城市拥护现象突出。公共交通是解决城市拥护的关键。公共交通是解决城市拥护的关键。公交降价是否有利于城市拥护现象的解决？公交降价是否有利于城市拥护现象的解决？