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2019/12/3,1,Chapter 5 How to use the multiple linear regression model,2,2019/12/3,General linear models Suppose that we have a model: It is inherently linear for the parameters if it can be transformed into Examples: 1. Exponential model:,3,2019/12/3,2. Reciprocal model: 3. Double-log(constant elasticity) model:,4,2019/12/3,But the following model is not inherently linear: For others, see page72-73,5,2019/12/3,What is the dummy variable 属性因素: Man and Woman, City and country, developed country and developing country 经济环境的变化: Peace and war 淡季和旺季 风调雨顺和洪灾旱灾 All these have a good or bad influence on economy.,6,2019/12/3,A dummy variable is a binary variable, that is, Example:,7,2019/12/3,加法方式: 消费函数 乘法方式: 消费函数 同时考虑两方式:,8,2019/12/3,临界值虚拟变量(Note: p76, 总消费函数例子是引入临界值虚拟变量） 进口消费品额 Y, 国民收入 X 进口消费品回归模型,9,2019/12/3,case studies(P77-78) Use of t and F-tests to test hypotheses Involving multiple parameters Joint tests on several regression parameters: Suppose that we have a model And the null hypothesis is,10,2019/12/3,The test statistic is 2. Tests involving linear functions of the regression parameters 3. Tests involving the equality of coefficients of different regression equations: Chow- test (a special F-test),11,2019/12/3,Regression model with random explanatory variables: 1)若X与误差项独立, 则前面所得结论仍成立. 2)若X与误差项不相关, 则OLSE是一致估计也是渐进无偏的. 3)若X与误差项相关,则OLSE不是一致估计也不是渐进无偏的. OLS失效. Homework: P87, ex5.1 and 5.2,
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