10.1 下表是某国的宏观经济数据（GDP——国内生产总值，单位：10 亿美元；PDI—— 个人可支配收入，单位：10 亿美元；PCE——个人消费支出，单位：10 亿美元；利润——公 司税后利润，单位：10 亿美元；红利——公司净红利支出，单位：10 亿美元）

9.1 设真实模型为无截距模型： Y X u i i = + 2 2 回归分析中却要求截距项不能为零，于是，有人采用的实证分析回归模型为：

7.1 表中给出了 1970~1987 年期间美国的个人消息支出(PCE)和个人可支配收入(PDI) 数据，所有数字的单位都是 10 亿美元(1982 年的美元价)

3.1 为研究中国各地区入境旅游状况，建立了各省市旅游外汇收入（Y，百万美元）、旅 行社职工人数（X1，人）、国际旅游人数（X2，万人次）的模型，用某年 31 个省市的截面 数据估计结果如下：

4.1假设在模型Y1=B1+B2X21+B3X32+u1中X2与X3之间的相关系数为零,于 是有人建议你进行如下回归:

One of the CLRM assumptions is: there is no perfect multicollinearity-no exact linear relationships among explanatory variables, Xs, in a multiple regression. In practice, one rarely encounters perfect multicollinearity, but cases of near or very high multicollinearity where explanatory variables are approximately linearly related frequently arise in many applications

The models we discussed are models that are linear in parameters; variables Y and Xs do not necessarily have to be linear The price elasticity of demand~the log-linear models The rate of growth~semilog model Functional forms of regression models which are linear in parameters, but not necessarily linear in variables:

Assumptions of the classical Linear Model (Clm) e So far, we know that given the Gauss Markov assumptions, OLS IS BLUE e In order to do classical hypothesis testing we need to add another assumption(beyond the Gauss-Markov assumptions) Assume that u is independent of x,x2…,xk and u is normally distributed with zero mean and variance 0: u- Normal(0, 02) Economics 20- Prof anderson

▪ 10.1 时间序列分解 ▪ 10.2 长期趋势分析 ▪ 10.3 季节变动分析 ▪ 10.4 循环波动分析 ▪ 10.5 时间序列的自相关分析 ▪ 10.6 时间序列的动态分析指标 ▪ 10.7 景气循环分析

Ch. 24 Johansen's mle for Cointegration We have so far considered only single-equation estimation and testing for cointe- gration. While the estimation of single equation is convenient and often consis- tent, for some purpose only estimation of a system provides sufficient information This is true, for example, when we consider the estimation of multiple cointe- grating vectors, and inference about the number of such vectors. This chapter examines methods of finding the cointegrating rank and derive the asymptotic