布鲁金斯学会主席,美前总统经济顾问委员会主 席奥肯(Arthur Okun)根据美国1947-1960年 的数据,得到如下回归方程,称之为奥肯定律 y

一、多重共线性的概念 二、多重共线性的后果 三、多重共线性的检验 四、克服多重共线性的方法 五、案例

一、序列相关性的概念——违反基本假设的定义及违反的原因 二、序列相关性的后果——违反基本假设会造成什么样的后果 三、序列相关性的检验——怎样诊断是否违反基本假设 四、具有序列相关性模型的估计——如何消除或减弱对基本假设的违反 五、案例

一、参数估计量的区间估计—不做介绍 二、预测值的区间估计

一、多元线性回归模型一般形式 二、多元线性回归模型的参数估计 三、OLS估计量的统计性质 四、样本容量问题 五、多元线性回归模型实例

Testing for a Fractional Unit Root in Time Series Regression Chingnun Lee, Tzu-Hsiang Liao2 and Fu-Shuen Shie Inst. of Economics, National Sun Yat-sen Univ Kaohsiung, Taiwan Dept. of Finance, National Central Univ, Chung-Li, Taiwan

Ch. 9 Heteroscedasticity Regression disturbances whose variance are not constant across observations are heteroscedastic. In the heteroscedastic model we assume that

Ch. 7 Violations of the ideal conditions 1 ST pecification 1.1 Selection of variables Consider a initial model. which we assume that Y=x1/1+E, It is not unusual to begin with some formulation and then contemplate adding more variable(regressors) to the model

Ch. 5 Hypothesis Testing The current framework of hypothesis testing is largely due to the work of Neyman and Pearson in the late 1920s, early 30s, complementing Fisher's work on estimation. As in estimation, we begin by postulating a statistical model but instead of seeking an estimator of 6 in e we consider the question whether

Ch. 3 Estimation 1 The Nature of statistical Inference It is argued that it is important to develop a mathematical model purporting to provide a generalized description of the data generating process. A prob bility model in the form of the parametric family of the density functions p=f(:0),0E e and its various ramifications formulated in last chapter