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丁洁Amy · 2021年05月19日

关于b0,b1到底等于啥的疑惑

* 问题详情,请 查看题干

NO.PZ201709270100000502

问题如下:

2. Based on the regression output in Exhibit 1, the first-differenced series used to run Regression 2 is consistent with:

选项:

A.

a random walk.

B.

covariance stationarity.

C.

a random walk with drift.

解释:

B is correct. The critical t-statistic at a 5% confidence level is 1.98. As a result, neither the intercept nor the coefficient on the first lag of the first-differenced exchange rate in Regression 2 differs significantly from zero. Also, the residual autocorrelations do not differ significantly from zero. As a result, Regression 2 can be reduced to yt = εt with a mean-reverting level of b0/(1 b1) = 0/1 = 0.

Therefore, the variance of yt in each period is Var(εt) = σ2. The fact that the residuals are not autocorrelated is consistent with the covariance of the times series, with itself being constant and finite at different lags. Because the variance and the mean of yt are constant and finite in each period, we can also conclude that yt is covariance stationary.

老师好,我看到讲解那里是根据t检验量得出b0和b1=0,但是我做着做着就有点懵了,下表里我红色框圈出来的不就是b0和b1这两个系数吗?我当时解题的时候是用下图圈出来的这两个数值排除了A和C。请问老师我什么时候用t检验来确定b0,b1值,什么时候根据ANOVA表来确定b0,b1值?谢谢老师


1 个答案
已采纳答案

星星_品职助教 · 2021年05月20日

同学你好,

表格中的b0和b1是根据数据估计出来的值。只要有数据,就可以估计出b0和b1。

但这种估计未必就是准确的,哪怕毫无规律的数据,也是可以估计出来系数。所以在得到b0和b1后还要对估计值做假设检验。

以本题为例,你红框圈出来的值就是根据原始数据得到的值。如果利用这个方程去预测Y是多少,就要用这两个数据。

但这两个数据对应的t统计量很小,也就是如果做假设检验,会发现找到的这个规律实际是不存在的。即因变量和自变量实际上没有这种关系,即本题中的变成0.

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