[求助]怎样检查自相关和多重共线性

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请问怎么检查模型的自相关和多重共线性问题呢，使用什么命令呢

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关键词：多重共线性 多重共线 共线性 自相关 多重共线性问题 模型

1). 自相关

Autocorrelation

Iterated GLS with autocorrelation does not produce the maximum likehood estimates, so we cannot use the likelihood-ratio test procedure, as with heteroskedasticity. However, Wooldridge (2002, 282–283) derives a simple test for autocorrelation in panel-data models. Drukker (2003) provides simulation results showing that the test has good size and power properties in reasonably sized samples.

There is a user-written program, called xtserial, written by David Drukker to perform this test in Stata. To install this user-written program, type

 . findit xtserial . net sj 3-2 st0039 (or click on st0039) . net install st0039 (or click on click here to install) 

To use xtserial, you simply specify the dependent and independent variables:

 . xtserial depvar indepvars 

A significant test statistic indicates the presence of serial correlation.

2). 多重共线性

Multicolinearity

Stata provides a built-in measure of multicolinearity, the variance inflation factor (VIF). To use the VIF, first estimate the regression equation, then type the command vif. below is an example:

reg y x5-x7
vif

As a rule of thumb, a variable whose VIF values are greater than 10 may merit further investigation. Tolerance, defined as 1/VIF, is used by many researchers to check on the degree of collinearity. A tolerance value lower than 0.1 is comparable to a VIF of 10. It means that the variable could be considered as a linear combination of other independent variables.