“Chow test”的意思、由来-开放百科全书

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Chow test

释义

Illustrations
Mathematical details
References
External links

The Chow test, proposed by econometrician Gregory Chow in 1960, is a test of whether the true coefficients in two linear regressions on different data sets are equal. In econometrics, it is most commonly used in time series analysis to test for the presence of a structural break at a period which can be assumed to be known a priori (for instance, a major historical event such as a war). In program evaluation, the Chow test is often used to determine whether the independent variables have different impacts on different subgroups of the population.

Illustrations

Applications of the Chow test
Structural break (slopes differ)	Program evaluation (intercepts differ)

At there is a structural break; separate regressions on the subintervals and delivers a better model than the combined regression (dashed) over the whole interval.	Comparison of two different programs (red, green) in a common data set: separate regressions for both programs deliver a better model than a combined regression (black).

Mathematical details

Suppose that we model our data as

If we split our data into two groups, then we have

and

The null hypothesis of the Chow test asserts that , , and , and there is the assumption that the model errors are independent and identically distributed from a normal distribution with unknown variance.

Let be the sum of squared residuals from the combined data, be the sum of squared residuals from the first group, and be the sum of squared residuals from the second group. and are the number of observations in each group and is the total number of parameters (in this case, 3). Then the Chow test statistic is

The test statistic follows the F distribution with and degrees of freedom.

Remarks

The global sum of squares (SSE) is often called the Restricted Sum of Squares (RSSM) as we basically test a constrained model where we have assumptions (with the number of regressors).
Some software like SAS will use a predictive Chow test when the size of a subsample is less than the number of regressors.

References

{{cite journal | doi=10.2307/1910133 | first1=Gregory C.|last1=Chow | title=Tests of Equality Between Sets of Coefficients in Two Linear Regressions | jstor=1910133 | journal=Econometrica | year=1960 | volume=28 | pages=591–605 | issue=3}}
{{cite book |last=Doran |first=Howard E. |year=1989 |title=Applied Regression Analysis in Econometrics |publisher=CRC Press |isbn=0-8247-8049-3 |page=146 }}
{{cite book |last=Dougherty |first=Christopher |year=2007 |title=Introduction to Econometrics |publisher=Oxford University Press |isbn=0-19-928096-7 |page=194 }}
{{cite book |last=Kmenta |first=Jan |authorlink=Jan Kmenta |title=Elements of Econometrics |location=New York |publisher=Macmillan |edition=Second |year=1986 |isbn=0-472-10886-7 |pages=412–423 }}
{{cite book |last=Wooldridge |first=Jeffrey M. |authorlink=Jeffrey Wooldridge |title=Introduction to Econometrics: A Modern Approach |location=Mason |publisher=South-Western |edition=Fourth |year=2009 |isbn=978-0-324-66054-8 |pages=243–246 }}

External links

[https://www.stata.com/support/faqs/stat/chow.html Computing the Chow statistic], [https://www.stata.com/support/faqs/stat/chow2.html Chow and Wald tests], [https://www.stata.com/support/faqs/stat/chow3.html Chow tests]: Series of FAQ explanations from the Stata Corporation at https://www.stata.com/support/faqs/
: Series of FAQ explanations from the SAS Corporation

2 : Time series statistical tests|Regression diagnostics

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