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Testing for Common Features

Sharon Kozicki

Bank of Canada

Robert F. Engle

New York University - Leonard N. Stern School of Business - Department of Economics; New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

October 1990

NBER Working Paper No. t0091

This paper introduces a class of statistical tests for the hypothesis that some feature of a data set is common to several variables. A feature is detected in a single series by a hypothesis test where the null is that it is absent, and the alternative is that it is present. Examples are serial correlation, trends, seasonality, heteroskedasticity, ARCH, excess kurtosis and many others. A feature is common to a multivariate data set if a linear combination of the series no longer has the feature. A test for common features can be based on the minimized value of the feature test over all linear combinations of the data. A bound on the distribution for such a test is developed in the paper. For many important cases, an exact asymptotic critical value can be obtained which is simply a test of overidentifying restrictions in an instrumental variable regression.

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Date posted: June 27, 2007  

Suggested Citation

Kozicki, Sharon and Engle, Robert F., Testing for Common Features (October 1990). NBER Working Paper No. t0091. Available at SSRN: http://ssrn.com/abstract=994520

Contact Information

Sharon Kozicki
Bank of Canada ( email )
234 Wellington Street
Ottawa, Ontario K1A 0G9
Robert F. Engle (Contact Author)
New York University - Leonard N. Stern School of Business - Department of Economics ( email )
269 Mercer Street
New York, NY 10003
United States
New York University (NYU) - Department of Finance
Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
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