Abstract
David Johnson and Robert McClelland (1996)
"A General Dependence Test and Applications."
We describe a test, based on the correlation integral, for
the independence of a variable and a vector that can be used
to detect model misspecification in serially dependent data.
In Monte Carlo simulations this test performs nearly as well
or better than the BDS test in univariate time series and
complements the BDS test in distributed lag models. Finally,
we apply our test to detect misspecification in models of
U.S. unemployment data.
Last Modified Date: July 19, 2008
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