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Testing for Autocorrelation with Missing Observations
N. E. Savin
Kenneth J. White
Abstract
This paper considers procedures for testing for autocorrelation when there are missing observations on both the dependent and explanatory variables. These procedures include Durbin-Watson type tests given the vector of residuals, tests based on a set of uncorrelated residuals, and large sample likelihood ratio and Wald tests.
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