In principle yes, accuracy is the fraction of properly predicted cases thus 1-the fraction of misclassified cases, that is error (rate). Both terms may be sometimes used in a more vague way, however, and cover different things like class-balanced error/accuracy or even F-score or AUROC -- it is always best to look for/include a proper clarification in the paper or report.

Also note that test error rate implies error on a test set, so it is likely 1-test set accuracy, and there may be other accuracies flying around.

In principle, accuracy is the fraction of properly predicted cases.

This is the same as 1 - the fraction of misclassified cases or 1 - the *error* (rate). 

Both terms may be sometimes used in a more vague way, however, and cover different things like class-balanced error/accuracy or even F-score or AUROC -- it is always best to look for/include a proper clarification in the paper or report.

Also, note that test error rate implies error on a test set, so it is likely 1-test set accuracy, and there may be other accuracies flying around.