After many equatings have been conducted in a testing program, equating errors can accumulate to a degree that is not negligible compared to the standard error of measurement. In this paper, the author investigates the asymptotic accumulative standard error of equating (ASEE) for linear equating methods, including chained linear, Tucker, and Levine, under the nonequivalent groups with anchor test (NEAT) design. A recursive formula for the ASEE is provided for a series of equatings that makes use of only historical summary statistics. This formula can serve as a new tool to measure the magnitude of equating errors that have accumulated over a series of equatings, and to help monitor and design testing programs.