In this paper, upper and lower bounds for identification error are established for finite observation samples. It was shown that the behavior of both the upper and lower bounds are described completely by a resolvability function which describes the degree of resolvability between different parameters in the parameter set. This allows one to derive identifiability conditions by investigating the asymptotic behavior of this function. Moreover, the resolvability function gives a quantitative measure of identifiability.