Approximate maximum likelihood estimation with data sets that exceed computer limits

A large number of observations is a delight for theoretical econometricians and statisticians. In practice, numerous observations can be a headache when the number exceeds computer limits. This paper provides a practical method of using all the observations regardless of computer core constraints. And, turning necessity to benefit, shows how the method can be used to determine the reliability of the norm approximation to the distribution of the estimator.