We consider a finite-state, finite-action, infinite-horizon, discounted reward Markov decision process and study the bias and variance in the value function estimates that result from empirical estimates of the model parameters. We provide closed-form approximations for the bias and variance,...

This paper presents a procedure for determining the number of simulation observations required to achieve a preassigned confidence interval for means estimated by simulation. This procedure, which is simple to implement and efficient to use, is compared with two other methods for determining the...

Many simulation experiments are concerned with the estimation of a ratio of two unknown means, the estimation of a conditional probability being an example. We propose confidence intervals for the case in which the ratio is estimated by using independent, identically distributed random pairs...

Care must be taken when interpreting the coefficients of dummy variables in semi-logarithmic regression models. Existing results in the literature provide the best unbiased estimator of the percentage change in the dependent variable, implied by the coefficient of a dummy variable, and of the...