Conditional and unconditional procedures are used for constructing confidence intervals for Pareto distribution parameters based on generalized order statistics via Monte Carlo simulations. The conditional confidence intervals for the parameters are derived for different sample sizes to allow an assessment of the amount of information lost when one bases confidence intervals on the unconditional distribution. Finally, a numerical example is given to illustrate the inferential methods developed in this paper.