Abstract
QCA has recently been subject to massive criticism and although the substance of that criticism is not completely new, it differs from earlier critiques by invoking simulations for the evaluation of QCA. In addition to debates about the meaning of the simulation results, there is a more fundamental discussion about whether simulations promise any relevant insights in principle. Some voices in the QCA community reject simulations per se because they necessarily lack case knowledge. As a consequence, the debate is at an impasse on a metalevel because critics of QCA rely on simulations, the results of which some QCA proponents refuse to consider as insightful. This article addresses this impasse and presents six reasons why simulations must be considered appropriate for evaluating QCA. I show that if taken to its conclusion, the central argument against simulations undermines the need for running a truth table analysis in the first place. The way forward in this debate should not be about whether simulations are useful, but how to configure meaningful simulations evaluating QCA.