The limit distribution of the normalized maxima of stationary sequences exists under specific conditions, even in the presence of some dependence structures. Dealing with sequences of maxima, the degree of dependence between observations can be studied in the limit distribution, when it exists, through a parameter of the Extreme Value distribution, named the extremal index, EI. The EI is theoretically known for some particular models and might be interpreted in different contexts, namely, as the limit of the reciprocal of clusters mean size of exceedances, or related to the multiplicity of a compound Poisson point process. Generally, EI estimation methods are focused on the limit mean size of clusters. In this study we investigate the direct estimation of the parameter itself as a proportion. The procedure takes into account the distribution of the inter-exceedances times and considers the proportion of strictly positive inter-exceedances times as an EI estimator. The results of a simulation study show that the method is more robust to different cluster dependence structures than the usual alternatives.