Statistical matching is studied inside a coherent setting, by focusing on the problem of removing inconsistencies. When structural zeros among involved variables are present, incoherencies on the parameter estimations can arise. The aim is to compare different methods to remove such incoherences based on specific pseudo-distances. The comparison is given through an exemplifying example of 100 simulations from a known population with three categorical variables, that carries out to the light peculiarities of the statistical matching problem.