• Composite indicators are widely used in sustainable development and elsewhere. • The effect of weights used in aggregating indicators is complex. • Three tools are presented which help developers and users to investigate effects of weights. • Case studies related to sustainable development demonstrate the benefits.

This paper addresses the problem of inference on the moving average impact matrix and on its row and column spaces in cointegrated 1(1) VAR processes. The choice of bases (i.e., the identification) of these spaces, which is of interest in the definition of the common trend structure of the system, is discussed. Maximum likelihood estimators and their asymptotic distributions are derived, making use of a relation between properly normalized bases of orthogonal spaces, a result that may be of separate interest. Finally, Wald-type tests are given, and their use in connection with existing likelihood ratio tests is discussed.