The analysis of cointegration in large systems requires a reduction of their dimensionality. To achieve this, an analysis proposes to obtain the integrated of order one - I(1) - factors in every subsystem and then analyze cointegration among them. A new way ofThe analysis of cointegration in large systems requires a reduction of their dimensionality. To achieve this, an analysis proposes to obtain the integrated of order one - I(1) - factors in every subsystem and then analyze cointegration among them. A new way of estimating common long-memory components of a cointegrated system is proposed. The identification of these I(1) common factors is achieved by imposing that they be linear combinations of the original variables and that the error-correction terms do not cause the common factors at low frequencies. Estimation is done from a fully specified error-correction model, which makes it possible to test hypotheses on the common factors using standard chi-squared tests. Several empirical examples are presented to illustrate the procedure.[+][-]