摘要：The concepts of potential growth and the output gap are important components inassessing the business cycle and productive capacity of an economy. However, being unobservable,these measures must be estimated. The Fiscal Compact will result in these concepts being usedto judge EU Member States adherence to budgetary rules. Therefore, it is vital that the methodsapplied for their estimation are as accurate as possible. A bivariate Kalman Filter (KF) modelusing capacity utilisation (CU) as the second series has been proven to produce more reliableestimates of the Total Factor Productivity (TFP) cycle than the Hodrick Prescott (HP) filtermethodology formerly used for this task. However, CU data is no longer collected in Ireland. Giventhe large turning point in the TFP series as a result of the financial crisis, this may no longer bethe first-best approach for future TFP cycle estimation. This paper compares the existing methodto an approach which uses an aggregated Purchasing Managers' Index (PMI) series as the secondseries in the bivariate KF model. This approach has the advantage that PMI data is collected onan on-going basis. The results show that PMI shares a common cycle with TFP, and that this newapproach leads to a reduction in the total estimation error variance and revisions required to TFPcycle estimates
