Output Gap Estimation Uncertainty: Extracting the TFP Cycle Using an Aggregated PMI Series

Daragh Clancy


The concepts of potential growth and the output gap are important components in assessing 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 used to judge EU Member States adherence to budgetary rules. Therefore, it is vital that the methods applied for their estimation are as accurate as possible. A bivariate Kalman Filter (KF) model using capacity utilisation (CU) as the second series has been proven to produce more reliable estimates of the Total Factor Productivity (TFP) cycle than the Hodrick Prescott (HP) filter methodology formerly used for this task. However, CU data is no longer collected in Ireland. Given the large turning point in the TFP series as a result of the financial crisis, this may no longer be the first-best approach for future TFP cycle estimation. This paper compares the existing method to an approach which uses an aggregated Purchasing Managers’ Index (PMI) series as the second series in the bivariate KF model. This approach has the advantage that PMI data is collected on an on-going basis. The results show that PMI shares a common cycle with TFP, and that this new approach leads to a reduction in the total estimation error variance and revisions required to TFP cycle estimates.

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