2.3  Output gap

The output gap is the difference between actual output and its potential level, expressed as a percentage of potential output. It is a measure of the cyclical state of the economy.

Potential output, and hence the output gap, is unobservable and therefore a model or statistical filter is used to estimate it. There exists a range of possible estimation techniques which means a range of estimates are reasonable.

Estimates of New Zealand's output gap are made by a range of institutions including the Treasury, the Reserve Bank of New Zealand, the OECD and the IMF. Estimates do differ because of differences in estimation technique (including the frequency of data used).

The Treasury's official measure of the output gap is derived from a potential output series which is estimated using a multivariate (MV) filter over history and a production function approach in the forecast period. The production function used is that of the New Zealand Treasury Model, a general equilibrium forecast model discussed in Ryan and Szeto (2009).

Figure 2 shows estimates of potential output using a variety of techniques: MV filter, Hodrick-Prescott (HP) filter, Kalman filter and a production function approach. The MV and HP filters are both statistical smoothing methods. Claus et al (2000) describe the MV filter as ‘semi-structural' in that it incorporates information from macroeconomic relationships into the HP filter. The Kalman filter is based on structural economic relationships (strictly, these are smoothed estimates of the Kalman filter using the unobservable-components time-series technique). The production function approach uses a Cobb-Douglas production function in which hours worked per employee, the employment rate, the participation rate, and total factor productivity are all filtered using the HP filter. The potential output series estimated using the MV and HP filters display a much more cyclical pattern compared with the Kalman filter, which in this case has the characteristic of being a much stiffer estimate, similar to a long-run trend. The estimates are all affected by the ‘end-point problem' to some degree, which means that estimates are sensitive to the last observations in the sample. Treasury’s official measure attempts to address this issue partially by using forecast information. The Kalman filter estimate is particularly sensitive to both its starting and end points which may be highly problematic, particularly given the last observations in the sample (the ‘end point’) are in the aftermath of a recession.

In selecting between the methods there is a trade off between attributing too much variation to cyclical factors (ie, demand-side shocks), and attributing too much variation to structural factors (ie, supply-side shocks). The statistical smoothing techniques appear to be show a high degree of cyclicality and may be overstating the amount of variation attributable to supply-side shocks. On the other hand, a stiff estimate risks attributing too much variation to the business cycle and thus underestimating structural change.

In considering the relative usefulness of the methods, it is useful to think about the purpose of the analysis. In attempting to bring a medium-term perspective to fiscal policy, to assess the sustainability of fiscal settings, it may be better to use a stiffer estimate. This is because short-lived supply-side shocks, while relevant when thinking about a short-term stabilisation objective, are ultimately temporary and therefore could lead to policymakers overestimating the degree of permanence in the fiscal position. Secondly, compared with monetary policy, fiscal policy tends to change at less frequent intervals, with longer lags in implementation, and it is harder to unwind policy loosening (ie, there is deficit bias induced by political economy). This may mean that, at least in boom times, it may be prudent to use the stiffer estimates so as to avoid the likelihood that potential growth has been overstated requiring difficult policy reversal later.

The resulting CAB estimates are presented in Figure 3 for both the MV and Kalman filters. The estimate made using the Kalman filter shows a less cyclical pattern since it ascribes much more of the growth over the 2000s as cyclical. Each estimate has technical merit. Ultimately, policymakers, and their advisors, need to make a judgement about the evolution of potential output based on the available evidence and the degree of conservativeness they wish to have in assessing potential growth.

In Figure 4, cyclically-adjusted nominal revenue and expenses are shown. Consistent with the operating balance path, it shows that the margin between cyclically-adjusted revenue and expenses is much smaller when using the Kalman output gap. The cyclical adjustment indicates that over 2005 to 2008, the non-structural, or temporary, component of tax revenues was about $1 billion per annum using the MV gap and $3 billion per annum using the Kalman gap.

Figure 2 – Real GDP, actual and potential estimates

Source:  Statistics NZ, The Treasury

Figure 3 – Cyclically-adjusted balance with MV and Kalman output gaps

Source:  The Treasury, author's calculations

Figure 4 – Total revenue and expenses, actual and cyclically adjusted

Source:  The Treasury, author's calculations.