Potential Output: Concepts and Measurement - Department of Labour

Darren Gibbs 101
FIGURE 9: Estimated potential output and output gap series—multivariate
filter method
20
15
10000
Output gap (%)
10
5
0
-5
-10
-15
-20
8000
6000
4000
2000
0
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
Output ($m 82/83)
1992
1993
June years
mfa200: output gap (left axis)
mfa100,000: output gap (left axis)
mfa200: potential output (right axis)
mfa100,000: potential output (right axis)
mfa1600: output gap (left axis)
gdp (right axis)
mfa1600: potential output (right axis)
equation was that derived using the Hodrick-Prescott method. The information
contained in the Okun regression was than embedded within the Hodrick-
Prescott minimisation formula (along with the Phillips curve regression) to yield
a bivariate estimate of potential output which is based on both the observed
behaviour of output and the observed behaviour of inflation and unemployment.
As with the bivariate filter, an iteractive technique was used to generate
successive replacement output gaps in the Phillips curve and Okun equation,
until the estimated coefficients converged.
As with the potential output estimates derived using the previous filtering
techniques three variations of the smoothness parameter were used, so that three
different multivariate filters were derived. Figure 9 illustrates the three estimated
potential output series (mfa1600, mfa200, mfa100,000) obtained by following the
above approach, and the estimated output gaps.
The general pattern of the multivariate output gaps is similar to the bivariate
filter estimates. However, the size of the negative output gap is more pronounced
in the late 1980s and early 1990s than that estimate derived from the
bivariate filter. Note also that the mfa200 measure suggests that potential output
fell in absolute terms in 1991. This is consistent with accelerated capital
scrapping and a rising natural unemployment rate.