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Extracting the Cyclical Component from

Australian Multi-Factor Productivity

Mark Zhang

Lewis Conn

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Background

The Australian Bureau of Statistics (ABS) produces two measures of Multi-Factor Productivity (MFP) growth Growth between adjacent years

Average annual growth between productivity peaks

The later is a more consistent measure of productivity growth

Reserve Bank Statement on Monetary Policy (9th Nov 2006)

"... Australia’s economic expansion has now reached a mature stage in which previously unused productive resources have been substantially re-employed ... this combination suggests that there may have been some underlying slowdown in productivity, either of a cyclical or structural nature, though its extent is difficult to explain. "

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In theory, at MFP peaks there is full capacity utilisation

By measuring MFP growth from peak to peak we assume we have consistent capacity utilisation

MFP Peaks are currently derived using an 11 term Henderson time series filter (Aspen, 1989)

Separates the business cycle from long term trend

Other economic series (Labour market, business expectations) are also considered when declaring peaks

Deriving Average Annual MFP Growth

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Objectives of This Study

Improve analysis and understanding of trends in multi-factor productivity

Review, update and explain the choice of method for estimating peaks in the productivity series.

Analysis of impact of methods on the productivity series

Analyse how industries' contribute to the aggregate productivity cycle (Phase 2)

Investigate how capacity utilisation may be taken into account when comparing productivity peaks (Phase3)

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Filters Considered

11-Term Henderson (1916) - Linear low pass filter

Hodrick Prescott (1980) - Linear low pass filter

Baxter-King (1997) - Band Pass Filter

Beveridge-Nelson (1981) – Model based approach which produces a stochastic trend

Unobserved Components Model – Uses a structural model framework to models trend, cycle, and irregular explicitly

Current ABS Method

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Frequency versus Model Based

Frequency based filters extract a signal within a predefined range. They implicitly apply a particular model to the data.

Hodrick and Prescott (1997) recommended a smoothing parameter of 1600 based on an empirical investigation of US quarterly GDP data.

Ravn (2002) recommended for annual data reducing the parameter by a factor of four (approx 6.25)

Model based filters fit the model directly to the data. They extract the signal from the estimated model.

Using the UCM to estimate the smoothing parameter 28.66

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Low Pass Annual Filters

t t t tMFP Trend Cycle ^

tCycle

^

( )

1

*

t tt

t t

t

t

Cycle MFP Trend

MFP LowPass MFP

LowPass MFP

HighPass MFP

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Frequency Response Function

11-Term HendersonHodrick-Prescott (6.25)Hodrick-Prescott (28.66)

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Frequency Response Function

0.5

6.949.9514.5

11-Term HendersonHodrick-Prescott (6.25)Hodrick-Prescott (28.66)

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Market MFP Cycle Conparison

ABS Declared Productivity Peaks

1994

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Results

All methods (with the exception of the Beveridge-Nelson) gave reasonably similar results

UCM verifies that the cycle component derived from HP filter is not spurious.

UCM derived parameter is larger than theoretical value

Baxtor King requires more data at the end point

Results support the Hodrick-Prescott method.

More commonly used in practice internationally

Less likely to produce spurious cycles

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Revision of Peaks

Looked at the amount of revision required using different methods

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Revision of Peaks

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Revision of Peaks

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Revision of Troughs

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Revision of Troughs

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Key Findings From Study

There is strong evidence of cyclic behaviour in the MFP series

The Henderson filter suppresses more power in low cycles (> 8 years) and amplifies cycles from 4 to 6 years

May produce spurious cycles

Results support updating methodology to Hodrick Prescott filter

Smoothing parameter, theoretical (6.25) or derived (28.66)?

Impact of change will affect the 1994 peak, but should not affect any other peaks

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Comparing Peaks in Market MFP and Industry MFP Manufacturing and Construction have similar peaks to Market MFP

Some industries (Electricity, Gas and Water, Wholesale) do not show any cyclic behavior

1999 Market MFP Peak:

PEAK TROUGH

Construction Mining

Accommodation, Cafes and Restaurants

Electricity, Gas and Water

Communication Transport and Storage

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Further Work

Finalise smoothing parameter

Further analysis of Industry MFP

Analysis of growth between adjacent years relative to average growth

Research capacity utilisation

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Questions