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1 Extracting the Cyclical Component from Australian Multi-Factor Productivity Mark Zhang Lewis Conn.

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Presentation on theme: "1 Extracting the Cyclical Component from Australian Multi-Factor Productivity Mark Zhang Lewis Conn."— Presentation transcript:

1 1 Extracting the Cyclical Component from Australian Multi-Factor Productivity Mark Zhang Lewis Conn

2 2 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. "

3 3  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

4 4 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)

5 5 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

6 6 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

7 7 Low Pass Annual Filters

8 8 Frequency Response Function 11-Term Henderson Hodrick-Prescott (6.25) Hodrick-Prescott (28.66)

9 9 Frequency Response Function 0.5 6.949.9514.5 11-Term Henderson Hodrick-Prescott (6.25) Hodrick-Prescott (28.66)

10 10 Market MFP Cycle Conparison ABS Declared Productivity Peaks 1994

11 11 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

12 12 Revision of Peaks  Looked at the amount of revision required using different methods

13 13 Revision of Peaks

14 14 Revision of Peaks

15 15 Revision of Troughs

16 16 Revision of Troughs

17 17 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

18 18 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: PEAKTROUGH ConstructionMining Accommodation, Cafes and Restaurants Electricity, Gas and Water CommunicationTransport and Storage

19 19 Further Work  Finalise smoothing parameter  Further analysis of Industry MFP  Analysis of growth between adjacent years relative to average growth  Research capacity utilisation

20 20 Questions


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