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1991 Feature Article - Picking Turning Points in the Economy
GRAPH 1. QUARTERLY GDP(A) GROWTH AND UNEMPLOYMENT RATE, SEASONALLY ADJUSTED AND TREND
8. This revision problem at the end of the series leads to a question of how quickly the provisional trend estimates can pick up turning points in the economy. Graph 2 illustrates the situation for growth in GDP(A) in terms of the recent peak. From this graph it is clear that the peak in growth in GDP(A) now identified as having been in March 1989, was detectable in June 1989, that is as soon as was possible.
GRAPH 2. GDP(A) TREND GROWTH RATE TURNING POINT IDENTIFICATION
9. Table 1 shows the situation for the corresponding trough in the unemployment rate. The unemployment rate, now identified as having ceased falling in August 1989 and plateauing through to the end of 1989, also ceased falling in terms of the provisional trend estimate in August 1989. The plateau was measured through September and October but provisional trend estimates for November and December showed a slight decline which was later revised away. From January 1990, both the provisional and stable trend estimates have shown the unemployment rate rising.
TABLE 1. UNEMPLOYMENT RATE
Yearly Growth Rates
10. Another means of smoothing time series often adopted by analysts in an attempt to determine underlying directions of series is the use of a growth rate measured over a time span considerably longer than the periodicity of the data. A common example of this is the percentage change from the corresponding month (quarter) of the previous year, hereafter referred to as yearly growth.
11 . The yearly growth rate is generally less volatile than the adjacent period to period movement. An additional feature, of some importance where seasonally adjusted data are not available, is that the yearly growth rate provides a crude adjustment for seasonal influences although it does not allow for trading day or moving holiday effects.
12. However, an undesirable feature of the yearly growth rate is that it delays detection of turning points and can lead to misinterpretation of the timing of past turning points.
13. Graph 3 compares the yearly growth of seasonally adjusted GDP(A) with that of the ABS quarterly trend growth. It can be seen that the quarterly trend growth measure discloses the growth peaks and troughs in Australia’s production of real goods and services about six months before they are detected by the yearly growth measure. For instance, the quarterly growth indicator points to a peak growth in GDP(A) in March quarter 1989, with growth declining thereafter, whereas the yearly growth discloses a peak two quarters later in September 1989. A similar situation occurs with the trough in December quarter 1982. Since September 1974 the quarterly trend growth measure has Indicated peaks and troughs two or more quarters earlier than the yearly growth series in about seventy percent of cases.
GRAPH 3. GDP(A) GROWTH RATES
14. Table 1 shows a similar situation with regard to the unemployment rate. For instance, whereas the ABS monthly trend rate indicates the unemployment rate stopped falling in August 1989, the yearly growth series places the turning point eight months later in April 1990.
15. The delay in detecting turning points through the use of yearly growth rates is a result of the one year span being too broad and insensitive to monthly (or quarterly) growth reversals. For instance, a yearly growth can only become negative when the current observation is below its counterpart one year ago, but monthly trend movements may have been in decline for many months.
Other Smoothing Techniques Commonly Used in Turning Point Analysis
16. Pseudo yearly growth rates: In some cases pseudo yearly growth rates are computed by analysts. For example, if December is the current month, the growth rate is estimated as the ratio of the December figure to the average for the twelve months ended in November. Because the interval from December to the middle of this twelve month average is 6.5 months the ratio is raised to the 12/6.5 power to convert it to an annual rate. The result, expressed as a percentage change at an annual rate, is attributed to December. A problem with this measure is that any irregularity present in the current month is amplified by the powering up of the growth rate. Also the averaging of the previous 12 months of data provides a very crude measure of trend behaviour. Pseudo yearly growth rates are also slow to detect turning points. For instance, as shown in Table 1, when applied to unemployment this measure points to a cessation of the fall in the unemployment rate having occurred in February 1990, nearly half a year late. Coincidentally, the amplification of short term volatility can also be seen in this month. Table 1 shows that the seasonally adjusted figure for February 1990 contains a relatively large upward irregular movement compared to the estimates immediately preceding and following. This short term volatility has led to the large 12.16 percent jump in the pseudo annual growth indicator.
17. Off-centred moving averages: The use of moving averages to smooth the seasonally adjusted series has the potential to proxy trend behaviour. However, in an effort to avoid the end point problem referred to in paragraph 7, analysts sometimes off-centre the result to the current end of the time series. For example, a three month moving average instead of being centred on the middle month, may be taken as indicative of the trend in the third month and the series plotted in this way. While this gives the perception of the availability of current information, it does distort the series and results in phase shifts, with the timing of past turning points being miscalculated.
18. Graph 4 illustrates the degree of distortion that occurs when the seasonally adjusted unemployment rate is smoothed by taking the average over twelve consecutive months to represent the trend of the last month in that span. It can be seen that the trend unemployment rate commenced rising in July 1981 but using the off centred moving average, would not have been identified till March 1982. Similarly the rising of the trend unemployment rate in January 1990 was not indicated till June 1990. Yearly growth of this phase shifted measure fails to indicate a rise until September 1990. From Graph 4 some other deficiencies of using simple averages can be seen; they can mis-estimate trend levels (eg refer to 1983), the sharpness of the turning points (eg refer to 1981) and points of inflexion (eg refer to 1984-85).
GRAPH 4. UNEMPLOYMENT RATE, AUSTRALIA
19. Annual movements: Smoothing is sometimes achieved by the simple accumulation of data rather than averaging. For example annual movements of GDP(A) are sometimes derived by taking the sum of the latest four quarters GDP(A) over the sum of the previous four quarters on a moving quarter to quarter basis as shown in Graph 5. The result is a delay in detecting turning points in the series if these movements are interpreted as representing current trend behaviour.
GRAPH 5. GDP(A) GROWTH RATES
20. Pseudo annual movements: These are computed by dividing the sum of the two most recent seasonally adjusted quarters by the sum of the two preceding ones, then annualising the movement by squaring the ratio and expressing it as a percentage change. Like the pseudo yearly growth rate discussed above the squaring of the change will accentuate any Irregularity in either of the two periods and construing it to be a current trend indicator introduces a delay in detecting the trend turning points as shown in Graph 6, although the delay is less than for pseudo yearly growth rates and annual movements.
GRAPH 6. GDP(A) GROWTH RATES
21. Year to Date movements: Another procedure similar to the annual accumulation method discussed above, is the use of the so called year to date measure as an indication of trend behaviour. Comments of the following type are commonly made: “However, as usual, given the normal volatility of these numbers it is better to look at the longer term trend. In the first seven months of this financial year, Australia’s current account deficit was $6,730 million, or $2000 million lower than in the same period of 1986-87”. The deficiency of the year to date measure is that with each additional month of data the extent of smoothing implicit in the year to date accumulation varies, giving for each month a different form of trend estimate. For example, smoothing three months of data gives a different proxy trend estimate to smoothing eleven months of data. Additionally, different degrees of phase shifting occur when the analyst assumes the year to date growth represents the current trend performance.
22. There are a wide variety of smoothing techniques in common use by analysts interested in picking underlying directions in volatile economic time series. This paper indicates some of the pitfalls associated with a number of these techniques and points to the need for care in their use.
23. From an historical perspective the trend estimates produced by the ABS have a number of desirable features in terms of accurately identifying trend turning points. The ABS’s trend series do suffer however, the disadvantage of being subject to revision at the current end of the series but despite this they frequently perform well relative to other smoothing techniques in the early detection of turning points. In addition relatively sophisticated procedures are available for discerning the likely extent of revision to particular trend series (footnote 3).
24. At the current end of series it is recommended that, when available, the ABS’s trend movements be used in conjunction with, rather than instead of, the seasonally adjusted figures to provide analysts with the best picture of the recent underlying direction of the series.
25. The ABS trend approach can be applied to any non-seasonal or seasonally adjusted series. However, if trend estimates are not available, alternative techniques may need to be used. In this case analysts should be aware of their shortcomings as outlined above.
This feature article was contributed by Susan Linacre and John Zarb, ABS.
1. GDP(A) is the Gross Domestic Product average measure. It is the simple average of the Income, Expenditure and Production based GDP measures, at average 1984-85 prices. < Back
2. See cat. no. 1316.0 for details of Henderson moving averages and surrogate averages. < Back
3. Contact The Director, Time Series Analysis for further details. Telephone (02) 6252 5132. < Back
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