![]() ![]() ![]() |
|||
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Budget Estimate for Current Year |
||||||
|
|
|
Actual |
Budget Forecast for next year |
Actual |
Errors |
|
|---|---|---|---|---|---|---|
|
|
|
|
|
|
Current |
Next Year |
|
1978 budget |
|
|
4 |
5.6 |
|
1.6 |
|
1979 budget |
|
|
2.25 |
2.5 |
|
0.25 |
|
1980 budget |
|
|
3 |
3.3 |
|
0.3 |
|
1981 budget |
|
|
3.5 |
3.1 |
|
-0.4 |
|
1982 budget |
|
|
3 |
-2.5 |
|
-5.5 |
|
1983 budget |
|
|
3 |
5.6 |
|
2.6 |
|
1984 budget |
|
|
4.5 |
5.1 |
|
0.6 |
|
1985 budget |
|
|
4.5 |
4.3 |
|
-0.2 |
|
1986 budget |
|
|
2.25 |
2.6 |
|
0.35 |
|
1987 budget |
|
|
2.75 |
5.3 |
|
2.55 |
|
1988 budget |
|
|
3.5 |
4.2 |
|
0.7 |
|
1989 budget |
|
|
2.75 |
3.6 |
|
0.85 |
|
1990 budget |
|
|
2 |
-0.2 |
|
-2.2 |
|
1991 budget |
|
|
1.5 |
0.4 |
|
-1.1 |
|
1992 budget |
|
|
3 |
3.6 |
|
0.6 |
|
1993 budget |
|
|
2.75 |
4.1 |
|
1.35 |
|
1994 budget |
4 |
4.1 |
4.5 |
4.5 |
0.1 |
0 |
|
1995 budget |
4.75 |
4.5 |
3.75 |
4.4 |
-0.25 |
0.65 |
|
1996 budget |
4.1 |
4.4 |
3.5 |
3.6 |
0.3 |
0.1 |
|
1997 budget |
3.25 |
3.6 |
3.75 |
4.8 |
0.35 |
1.05 |
|
1998 budget |
3.75 |
4.8 |
3 |
5.4 |
1.05 |
2.4 |
|
1999 budget |
4.25 |
5.4 |
3 |
4.4 |
1.15 |
1.4 |
|
2000 budget |
4.25 |
4.4 |
3.75 |
na |
0.15 |
|
|
2001 budget |
2 |
na |
3.5 |
na |
|
|
|
Average forecasting errors |
|
|
|
|
0.41 |
0.36 |
|
Mean absolute errors |
|
|
|
|
0.48 |
1.22 |
Source: Budget Paper No 1, various years, Australian Bureau of Statistics, National Income, Expenditure and Product, March quarter 2001, cat no 5206.0, 6 June 2001; Reserve Bank of Australia web site http://www.rba.gov.au/Statistics/Bulletin/G09hist.xls.
The figures in Table 1 have been used to construct the following graph which shows how the official forecasts compare with the actual outcomes as well as the forecast error for each year.
The final column in the above Table indicates that the average forecast was 0.36 of a percentage point below the eventual outcome. So, on average the official forecasts understated GDP growth by 0.36 per cent. However, the mean absolute error was 1.22 per cent. That tells us that on average the outcome is the forecast plus or minus 1.22 per cent. The biggest forecast error was 5.5 percentage points in 1982. In that year the forecast was for 3 per cent growth but the outcome was a 2.5 per cent contraction. In fact, neither of the two years of negative growth (1982 and 1990) were forecast. In more recent years, following the Asian financial crisis, economic growth was consistently underestimated. Whenever economic growth was above average at 5 per cent or more the official forecasts seriously underestimated growth. In our sample, economic growth has been 5 per cent or more on five occasions but there has not been one case where the forecast has been 5 per cent or more.
It is useful to compare the official forecasts with a know-nothing rule or a naïve forecast which just makes the hypothesis that next year's growth will be the same as this year's growth. The average forecasting error under that rule is minus 0.057. So it would just under-predict growth by 0.06 per cent compared with the official over-prediction of 0.36 per cent. The mean absolute error is 1.65 per cent which is a bit worse than 1.22 per cent, being the average forecast error in the official estimates.
Another rule could be to assume that economic growth will be 3.5 per cent every year. That is the figure the Budget Papers use to make their longer term projections beyond the forecast period. Using that rule gives an average forecast error of 0.08 per cent and a mean absolute error of 1.42 per cent, not significantly different from the mean absolute error in the official estimates.
The figures in the second to last column of Table 1 show errors made in estimating the current year's growth. Those estimates are made in May when there is only around 5 or 6 weeks of the financial year left. Nevertheless, substantial errors were made, especially for 1998-99 and 1999-2000. As it happens the estimates for the current year are downward biased by more than the downward bias for the next year forecasts. On average the forecasts were better for next year than the current year on these figures.
There is an important practical consequence of any downward bias in the forecasts. If the official growth estimates were biased downward by 0.41 per cent for the current year and 0.36 per cent for next year, then next year's GDP would be underestimated by 0.77 per cent. That could well translate into changes in the budget balance of well over $1 billion. Assuming a 0.77 per cent increase in GDP translates into a 0.77 per cent increase in the wages bill and a reduction in unemployment by 0.77 percentage points from a forecast 7 per cent, then, on the basis of the rules of thumb given in the Budget Papers, the budget balance would improve by approximately $1.7 billion.(3) Those figures illustrate the sensitivity of Budget figuring to the economic forecasts.
Unlike the weather forecast, the official economic forecasts fail to anticipate extreme values as earlier discussed. However, to some extent that may well be deliberate with economic forecasts. While governments may try to present honest forecasts they will also want to avoid publishing estimates that may be self-fulfilling. We have seen how the negative GDP growth figure for December adversely affected consumer and business confidence when it was published in March 2001. Yet by that time the objective conditions in the economy had vastly improved as was shown by the 1.1 per cent growth, or an annualised 4.5 per cent growth in the March 2001 quarter. News about our history gave rise to a pessimism that was later seen to be unwarranted. Given the effect news has on economic confidence and behaviour, it is possible that governments in the past have chosen not to publish forecasts of negative growth and instead chosen to publish estimates of slow positive growth instead.
Before leaving this section there is a technical point that needs to be made. Forecasts should include all information currently available. But a perfect forecast on the basis of present information cannot incorporate new developments and shocks that occur during the forecast period. That means that the actual outcomes will display more variability than 'perfect' forecasts. This insight has been used in an assessment of OECD forecasts to examine their efficiency.(4) A series of forecasts will be efficient if the variation in the forecasts is below the variation of the outcomes. This is confirmed for Australia's official forecasts with the standard deviation of the actual outcomes being 1.41 while the standard deviation of the forecasts is lower at 1.09.
Are the Forecasts Getting Better?
This section examines whether or not the forecasts are getting better over time. Mr Ian Macfarlane's comments above to the effect that forecasting has not improved over the last 30 years can be examined by splitting the above Table into two time periods. Those examined are the 1978 to 1988 budgets and the 1989 budget to the latest for which there is data. When that is done we obtain the results given in Table 2. Because of the distorting influence of the two downturns, the sub periods are estimated with and without the years 1982 and 1990.
Table 2: Economic Growth: Forecasting errors by sub period.
|
1978 to 1988 budgets |
1978 to 1988 without 1982 contraction |
1989 to 1999 budgets |
1989 to 1999 without 1990 contraction |
|
|---|---|---|---|---|
|
Average forecast error |
0.26 |
0.84 |
0.46 |
0.95 |
|
Mean absolute error |
1.37 |
0.96 |
1.06 |
0.73 |
The raw results in Table 2 suggest that theaverage forecast error has worsened from the first half to the second half of the sample. This result is not statistically significant.(5) The results suggest that if we ignore the failure to predict the contractions then the average error jumps to almost one percentage point by the second subset of the sample. This bias is in fact worse in the second half of the sample, suggesting that the official forecasts are more biased in more recent years. The mean absolute error appears to improve from the first to the second half and falls substantially if the failure to forecast the downturns are ignored. Once again the difference between the samples is not statistically significant.
Unemployment and Inflation: Actual versus Forecast
Other important variables that the Budget Papers attempt to forecast include unemployment and inflation. Those forecasts are intrinsically important but are also important for deriving government expenses (previously 'outlays') and revenues.
Table 3 presents budget-time forecasts for unemployment and inflation since the 1978-79 Budget. Some of the early years presented problems because estimates were not always given as a precise numerical forecast. In constructing Table 3 some of the actual numerical targets had to be inferred from the relevant Budget papers. For example, the discussion in the 1978-79 Budget Papers predicted unemployment would be 'unchanged' when the latest figures then published showed unemployment to be 6.8 per cent in the relevant quarter. In following years unemployment was forecast to be 'broadly unchanged (1979),' 'little if any decline (1980),' 'slight fall (1981),' 'marked increase (1982),' 'higher (1983),' 'decline slightly (1984),' '7.5 to 8' at the end of the year (1985), and 'some increase from 7 (1986).' In each case, where there was no specific number mentioned, but the outcome was consistent with the anticipated movement, the Table credits the forecasts with getting the outcome exactly right. Since 1986 the Budget Papers have provided tables with detailed numerical forecasts rather than the more impressionistic discussions. The situation was better with inflation. However, in 1980 the forecast avoided a numerical target and said 'about the same or slightly faster at 10. 'The 1984 Budget forecast a through-year CPI increase because of the complications of the Medicare effect, whereby the introduction of Medicare was expected to distort year on year figures.
Table 3: Unemployment and Inflation: Forecasts and Outcomes
|
Unemployment rate-year |
Inflation-year average |
|||||
|---|---|---|---|---|---|---|
|
Budget forecast for next year |
Actual |
Error |
Budget forecast for next year |
Actual |
Error |
|
|
1978 budget |
6.8 |
6.3 |
-0.5 |
6.0 |
8.1 |
2.1 |
|
1979 budget |
6.6 |
6.2 |
-0.4 |
10.0 |
10.2 |
0.2 |
|
1980 budget |
6.2 |
5.9 |
-0.3 |
10.0 |
9.3 |
-0.7 |
|
1981 budget |
6.0 |
6.2 |
0.2 |
10.75 |
10.4 |
-0.35 |
|
1982 budget |
9.0 |
9.0 |
0 |
10.75 |
11.5 |
0.75 |
|
1983 budget |
9.6 |
9.6 |
0 |
7.5 |
6.9 |
-0.6 |
|
1984 budget |
8.6 |
8.6 |
0 |
5.25 |
6.6 |
1.35 |
|
1985 budget |
7.75 |
7.5 |
-0.25 |
8.0 |
8.4 |
0.4 |
|
1986 budget |
8.0 |
8.1 |
0.1 |
8.0 |
9.3 |
1.3 |
|
1987 budget |
8.25 |
7.5 |
-0.75 |
7.0 |
7.3 |
0.3 |
|
1988 budget |
6.25 |
6.4 |
0.15 |
7.5 |
7.3 |
-0.2 |
|
1989 budget |
7.25 |
5.9 |
-1.35 |
5.5 |
8.0 |
2.5 |
|
1990 budget |
7.25 |
8.1 |
0.85 |
6.5 |
5.3 |
-1.2 |
|
1991 budget |
10.5 |
10.0 |
-0.5 |
3.0 |
1.9 |
-1.1 |
|
1992 budget |
10.5 |
10.7 |
0.2 |
3.0 |
1.0 |
-2.0 |
|
1993 budget |
10.75 |
10.2 |
-0.55 |
3.5 |
1.8 |
-1.7 |
|
1994 budget |
9.75 |
8.7 |
-1.05 |
2.25 |
3.2 |
0.95 |
|
1995 budget |
8.25 |
8.1 |
-0.15 |
4.0 |
4.2 |
0.2 |
|
1996 budget |
8.5 |
8.3 |
-0.2 |
2.0 |
1.3 |
-0.7 |
|
1997 budget |
8.25 |
8.0 |
-0.25 |
1.0 |
0 |
-1.0 |
|
1998 Budget |
8.0 |
7.4 |
-0.6 |
2.5 |
1.3 |
-1.2 |
|
1999 budget |
7.5 |
6.6 |
-0.9 |
2.0 |
2.4 |
0.4 |
|
2000 budget |
6.5 |
5.75 |
||||
|
2001 budget |
7.0 |
2.0 |
||||
|
Average forecasting errors |
-0.28 |
-0.01 |
||||
|
Mean absolute error |
0.42 |
|||||
Source: Budget Paper No 1, various years, Reserve
Bank of Australia web site
http://www.rba.gov.au/Statistics/Bulletin/G09hist.xls.
Before commenting on the inflation and unemployment forecasts is should be pointed out that labour market forecasts will depend heavily on the forecasts for economic growth. Errors in the latter will mean errors in the former. Table 3 shows the influence on unemployment estimates of the earlier discussed errors in growth forecasts. The average error of 0.28 means that the forecasts have overestimated unemployment, consistent with underestimating growth. The mean absolute error seems reasonably low, however, indicating fairly accurate forecasts for unemployment.
Inflation forecasts are very interesting. The negligible average forecast error is very impressive. This suggests a record of unbiased estimates of inflation. The mean absolute error is also reasonable given the rather volatile nature of inflation over the last 20-odd years. However, it is also interesting to split the sample in two to examine whether or not forecasting has improved or otherwise changed. This is done in the following table.
Table 4: Unemployment and Inflation: Forecasting errors by sub period.
|
1978 to 1988 budgets |
1989 to 1999 budgets |
|
|---|---|---|
|
unemployment |
|
|
|
average forecast error |
-0.16 |
-0.41 |
|
mean absolute error |
0.24 |
0.60 |
|
inflation |
|
|
|
average forecast error |
0.41 |
-0.44 |
|
mean absolute error |
0.75 |
1.18 |
It has already been noted that unemployment errors tend to reflect growth errors. The average forecasting error for unemployment increased somewhat between the two periods. That lower early error may only reflect the manner in which the data was constructed for the earlier period as described above. However, the inflation figures will not depend so much on growth forecasts. The impressive unbiased forecasts for the 22 year period are not so impressive when the sample is split in two. Now Table 4 indicates that in the first half there was a systematic bias towards underestimating inflation while in the second half there was a systematic bias towards overestimating inflation. The latter seems to have reflected a period of overestimating inflation following the 1990 downturn, as well as some overestimating inflation around the time of the Asian financial crisis and the aftermath. The mean average error has also increased somewhat between the two sub-samples suggesting that the official forecasts are not as good as they used to be. Once again, however, the differences in the Table are not statistically significant.